xml version 1.0 encoding UTF-8 standalone no
record xmlns http:www.loc.govMARC21slim xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.loc.govstandardsmarcxmlschemaMARC21slim.xsd
leader nam 2200385Ka 4500
controlfield tag 001 001989269
007 cr mnu|||uuuu
008 090217s2007 flu s 000 0 eng
datafield ind1 8 ind2 024
subfield code a E14-SFE0002249
A comparative study of healthcare procurement models
h [electronic resource] /
by Arka Bhattacharya.
[Tampa, Fla] :
b University of South Florida,
Title from PDF of title page.
Document formatted into pages; contains 87 pages.
Thesis (M.S.I.E.)--University of South Florida, 2007.
Includes bibliographical references.
Text (Electronic thesis) in PDF format.
ABSTRACT: Group Purchasing Organizations (GPOs) play a significant role in the healthcare industry. The presence of GPOs helps the healthcare centers to offload their responsibilities so that they can focus on more critical areas which require attention like providing quality care. This thesis involves the comparison of three models of procurement operations in terms of cost efficiency. This cost comparison model features a healthcare organization associated with a national GPO, a healthcare organization which procures by self sourcing (not associated with a GPO), and a hybrid procurement model involving a national GPO and a regional GPO. The comparison model highlighted the cost effectiveness of these three different ways of procurement, which threw significant light on the purchasing operations of healthcare organizations.In the second part of this research study, we formulated a method to measure the degree of access to innovative products across the above mentioned procurement models either involving on-contract (from a GPO) purchasing, or off-contract purchasing (from individual manufacturers not affiliated to GPO) or both. We also identified the metrics for innovation and measure the innovativeness of products. Based on the literature study, it was found that purchasing groups may also be an entry barrier to new suppliers (Zweig 1998), with big national GPOs dominating the market and dictating the pricing of commodities.The first hypothesis H1 of this research study was stated as "National GPOs (Group Purchasing Organizations) enable the healthcare establishments to lower the cost of medical services and operations." The second hypothesis H2 of this research study was acknowledged as "National GPOs a barrier to entry of Innovative product manufacturers in the healthcare industry." This thesis will identify the advantages and disadvantages of each type of procurement operation and address the economic issues which affect the relationship between a healthcare center and a GPO. The proposed research would indirectly help to identify whether cost savings are being shared by the links in the downstream supply chain and the savings are being percolated to the patients for the added welfare of the society. It will also identify the importance of innovative products in the society and will raise the bar of specialty treatments without compromising on the level of service being offered to the patients.This thesis will also highlight positive aspects of niche manufacturers of innovative products with smaller volumes which are currently marginalized in the market by the big national players. To the best of the author's knowledge, the research objective of measuring innovation of products has not been addressed yet in academic literature and will have the benefit of comparing three different purchasing models used in healthcare industry.
Mode of access: World Wide Web.
System requirements: World Wide Web browser and PDF reader.
Advisor: Kingsley Reeves, Ph.D.
x Industrial Engineering
t USF Electronic Theses and Dissertations.
A Comparative Study of Healthcare Procurement Models by Arka P. Bhattacharya A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Industrial Engineering Department of Industrial and Ma nagement Systems Engineering College of Engineering University of South Florida Major Professor: Kingsley A. Reeves, Ph.D. Grisselle Centeno, Ph.D. Jos Zayas-Castro, Ph.D. Date of Approval: October 30, 2007 Keywords: GPO, healthcare organizations, Wilcoxon, comparative study, DEA, Delphi method Copyright 2007, Arka P. Bhattacharya
DEDICATION To my parents and my lovely wife fo r their unconditional support and love. To my advisor Dr. Kingsley Reeves for his cons tant guidance, encouragement and for his excellent mentorship. To Dr. Bob Sullins, Dr. Janet Moore, Ms. Margaret Martinroe and Ms. Mia Fluitt from the Dept. of Undergraduate Studies for their unstinted support, encouragement and inspiration.
ACKNOWLEDGEMENTS I would like to thank Dr. Kingsley Reev es for his guidance, support, belief, encouragement and patience. I also would like to thank the committee members and faculty members of the Industrial Engineerin g Department at the University of South Florida for their teaching and support. I also would like to thank my colleagues and the Department of Undergraduate Studies for thei r assistance in fulfilling my research goals.
i TABLE OF CONTENTS LIST OF TABLES iii LIST OF FIGURES iv ABSTRACT v CHAPTER 1 INTRODUCTION 1 CHAPTER 2 OBJECTIVES AND SIGNIFICANCE 4 2.1 Hypothesis 5 2.2 Effects of GPO Sourcing 7 2.3 Broader Impact of the Research 8 CHAPTER 3 RELATIONSHIP TO CURRENT LITERATURE 9 3.1 Evolution of GPOs 11 CHAPTER 4 INSIGHT INTO GPOS 13 4.1 Functions and Services of GPOs 13 4.2 Importance of GPOs in Healthcare Industry 14 4.3 Importance of Innovation/Innovative Products 16 4.4 Impact of Purchasing Groups 19 4.5 Classifications of GPOs 20 CHAPTER 5 COST COMPARISON ANALYSIS 24 5.1 Cost Comparison Methodology 24 5.1.1 Building the Cost Model 25 5.1.2 Comparison of Unit Overall Cost (Wilcoxon Paired Test) 29 5.2 Results of Cost Comparison 34 5.2.1 Procurement Model A versus Procurement Model B 34 5.2.2 Procurement Model A versus Procurement Model C 36 5.2.3 Procurement Model B versus Procurement Model C 38 5.2.4 Summarization of Results of Cost Comparison Study 39 5.3 Analysis of Cost Comparison 41 5.3.1 Overall Comparison 41 5.3.2 Medical Devices Comparison 44 5.3.3 Surgical Devices Comparison 46
ii CHAPTER 6 MEASUREMENT & COMPARISON OF INNOVATION (DEA) 48 6.1 Methodology of Innovation Measur ement & Cost Comparison 48 6.1.1 Identifying Innovation Metric 49 6.1.2 Analyzing Innovation Metric Using Delphi Method 51 6.1.3 Innovation Metric Scal e and Innovation Score 53 6.1.4 Theoretical Analysis versus Empirical Analysis 54 6.1.5 Comparison and Ranking Using DEA 56 6.1.6 Data Envelopment Analysis (DEA) 57 6.1.7 Selection of Decision Making Units (DMUs) 59 6.1.8 Simulated Costs of DMUs (Input) 62 6.1.9 Simulated Innovation Score (Input) 65 6.1.10 Simulated No. of Beds (Output) of DMUs 68 6.1.11 Selection of (DEA) Model 69 6.2 Results of Comparison of Access to Innovation with Cost 71 CHAPTER 7 CONCLUSION AND DISCUSSIONS 78 REFERENCES 81 APPENDICES 83 Appendix A Process Map of Self Sourcing Model 84 Appendix B Process Map of GPO Model 85 Appendix C Process Map of Hybrid Model 87
iii LIST OF TABLES Table 5.1 Wilcoxon Results of Comparison of HC A and HC B 35 Table 5.2 Wilcoxon Results of Comparison of HC A and HC C 36 Table 5.3 Wilcoxon Results of Comparison of HC B and HC C 38 Table 5.4 Cost Efficiency of Procurement Models 41 Table 6.1 Simulated DMUs 59 Table 6.2 Simulated Costs of DMUs (Input) 63 Table 6.3 Simulated Innovation Scores of DMUs (Input) 66 Table 6.4 Simulated Values of Outputs (No. of beds) 68 Table 6.5 Ranking and Efficiency Scores of DMUs 72 Table 6.6 Statistics on Input/Output Data 75 Table 6.7 Projection of DMUs 76
iv LIST OF FIGURES Figure 1.1 Healthcare Value Chain 3 Figure 2.1 Procurement Models Used in the Research 5 Figure 4.1 Rationa le for Group Purchasing 14 Figure 4.2 Importance of Innovative Capabilities 17 Figure 4.3 Classification of GPOs 21 Figure 4.4 Ranking of GPOs by Contra ct Purchases and Memberships 22 Figure 4.5 Market-share of GPOs 23 Figure 5.1 Screen Shot of Cost Model Template 29 Figure 5.2 Distribution of Data Obtained from Healthcare Organization C 30 Figure 5.3(a) Overall Comparison Ba sed on Total Price Difference 41 Figure 5.3(b) Overall Comparison Ba sed on Mean Price Difference 42 Figure 5.3(c) Overall Comparison Base d on Mean Percentage Difference 42 Figure 5.4(a) Medical Device Comparis on Based on Total Price Difference 44 Figure 5.4(b) Medical Device Comparis on Based on Mean Price Difference 45 Figure 5.5(a) Surgical Device Comparis on Based on Total Price Difference 46 Figure 5.5(b) Surgical Device Comparis on Based on Mean Price Difference 46 Figure 6.1 Flowchart Showing Processes of Delphi Method 53 Figure 6.2 Graph Showing Effi ciency Scores of DMUs 74
v A Comparative Study of Healthcare Procurement Models Arka P. Bhattacharya ABSTRACT Group Purchasing Organizations (GPOs) play a significant role in the healthcare industry. The presence of GPOs helps th e healthcare centers to offload their responsibilities so that they can focus on more critical areas which require attention like providing quality care. This thesis involves the comparison of th ree models of procurement operations in terms of cost efficiency. This cost comparison model features a healthcare organization associated with a National GPO, a healthca re organization which procures by Self sourcing (not associated with a GPO), a nd a Hybrid procurement model involving a National GPO and a regional GPO. The co mparison model highlighted the cost effectiveness of these three different ways of procurement, which threw significant light on the purchasing operations of healthcare organizations. In the second part of this research study, we formulated a method to measure the degree of access to innovativ e products across the above me ntioned procurement models either involving on-contract (f rom a GPO) purchasing, or o ff-contract purchasing (from
vi individual manufacturers not affiliated to GPO) or both. We also identified the metrics for innovation and measure the innovativeness of products. Based on the literature study, it was found that purchasing groups may also be an entry barrier to new suppliers (Zweig 1998), with big National GPOs dominating th e market and dicta ting the pricing of commodities. The first hypothesis H1 of this research study was stated as National GPOs (Group Purchasing Organizations) enable the hea lthcare establishments to lower the cost of medical services and operations. The second hypothesis H2 of this research study was acknowledged as National GPOs a barrier to the entry of innovativ e product manufacturers in the healthcare industry. This thesis will identify the advantages and disadvantages of each type of procurement operation and address the economic issues which affect the relationship between a healthcare center an d a GPO. The proposed research would indirectly help to identify whether cost savings are being shared by the links in the downstream supply chain and if savings are being percolated to pa tients for the added welfare of the society. It will also identify the importance of innovativ e products in the soci ety and will raise the bar of specialty treatments without compromi sing on the level of service being offered to the patients. This thesis will also highlight positive aspects of niche manufacturers of innovative products with smaller volumes, curre ntly marginalized in the market by the big National players.
vii To the best of the authors knowledge the research objective of measuring innovation of products has not been addressed ye t in academic literature and will have the benefit of comparing three different purchas ing models used in healthcare industry.
1 CHAPTER 1 INTRODUCTION Group Purchasing Organizations have become very significant in the healthcare industry. The GPOs (also called purchasing groups) have mostly become popular in healthcare, education and government organizations. Th e healthcare industry is faced with the constant pressure to cut down costs and stiff competition among healthcare centers which have led to mergers and acquisiti ons resulting in supplie rs of larger size. The most frequent reason given by a health care center to be affiliated with a GPO is advantageous contractual c onditions. The modern GPOs ha ve changed the conservative method of procurement. The huge pressure of lowering th e prices has mostly been beneficial to the end user which in our cas e is a customer to a healthcare center. A GPO is a formal and virtual structure that facilitates the consolidation of purchases for many organizations (Nollet 2005) The outsourcing of purchasing to GPOs has facilitated healthcare centers to focus on their critical areas like providing healthcare. This has taken off the burden of purchasi ng operations which many healthcare centers used to face previously. It has been estimated that more than 70 percent of the healthcare purchases are done through group purchasing (Nollet 2002). These purchasing groups have a stronger negotiating capacity in dealing with th eir suppliers and have the necessary volume to support, which lowers the cost of commodities (standardized objects). Purchasing groups empower their me mbers in negotiation and create favorable
2 conditions for their members. However, the pr ice advantages are grea ter for larger GPOs as they have more negotiating capacity. Th ere is also a general agreement that GPOs generate savings between 10 and 15 percen t amounting to $12.8 bi llion to $19.2 billion (Hendrick 1997) and (Schneller 2000). Thus, it is quite evident that in the healthcare industry, the existence of GPOs cannot be ignored. According to a recent Health Industry Group Purchasing report, goods and purchased services accounted for the second largest dollar expenditure (55% labor and 45% non labor supplies, services and capital equipment) in the hospital organization (Schneller 2000). The main rationale for gr oup purchasing is to achieve lower prices, ensure price protection, implementing impr oved quality programs, reduced contracting costs and monitoring market conditions (Schneller 2000). Estimates place the GPO market for healthcare organi zations and nursing homes at between $148 and $165 billion dollars and growing to $257 and $287 billion per year by 2009 (Hewitt 1995). It is also noteworthy that 72 to 80 percent of every healthcare (acute care organization) supply dollar is acquired through group purchasing (Schneller 2000). In addition to purchasing options, GPOs offer information sharing, clinical and operational benchmarking and value assistance benchmarking that could strategically differentiate GPO members in their market (Schneller 2000). Schneller also stated from a report that product standardization and ente ring into GPO contracts were the most effective cost reduction strategies (Schneller 2000). In choosing to contr act with a GPO, a company must evaluate the performance of its suppliers with that of the GPOs performance in terms of purch asing power (Schneller 2000).
