ASIAN JOURNAL OF MANAGEMENT RESEARCH Online Open Access publishing platform for Management Research © Copyright 2010 All rights reserved Integrated Publishing association Research Article ISSN 2229 – 3795
Hospitals ranking using fuzzy analytic hierarchy process ­ Balanced Score Card Morteza Mousakhani 1 , Hamed Rahmani 2 , Naser Hamidi 3 1­ Phd public management, Phd holder from tarbiat modarres, Associate professor and President, Qazvin Islamic Azad of university. 2­ Master of industrial management, Qazvin Islamic Azad of university 3­ Phd scholar, Islamic Azad of university, QIAU faculty member pres@qiau.ac.ir ABSTRACT Hospitals ranking is an important index showing the hospitals' quality and standards. Inspired by high ranking, hospitals managers invest more time and energy in order to improve their services. Having undergone some evolutionary stages, Balanced Score Card is considered as a comprehensive system of performance evaluation whose advantages are as follows: It yields the criteria and indices based on the strategic goals 2­ It takes into account both observable and unobservable indices. BSC yields measures of great use. This is because these measures are derived based on strategic objectives. Moreover, they put more emphasis on intangible assets and lead measures compared with other techniques. This study seeks to solve the quantification problem in an operational context, which is considered as a shortcoming of BSC, through using Fuzzy Hierarchicy Analytic Process. Keywords: Balanced Score Card, Performance Evaluation, Hospitals Ranking, Fuzzy Analytic Hierarchy Process. 1. Introduction Recently, the advances in health plans as well as in diseases prevention methods have improved the quality of life. However, the costs incurred by diseases treatment are skyrocketing. For example, 20 percent of the Americans' income is paid for health care costs, which is expected to double between 2006­2016,reaching 4/1 billion from current 2/1 billion rate . Throughout the world, managers of health care systems are grappling with a common challenge, namely, how to control the increasing gap between the demands for health care services and limited financial resources. The aging population in Europe, North America, and Japan has led o a need for better health care programs. This results in more costly services.
ASIAN JOURNAL OF MANAGEMENT RESEARCH 666 Undoubtedly, the organization of any sort needs to be evaluated, should it be successful. Evaluating and ranking the performance of hospitals are considered as one of the most important challenges faced by hospitals, highlighted by the Iranian Minister of health, treatment and medical education. 1.1 Performance Evaluation Hospital ranking is based on the evaluation score. Thus, attempts should be made to define performance evaluation and to discuss the part BSC (Balanced Score Card) should play in evaluating and ranking hospitals. The following definitions are evident in the literature. According to Rue & Buyar (2005), the performance evaluation indicates how staff define their own work, consequently building communication and making decision to improve the performance (Yi Wu et al, 2009). According to Robbins (1990), performance evaluation measures the extent to which the organization's objectives have been achieved. The company's pushing for the objectives improves the business performance. The most typical examples of financial and business functional indicators are as follows: investments return rate, sale income and profitability which researchers adopt as index of performance evaluation in the early years ( Robbins, 1990). Evaluation is a guided study, aiming to identify the competency, and the value derived out of being evaluated. Evaluation of performance is an exploratory and critical estimation of an organization's activities ( Soltani,I.2002). The traditional methods of performance evaluation focus on tangible indictors and financial perspective with the latter maintaining that line creates added value and staff inflicts costs. This perspective sounds illogical. That staff doesn’t create any added value is not of importance. However, as a matter of fact, it's more difficult to find value in staff units than in line units which produces or sells the product directly. Yet, recently the staff units have been seen to be managed as value­added operation ( Ghelich , 2007). As it is evident by the application of evaluation models, the focus should not be only on the traditional performance levels which include finical perspective, operational and financial effectiveness. Put it another way, the non­financial measures including resources management, market, and share holders should be considered as well. Below, several performance evaluation models are presented. ­ Rappaport (1986) proposed the value of share holder (Rappaport , 1986). ­ ­Kaplan & Cooper (1997) proposed the activity­based cost estimation (Kaplan and Cooper,1997). ­ ­Kaplan & Norton (1992, 1996) proposed the balanced score card (Kaplan and Norton,1992 , 1996). ­ ­Lynch & cross (1990) proposed the performance pyramid (Lynch and cross , 1990).