The purchasing groups facilitate their me mbers to get more favorable conditions than they would have obtained individually (Rozemeijer 2000). The administrative costs also get lowered due to the fact that a single organizat ion performs the negotiations instead of many. There are two types of st ructures among GPOs. The first type is cooperative structure where the purchases to be performed by the group are distributed among members. Second type of structure is the third party structure where a distinct organization negotiates and writes contra cts according to a mandate given by the members (Hendrick 1997). The healthcare va lue chain is shown below in figure 1.1. Figure 1.1 Healthcare Value Chain 3
4 CHAPTER 2 OBJECTIV ES AND SIGNIFICANCE In this thesis our main objective is to compare the three models of procurement operations in terms of cost effectiveness by capturing the purchasing costs per unit of the commodities/items procured by different healthcare organizations. This comparative study focuses on three scenarios featuring a healthcare organization which procured through a National level GPO, a healthcare or ganization which procured by Self sourcing and a Hybrid procurement model (comprising a National GPO and a regional GPO). In this study, items procured by the healthcare or ganizations are classified into 2 main categories, medical devices and surgical de vices. These items are common items required in daily operations and procured in bulk quantities by the healthcare organizations. The procurement costs of these items are highlighted through this comparative study. Apart from supplying commodities and surgical in struments to healthcar e organization, many GPOs are now focusing on diversifying their product range and providing additional support services like maintaining medical records and training hospital employees in new technologies. This has led to an overall growth of technology and made the daily operations more efficient. Our comparison model evaluates and highlights the economic benefits of these three different ways of procurement, which will throw significant light on the purchasing operations of healthcare organizations.
Figure 2.1 Procurement Models Used in the Research We have also captured the degree of access and compared the cost associated with the procurement of innovative products thr ough a National GPO, a Hybrid model, and Self sourcing. This is done by firstly iden tifying metrics for innovation and formulating a technique to measure the degree of innova tion of products sourced from healthcare organizations involving a Nationa l GPO model, a Self sourci ng and a Hybrid one either involving on-contract (from a GPO) purchas ing, or off-contract purchasing (from individual manufacturers not a ffiliated to a GPO) or bot h. The measure of innovation is tied to the cost of the products and both the factors are used in the comparison of models. This may highlight the fact that when it comes to innovative products (for example pacemakers), whether a procurement model is rated higher in terms of innovation and also whether the advantages of low co st outweigh the advantages of innovation. 2.1 Hypothesis Based on our literature review, it was f ound that purchasing groups may also be an entry barrier to new suppliers (Zweig 1998). Big National GPOs provide commodities at a much lower price due to large volum es, which gives an advantage to existing 5
6 suppliers, since suppliers with innovative pr oducts do not have sufficient sales volume to allow them to take advantage of economies of scale and to offer competitive prices (Elhauge 2002). Formally, the hypothesis can be stated as follows: H1 National GPOs (Group Purchasing Organizations) enable the healthcare establishments to lower the cost of medical services and operations. H2 National GPOs a barrier to entry of Innovative product ma nufacturers in the healthcare industry. This proposed thesis will throw light on the pros and cons of each type of procurement operation. There is a strong need to address these economic issues as they will affect the relationship between a healthcare center and a GPO. These factors can affect the consistency of healthcare delivery quality which will have a social impact. Our thesis will highlight positiv e aspects of niche manufacturer s of innovative products with smaller volumes which are currently margin alized in the market by the big National players. Most of the big players in the GP O market are driven by costs and big volumes and they sideline the smaller players wh ich manufacture innova tive products (Zweig 1998; Everard 2005). One added advantage of our project will be th at it will help the specialty healthcare organiza tions realize the importance of innovative products and help them choose the procurement model for innovative products which will be most cost effective. This will help to reduce the cost of innovative products in the market and help the patients in accessing high end products at reasonable price. To these healthcare organizations, technology of the products will be of higher priority which will help to raise the quality of specialty healthcare services. To the best of the authors knowledge,
7 the research objective of measuring innovation of products has not been addressed yet in academic literature and will have the benef it of comparing three different purchasing models used in healthcare industry. 2.2 Effects of GPO Sourcing GPOs have a large effect on the health care industry. Based on our study, we have found that there can be positive as well as ne gative effects when a healthcare organization affiliates with a GPO. However, since the mini mization of cost is a top priority for many healthcare organizations, these negative e ffects are sometimes overshadowed. With affiliation to a GPO, healthcare organizatio ns enjoy lower prices, protected pricing, improved quality control programs, reduced contracting costs and GPOs also monitor market conditions (Schneller 2000). This price protecte d market gives healthcare organizations some form of security against price fluctuations. However, along with these favorable conditions there are quite a number of cons associated. Affiliation to a GPO, reduces the autonomy of an individual health care organization and often it gets bound by a contract and cannot come out of it (Nollet 2005). This may l ead to dissatisfaction among some physicians who wish to maintain th eir autonomy in choosing products, and may sometimes circumvent the contract terms of the GPO to access those products (Burns 2002). This reduces the overall cost savings of the GPO in the long run. GPOs also create an entry barrier to small innovative produc t suppliers, who cannot compete with large volume existing suppliers due to small volumes (Zweig 1998). This may affect quality of specialized commodities in the long run and result in dissatisfied customers. Thus, the cost associated with loss of business has to be considered. Due to the large size of GPOs
8 and long term contracts with the suppliers, fe w big players dominate the market and many small players have complained about the la ck of competitive access (Burns 2002). This creates an oligopolisti c market scenario, and big play ers end up dominating the market, while the smaller ones are marginalized. Close cooperation among healthcare comp etitors sourcing from the same GPO also gives rise to anti-trust issues(Nollet 2005). Sometimes members do not want to share sensitive information with their rivals. Sometimes National players are not able to deliver their products on time due to logistic problems and during calamities. This causes unscheduled delays to patients and the service quality of the healthcare organizati on suffers. In this aspect, local or regional suppliers are sometimes better off as their l ogistic operations prove to be better. Many local players also share their warehouses with their clients which may help in product delivery and reduce overhead. This is our added research objective and will determine innovation metrics to analyze whether regional sourcing improves quali ty of products and results in a superior distribution model. 2.3 Broader Impact of the Research The proposed research would indirectly help to identify whether cost savings are being shared by the links in the downstream supply chain and if the savings are being percolated to patients for the added welfare of the society. It will also identify the importance of innovative products in the soci ety and will raise the bar of specialty treatments without compromising on the level of service being offered to the patients.
9 CHAPTER 3 RELATIONSHIP TO CURRENT LITERATURE One of the most common issues dealt in th e past and current lit erature is about the optimal size of GPOs and the benefits which healthcare organizations gain by affiliating with a GPO. There is an overall consensus th at affiliation with a GPO indeed results in cost savings. The past literatu re has dealt with issues like size of purchasing group and the types of benefits which can be extracte d with affiliation to a GPO (Nollet 2005). This study was based mostly on the interviews with health managers. Je an Nollet and Martin Beaulieau identified the different aspects of a relationship with a GPO. The paper evaluated the impacts of a GPO on a supply market. The issue related to the size of a GPO and its effects on the buye rs and the suppliers were al so discussed. They further went on to discuss the member character istics and the issues faced by them. M. Essig described the concept of gr oup purchasing as Purchasing Consortium and has introduced it as a supply management concept combining sy mbiotic horizontal relationships and strategic understanding to gain competitive advantage (Essig 2000). This paper focused on the sy mbiotic relationship among the members in a similar hierarchy level. This literature further descri bed and classified sourcing options available to a GPO and illustrated the bene fits associate with each type. Member commitment has a huge role to play in the success of a GPO and also the growth of member enrollment depends on it (Nollet 2002). W. R. Doucette pointed out
10 that the transparency in sharing of informa tion between the members and the trust issues shape the success of GPOs by creating a st rong member commitment (Doucette 1997). Member commitment is influenced by other members to a great extent. The major chunk of literature ha s dealt with the identifica tion of costs and the cost saving benefits enjoyed by the healthcare organizations (Schneller 2000), (Rozemeijer 2000) and (McFadden 2000). Any healthcare cent er affiliated to a GPO benefits from three types of cost reductions: price, admini strative costs and utilization costs (Anderson 1998). As has been discussed earlier that aff iliation to a GPO can generate savings up to 10 to 15 percent which is a direct cost sa vings (Hendrick 1997) and (Schneller 2000). The healthcare organizations can utilize the savings generated in more vital areas which relate directly to technical quality (qua lity of healthca re delivery). Chapman mentioned that the real savings in the healthcare savings come from product standardization (Chapman 1998). However certain types of purchases like commodities are suited for larger savings and standardization may be enforced by certain purchasing groups by forcing healthcare centers to use all the produc ts in the package (Nollet 2005). A significant amount of study has been carried out previously about the role of GPOs and identifying the economic co sts and its impact on the entire supply chain (Schneller 2000). However, based on our literatur e research, it is found that there has been a dearth of work related to the comparison of procurement models through Self sourcing, National GPO sourcing and regional GPO sourcing. Most of the earlier or present literatures have identified economic and non economic costs associated with a GPO (Dobler 1996; Anderson 1998; Chapman 1998; Schneller 2000), but there has been no direct
11 comparison between three different procurem ent models. Also most of the earlier literatures have just mentioned non economic costs like loss of autonomy of physicians and barrier to entry of innova tive products (Zweig 1998) and (Elhauge 2002). Our current research focus will be to address this issue of access to i nnovative products while sourcing from a GPO. This thesis will identify innovation metrics to evaluate the degree of innovation in products and wi ll also illustrate which pr ocurement method gives access to the highest level of innovative products an d at the same time keeping the cost to a reasonable level. Based on our literature research, it can be sa id that this proposed research topic is unique because it identifies i nnovation metrics to analyze the degree of innovation in a particular item which again reflects the proc urement model. To the best of our knowledge their has been no scholarly work which de als with the comparison of procurement processes associated with a GPO and measures a products innova tiveness by analyzing particular metrics. 3.1 Evolution of GPOs The concept of GPO took birth way back in 1910 in New York with the formation of Hospital Bureau of Standard S upplies of New York (Barlow 2005). However, with the advent of 1970s, the formation and growth of GPOs really took shape and the regional groups gave in to National level organi zations. Almost close to 37% of the purchasing groups were set up during this peri od (Nollet 2002). This sudden surge in the number of purchasing gr oups was due to the increased government pressure on cost reduction.
12 This augmentation in the number of GPOs resulted in stiff competition among the members in a price sensitive market. GPOs could not enlarge by adding members as most of the healthcare organizations were already serviced by one of them (Nollet 2002). To stay afloat with the competition, GPOs st arted extending additional services which facilitate the operational efficiency of a healthcare organization. Th ese services include consulting, contact management, human resource management, computing services, etc. The consolidation of purchasing groups began in the 1990s. This age was the age of mergers and acquisitions. For example, No vation resulted from the merger of VHA and HealthSystem Consortium (Doucette 1997).