ASIAN JOURNAL OF MANAGEMENT RESEARCH 667 ­ ­Brown (1996) proposed the macro process (Brown, 1996). ­ Kanji & Sa (2002) proposed business score card (Kanji and Sa , 2002). ­ Neely et al (2002) proposed performance charter (Neely and Kennerley , 2002). Performance evaluation and accountability of an organization is the first step an organization takes toward achieving a superior status. This shows that organizations officials were not satisfied with the reliability of traditional performance evaluation. The officials were fed up with these data yet here were shortages of relevant performance data (those data distinguishing success from failure) (Villalobos and Geraldina 2005). Adopting large numbers of variables and a multi­dimension approach, balanced score card is considered as one of the most effective method of evaluation .According to Kaplan & Norton(1992),as a method to study the organization, performance evaluation incorporates the achievement of both financial and non­financial objectives. 1.2. Balanced Score Card Kaplan & Norton (1996) conducted a study on 12 American leading companies, examining the methods and criteria used to measure the companies' performance. The findings showed that most of the successful companies had categorized their strategic objectives in terms of 4 groups: financial, internal process, customer, learning and growth. The companies evaluated their own performance, using these 4 groups ( Kaplan and Norton , 2004a). Keegan et al (1989) proposed a multi­dimension model which is considered as a model of balanced internal­external measures. Cross & Lynch (1989) proposed the pyramid interpretive model which includes the measures integrating the performance through hierarchy. Fitzgerald et al (1991) proposed a model distinguishing outcomes from determinants. Balanced score card (BSC) was proposed for the first time in a paper entitled "the indicators as performance stimulus" (1992) ( Deshmukh et al , 2007). BSC takes account of both observable and intangible assets as well as of perspectives such as financial, customer, internal processes, business, and learning & growth. As a common language in all 4 perspectives, financial and non­financial measures help strike a balance between manager and employees on the one hand and organization's vision on the other hand (Kaplan and Norton, 2004b). Currently, this model is the most common and effective model used in the form of electronic technology in the sophisticated organizations. A study conducted by Harvard university and Hosing Research Institute showed that 96% of modern organizations have either already implemented BSC or are planning to do so. In line with the second objective stated in the country's fourth development plan, namely, knowledge­based development approved by the country Management & Planning Organization, BSC has been selected as a national pilot model in Iran ( Kaplan and Norton , 2005).
ASIAN JOURNAL OF MANAGEMENT RESEARCH 668 According to the literature, BSC has the following characteristics: In 1990, performance evaluation through discussion over strategy map and using the map for connecting the key performance indicators were regarded as the dominant perspective (Radnor and McGuire , 2004). Initially, Kaplan & Norton proposed BSC as a performance evaluation tool in 1992 ( Kaplan and Norton , 1992), as a strategy implementation tool in 1996 ( Kaplan and Norton , 1996), as a framework for balancing organizational, informational, and human assets in 2004 (Kaplan and Norton , 2004c), and finally as a strategic management system in 2008 ( Kaplan and Norton , 2008). Kaplan & Norton (1996) maintained that BSC can integrate the measures related to past business performance (Lag indicators) with those related to the future (lead Indicators). BSC is wide­ranging, contributing control and plan to the organization through performance evaluation tool (Yuksel, and Dagdeviren , 2009). Essentially, BSC holds that there must be a balance between financial indicators and non­ financial indicators ( Deshmukh et al , 2007). This model translates the vision and mission of the organization into a set of objectives through identifying the key factors of success and key performance indicators ( Chen Huang , 2008). BSC model improved the traditional performance evaluation systems in two ways: 1­the model identifies four perspectives in all organizations 2­ the model sheds light on the relationship between the lag indicators and leading indicators in financial and non­financial performance ( Liberatore and Miller 2005). Consider 2 cases below and the outcomes of BSC: Duke Children Hospital The cost of each treatment case increased by 35% between 1994 and 1995. BSC implementation resulted in a decrease in the costs by 30 million dollars and an increase in net profit by 50 million dollars. Shahid Hasheminejad Hospital This hospital started to implement BSC in 2007.Currently, the hospital is recognized by the Ministry of Health as a health center enjoying the highest ranking in Iran. The following studies used BSC to evaluate the performance: Lib et al (2005) used analytic hierarchical Process as a tool linking balanced evaluation and costing systems (Yao and Liu , 2006).