13 CHAPTER 4 INSIGHT INTO GPOS 4.1 Functions and Services of GPOs A GPO is a group of organizations which co nsolidate their resources to have more leverage on their suppliers. Based on past lite rature, it is seen that a GPOs procurement strategy creates better operational links with the suppliers, shorter lead times, and creates more competition in the market. This favors th e end user in terms of lower costs and has a socio economic benefit too. GP Os also provide joint purchas ing programs to clinicians, and other healthcare entities. The areas where GPOs use their influence in negotiating the prices are pharmacy, laboratory, diagnostic imaging, of fice facilities, dietary, main tenance, IT, and insurance (Burns, 2002). Apart from negotiating prices, a GPO serves as an instrument for price protection for its members as it functions lik e a link between the la rge number of vendors and the healthcare organization. In past, GPOs offered their members the sa me standardized pric ing irrespective of the volume they purchased. This proved to be advantageous to the smaller members and the bigger players felt that they had to bear the burden of subsidizing the smaller ones (Burns 2002). However, the concept of tie red pricing (Burns 2002) has come into effect recently which relates the pricing of products to th e volumes members purchase. Affiliation to a GPO is a win-win situation for both the healthcare organization as well as the GPO. The healthcare organization gets the benefit of cash incentives, cost savings and outsourcing of purch asing function to a third party which in turn helps them
to streamline their operations. GPOs gain by the added negotiating cap acity in controlling the price of the products and also the contra ct administration fees paid by the vendors. Apart from controlling and lowering of co sts, GPOs offer addi tional services to their members like materials management, contract management, operations consulting, programs to improve product standardiz ation, insurance services, technology management programs, disease management human resource management, education, and marketing (Burns 2002). Figure 4.1 briefl y summarizes the justifications as mentioned in the past literature for a healthcare organization to be affiliated to a GPO. Figure 4.1 Rationale for Group Purchasing 4.2 Importance of GPOs in Healthcare Industry The process of sourcing through GPO in healthcare industry is mostly seen for non critical items where the level of customization is almost non existent. Most commonly, commodities which are required in bulk quantities and other pharmaceutical 14
15 products along with office supplies are source d through GPOs. Over the years its been seen that this model of procurement through GPO has seemed to be more cost effective and more and more healthcare organizations ar e getting affiliated to big National GPOs. The most distinctive factors which have cont ributed to the rise of GPOs are high volume of commodities being sourced which has helped to lower the price of commodities and the standardization of products being sourced. The levels of customization of products sourced through GPOs have been minimal. A ccording to Dobler and Burt (Dobler 1996), evidence is plentiful that simplification or standardization can result in big savings. Standardization and simplification is also the focus of major efforts in healthcare providers as a tactic for re ducing costs (McFadden 2000). This is where the GPOs have a substantial advantage over sma ller players in the industry. This leads them to dominate the market. In healthcare industries, since GPOs ar e mostly concerned with non critical items, issues like loss of confiden tiality are not important. I nnovation and technology are not given high importance in the bus iness of non critical items. Unlike other verticals, healthcare i ndustry has socio-economic obligations. Providing quality healthcare at a low cost has been one of th e challenges of the modern healthcare industry. Since it affects the medi cal services to the common man, controlling the cost becomes a crucial fa ctor. GPOs have played a big role in this by providing commodities at very low costs. This has en abled the healthcare organizations to offer medical services to the common man at reasonable prices and has raised the standards of healthcare quality in the country. Moreover, GP Os also offer other services like data warehousing, information technology services and training of staff in the latest
16 technologies to the healthcare establishments and healthcare organization, which have taken off the workload out of these healthcar e organizations and helped them focus on more critical issues like operational issues. 4.3 Importance of Innovation/Innovative Products Based on our research, it can be said that most of the items procured through a GPO are commodities which are pretty simple items and require little or no innovation. These items are sourced in bulk quantities a nd are supplied at a very low cost. However, it is also seen that healthcare organizations source few type of items like pacemakers and other surgical quantities which are sophisti cated and require a hi gh degree of innovation. Though the volumes of these advanced item s are quite low compared to the bulk quantities, they have a huge impact on the qua lity of specialty care. These specialized items require sustained innovation in their lifecy cle which is essential for their existence. Many of these state of the art items ar e manufactured and supplied by niche manufacturers who do not ha ve a strong influence on th e National GPOs and cannot deliver at a rock bottom price to the mark et because of their low volumes. Sometimes these manufacturers are sidelined and the ma rket dominated by the big National GPOs creates a barrier for their entry in the busine ss. According to Muller, companies must exploit their innovative capabilit ies to develop new businesses if they are to successfully confront the disruptive effects of emergi ng technologies, empowered customers, new market entrants, shorter product life cycles, geopolitical instability, and market globalization (Muller 2005).
Geopolitical Instability Globalization threat Shorter product Life c y cles New market entrant threats Emerging Capabilities Innovative Capabilities/ Sustained Innovation Counters Figure 4.2 Importance of Innovative Capabilities Source: Adapted from St rategos et (Muller 2005) Innovation management can be also defi ned as coping with rapidly changing environment or in turbulent environments. Ca lantone, Garcia and Droge define turbulent environments as those in which market needs or technology are uncertain and have impact on new product development proces ses (Buganza 2006). Further this paper discusses that to manage turbulent environments, companies have to reduce the development time and increase the ability to react to changes. That is, a product must have high degree of Life Cycle Flexibility. Life Cycle Flexibility of a product is the ability to introduce innovations during life cycle pr ocesses at a low cost and shortest time. 17 This allows the product to adapt and be redesigned according to contextual changes and opportunities, i.e., flexibility af ter the product has been released. Such examples are quite common in the industry and can be clearly seen in the automotive industry. In the automotive industry, cosmetic changes to a product happen often within a
18 product life cycle based on changing customer views and perceptions. Some cars even undergo major changes in the form of engine capacity and technolo gy to cater to the customer demands. According to Tommaso Buganza and Robert o Verganti, the metrics for LCF (Life Cycle Flexibility) are (Buganza 2006) : 1. Frequency of adaptation: Number of new features per unit time. 2. Rapidity of adaptation: Inverse of the tim e needed to adapt to the service/product as a reaction to the launch of the new f eature by the competitor = (1/Time needed for reaction). 3. Quality of adaptation: Ability to be consistent with quality through different service package adaptations such as robustness as a dimension of quality. In our proposed thesis we have iden tified certain metrics for innovation which were proposed in a more generic way by Amy Muller, Liisa Valikangas and Paul Merlyn (Muller 2005) to cater closely to the heal thcare industry and which will make it more feasible for data collection. These innovati on metrics are essentially product based and the ones which are the most appropriate and will make data collection feasible will be considered. The innovation metrics we have id entified for data collection are (adapted from (Muller 2005)) : 1. Measure R&D budget as a % of annual sales of a particular product. 2. No. of patents/new ideas filed by the company in the last year/last month. 3. Measure % of capital that is i nvested in radical projects. 4. Average time required from idea ge neration to product/service launch. 5. Ratio of revenue from innovative/new products to commodities.
19 6. Measure % of employees that are involve d in developing an innovative product. 7. Measure innovation revenue per empl oyee from the new product/service developed. 8. % of management that is accountable to development of a new product in terms of time (man hour). 9. No. of incentive schemes to support innovation. Out of these metrics only few will be consider ed based on accessibility of data from the three different sources. 4.4 Impact of Purchasing Groups The purchasing groups play a very impor tant role in manipulation of the commodity prices. The bigger pl ayers in the market exploi t their leverage with the supplier resulting in the wiping out of the smaller players who lack the negotiating capability. Due to the concentrated market sh are by the big dominant players, entry of small players in the market becomes very difficult (Sethi 2006). It is prohibitively expensive for a new entrant to gain significant market share because most current and potential customers are alrea dy locked in to existing GPOs through various contractual arrangements (Sethi 2006). The extermination of smaller players from the market creates an oligopolistic market scen ario where the bigger ones so metimes dictate terms to the buyers as well as the suppliers. This sometimes results in poor service quality by the healthcare organizations. The growth of bigger purchasing groups may result as an advantage to the existing suppliers as smaller volume suppliers may lose out in a price
20 conscious market even though their product may be technologically superior. This affects the quality of products in the long run. 4.5 Classifications of GPOs GPOs can be classified based on th eir ownership, membership, geographical scope, and size (Burns 2002). When GPOs are classified based on ownership, they are distinguished as for-profit, non-profit and public GPOs (Burns 2002). The two largest for-profit GPOs are divisions of the two larg est investor owned hos pital systems: HCA ( Health Trust Purchasing Group) and Tenet (BuyPower) (Burns 2002). The three largest non profit GPOs are hospital cooperatives like Novation, which is a group purchasing arm for VHA/UHC (Burns 2002). The larg est public GPO is the VA. Healthcare organizations which are a part of for-profit and the VA systems are more committed to their group purchasing contracts. Healthcare organiza tions within the n on profit alliances join their GPOs voluntarily (Burns 2002). GPOs also differ in the type of membership. Some GPOs are committed to the larger healthcare organizations where as some of them focus on smaller buyers like ambulatory centers and physicians offices. Many GPOs try to focus on two types of market in order to have a stronger presence (Burns 2002). Many GPOs differ in their reach to cater to different markets. Some or rather smaller players focus on regional healthcare or ganizations. This helps them to consolidate their resources and sometimes perform bette r in logistical operations than National players. Large GPOs generally focus on a Natio nal level. They have better reach which is facilitated by their financial muscle and volumes of purchases. These GPOs sometimes
result in extermination of regional players which has been discussed earlier. Figure 4.3 briefly summarizes the classification of GPOs. Figure 4.3 Classification of GPOs 21
Figure 4.4 Ranking of GPOs by Contract Purchases and Memberships 22
Figure 4.5 Market-share of GPOs 23
24 CHAPTER 5 COST COMPARISON ANALYSIS In this project, we would like to focus on two aspects of hea lthcare industry. The first aspect would be comparing the prices of the bulk items across three different procurement models. The second aspect woul d be to compare the degree of access to innovative items across different procurem ent model using a technique called data envelopment analysis (DEA). The second part of the research is expl ained in chapter 6. 5.1 Cost Comparison Methodology Firstly, we would like to capture the total cost of procuring items through three different procurement models. This involve s comparison of procurement models of commodities through a Self sourcing unit, a Na tional GPO and a Hybrid model. A Self sourcing healthcare organization procures items through indivi dual contracts with vendors and manufacturers. A healthcare organization affiliated to a National GPO procures most of its items through the GPO and is bounded by GPO contracts. These organizations also have to take into acc ount the mandatory compliance rate sometimes being enforced by some GPOs. It is important to note here that during the course of interaction with the staff of healthcare organizations under consideration in this study, the compliance rate was found to vary among GPOs ranging from 60 percent to 90 percent. The Hybrid model in the study features healthcare organizations which are affiliated to a National GPO as well as to a regional GPO. In this model, the healthcare organization
25 procures items from a National GPO as well as a regional GPO and has the flexibility to choose products from either of them depe nding on the lower prices. This chapter will include a comparison of the costs associated with these procurement models. In order to achieve this, a clear understandi ng of the series of processe s and operations undertaken in each of these procurement models is requi red. This involved mapping out the entire process/operation in the form of a flow diagram (Process Map) with each operation described briefly and the resour ces associated with it for ea ch of the procurement model (Please refer appendix A, B and C). 5.1.1 Building the Cost Model The cost model was designed to capture an estimated overall price/cost of the items which includes the overhead. Please refer figure 5.1 on page 29 which displays the screenshot of the MS Excel based model. Primary Overhead includes the human reso urce cost only which means the salary of individuals involved in the purchasing opera tion or part of their function relates to purchasing. Secondary overhead comprises of the administrative fees paid by the healthcare organization to the GPO (applicable only for GPO members) and the rebates gained by the hospital from the GPO due to va rious reasons like compliance/loyalty etc. Primary Overhead has been cla ssified into seven types: 1. Legal staff negotiates the contracts with the supplier. 2. Follow up staff checks the price and the quality of the suppliers (gets the price quotes) and chooses the suppliers.
26 3. Administration staff works on the purchas e orders and sends the orders to the suppliers. 4. Inventory staff maintains the inventor y and works on them and notifies when there is some short fall of some items. 5. Finance staff processes the funding a ssociated with funding and releases the money. 6. Stocking staff manages the stocking of the products in the warehouse after they are obtained from the suppliers. 7. Transportation Staff manages the transp ortation of products/items within the campus. This is a general classification and only those teams/buckets which are applicable to a particular hospital or healthcare orga nization are taken into consideration. For example: There may be legal staff involved in the procurement of items for hospital A whereas it might be absent for hospital B. In calculating the overhead, the average annual salaries of the individuals or the titles th ey represent are taken. Once the final annual overhead is calculated (sum of the annual average salaries of all the individuals involved), it is then calculated per day by taking the number of work days in a year as 260. Also, it should be noted here that the proportionate salary of the average annual salary should be taken into comparison. If a staff has a fraction of the responsibility involved in procuring operations, then that fraction should be multiplied with the annual average salary and then that amount should be filled in as the annua l average salary. For
27 example, if staff A earns $50,000 per year and 50% of his job respons ibilities fall in the procurement operations, then .50* 50,000=25,000 will be his annual average salary. Secondary Overhead has been classified into: 1. Administrative fees The fee paid by the GPO members to the GPO on an annual basis. This fee is only applicable to the healthcare organization associated with the GPO. This amount calculated on a yearly basis is added to the Total Overhead in a year. 2. Rebates The money paid to the GPO members by the GPO for a variety of reasons. This could be loyalty of the me mber to the GPO or for maintaining good compliance rates or sometimes to clinch deals with the me mbers in a very competitive market. This amount taken annually is subtracted from the Total Overhead calculated annually. Spending per category is defined as the total amount spent on each category like drugs, office supplies, medical devices, etc. We have coined a term ICV which is the Total average cash value of the items in th e inventory per day (ICV). The ICV of the four categories in consideration are finally added to get the total amount spent or total ICV per day. The cost model is then built on the average daily inventory of the items (for example: 1, 3, 6, 10, 200, etc.) wh ich are procured and their s tandard price in the next column in the spreadsheet. The product of th ese two will give the Total $$ amount/day of products in the column next to th e standard price in the spreadsheet. Spending % Value is the percentage of Total $$ amount/day spent on each item to the total amount spent or total ICV per day.
28 % Overhead is the product of the Spending % Value with total overhead/day to get the % of overhead added in every product's cost. The sum of % Overhead and the Total $$ amount/day will give an estimated Overall Cost of each item. This Overall Cost is then divided by the average daily inventory to finally calculate the estimated Unit Overall Cost for each of the items. The estimated Unit Overall Cost for each item will be taken for comp arative study. It is this cost which will be used for the comparison of each item across the different healthcare organizations. Maintaining the confidentiality of data has been given the utmost importance in this thesis. This cost model based on the MS Excel was created to get an estimated pricing of the products/items, since informati on regarding actual pricing of the products could not be accessed by us. The Excel sheet has been designed in a way that the items which are commonly procured ar e divided into two categories (Please refe r figure 5.1 on page 29). They are medical devices and surg ical supplies. The excel model would be populated with 50 to 100 items for each of the above mentioned categories for the procurement models (with the help of in formation accessed from each of these three healthcare centers respectively) being in operation in the healthcare organizations considered in the study. The items in each of those two categories must be common to all the three healthcare centers havi ng different procurement models. To maintain the confidentiality, the data concerning overhead, spending per category, standard price and daily inventory ar e entered by the staff from the hospital. After the data was filled in these shaded cells (refer to the screenshot), the spreadsheet would automatically calculate the overhead, overhead% and finally the unit overall
cost Also, to maintain error proofing, the cells other than those shaded ones (where the data is entered by the hospital staff) were formulated and locked This is the column we were interested in and this column unit overall cost and the products/items column were then copied and pasted in a different ex cel sheet and sent to us. We had no access to the actual pricing information and actual salary figures which are confidential. Figure 5.1 Screen Shot of Cost Model Template 5.1.2 Comparison of Unit Overall Cost (Wilcoxon Paired Test) The unit overall cost of each of the it ems in the two categor ies, i.e., medical devices and surgical devices were used for the comparison model to compare the prices of the bulk items. 29 The categories medical devices and su rgical devices were taken into consideration, because these were the two categories of products which were common across the three healthcare organizations in this comparison study. During the course of
this research, we were assist ed by the staff from the materi als management department of all the three healthcare orga nizations. Also, there was no data available for the procurement of office supply equipment. Am ong the inventory of bul k items which were procured by the three hea lthcare organizations, we coul d get 222 items which were common across all the three healthcare orga nizations. This number could be further broken down into 156 medical device items and 66 surgical devices items. Utmost effort was made to match the products having sim ilar generic names and features. The data obtained from the three health care organizations were non-para metric in nature which is shown in the figure 5.2 below. HC Setting C46.041068 28.225177 24.256975 21.218927 20.097927 16.514731 14.082562 13.572106 13.211785 12.521169 11.11778 9.888821 8.894224 8.137258 8.007142 7.396598 6.796062 6.365678 6.035384 5.164607 4.80086 4.1439 3.913491 3.234263 3.032122 2.962643 2.792491 2.502232 2.201964 1.991093 1.77158 1.40125 1.161036 1.000893 0.920821 0.725647 0.680607 0.570509 0.47042 0.400357 0.323426 0.230205 0.161713 0.050045 Frequency5 4 3 2 1 0 Figure 5.2 Distribution of Data Obtained from Healthcare Organization C Since prices obtained from the three h ealthcare organizations do not follow a normal distribution, we considered implementing Wilcoxon signed-rank test. 30
31 Wilcoxon signed-rank test is a non parametric alternative to the paired Students t-test for comparison of two related samples of data. In this study, we are comparing the prices of same bulk items (paired) across two healthcare organizations at a time, i.e., first we will be comparing the prices of bulk it ems between healthcare organization A and healthcare organization B, followed by compar ison between healthcare organizations A and C, and between B and C. Wilcoxon test is used to compare differences between measurements at interval levels. This enab les to compare differences between arbitrary pairs of data. 1. Wilcoxon test assumes that the difference between two samples of data, i.e. d i = A i B i for i = 1 to..n. are simulated to be independent. Where A and B are two related samples of data and d is the difference between these two samples at each measurement. 2. Each difference d i is drawn from a continuous population. Testing the null hypothesis (f or a paired t-test): H o : d = 0 H 1 : d 0 Where d is the mean difference between the m easurements. In a paired t-test, the null hypothesis H o : d = 0 will be rejected if the m ean difference between the sample measurements is not equal to zero. However, the null hypothesis in Wilcoxon test is that the median difference between pairs of observa tions is zero. By testing and rejecting the null hypothesis, it can be shown that the data samples do not have the same median and are drawn from different populations. This is done by ranking the ab solute value of the differences between observations from the sm allest to the largest, with the smallest
32 difference getting a rank of 1, followed by the next larger difference getting the 2 nd rank, etc. Ties are given average ranks. The ranks of all differences in the (positive) direction are summed, and the ranks of all differences in the negative directi on are summed. In this study, only after the null hypothesis in the W ilcoxon test has been rejected, the cost efficiency of one procurement model can be compared with the other by measuring the mean difference of prices and the mean percentage differences of prices (difference between the prices of commodities and expressed as a percentage of the price of the commodity from which it is su btracted). If the null hypothesis is not rejected, then the mean difference of the prices and the mean percentage difference between the samples will be zero and the cost efficiency of one procurement model versus the other cannot be determined. For example: If we compare procurement models of healthcare (now onwards we would call healthcare as HC) organization A ve rsus HC organization B, then the mean difference of prices of all the bulk items is calculated, i.e., we are subtracting the prices of the bulk items of HC organizati on B from HC organization A. If the mean difference is a positive value, then we can conclude that HC organization B is more cost efficient than HC organization A or vice versa. This will enable us to rank the different procurement models in terms of cost efficiency. In this study, comparison model will comprise of HC organization A versus HC organization B, HC organization A versus HC organization C and HC organization B versus HC organizatio n C, with the latter models procurement prices subtracted from the former ones. Similarly, the percentage difference between the prices of all the commodities are calculated, and if the mean percentage difference of all the commodities in comparison is
zero, then the two procurement models cannot be compared. If its not zero but a positive or a negative value then there exists a difference and it can be determined which procurement model is more cost efficient. When HC organization A and B are compared the percentage differe nce is calculated by % difference = ((Cost A Cost B)/Cost A)*100. The mean percentage difference is given by = ( i n % difference)/n (where n = 222). The null hypothesis is tested by the relations below. (Adapted from http ://www.nist.gov/speech/test s/sigtests/wilcoxon.htm ): The mean is given by 4 )1( nn Eq. 5.1 The variance is given by 24 )12)(1(2 nnn Eq. 5.2 Sum of the positive and negative ranks 2 )1( nn ZZ Eq. 5.3 Where Z + and Z are sum of positive and negative ranks respectively. The test statistic W is W= Z Eq. 5.4 The null hypothesis in the Wilc oxon test will be rejected if P(W) value Eq. 5.5 Where = P(type I error) = P(reject H o |H o is true), is the significance level. The assumption here is that the significance level of the test is simulated to be 0.05. Therefore the percent confidence interval of the test is 100(1 ) = 95. 33
As discussed earlier, only if the null hypot hesis is rejected, we can compare the cost efficiency between the procurements models and rank them accordingly from the most to the least. The procurement model with the lowest price in the comparison study will emerge as the most economical leader in procurement operations and also help to determine whether GPOs are the most economical ways of procuring items. 5.2 Results of Cost Comparison As mentioned in the previous section, the cost comparison study was performed by matching almost exact bulk items across thr ee different procurement models, i.e., Self sourcing, GPO model and Hybrid model. All in all, 222 bulk items were found common across these three procurement models which can be further classified as 156 medical devices and 66 surgical devices. 5.2.1. Procurement Model A versus Procurement Model B In this cost comparison model we co mpared the procurement model of HC organization A versus HC organization B, i.e. the comparison of Self source model with that of National GPO model. The pr ices of each of the bulk items (totaling 222 items) of the HC organization B are subtracted from those of HC organization A to get the differences at each sample point. Using the assumptions and equations mentioned in section 5.1.2, we get n = 222. The mean is given by Eq 5.1 4 )1( nn = 12,376.5 34
The variance is given by Eq. 6.2 24 )12)(1(2 nnn = 917,923.75 After running Wilcoxon test in the MS excel solver for the sum of ranks, the results are displayed in table 5.1 Table 5.1 Wilcoxon Results of Comparison of HC A and HC B Differences N Rank-Sum Negative 59 6991 Positive 163 17762 Zero 0 P 1.89725E08 From table 5.1 it can be said the number of positive ranks are higher than negative ranks. Thus, sum of positive ranks and negative ranks 2 )1( nn ZZ = 24,753. The Z + and Z values are 17762 and 6991 respectively. Thus te st statistic given by Eq. 6.4 W= Z = 5.621. Now, P(5.621), i.e. the significance of th e difference from the table 7.1 as given by the solver is 1.89725E-08. Thus using Eq. 5.5, the null hypothesi s in the Wilcoxon test will be rejected as: P(W) value = 1.89725E-08 < 0.05 Since the null hypothesis is rejected, two procurement models can be compared against each other based on their cost efficien cy. The mean difference when the prices of commodities of HC organization B (GPO model) are subtracted from those of HC organization A is $2.77, which is a positive value. The mean percentage difference of the prices of the commodities is 6.17 percent, ag ain a positive value. Thus, we can say that 35
the average prices of commodities procured by the Self source model are more than the GPO model as shown by a positive value of mean difference and mean percentage difference. Thus, in this comparison m odel the GPO procurement model of HC organization B is more cost efficient than that of Self sourcing m odel of HC organization A. 5.2.2. Procurement Model A versus Procurement Model C In this cost comparison model we co mpared the procurement model of HC organization A versus HC organization C, i.e. the comparison of Self source model with that of Hybrid model which encomp asses procurement through a National GPO as well as a regional GPO. The pr ices of each of the bulk item s (totaling 222 items) of the HC organization C are s ubtracted from those of HC organization A to get the differences at each sample point. Using the assumptions and equations mentioned in section 5.1.2, and the values of mean, variance and n= 222, the sum of positive ranks is displayed in table 5.2. Table 5.2 Wilcoxon Results of Comparison of HC A and HC C Differences N Rank-Sum Negative 51 4967 Positive 171 19786 Zero 0 P 1.04361E14 From the table 5.2 it can be said the number of positive ranks are higher than the negative ranks. Thus, sum of positive ranks and negative ranks 2 )1( nn ZZ = 36
24,753. The Z + and Z values are 17762 and 6991 respectivel y. Thus, test statistic given by Eq. 5.4 W= Z = 7.73 Now, P(7.73), i.e. the significance of the difference from the table 5.2 as given by the solver is 1.04361E-14. Thus, using Eq. 5.5, the null hypothesis in the Wilcoxon test will be rejected as: P(W) value = 1.04361E-14 < 0.05 Since the null hypothesis is rejected, the cost effici ency of one model versus the other can be determined. The mean difference when the prices of commodities of HC organization C (Hybrid model) are subtracted from those of HC organization A is $3.96, which is a positive value and the mean percentage difference is 14.87 %, again a positive value. Thus, we can say that the average pr ices of commodities procured by the Self source model are more than the Hybrid model as shown by these positive values. Thus, in this comparison model the Hybrid procurement model of HC organization C is more cost efficient than that of Self sourcing mode l of HC organization A. One interesting observation can be made here, the mean differe nce of prices between HC organization A and HC organization C (when subtracted) is more than the mean difference of prices between HC organization A and HC organi zation B. Thus, we can say that HC organization C is not only more cost effi cient than HC organi zation A but also HC organization B. This can be illustrated further in the following section which shows the comparison between HC organiza tion B and HC organization C. 37
5.2.3. Procurement Model B versus Procurement Model C In this cost comparison model we co mpared the procurement model of HC organization B versus HC organization C, i. e. the comparison of National GPO model with that of Hybrid model. The prices of each of the bulk items (totaling 222 items) of the HC organization C are subtracted from those of HC organization B to get the differences at each sample point. Again rep eating the steps mentioned in the preceding sections using the assumptions and equations mentioned in section 5.1.2, and the values of mean, variance and n= 222 the sum of positive ranks is displayed in table 5.3. Table 5.3 Wilcoxon Results of Comparison of HC B and HC C Differences N Rank-Sum Negative 97 10243 Positive 125 14510 Zero 0 P 0.025957856 From the table 5.3 it can be said the number of positive ranks are higher than negative ranks. Thus, sum of positive ranks and negative ranks 2 )1( nn ZZ = 24,753. The Z + and Z values are 17762 and 6991 respective ly. Thus test st atistic given by Eq. 5.4 W= Z = 2.226. Now, P(7.73), i.e. the significance of the difference from the table 5.3 as given by the solver is 0.025957856. Thus using Eq. 5.5, the null hypothesis in the Wilcoxon test will be rejected as: P(W) value = 0.025957856 < 0.05. Again while comparing the cost efficiency of the GPO model versus the Hybrid model, the mean difference when the pric es of commodities of HC organization C 38
39 (Hybrid model) are subtracted from those of HC organizati on B (GPO model) is $1.18, and the mean percentage difference is 11.61 pe rcent. Thus, we can say that the average prices of commodities procured by the GPO mode l are more than the Hybrid model. Thus in this comparison model the Hybrid procur ement model of HC organization C is more cost efficient than that of GPO model of HC orga nization B. However, it should be noted that mean difference of prices between thes e two models is the least, which goes on to show that these two models are quite close in terms of cost efficiency with Hybrid model being the most. 5.2.4. Summarization of Re sults of Cost Comparison Study The results obtained by the comparison study shows the comparative cost efficiency of each of the three procurement models in consideration. From the results obtained above, it can be conc luded that GPOs overall deliv er products to healthcare organizations at a much reduced price, or in other words they are more cost efficient compared to Self sourcing models. This can be attributed to the vol ume of bulk products the GPOs carry in their inventory and their negotiating skills with the manufacturers. However in this study, two healthcare organi zations B and C are affiliated to GPOs with C being further associated with a regional GPO. HC organization C fared the best with being the most cost efficient among the th ree models due to their flexibility of procurement contracts with a National GPO as well as a regional GPO. During the course of interaction, staff from HC organiza tion C acknowledged that affiliation to both National GPO and regional GPO is important to drive prices low. Moreover, this gives the model more leverage to procure items through two different sources depending on lower prices. Apart from the be nefit of choosing the lowest priced products being offered
40 by the competing National and regional GPO, another factor which might be responsible for the Hybrid model to achieve the highest cost efficiency would probably be larger volume of items. High compliance rate with the National as well as regional GPO contracts may be another reason why the prices of the items in the Hybrid model are low as compared to others. During the course of interaction with the staff from HC organization C, it was brought to our knowledge that the compliance rate is very high and that helps them to drive costs low. The compliance rate varies from one healthcare organization to another and ha s a significant effect on the pricing of the items being procured. By staying within the contract with the GPOs, the healthcare organizations are making use of the power enjoyed by the GPOs with manufacturers in reducing costs. As suggested in the past literature, GPOs have the capacity to supply the varied items at large volumes as compared to small scale manufacturers. This might be the same reason why HC organization A is the least cost effici ent as all the items are Self sourced from individual manufacturers loca lly. By increasing the volume of items, the cost per item reduces, and this can be exploited by many healthcare organizations which have high volumes of procurement to get affiliated to a GPO and contract for a variety of items. Thus, in this study we can rank the Hybrid model of HC organization C as the most cost efficient, followe d by GPO model of HC organi zation B and the least being Self source model of HC A. The table 5.4 in the following page would summarize the results.