ASIAN JOURNAL OF MANAGEMENT RESEARCH 669 Yao & Lio (2006) presented BSC as a practical framework linking performance measuring with strategic planning ( Khorshid and Zabihi , 2010). 1.3. Fuzzy Analytic Hierarchy Process Fuzzy analytic hierarchy process (FAHP) is a technique that applies fuzzy set in AHP. The decision­making problems make use of fuzzy sets which are more effective than classic sets. In fact, fuzzy decision­making theories try to model the uncertainties related to performance, objectives and limitations of decision­making. Fuzzy sets deal with categorizing data along the boundary lines which are not defined clearly. Fuzzy theories are used in uncertain contexts where the data are similar and changeable. This is considered as the main advantage of fuzzy sets ( Kanji and Sa , 2002). As a multi­dimension decision­making hierarchy, Analytic Hierarchical Process (AHP) is used to solve decision­making problems. Using a one­way, hierarchical relation, AHP is a decision­making framework which makes up for the shortcomings of evaluation and measuring (Najafi , 2010). AHP provides an extensive context in which all problems can be solved. Though these problems involve senses, rationality, irrationality and are multi­purpose, multi­criteria, and multi­decision­ makers in certain and uncertain situations (Stwart and Mohamad , 2001). The following studies have used the AHP: Using AHP and desirability theory, Stwart (2001) offered a BSC framework to evaluate IT unit( Clinton et al , 2002). Clinton and Hassel (2002) used AHP as a process complementing the BSC ( Chiang , 2005). Chiang (2005) offered a dynamic approach based on AHP and BSC for purpose of choosing the sellers ( Leung , 2006). Leung et al (2006) proposed an approach integrating AHP and Analytic Network Process (ANP) with BSC ( Sharma and Rajab , 2007). Sharma et al(2007) used a model integrating AHP with Score Card in order to evaluate IT unit in a manufacturing factory in Taiwan. Cebeci (2009) drew on an approach integrating fuzzy analytic hierarchy process and score card in order to select the most appropriate ERP system in textile industry (Cebeci , 2009). 2. Methodology Initially, the objectives and BSC indicators of 4 perspectives were determined, using questionnaires and brainstorming. Then, the hospitals were ranked, drawing on FAHP as well as the obtained indictors and objectives. It is worth mentioning that the indicators used by FAHP were obtained, using questionnaire, interview with experts and the documents available in hospital A (the only hospital in Iran which has implemented BSC.
ASIAN JOURNAL OF MANAGEMENT RESEARCH 670 3. Investigation Method FAHP was applied, using Chang extent analysis. Eq. (1) Where all numbers are fuzzy triangle numbers with a, b, c representing fuzzy numbers. Table 1: shows the variables and the respective fuzzy triangle numbers Literal variables Positive fuzzy triangle numbers (1,1,1) Equal significance Positive Inverse fuzzy triangle numbers (1,1,1) Equal­to­a little significant (1,2,3) (1/3,1/2,1) A little significant (2,3,4) (1/4,1/3,1/2) A little significant­to significant­ (3,4,5) (1/5,1/4,1/3) Significant (4,5,6) (1/6,1/5,1/4) Significant­to­very significant (5,6,7) (1/7,1/6,1/5) Very significant (6,7,8) (1/8,1/7,1/6) very significant­to­completely significant completely significant (7,8,9) (1/9,1/8,1/7) (9,9,9) (1/9,1/9,1/9) This technique consists of the following steps: Step 1: If
represent the values of i th objective extent analysis against m­ objective ,then the fuzzy synthetic extent of m objective for i th objective is as follows: �
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
m é n m
ù
(2) S i = å M gi j ´ ê[ å å M gi j ] - 1 ú
j ë i =1 i =1 û
�
If
�
�
�
�
�
�
�
�
�
�
�
, then
�
�
�
�
�
�
�
�
�
�
�
�
is defined by fuzzy addition operation of m extent analysis �
�
�
�
�
�
value such that: m
(3)
å M j gi = ( a i 1 , b i 1 , c i 1 ) + ( a i 2 , b i 2 , c i 2 ) + .....( a im , b im , c im ) j = 1
m
m
m
= ( å a ij , å b ij , å c ij ), i = 1 , 2 , n j = 1 j =1 j = 1 ASIAN JOURNAL OF MANAGEMENT RESEARCH 671 é n m
ù
To obtain ê[ åå M gi j ] - 1 ú ,using the fuzzy addition ,it follows ë i =1 j =1 û
n m n n
n
(4) åå M gi j = [ å ai , å bi , å ci ] i =1 j =1 Thus: i =1 i =1 i =1 n m
1 1 1 (5) [ åå M gi j ] -1 = [ n , n , n ] i =1 j =1
å ci å bi å ai i =1 i =1 i =1 Step 2: If M1=(a1,b1,c1) and M2=(a2,b2,c2),the preference degree of M2 over M1 represented by V ( M 2 > M 1 ) is as follows: (6) V ( M 2 ³ M 1 ) = sup[min( m m1 ( x ), m m 2 ( y )] Which can be equal to the following equation