Table 5.4 Cost Efficiency of Procurement Models Healthcare Organization Procurement Model Ranking based on Cost Efficiency (Most to Least) C Hybrid 1 B GPO 2 A Self 3 5.3 Analysis of Cost Comparison The analysis of the results for each of the three comparison studies of procurement models has been classified in to further three sections, i.e, overall comparison, medical devices comparison and surgical devices comparison. 5.3.1. Overall Comparison Overall comparison involves the comparis on of the total price difference and the mean price difference of all the bulk it ems (totaling 222 in number) between HC organizations A and B, A and C and B and C. Overall Comparison A B, $615.79 A C, $878.71 B C, $262.93$0.00$200.00$400.00$600.00$800.00$1,000.0 0 A B A C B CHC OrganizationsTotal Price Difference Total Price Difference Figure 5.3 (a) Overall Comparison Based on Total Price Difference 41
A B, $2.77 A C, $3.96 B C, $1.18 $0.00$1.00$2.00$3.00$4.00Mean Price Difference A B A C B CHC OrganizationsOverall Comparison Mean Price Difference Figure 5.3 (b) Overall Comparison Based on Mean Price Difference Overall ComparisonA B, 6.17% A C, 14.87% B C, 11.61% 0.00%5.00%10.00%15.00%20.00% A B A C B CHC OrganizationsMean Percentage Difference Mean Percentage Difference Figure 5.3 (c) Overall Comparison Ba sed on Mean Percentage Difference From the figures 5.3(a) and 5.3(b), it can be concluded that th e Hybrid model of HC organization C is the most cost effi cient, followed by the GPO model of HC organization B and the Self sour cing model of HC A being the least efficient. This is because the difference of both the total price as well as the mean price is maximum with a positive value of $878.71 and $3.96 respecti vely when the HC organization C is compared with HC organization A (with prices of HC organization C subtracted from HC 42
43 organization A) with respect to other co mparison between HC or ganization B and HC organization A. From figure 5.3 (c), the mean percentage difference between HC organization A and HC organization C (14.87 percent) is also higher than HC organization A and HC organiza tion B (6.17 percent). This again proves that the Hybrid model is the most cost efficient as the percen tage difference is the largest when compared with HC organization A as compared to wh en HC organization B with HC organization A. However, the difference in the total pri ce as well as the mean price of items between HC organization B and HC orga nization C (with prices of HC organization C subtracted from HC organization B) are smaller positive numbers of $262.93 and $1.18 (HC organization C being more cost efficient) with respect to the other two comparisons. This can be due to the fact that both the healthcar e organizations are affiliated to a GPO which helps to bring down the cost of procuremen t. The Hybrid model of HC organization C has more leverage to choose between commoditie s based on lower prices as it is affiliated to a National GPO as well as a regional GPO. As mentioned earlier and acknowledged during the course of this study by the staff of HC organization C, in a Hybrid model the healthcare organization has more freedom to negotiate the prices of items with the National GPO and many times they procure ite ms from the regional GPO at costs lower than those offered by a National GPO. In f act, as acknowledged by the HC organization C staff, that by negotiating cont racts with regional GPOs, th e healthcare organization can get rebates on a yearly or quarterly basis whic h can result in huge savings in the long run. This may not be possible for National GPOs, as they are bounded by much standardized pricing across the country and may have many healthcare organizations affiliated to them. Based on the past literature and recognized by the staff of HC organization C, the
regional GPOs have the added advantages of better knowledge of regional market dynamics and may provide better logistics and warehousing facilities to the regional healthcare organizations as compared to the National GPOs. At the same time, the regional GPOs have fairly large invent ory and sufficient number of healthcare organizations in that particular region to k eep costs low. Thus, a healthcare organization following a Hybrid model of procurement i nvolving a National GPO and a regional GPO gets the best of both worlds and has more flex ibility in choice of products as compared to a healthcare organization following only the GPO model. 5.3.2. Medical Devices Comparison This gives more in dept h analysis of the cost comp arison of procured medical devices by comparing the total price difference and the mean price difference of only the medical devices (totaling 156 in number) be tween HC organizations A and B, A and C and B and C. Medical Devices ComparisonA B, $572.81 A C, $646.09 B C, $73.28 $0.00$200.00$400.00$600.00$800.00 A B A C B CHC OrganizationsTotal Price Difference Total Price Difference Figure 5.4 (a) Medical Device Compar ison Based on Total Price Difference 44
A B, $3.67 A C, $4.14 B C, $0.47 $0.00$1.00$2.00$3.00$4.00$5.00Mean Price Difference A B A C B CHC OrganizationsMedical Devices Comparison Mean Price Difference Figure 5.4 (b) Medical Device Compar ison Based on Mean Price Difference From figures 5.4(a) and 5.4( b), it can be again conclude d that Hybrid model is the most cost efficient followed by GPO mode l and the least being Self sourcing model concerning the procurement of me dical devices. However, it should be noted here that the differences in total price as well as the mean price of medical devi ces when healthcare organization B and C (prices of medical devices of HC organization C being subtracted from those of HC organization B) are comp ared are very small positive values. This suggests that though Hybrid model followed by HC organization C is more efficient than the GPO model followed by HC organization B, but its by a very narrow margin. With the difference in total price and mean price being small, positive numbers of $73.28 and $0.47, respectively, it can be concluded that the cost efficiency of GPO model of HC organization B comes very close to that of H ybrid model of HC organization C (almost as cost efficient as C) when the procuremen t of medical device items is concerned. 45
5.3.3. Surgical Devices Comparison This section involves the comparison of the total price difference and the mean price difference of only the procured surg ical device items (totaling 66 in number) between HC organizations A and B, A and C and B and C. Surgical Devices ComparisonA B, $42.98 A C, $232.63 B C, $189.65$0.00$50.00$100.00$150.00$200.00$250.00 A B A C B CHC OrganizationsTotal Price Difference Total Price Difference Figure 5.5(a) Surgical Device Compar ison Based on Total Price Difference A B, $0.65 A C, $3.52 B C, $2.87 $0.00$1.00$2.00$3.00$4.00Mean Price Difference A B A C B CHC OrganizationsSurgical Devices Comparison Mean Price Difference Figure 5.5 (b) Surgical Device Comparison Based on Mean Price Difference From figures 5.5(a) and 5.5( b), the analysis of the comparative cost efficiency of the procurement models leads to the same infe rence of Hybrid model being the most cost efficient, followed by the Hybrid model and the Self sourcing one being the least when 46
47 surgical devices are concerned. It is important to note that the GPO model fairs poorly in terms of cost efficiency compared to the H ybrid model. Its just the reversal of GPO models performance in the medical devices comparison. In fact, the GPO affiliated HC organization B is slightly better than the Se lf sourcing model of HC organization A as displayed by the small positive values of differences of total price and mean price when HC organizations A and B are compared. Here the Hybrid model of HC organization C outperforms the GPO model of HC organiza tion B by a big margin in terms of cost efficiency. The differences in the total price and the mean price of the surgical devices procured by the HC organization B and HC or ganization C are quite large positive values of $189.65 and $2.87 respectively which suggest s that the GPO model is trailing behind the Hybrid model in terms of co st efficiency significantly.
48 CHAPTER 6 MEASUREMENT & COMPARISON OF INNOVATION (DEA) 6.1 Methodology of Innovation M easurement & Cost Comparison This is the second aspect of our research. Here we will be identifying certain innovation metrics in measuring the degree of access to innovative products procured through offcontract as well as on-contract negotiations in different procurement models. Innovative products in this study can be classified as those products which have a fairly higher degree of sophistication and advanced technologies as compared to bulk items. Common items which falls under this catego ry are temporary pacemakers, splines, ventilators, beds, etc, which might be procured in very fe w quantities or in low numbers for specialized medical cases. This aspect of the project would enable us to compare the different procurement models based on the off-contract and on-contract price of innovative products and degree of access to inno vative technologies. This is independent of the cost comparison study and would involve more than three heal thcare organizations. During the course of the study it was found that there exists lo t of variation in the models employed by the healthcare organizations in procurement of innovative items. Many healthcare organizations procure innovative items strictly on an on-contract basis either through a GPO or a regional GPO whereas some healthcare organizations purchase these items through off-contract means and some procure similar type of items through both on-contract as well as off-c ontract means. This would throw light on the concern as mentioned in the past literature (Zweig 1998) that sometimes National GPOs (mostly on-
49 contract purchases) are a hi ndrance to the entry of nich e manufacturers of innovative products (mostly off-contract purchases) and as a result th e healthcare organizations affiliated to only GPOs may sometime lose out on the more advanced technologies available in the market. The items which are procured through GPOs are termed as on contract purchased items and the ones which are procured from local manufacturers or vendor which are not affiliated to an y GPO are called off-contract items. In this study three types of models of procurement of innovative items are studied: 1. Healthcare organizations which pr ocure innovative items only through oncontract purchases, i.e. through contracts with GPOs. 2. Healthcare organizations which procure innovative items only through offcontract purchases, i.e. through contracts with i ndividual manufacturers and vendors not affiliated to any National or regional GPO. 3. Healthcare organizations which procur e innovative items through on-contract purchases as well as off-contract purchas es, i.e., again different models of a particular generic item like pacemaker, purchased though both the sources (dual sourcing). 6.1.1 Identifying Innovation Metric Based on the literature research, we have identified certain innovation metrics which will help us in measuring access to innovative technologies. The innovation metrics we have identified for data collection can be classified into two types: Product Innovative Metrics (metri cs specific to the product): 1. Product features and specifications of the product.
50 2. Life cycle of the product. 3. Warranty details of the product. 4. Support from the manufacturer of the produc t in terms of training and technical expertise. 5. Ease of operation of the product. 6. Reliability and quali ty of the product. Corporate Innovative Metrics (ada pted from (Muller 2005)): These are the metrics applicable at the corporate level for the manufacturers of innovative products whic h are listed below: 1. Measure R&D budget as a % of annual sale s of a particular product manufacturer. 2. No. of patents/new ideas filed by the ma nufacturing company of that particular item in the last year/last month. 3. Measure % of capital that is invested in radical projects by the company manufacturing the innovative product. 4. Ratio of revenue from innovative/new products to commodities. 5. Measure % of employees that are involve d in developing an innovative product. 6. Measure innovation revenue per empl oyee from the new product/service developed. 7. % of management that is accountable to development of a new product in terms of time (man hour). 8. No. of incentive schemes to support innovation. The most substantial metrics will be considered which is totally dependent on accessibility and feasibility of data from the different sources, i.e., the data obtained from
51 the healthcare organizations as well as the product manufacturers. Data concerning innovation metrics will be acces sed from these sources and analyzed using the Delphi Method. 6.1.2 Analyzing Innovation Me tric Using Delphi Method The data available for the innovative products from different sources will be utilized to measure the degree of access to innovative technologies of the healthcare organizations which procures that particul ar item. To measure the degree of access of innovation, the Delphi method will be used wh ich will enable us to get an innovation score which is discussed in the latter part of this study. Delphi method is extremely useful in cas es where there is lack of scientific knowledge. Delphi method becomes handy in forecasting and making judgments. This involves expert opinion, intui tion and experience. Most of the Delphi applications are used for generating information for decision making Delphi method involves a panel of expert s from the related disciplines who are given questionnaires concerning the partic ular subject. The experts chosen are knowledgeable individuals who can draw from their extensiv e experience to assist in forecasting results. In this study, the panel of experts will involve physicians who use the products on a daily basis and material management staff who procure these items when they are on-contract. During the initial contact, the nominated persons are told about the Delphi and invited to participate. They are a ssured of anonymity in the sense that none of their statements will be attributed to them by name (Gordon 1994). Each expert is provided with a feedback on the preceding round of replies before the beginning of the next round of questionnaire. In the first round the participants are asked to provide their
52 views on the subject in discussion. Then an an alysis of the first round will throw light on the range of opinions. In the second round, the range would be presented to the group, and experts holding opini ons at the extremes of the range would be asked to reassess their opinions in view of the group's range and pr ovide reasons for their positions (adapted from Theodore (Gordon 1994)). These reasons would be synthesized by the researchers at the end of round two; the synthesized r easons would form the basis for the third questionnaire (Gordon 1994). In the third round, the questionnaire comprises of the new opinions of the panel members. The opinions along with the reasons are then presented to the participants. Each member of the group would be asked to reassess his or her position in view of the reasons presented. They might also be asked to refu te, if appropriate, the extreme reasons with facts at their disposal (Gordon 1994). In a fourth and final round, these argumen ts would be presente d, along with the evolving group consensus, and a reassessment requested (Gordon 1994). In a sense, Delphi method is a controlled debate. Th e reasons for extreme opinions are made explicit, fed back coolly and wit hout anger or ranc or (Gordon 1994). The idea is that the consensus will lead to the best response. Statistically, the midpoint of responses is identified by the medi an score. With every round, the range of responses by experts is supposed to reduce whic h will help the median move closer to the best response. A flowchart of the Delphi method processes is shown in figure 6.1 on the next page. Some of the advantages of the Delphi me thod include that the panelists need not be physically present at the same location to give their responses and the process does not require agreement by all the members as cons ensus is sought to arrive at the median.
Start Define and identif y a p roble m Feedback and anal y sis of res p onses Preparation and distribution of questionnaire Selection of panel of members based on expertise. Has consensus been reache d ? Provide additional/requested info. Final consensus/re p or t Yes N o Figure 6.1 Flowchart Showing Pr ocesses of Delphi Method (Adapted from http://www.ryerson.ca/ ) 6.1.3 Innovation Metric S cale and Innovation Score After the opinions and the feedback e xpressed by the panel of experts, each innovative product is rated on a scale of 1 to 5 by these experts which has been termed as innovation metric scale (IMS). The IMS w ill be used to assign each product a particular rating termed in this study as i nnovation score from 1 to 5 with 1 being the 53
54 most innovative and 5 being the least. Thus, every product will have a specific innovation score from a range of 1 to 5 which will be used in the data envelopment analysis (DEA) later. 6.1.4 Theoretical Analysis versus Empirical Analysis During the course of this research, ge tting access to data from the product manufacturers as well as the healthcare organizations has b een a very thorny task since the start. Data concerning the pricing of innovative products, warranty details, product features manufacturers details and model numbers are crucial to have a realistic analysis. As mentioned earlier in the past literatu re (Zweig 1998; Everard 2005; Sethi 2006), the big National GPOs quite often create a hindran ce to the entry of manufacturers of high technology products in to the market. Due to this reason, as was mentioned in the past literature (Zweig 1998), physicians sometimes circumvent the hospital contracts with a GPO and procure these items th rough off-contract means, wh ich becomes an added cost to the healthcare organizations. Due to less vol ume of these items c oupled with high level of sophistication, healthcare (HC) organizati ons may not be in a position to negotiate and reduce costs. Also, the compliance rate of the HC organizations reduces as more and more physicians prefer the offcontract route. However, cont rary to the past concerns about the HC organization not maintaining th e compliance rate as discussed earlier, we found that based on the interaction and our correspondence with the materials management departments of almost seven HC organizations, that contract compliance is more or less enforced by these healthcare organization managements on the physicians. If a particular product is being preferred by th e physicians, the physician has to provide suitable justifications for choosing the particular product. The chances for the physician
55 preferred items to be approved by the mate rial management department for purchase would depend on strict evaluation of the products capabilities, long term cost savings and relevance. Only after the product has satisf ied the entire requirements specific to a particular HC organization, would the produc ts be approved for purchase. Once the product has been approved for purchase it becomes th e new standard a nd would be added in the list of on-contract items. Thus, by ensuring large volumes of purchase, the HC organizations tend to drive costs low. This trend was observed across all the seven HC organizations we had interacted. This made the accessibility of data even more difficult and so the comparison between on-contract items and off-contract ones could not be undertaken as all the HC organizations s eem to have products sourced through oncontract means only. Secondly, information regarding product manufacturers and warranty details were consid ered confidential by both the HC organizations and the manufacturers and could not be accessed by us. In the first aspect of this research project involving the comparison of cost of bulk items we could get hold of only an estimated price for each of those products using the MS Excel model and thus we could compare the estimated cost of those products. The information regarding manufacturers details, warranty, technical expe rtise (considered confidential) we re not required unlike in this second part. Without specific information of a product like features, model numbers, pricing and warranty details, it is impossible to carry out our research into measuring the degree of access of innovative technologies across different HC organizations following different procurement models. As a result, the main idea about this section is to propose a research methodology which can be implemente d if real data fr om the industry is available. This is more of a theoretical analys is and if empirical data is available, this
56 methodology can be used to realistically co mpare the HC organizations. In order to simulate real world scenarios, suitable and realistic data has been taken into consideration, which would give us simulated results. However, this research idea can be replicated not only in healthcare vertical bu t also other sectors where similar procurement models are followed and GPOs have been known to exist. The fundamental question which has been addressed in th is section is to determine whether items classified as innovative have the same levels of innovati on (compare the degree of innovation and cost of procurement) when they are procured by different means like on-contracting in the form of a GPO or off-contra cting through niche manufacturers. This also underlines the concerns in the past literature that Nationaliz ed GPOs cause a barrier to the entry of niche manufacturers and slow down the entry of new advanced products (Everard 2005) than currently available in the market. Data which is vital for undertaking Delphi method has been simulated and so is the outcome of De lphi method which is the innovation score. 6.1.5 Comparison and Ranking Using DEA In actual scenario with available real data after the products are assigned a particular innovation score by the panel of expe rts, a data envelopment analysis (DEA) is carried out to compare and rank every proc urement model followed by HC organizations considered in this study for a particular produ ct. For example, say healthcare organization (HC) 1 uses both off-contract and on-contract models to procure an innovative product like pacemaker. Thus it will have two diffe rent models of pacemakers with different pricing and different innovation score (every model of a particular generic item will have a unique pricing and innovation score), i.e., on-contract and off-contract pricing. So the pacemaker model procured by HC 1 by on-contract means with a unique pricing and
57 innovation score will be compared with the pa cemaker model procured by HC 1 with offcontract means with a different pricing a nd innovation score, as well as with other pacemaker models procured by other healthcare organizations using either of the three procurement models like only off-c ontract, only on-cont ract and both. 6.1.6 Data Envelopment Analysis (DEA) Data envelopment analysis is a perfor mance measurement approach used to measure the relative performance of a number of entities called decision making units (DMUs) by evaluating their effi ciencies. DMUs can be various entities like departments, HC organization, manufacturers etc. This is mostly used where there are multiple inputs and multiple outputs where the DMUs are rated based on their efficiency as there are limitations when multiple inputs and outputs are involved to evaluate efficiency of units in conventional statistical approaches. The statistical approaches reflect average or central tendency behavior of the observa tions while the DEA deals with the best performance and evaluates all performances by deviations from the efficient frontier line (Cooper 2006). The effici ent frontier line connects the most efficient DMUs and all the lesser efficient DMUs are either above or below this line in a output versus input graph. This approach helps to identify the performance leaders which have the most efficiency in a particular group and compares every DMU with these leaders. DEA had been used to benchmark particular organiza tions as most efficient ones to highlight inherent inefficiencies of the poor perfo rming ones in that industry vertical. DEA utilizes mathematical programming techniques which can handle large number of variables and rela tions (constraints) in terms of inputs and outputs and this relaxes the requirements that are often encountered when one is limited to choosing only
a few inputs and outputs because the techniques employed will otherwise encounter difficulties (Cooper 2006). For every DMU a fractional programming problem is formulated where the relative efficiency of the DMU is obtained by maximizing the objective function which is a ratio of output DMU weights to input DMU weights. The Fractional Programming (FP) solution for ev ery DMU produces weights which are most favorable to that particular DMU for maxi mizing efficiency. Since the objective function is a ratio of the DMU output weights to DMU i nput weights, the optimal efficiency is at most 1. The mathematical model is as follows (Cooper 2006) ),......1(1 0................. ,........., 0................ ,........., .................. .......... ............... .......... ............... .......... .................. .......... max21 21 11 11 2211 2211nj u uu v vv xv xv yu yu ST xv xvxv yu yuyus m mjm j sjs j mom o o sos o o Eq 6.1 The constraints signify that the ratio of the output weight s to input wei ghts should not exceed 1, i.e., the optimal objectiv e value can be at most 1. After replacing the above fractional progr amming model to linear programming model the basic DEA algebraic model becomes m iv s ru no xv yu ST xv yui r m i ioi s r ror m i ioi s r ror...,.........1;0 ..,.........1;0 ),.....1(,1 max1 1 1 1 Eq 6.2 58
59 Where v i is the optimal wei ght for the input item i and its magnitude expresses how highly the item is evaluated. Similarly, u r does the same for the output item r. (Cooper 2006). 6.1.7 Selection of Deci sion Making Units (DMUs) As mentioned earlier, non accessibility of re al data led us to consider realistic simulated data. In this section, the deci sion making units will be model type of product/name of hospital for a particular generic product. For example, for temporary pacemakers, the different DMUs will be model1/hospital 1 (Hybrid on-contract), followed by other different permutations. Th us, there will be a unique product, i.e., unique model of say pacemaker which will be compared with other models of pacemakers procured through different sources. Even within the sa me HC organization two different types of pacemakers may be pr ocured if they follow both on-contract as well as off-contract purchasing. The table 6.1 below displays all the DMUs which will be considered in this analysis. Table 6.1 Simulated DMUs DMUs Hospital Type Procurement model considered by the hospital. Model 1/Hosp A General Self sourcing off-contract Model 2/Hosp B General GP O model with on-contract Model 3/Hosp C General GPO model with off-contract Model 4/Hosp D (oncontract model of Hosp D) General GPO model with both off and oncontract purchasing Model 5/Hosp D (off-contract model of Hosp D) General GPO model with both off and oncontract purchasing
60 Table 6.1 (continued) DMUs Hospital Type Procurement model considered by the hospital. Model 6/Hosp E General Hybr id model with on-contract Model 7/Hosp F General Hybrid model with off-contract Model 8/Hosp G (oncontract model of Hosp G) General Hybrid model with both off and oncontract purchasing Model 9/Hosp G (off-contract model of Hosp G) General Hybrid model with both off and oncontract purchasing Model 10/Hosp H Specialty Specialty Hospital with Self sourcing (off-contract) Model 11/Hosp I Specialty Specialty Hospital with GPO model (on-contract) Model 12/Hosp J Specialty Specialty Hospital with GPO model (off-contract) Model 13/Hosp K Specialty Specialty Hospital with Hybrid model (on-contract) Model 14/Hosp L Specialty Specialty Hospital with Hybrid model (off-contract) Model 15/Hosp M (on-contract model of Hosp M) Specialty Specialty Hospital-GPO model with both off and on-contract purchasing Model 16/Hosp M (off-contract model of Hosp M) Specialty Specialty Hospital-GPO model with both off and on-contract purchasing Model 17/Hosp N (on-contract model of Hosp N) Specialty Specialty Hospital-Hybrid model with both off and on-contract purchasing Model 18/Hosp N (off-contract model of Hosp N) Specialty Specialty Hospital-Hybrid model with both off and on-contract purchasing The DMUs under consideration in this research are different models of a particular generic product like pacemakers s ourced from diverse healthcare organizations. There are two types of healthcare organizations under consideration (2 nd column in table 6.2 titled hospital type) i.e., general and special. General type represents HC organizations which cater to all sorts of me dical cases from orthopedics to pediatrics.