I �
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
(7) One needs the values of V to compare M1, M2 Figuer1: the values of V to compare M1, M2 Step 3: The following relation holds for fuzzy triangle numbers (8) V ( M ³ M 1 . M 2 ,... Mk ) = v [( M ³ M 1 ), ( M ³ M 2 ),...( M ³ Mk )] =
min v ( M ³ M 1 ), i = 1 , 2 , 3 ,..., k Assume:
ASIAN JOURNAL OF MANAGEMENT RESEARCH 672 (9) d ( A i ) = min V ( si ³ s k ) k = 1 , 2 ,..., n ; k ¹ i . whereA j ( i = 1 , 2 ,..., n ) Then the following weights are derived (10) Where the final weights which are not fuzzy numbers anymore are as follow (11) W=(d (A1),d (A2),…d (An)) T 4. Ranking the hospitals based on fuzzy hierarchical analytic process Figure 2: Diagram of available indicators hierarchy
ASIAN JOURNAL OF MANAGEMENT RESEARCH 673 The matrix compares the main criteria in pairs against the objective. Table 2: The matrix compares the main criteria in pairs against the objective Financial Customer (1,1,1) (1,1,2) Internal Processes (1,2,3) (1,1,1) (1,1,2) (1,1,2) Internal Processes (1,1,1) (1,1,1) Development And Growth (1,1,1) (1,1,1) Objective Financial Customer Development And Growth (1,2,3) The weights of indicators based on Chang development Analysis are:
ASIAN JOURNAL OF MANAGEMENT RESEARCH 674 Table 3: The matrix compares the main criteria in pairs against the objective Financial perspective Revenue and cost management productivity Revenue and cost management (1,1,1,) (0.6,0.87,1.15) Productivity (0.87,1.5,1.64) (1,1,1) Revenue and Costs Management S1=(1.87,2.15,2.64)×(0.2,0.25,0.29)=(0.374,0.537,0.766) Productivity S2=(1.6,1.87,2.15)×(0.2,0.25,0.29)=(0.32,0.467,0.623) The weights of these indicators based on Chang Development Analysis are W= (1, 0.78) Results of hospitals ranking based on the resulting weights means: Hospitals A C B E D Scores 25 24 19 12 2 D, 2.50% E, 15% C, 29% A B A, 30.50% B, 23% C D E
Figure 3: Scores of Hospitals ASIAN JOURNAL OF MANAGEMENT RESEARCH 675 5. Conclusion Hospitals ranking is one of the most important concerns highlighted by the Iranian Minister of health recently. Hospitals ranking is only possible through strict evaluation. Having undergone some evolutionary stages, BSC is considered as a comprehensive system of performance evaluation whose advantages are as follows: It derives the criteria and indices based on the strategic goals 2­ It takes into account both observable and unobservable indices. Using FAHP technique to rank hospitals resulted in distinguishing the hospitals enjoying BSC from those lacking BSC. As hospitals ranking is based on evaluation score in Iran, it is very important to pay due attention to how evaluation is performed. Using the indicators which take account of 4 perspectives, namely financial, customer, internal processes a, and growth and learning, this study ranks the hospitals accurately. The successful implementation of BSC by big hospitals such as Duke children Hospital, Monte Fivere Hospital, the health systems of Holy Mary hospital s and Mary Dalls Clinic indicates that not only can BSC be used for evaluating the performance as well as ranking the hospitals but it can be used as a management system in hospitals. References 1. Brown, M.G.(1996). Keeping Score: Using the Right Metrics to Drive World­class Performance, Quality Resources, New York. 2. Cebeci, U. (2009). Fuzzy AHP­Based Decision Support System for Selecting ERP Systems in Textile Industry by Using Balanced Scorecard, Expert Systems with Applications, Vol. 36, pp. 8900­8909. 3. Chen Huang , Hao & Chu, Wenyi & Chi Lai, Mei & Hsuan Lin , Lee. (2008). Strategic linkage process and value­driven system: A dynamic analysis of high­tech firms in a newly­industrialized country ; Journal Of Expert. 4. Chiang, Z. (2005). A Dynamic Decision Approach for Long­Term Vendor Selection Based on AHP and BSC. In D.S. Huang, X.­P. Zhang, & G.­B. Haung (Eds.), PP. 257­ 265. 5. Clinton, D., Webber, S.A., Hassel, J.M. (2002). Implementing the Balanced Scorecard Using the Analytic Hierarchy Process. Management accounting quarterly, pp.1­11. 6. Deshmukh ,S.G & Gupta , A.D & Shankar , Ravi (2007). Development of a balanced scorecard, International Journal of Productivity , 56(1) ,pp.25­59. 7. Ghelich Li , B.(2007). Human Resources Promotion: Evaluation, Planning and improvement, HR & Productivity Studies Institute, Tehran.