61 These may have a wide range of departments like cardiology, neur osurgery, orthopedics etc. The specialty type represents the HC organizations which cater to special treatments and research like cancer, cardiac ailmen ts, geriatric disord ers, neuro-surgery etc. These are more focused in treatment of special cases and research and tend to be more advanced over general HC organization. However they cater to a smaller population sample and it is simulated that the features of the items they procure are more sophisticated. The next sub classification of DMUs is the procurement model they follow like Self sourcing, GPO or Hybrid. Again thes e procurement models can be followed by either general or specialty HC organiza tion. These HC organizations following a particular procurement model for example Hy brid model can procure innovative items by only on-contract means, or only off-contract means or both (Model 8 and model 9). Sometimes the same hospital can procure two different models of an item with one being procured through on-contract wa y and the other through off-c ontract. It should be noted the models of products are un ique which are the DMUs in this study. For example: the model 2 is different from m odel 3 of a particular item as they are procured by two different HC organizations, with model 2 bein g procured by on-contract means which is being followed by hospital B whereas model 3 is being procured by on-contract means which is being followed by hospital C though hospital B and C are affiliated to a GPO. Similarly in a more complicated case where the same hospital follows two different sources of contracting, the models of the items procured will be different and unique for that particular s ource of contracting. For example: model 4 and model 5 are
62 two different models of an item procured by the same hospital using two different sources of contracting as shown in table 6.1. Sa me pattern is repeated in specialty HC organizations. However, Self sourcing HC or ganizations are unique as they do only offcontracting as they are not affiliated w ith any GPO or bounded by any contract. They procure their bulk items as well as innovative items the same way. DEA models vary from having single out put and single input to multiple inputs and outputs. In this research methodology, all the data concerni ng outputs and inputs have been realistically simulated due to non acc essibility of data from the industry. Two inputs are considered in this study with one output. These two inputs are in the form of: 1. Cost of innovative products. 2. Innovation Score (1 being the most innovative and 5 being the least). The output considered is the the number of hospital beds. This would give an idea about the maximum number of patients a hospital can treat. It is simulated and highlighted in the past literat ure that there is an underlyi ng link with the cost of the product as larger volume of products will drive costs low. Thus, it is simulated that if a hospital has the capacity to treat a large num ber of patients, its cost for procuring a particular item will be lower than another hospital which has lesser capacity of treating patients. 6.1.8 Simulated Costs of DMUs (Input) Cost of innovative products has been adjusted based on the healthcare organizations. That is, the underlying assumption is that the cost of a particular DMU of a general HC organization is lower than a specialty one under both off-contract and oncontract means. Similarly as evident from th e first aspect of the thesis, it has been
63 simulated that the DMUs under the Hybrid mode ls are the most cost efficient, followed by those under GPO models for both general and specialty HC or ganization only when the items are sourced through on-contract means. Off-contract purchase costs for all HC organizations having different procurement models, are simulated to be quite close but not same as it depends on the negotiating power of the respective HC organization with the vendors when they off-contract. But it differs in a case where a particular HC organization has two sources of contracting as mentioned in this study. For the same HC organization, cost of a DMU by off-contract means is simulated to be higher than an oncontract one for both general and specialty type organizations having dual sources of contracting. Another assu mption is that the cost of procur ement for Self sourcing will be higher than those of GPO and Hybrid models by on-contract means for both general and specialty HC organizations. Table 6.2 displays the simulated costs of innovative items for the DMUs. The simulated cost of generic item pacemaker is taken into consideration with a price range between $4000 and $5000 for a general HC organization and between $5100 and $6000 for the specialty ones. Table 6.2 Simulated Costs of DMUs (Input) DMUs Hospital Type Procurement model considered by the hospital. Simulated Costs in US Dollars (input) Model 1/Hosp A Gen Self sourcing off-contract 5000 Model 2/Hosp B Gen GPO model with oncontract 4400 Model 3/Hosp C Gen GPO model with offcontract 4900 Model 4/Hosp D (on-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 4500
64 Table 6.2 (Continued) DMUs Hospital Type Procurement model considered by the hospital. Simulated Costs in US Dollars (input) Model 5/Hosp D (off-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 4850 Model 6/Hosp E Gen Hybrid model with oncontract 4200 Model 7/Hosp F Gen Hybrid model with offcontract 4900 Model 8/Hosp G (on-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 4300 Model 9/Hosp G (off-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 4950 Model 10/Hosp H Sp Specialty Hospital with Self sourcing (offcontract) 5800 Model 11/Hosp I Sp Specialty Hospital with GPO model (on-contract) 5400 Model 12/Hosp J Sp Specialty Hospital with GPO model (off-contract) 5900 Model 13/Hosp K Sp Specialty Hospital with Hybrid model (on-contract) 5150 Model 14/Hosp L Sp Specialty Hospital with Hybrid model (off-contract) 5900 Model 15/Hosp M (on-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 5300 Model 16/Hosp M (off-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 6000 Model 17/Hosp N (on-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 5250 Model 18/Hosp N (off-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 5850
65 In the above table Gen represents general category of HC organizations and Sp represents specialty units. 6.1.9 Simulated Innovation Score (Input) When assuming innovation scores of DMUs under consideration, similar pattern is seen. As discussed earlie r, the innovation score ranges from 1 to 5 with 1 being the highest or most innovative and 5 being the least innovative. For example, when the innovation score of a particular model A is 3 and another model B is 5, it can be said that model A will have higher innovation score th an the model B. The innovation score of a particular DMU of a specialty hospital having a certain procurement model and contracting source is simulated to be highe r than that of a co rresponding DMU of a general hospital. Again the innovation score of the DMUs of Hybrid models is simulated to be higher than those of GPO models onl y for on-contract means for both general and specialty HC organizations. This is because of the assumption that Hybrid models have more flexibility than just GPO models in th e choice of products and have generally wider range. However, for off-contract purchases, in novation score is simulated to be constant for all the three models of pr ocurement for comparisons within general and specialty HC organizations. It is also simulated th at the innovation score for DMUs of HC organizations having two sources of contract ing for both GPO as well as Hybrid models of procurement under both general and specia lty categories will be higher for the ones through off-contracting than those procured through on-contract ing. Again, it has been simulated that the innovation score of the Self sourcing DMUs for both general and specialty categories will be higher than th eir respective Hybrid and GPO on-contract DMUs, whereas remaining the same as that of their respective off-contract DMUs.
66 It should be noted here that under a category of HC organization like general, certain DMUs will have the same innovation score whereas their cost will vary slightly. For example, models 1, 3, 5, 7, and 9 under general HC organizati on type are simulated to have same innovation score whereas they ma y not have same cost prices as cost is dependent on the negotiating power and the volume of the items a HC organization purchases when making off-contract purchases. However, their costs are simulated to be quite close if not the same. The DEA will be unique for each kind of generic item, i.e. say for pacemakers, there will be a DEA model with different models of pacemakers numbered from 1 to 18 forming the DMUs. Similarly, other generic it ems like implants etc. will have their own respective DEA. Thus in this study, i nnovation score and the out put the number of hospital beds is simulated to remain consta nt for a particular DMU under different DEA models. For example, model 3 will have same simulated values for innovation score and no. of beds constant for all generic item DEA models. Only the cost of innovative items (simulated input) will change acro ss the DEA models because every generic innovative item costs differently. Table 6.3 listed in the followi ng page displays the simulated innovation scores for the DMUs. Table 6.3 Simulated Innovation Scores of DMUs (Input) DMUs Hospital Type Procurement model considered by the hospital. Innovation Score (input) Model 1/Hosp A Gen Self sourcing off-contract 3 Model 2/Hosp B Gen GPO model with oncontract 5 (same for all general GPO on-contracts) Model 3/Hosp C Gen GPO model with offcontract 3 (same for all general offcontracts) Model 4/Hosp D (on-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 5
67 Table 6.3 (Continued) DMUs Hospital Type Procurement model considered by the hospital. Innovation Score (input) Model 5/Hosp D (off-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 3 Model 6/Hosp E Gen Hybrid model with oncontract 4 (same for all general Hybrid on-contracts) Model 7/Hosp F Gen Hybrid model with offcontract 3 Model 8/Hosp G (on-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 4 Model 9/Hosp G (off-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 3 Model 10/Hosp H Sp Specialty Hospital with Self sourcing (offcontract) 1 (same for all specialty off-contracts) Model 11/Hosp I Sp Specialty Hospital with GPO model (on-contract) 3 (same for all specialty GPO on-contracts) Model 12/Hosp J Sp Specialty Hospital with GPO model (off-contract) 1 Model 13/Hosp K Sp Specialty Hospital with Hybrid model (on-contract) 2 (same for all specialty Hybrid on-contracts) Model 14/Hosp L Sp Specialty Hospital with Hybrid model (off-contract) 1 Model 15/Hosp M (on-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 3 Model 16/Hosp M (off-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 1 Model 17/Hosp N (on-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 2 Model 18/Hosp N (off-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 1
68 6.1.10 Simulated No. of Beds (Output) of DMUs The simulated values of the output of the DMUs in the DEA the specialty HC organization has will have lesser number of be ds compared to general ones as the former ones are more focused to a particular type of treatment whereas the latter ones cater to a wider range of treatments and population. Ho wever, the number of beds (output) for DMUs which fall under the category of HC organizations which have dual contract sources is simulated to be same as they are the same HC organization. Table 6.4 listed below shows the simulated values of outputs (No. of beds) for the DMUs Table 6.4 Simulated Values of Outputs (No. of beds) DMUs Hospital Type Procurement model considered by the hospital. No. of Beds (output) Model 1/Hosp A Gen Self sourcing off-contract 300 Model 2/Hosp B Gen GPO model with oncontract 350 Model 3/Hosp C Gen GPO model with offcontract 325 Model 4/Hosp D (on-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 250 Model 5/Hosp D (off-contract model of Hosp D) Gen GPO model with both off and on-contract purchasing 250 Model 6/Hosp E Gen Hybrid model with oncontract 400 Model 7/Hosp F Gen Hybrid model with offcontract 350 Model 8/Hosp G (on-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 325 Model 9/Hosp G (off-contract model of Hosp G) Gen Hybrid model with both off and on-contract purchasing 325 Model 10/Hosp H Sp Specialty Hospital with Self sourcing (offcontract) 150 Model 11/Hosp I Sp Specialty Hospital with GPO model (on-contract) 175
69 Table 6.4 (Continued) DMUs Hospital Type Procurement model considered by the hospital. No. of Beds (output) Model 12/Hosp J Sp Specialty Hospital with GPO model (off-contract) 160 Model 13/Hosp K Sp Specialty Hospital with Hybrid model (on-contract) 180 Model 14/Hosp L Sp Specialty Hospital with Hybrid model (off-contract) 145 Model 15/Hosp M (on-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 170 Model 16/Hosp M (off-contract model of Hosp M) Sp Specialty Hospital-GPO model with both off and on-contract purchasing 170 Model 17/Hosp N (on-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 165 Model 18/Hosp N (off-contract model of Hosp N) Sp Specialty Hospital-Hybrid model with both off and on-contract purchasing 165 6.1.11 Selection of (DEA) Model The DEA model chosen in this study will be CCR input-oriented bounded model. The CCR model was proposed by Ch arnes, Cooper and Rhodes in 1978 (Cooper 2006). The main assumptions of the CCR model are (Cooper 2006) 1. Constant returns to scale which assumes that a proportional ch ange in the inputs also increases the output by the same proportion. 2. Since all the data (inputs and outputs) are simulated to be positive, translation invariant capability is not required. Translation invari ance converts negative data to positive values, which are not a concern in this study.
Expressing the linear programmi ng model of DEA (Eq. 6.2) from section 6.2.5 in the form of vector matrix notation (Cooper 2006), (LP o ) max v,u = uy o subject to vx o = 1 Eq. 6.3 -vX + uY 0 .0,0 u v Where matrix(X,Y) comprises of row vector v as input multipliers and u for as output multipliers. Input-oriented CCR models minimize inputs to satisfy the desi red output levels. In this research study, the main objective woul d be to minimize the va lues of inputs, i.e. the cost and innovation score. The DMUs with the relati ve minimum innovation score and relative minimum cost would be the optimal DMU against which the other DMUs will be measured. It was decided to mini mize input because the output which is the number of beds, cannot be varied as that is constant and specific to a hospital. Minimization of input is the sole reason for choosing a inverted innovation scale with 1 being the most innovative and 5 being the least. The dual problem of the (LP o ) in equation 6.3 expresse d with a real variable and the transpose of non negative vector = ( 1 ,.. n ) (Cooper 2006) (DLP o ) min Subject to x o X 0 Eq. 6.4 Y y o 0. 70
Since the innovation score is bounded by an inverted scale of innovation score of a maximum value of 1 and minimum value of 5. The innovation score cannot go out of this range and this is the sole reason why bounded input-oriented CCR model is applied as the solution will try to minimize the innova tion score and give optimal efficiency for each DMU. The bounded equations are: l x o X u x o Eq. 6.5 l y o Y u y o Eq. 6.6 where ( l x o u x o ) are lower and upper bound vectors to inputs and ( l y o u y o ) to outputs respectively. 6.2 Results of Comparison of Access to Innovation with Cost This section of the study deals with the comparison of degree of access to innovative products across vari ous HC organizations follow ing different procurement models and contract sources. As discussed ear lier, accessibility of data for off-contract items has not been possible due to the rece nt phenomenon of HC organizations to lay stress on on-contract purchasing. Also, information regarding product features, manufacturers details was not available to us due to confidentiality concerns shared by the hospital staff and the manufacturing units. This comparison model is totally based on simulated data which has been tailored to suit real world scenarios as closely as possible. The conditions and the justifica tions for the assumptions have been explained in detail in the methodology section. The main idea here is to bind the two factors cost and innovation score and rate the models of p acemakers which are the DMUs in terms of 71