ASIAN JOURNAL OF MANAGEMENT RESEARCH 676 8. Kanji, G.K. and Sa, P.M.(2002). Kanji , s business scorecard , Total Quality Management, 13(1), pp. 13­27. 9. Kaplan, R. S. and Cooper, l. (1997). Cost and Effect, Harvard Business School Press, MA. 10. Kaplan, R. S. and Norton, D. P. (1992). The balanced scorcard – measure that drive performance, Harvard Business Review. 11. Kaplan, R. S. and Norton, D. P. (1996). The balanced scorecard ­ translating strategy into action, Boston , MA: Harvard Business School Press. 12. Kaplan R. S. and Norton D. P. (2004a). Strategy­Focus Organization, Translated by Parviz Bakhtiyari, Industrial Management Organization, Tehran. 13. Kaplan R. S. and Norton D. P. (2004b). Strategy Map (Converting intangible Assets to tangible Assets), Translated by Akbari, Soltani, and Maleki, Industrial Management Organization, Tehran. 14. Kaplan, R. S. and Norton, D. P. (2004c). Organizational capital: Leadership,alignment and teamwork. balanced scorecard Report, Article Reprint B0403A. 15. Kaplan R. S. and Norton, D. P. (2005). Strategic Management Office, Translated by Dr. Mohsen Ghadami and Masoud Niyazmand, Management Reviews No 53.Tehran. 16. Kaplan, R. S. and Norton, D. P. (2008). Integration Strategy Planning and Operational Execution, Harvard Business School Press. 17. Khorshid,S. and Zabihi, R. (2010). A Quantitative Model Evaluating the Value of Products Trademarks and Brands, Using Fuzzy Networks Analysis –Data Coverage Analysis based on BCS, Journal of Industrial Engineering and Production Management, Tehran, volume 1. 18. Leung, L.C., Lam, K.C., Cau, D. (2006). Implementing the Balanced Scorecard Using the Analytic Hierarchy Process & the Analytic Network Process .Journal of the Operational Research Society, pp. 682­691. 19. Liberatore, Matthew, J. and Miller, Tan. (2005). A Framework for Integrating Activity – Based Cocting and the Balanced Scorecard into the Logestics Strategy Development and Monitiring Process. Journal of Business Logestics, 19(2), pp. 131­154. 20. Lynch, R.L. and cross, K.F.(1990). Measure Up!Yardstick for Continuose Improvement, Blackwell, Cambridge, MA. 21. Najafi, A.(2010). Application of ANP to analyze the structural challenges and the operational environment of organization in Projects Management, Journal of Industrial Engineering and Production Management, Volume 21, Tehran.
ASIAN JOURNAL OF MANAGEMENT RESEARCH 677 22. Neely, A., Adams, C. and Kennerley, M.(2002). The Performance Prism: The Scorcard for Measuring and Managing Business Success, Financial Time­Prentice Hall, London. 23. Radnor, Zoe and McGuire , Mary. (2004). Performance management in the public sector, International Journal Of Productivity and performance Management, 53(3) , PP. 245­260. 24. Rappaport, A. (1986). Creating Shareholder Value, The Free Press, New York. 25. Robbins (1990), Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi Method ; Journal Of Expert Systems with Applications). 26. Sharma, Kumar, M., Rajab, B. (2007). An Integrated BSC­AHP Approach for Supply Chain Management Evaluation, Measuring Business Excellence, 11, pp. 57­68(12). 27. Soltani,I.(2002). the Management of Performance conducive to Human Resources Training, Isfahan Publication, Isfahan. 28. Stwart, R.A., Mohamad, S. (2001). Utilizing the Balanced Scorecard for IT/IS Performance Evaluation in Construction. Construction Innovation, pp.147­163. 29. Villalobos Quezada and Geraldina (2005). Performance Evaluation Models For Strategic Decision – Making : Towards A Hybrid Model ; Dissertation For Degree Of Philosophy. 30. Yao, Kao­hua, LIU, Cang­chuam.(2006). An Integrated Approach for Supply Chain Performance. Journal of Modern Accounting and Auditing, 2(10), pp. 54­58. 31. Yi Wu , Hung & Hshiung Tzeng , Gwo and Hsuan Chen , Yi (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard; Journal Of Expert Systems with Applications, 36, 10135­10147.
ASIAN JOURNAL OF MANAGEMENT RESEARCH 678