72 efficiency and ultimately rank them. There is a link between the co st and the degree of access of innovation rated by innovation score and based on these two factors, the DEA model tries to find out the optimal efficien t DMU which would be rated as the most efficient and all other DMUs will be meas ured against it in terms of efficiency. The DEA model is run for the generic it em pacemaker using DEA solver and the results are shown below. Table 6.5 Ranking and Effici ency Scores of DMUs Rank DMU Score Reference set (lambda) 1 6 1 6 2 8 0.976734 6 3 2 0.954536 6 4 4 0.933324 6 5 5 0.865971 6 6 3 0.857134 6 6 7 0.857134 6 8 9 0.848476 6 9 1 0.839992 6 10 13 0.815526 6 11 17 0.799992 6 12 15 0.792445 6 13 11 0.77777 6 14 10 0.724131 6 15 18 0.717942 6 16 12 0.711857 6 16 14 0.711857 6 18 16 0.699993 6 Table 6.5 above displays the efficiency score of each DMU and the rankings based on efficiency score. The efficiency sc ore is the efficiency of each DMU evaluated against the most efficient DMU which in this study is model 6. The reason for model 6 to be ranked most efficient is due to lower cost as Hybrid model in this study is simulated to have lowest cost for on-contract purchases (a ssumption is taken from the cost comparison
73 analysis where the Hybrid model had the lo west cost) as compared to GPO and Self sourcing and at the same time fair better on the innovation scale than the GPO model. Understandably, the second ranking DMU is model 8 which again is from Hybrid model and has on-contract purchas e sources. It can be seen th at there is a huge difference in ranking between second ra nking model 8 and eighth ranking model 9. Both the models are procured by the same hospital G, however the extremely low prices of on-contract Hybrid models (low even compared to GPO on contract) as compared to off-contact prices which are quite similar across the Hybr id, GPO and Self sourci ng model, drive the difference in rankings. Because the difference between the simulated off-contract pricing and on-contract pricing for the GPO model of the same hospital is less as compared to the Hybrid model, model 4 and model 5 trail clos ely in ranking at 4 and 5, with model 4 being the more efficient one. However, it is closely followed by GPO on-contract DMUs models 2 and 4 at ranks 3 and 4. Since DMU mode l 6 is the most efficient, it is taken as a reference set against which other DMUs will be rated. Quite expectedly, model 1, which is procured by off-contract Self sourcing is the least efficient among general items as it is generally simulated to have a highest price. From the table it can be said that the general HC organization are more efficient than sp ecialty ones. The majo r factors behind this might be the fact that the average cost of items in specialty units are much higher than those of general HC organization (higher inpu ts) and at the same time lower outputs in terms of number of bed. When rated on innovation score, specialty ones will outperform the general ones (as they have be tter innovation score) but when costs are tied with innovation they seem to be less efficient overall. Similar trends as in the general
hospital can also be observed in the specialty HC organizati on. The figure 6.2 shows the efficiency of DMUs in a graphical form below. Score 00.10.20.30.188.8.131.52.80.91 1 3 5 7 9 11 13 15 17DMUEfficiency Figure 6.2 Graph Showing Efficiency Scores of DMUs 74
75 Table 6.6 Statistics on Input/Output Data (IB)InScore (I)Cost (O)Beds Max 5 6000 400 Min 1 4200 145 Average 2.666666667 5141.667 241.9444 SD 1.290994449 564.764 84.19783 Correlation (IB)InScore (I)Cost (O)Beds (IB)InScore 1 -0.92579 0.741941 (I)Cost 0.925789863 1 -0.84902 (O)Beds 0.741940575 -0.84902 1 DMUs with inappropriate Data with respect to the chosen Model No. DMU None No. of DMUs 18 Average 0.826934118 SD 0.09234159 Maximum 1 Minimum 0.699993 No. of DMUs in Data = 18 No. of DMUs with inappropriate Data = 0 No. of evaluated DMUs = 18 Average of scores = 0.826934 No. of efficient DMUs = 1 No. of inefficient DMUs = 17 Table 6.6 above shows the st atistics like maximum, minimum and average values of outputs and input. It also di splays the correlation betwee n the inputs to the outputs, standard deviation, and average efficiency score along with the maximum and minimum values. The correlation is of pa rticular importance here. It describes the strength and the nature of relationship between the inputs a nd between the inputs and the output. As seen from the table, the bounded input InScore (Innovation Score) has inverse correlation with output variable Cost and is equal to -0.92579. The relationship between InScore
76 and Cost is however stronger than the relationship between Cost and Beds and InScore and Beds. The inverse correlation sh ows that as InScore increases the cost would decrease. This is because of the usage of inverted Innovation Scale where the most efficient is rated as 1 and the least 5. The model also has been based on assumptions that on-contract purchases are low on innovation as compared to o ff-contract ones, i.e. oncontract purchases have an innovation score range between and 3 and 5 whereas offcontract ones range between 1and 3. At the same time on-contract items have a much lower price as compared to off-contract and this would be the reason for inverse correlation. Similarly, the correlation betw een input cost and output bed is also shown as inverse with a value of -0.84902, which can be jus tified as the cost decreases with the increase of capacity of the hospital to treat patients. Table 6.7 Projection of DMUs No. DMU Score I/O Data Projection Difference % 4 4 0.933324 (IB)InScore 5 3.99996 -1.00004 20.00% (I)Cost 4500 4199.958 -300.042 -6.67% (O)Beds 250 399.996 149.996 60.00% 5 5 0.865971 (IB)InScore 3 3.99996 0.99996 33.33% (I)Cost 4850 4199.958 -650.042 13.40% (O)Beds 250 399.996 149.996 60.00% 6 6 1 (IB)InScore 4 4 0 0.00% (I)Cost 4200 4200 0 0.00% (O)Beds 400 400 0 0.00% 7 7 0.857134 (IB)InScore 3 3.99996 0.99996 33.33% (I)Cost 4900 4199.958 -700.042 14.29% (O)Beds 350 399.996 49.996 14.28%
77 Table 6.7 (Continued) 8 8 0.976734 (IB)InScore 4 3.99996 0 0.00% (I)Cost 4300 4199.958 100.042 -2.33% (O)Beds 325 399.996 74.996 23.08% 9 9 0.848476 (IB)InScore 3 3.99996 0.99996 33.33% (I)Cost 4950 4199.958 750.042 15.15% (O)Beds 325 399.996 74.996 23.08% The above table 6.7 shows the projection of DMUs to the efficient frontier. The projection of model 4 to model 9 has been chosen to be displayed here. Model 6 is the reference set and is the most efficient DMU. In order to achieve optimal efficiency, the DMUs are projected to the efficient frontier, and their difference and percentage changes are also highlighted. As can be seen, since DMU model 6 is the most efficient, the percentage change and difference in input and output weights for it to be projected to the efficient frontier are both zero. The other DMUs either have positive or negative changes to their input and output values for them to be projected to the efficient frontier, as they are less efficient than model 6.
78 CHAPTER 7 CONCLUSION AND DISCUSSIONS As discussed earlier, this research study has two contributions. In the first section, the goal was to determine whether National GPOs help the healthcare organizations affiliated to them to drive their costs low as compared to the healthcare organization which Self contract. Based on the available data from thr ee healthcare organizations involving a Self sourcing mode l, a GPO model and a Hybrid model, our results clearly prove that healthcare organizations affiliated to National GPO are indeed more cost efficient than the Self sourcing ones. A H ybrid model was also used in the comparison and it was the clear winner in terms of cost efficiency in the comparison test. The Self sourcing model has significantly higher overall costs compared to the GPO model and the Hybrid model. The Hybrid model achieves th e efficiency by having the flexibility of wider range of products and the ability to c hoose between the best prices offered by a National GPO and a regional GPO. Thus, base d on the results of this cost comparison study, the first hypothesis H1 National GPOs (Group Purchasing Organizations) enable the healthcare establishments to lower the cost of medical services and an operations is valid. It should be mentioned that during the co urse of research, it was found that no two healthcare organizations affiliated to the same GPO have the same price figures. Thus, two different healthcare organizations under the same GPO will have different cost efficiencies. This is dependent on the negotiating capacity of each healthcare organization, volume of purchase, and the comp liance rate of the heal thcare organization.
79 For example, a healthcare organization havi ng a high compliance rate and high volume of purchase will have lower prices of products from the GPO as compared to another which has lesser compliance rate and volume unde r the same GPO. Also, many GPOs have mandatory compliance rates. The second aspect of this research wa s to measure and compare the degree of access to innovative products across HC organi zation with different procurement models and modes of contracting. In this study, since data was not available, realistic data were simulated. The results achieved with the si mulated data, models of items procured through contracts by a GPO and Hybrid mode l driven HC organization faired most efficient as compared to Self sourcing a nd off-contracted models. In spite of oncontracting models having lesser innovative feat ures as compared to off-contracting ones, the fact that they are more cost efficien t, improves their efficiency. Thus, many HC organizations in their attempts to drive cost s lower might go for on-contracting source of procurement and might compromise on the quality of products as they are more cost efficient. This might create a barrier to th e entry of niche manufact urers of high end items whose products are more advanced than the ones offered by the GPOs, but do not have the necessary volumes to drive the cost low. They might be beaten out in the race and since they are generally not affiliated to GPOs, they may not find the support from the HC organization to sustain in the competitive marker. Thus, if this research study is performed with real world data and if it is quite similar to th e simulated data used in this project, the hypothesis H2 National GPOs a barrier to entry of innovative product manufacturers in the healthcare industry can be proved, which again reflects the concerns shared by the past literature.
80 In this research project, the most comm on procurement models like Self sourcing, GPO and Hybrid are compared and discussed in terms of cost efficiency. But, during the course of the study, it came to our knowledge that one more type of procurement model is gaining acceptance in the healthcare indus try. This model is the recent phenomenon of formation of regional cooperatives. In th is model, multiple he althcare organizations which are in the close proximity geographi cally create a purchasing and logistics subsidiary, which is solely responsible fo r procurement operations to those healthcare organizations. Based on our interaction w ith the healthcare professionals, we could interpret that regional cooperatives generally drive high compliance rate and have contracts with local manufactur ers. Contracting with loca l vendors and maintaining high compliance rate for the items might result in low costs and better distribution facilities and supply lines. They might also have better access to latest technologies in the industry through contracting with niche manufactures, and since multiple hospitals have shares in a regional cooperative, a larg e volume would help to drive costs low. It would be interesting to compare this procurement model with the three compared in this study as a future research study. Future research can also involve actually comparing off-contract pricing with oncontract pricing for innovative items, as ther e would be several healthcare organizations where the physicians circumvent and procur e their preferred produc ts. Unfortunately, in this study, almost four h ealthcare organizations we worked with, had no way of accounting for off-contract purch asing, as they st rictly enforce the compliance rate to drive costs low.
81 REFERENCES Anderson, M. G., and Katz, P.B. (1998). "Strategic sourcing." International Journal of Logistics Management 9(1): 1-13. Barlow, R. D. (2005). "Glancing back." Healthcare Purchasing News. Buganza, T. a. V., Roberto (2006). "Life-Cycle flexibility: How to measure and improve innovative capability in turbulent environments." The Journal of Product Innovation Management 23: 393-407. Burns, L. R. (2002). "The Health Care Value Chain." Chapman, T. L., Gupta, A., Mango, P.D. ( 1998). "Group Purchasing is not a panacea for US Hospitals." McKinsey Quarterly 1: 160-165. Cooper, W. W., Seiford, Lawrence M., Tone Kaoru (2006). "Introduction to Data Envelopment Analysis and Its Uses." Dobler, D. W., and Burt, Davi d N. (1996). "Test and Cases." Purchasing and Supply Management Doucette, W. R. (1997). "Influences on Member Commitment Group Purchasing Organizations." Journal of Business Research 40: 183-189. Elhauge, E. (2002). "The exclusion of competition for hospital sales through group purchasing organizations." unpublished Essig, M. (2000). "Purchasing consortia as symbiotic relationships: developing the concept of consortium sourcing'." European Journal of Purchasing & Supply Management 6: 13-22. Everard, J. L. (2005). "Defining and Meas uring Hospital Product-Based Cost Savings." Gordon, T. J. (1994). "THE DELPHI METHOD." AC/UNU Millennium Project Hendrick, T. E. (1997). "Purchasing Cons ortiums: Horizontal Alliances Among Firms Buying Common Goods and Servic es: What? Who? Why? How?" Hewitt, D. (1995). "The Consortium Option." Purchasing and Supply Management : 32.
82 McFadden, C. D., and L eahy, Timothy M., (2000). US Healthcare Distribution Muller, A., Liisa Valinkangas, and Merl yn, Paul (2005). "Metrics for Innovation: Guidelines for developing a customized suite of innovation metrics." Strategos, An International Strategic Management Consultancy Nollet, J., and Beaulieu, Ma rtin (2002). "The developm ent of group purchasing: an empirical study in the healthcare sector." Journal of Purchasing & Supply Management. Nollet, J., and Beaulieu, Martin (2005). "Should an or ganization join a purchasing group? Supply Chain Management: An International Journal 10(1): 11-17. Rozemeijer, F. (2000). "How to manage corp orate purchasing syner gy in a decentralized company? towards design rules for managi ng and organizing purchasing synergy in decentralised companies." European Journal of Purchasing & Supply Management 6(1): 5-12. Schneller, E. S. (2000). "The value of group purchasing in Health Care Supply chain." Sethi, P. (2006). "Group Purchasing Organiza tions: An Evaluation of their Effectiveness in Providing Services to Ho spitals and Their Patients." HGPII Report, 07-20-06 Zweig, P. L., Zellner, W. (1998). "Locked out of the Hospital." Business Week 3569: 7576.
APPENDIX A Process Map of Self Sourcing Model 84 Medical clinic AP Clerks create PO from invoices Director approves PO online Supervisor approves PO online CFO approves PO online Copies are made and paperwork completed by financial analysts. Checks are cut at UMSA. Vendors receive checks. Financial analysts complete the receipts Is PO value < = $ 500 Is PO value >$500 & <$5000 Orders <=$500 Yes N o >$500 & <$5000 Yes N o >$5000 After A pp roval POs sent back to AP Copies are sent to UMSA
APPENDIX B Process Map of GPO Model There are 4 kinds of items sourced by this GPO affiliated 1. Inventory Items (Frequently ordere d and officially booked inventory) 2. Non-Inventory Items: a. Non Stocks----Not officially booked inventory (Not in the ledger, frequently ordered) b. Special Items-------Not officially booked inventory (infrequently accessed). 3. Services. ProcessMaps: 1. Inventory Items Inventory items ( max stockweek supply) Computer system decrements inventory Min. inventory level--(buffer stock level) Re-order requisition generated by the computer system within EDI (Electronic Data Interchange) system orders vendors to supply the inventory. Vendors receive the computer generated orders to supply Requisition converted to POs 85
APPENDIX B (CONTINUED) 2. Non Inventory Items Depts. Needs non inventory items. Depts. Generate requisition in the computer system Requisition goes through approval EDI (Electronic Data Interchange) system orders vendors to supply the inventory. Vendors receive the computer generated orders to supply Dept. Chairs or directors approve the requisition Requisition s converted to POs. 86
APPENDIX C Process Map of Hybrid Model 87 Department (Requestor) Procurement Sourcing Purchasing Price Confirmation Lawson (Requisition) Receiving & Distribution Accounts Payable/GL VAT Rebates Delivery Rebates