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Journal of Medical Systems

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01.04.2011 | Original Paper

Strategic Enterprise Resource Planning in a Health-Care System Using a Multicriteria Decision-Making Model

verfasst von: Chang Won Lee, N. K. Kwak

Erschienen in: Journal of Medical Systems | Ausgabe 2/2011

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Abstract

This paper deals with strategic enterprise resource planning (ERP) in a health-care system using a multicriteria decision-making (MCDM) model. The model is developed and analyzed on the basis of the data obtained from a leading patient-oriented provider of health-care services in Korea. Goal criteria and priorities are identified and established via the analytic hierarchy process (AHP). Goal programming (GP) is utilized to derive satisfying solutions for designing, evaluating, and implementing an ERP. The model results are evaluated and sensitivity analyses are conducted in an effort to enhance the model applicability. The case study provides management with valuable insights for planning and controlling health-care activities and services.

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Note: Eigenvalues and eigenvectors are derived from the German word “eigen” which means “proper” or “characteristics.” In matrix algebra, an eigenvalue of a scalar matrix is a scalar that is usually represented by the Greek letter λ (lambda). An eigenvector is a non-zero vector, commonly denoted by the smaller letter x. All eigenvalues and eigenvectors satisfy the equation Ax = λx for a given square matrix A. Definition: Consider the square matrix A. It is called that λ is an eigenvalue of A if there exists a non-zero vector x such that Ax = λx. In this case, x is called an eigenvector (corresponding λ), and the pair (λ, x) is called an eigenpair for A.

van Merode, G., Groothuis, S., and Hasman, A., Enterprise resource planning for hospitals. Int. J. Med. Inf. 73(6):493–501, 2004.CrossRef

Grimson, J., Delivering the electronic healthcare record for the 21st century. Int. J. Med. Inf. 64(2–3):111–127, 2001.CrossRef

Pedersen, M. K., and Larsen, M. H., Distributed knowledge management based on product state models: The case of decision support in health care administration. Decis. Support Syst. 31(1):139–158, 2001.CrossRef

Collen, M. F., A vision of health care and information in 2008. J. Am. Med. Inf. Assoc. 6(1):1–5, 1999.

Li, L. X., Benton, W. C., and Leong, G. K., The impact of strategic operations management decisions on community hospital performance. J. Oper. Manag. 20(4):389–408, 2002.CrossRef

Oddoye, J. P., Jones, D. F., Tamiz, M., and Schmidt, P., Combining simulation and goal programming for healthcare planning in a medical assessment unit. Eur. J. Oper. Res. 193(1):250–261, 2009.MATHCrossRef

Kursters, R. J., and Groot, P. M. A., Modeling resource availability in general hospitals design and implementation of a decision support model. Eur. J. Oper. Res. 88(3):428–445, 1996.CrossRef

Jenkins, E. K., and Christenson, E., ERP (enterprise resource planning) systems can streamline healthcare business functions. Healthc. Financ. Manage. 55(5):48–52, 2001.

Newman, K., Towards a new health care paradigm, patient-focused care: The case of Kingston hospital trust. J. Manage. Med. 11(5–6):357–371, 1997.CrossRef

10.

Davenport, T., Putting enterprise into the enterprise system. Harvard Bus. Rev. 76(4):121–131, 1998.

11.

Klaus, H., Rosemann, M., and Gable, G. G., What is ERP? Inf. Syst. Front. 2(2):141–162, 2000.CrossRef

12.

Motwani, J., Mirchandani, D., Madan, M., and Gunasekaran, A., Successful implementation of ERP projects: Evidence from two case studies. Int. J. Prod. Econ. 75 (1–2):83–96, 2002.CrossRef

13.

Teltumbde, A., A framework for evaluating ERP projects. Int. J. Prod. Res. 38(17):4507–4520, 2000.CrossRef

14.

Siau, K., Health care informatics. IEEE Trans. Inf. Technol. Biomed. 7(1):1–7, 2003.CrossRef

15.

Soh, C., Kien, S. S., and Tay-Yap, J., Enterprise resource planning: Cultural fits and misfits: Is ERP a universal solution? Commun. ACM. 43(4):47–51, 2000.CrossRef

16.

Botta-Genoulaz, V., and Millet, P.-A., An investigation into the use of ERP systems in the service sector. Int. J. Prod Econ. 99(1–2):202–221, 2006.CrossRef

17.

Trimmer, K. J., Pumphrey, L. D., and Wiggins, C., ERP implementation in rural health care. J. Manage. Med. 16(2/3):113–132, 2002.CrossRef

18.

Sia, S. K., Tang, M., Soh, C., and Boh, W. F., Enterprise resource planning (ERP) systems as a technology of power: Empowerment or panoptic control? Database Adv. Inform. Syst. 33(1):23–37, 2002.

19.

Charnes, A., and Cooper, W. W., Management models and the industrial applications of linear programming, vols. 1-2. Wiley, New York, 1961.

20.

Onut, S., Kara, S. S., and Isik, E., Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Syst. Appl. 36(2):3887–3895, 2009.CrossRef

21.

Saaty, T. L., The analytical hierarchy process. McGraw-Hill, New York, 1980.

22.

Saaty, T. L., Decision making for leaders: The analytical hierarchy process for decisions in a complex world, 3rd edition. RWS, Pittsburgh, 1999.

23.

Earnshaw, S. R., and Dennett, S. L., Integer/linear mathematical programming models: A tool for allocating healthcare resources. PharmacoEconomics. 21(12):839–851, 2003.CrossRef

24.

Kwak, N. K., and Lee, C. W., Business process reengineering for health-care system using multicriteria mathematical programming. Eur. J. Oper. Res. 140(2):447–458, 2002.MATHCrossRef

25.

Epstein, D. M., Chalabi, Z., Claxton, K., and Sculpher, M., Efficiency, equity, and budgetary policies: Informing decisions using mathematical programming. Med. Decis. Mak. 27(2):128–137, 2007.CrossRef

26.

Oddoye, J. P., Yaghoobi, M. A., Tamiz, M., Jones, D. F., and Schmidt, P., A multi-objective model to determine efficient resource levels in a medical assessment unit. J. Oper. Res. Soc. 57(10):1173–1179, 2006.CrossRef

27.

Liberatore, M. J., and Nydick, R. L., The analytic hierarchy process in medical and health care decision making: A literature review. Eur. J. Oper. Res. 189(1):194–207, 2008.MATHCrossRef

28.

Wilson, R. M., and Gibberd, R. W., Combining multiple criteria for regional resource allocation in health care systems. Math. Comput. Model. 13(8):15–27, 1990.MATHCrossRef

29.

Flessa, S., Priorities and allocation of health care resources in developing countries: A case-study from the Mtwara region-Tanzana. Eur. J. Oper. Res. 150(1):67–80, 2003.MATHCrossRef

30.

Cardoen, B., Demeulemeester, E., and Belien, J., Sequencing surgical cases in a day-care environment: An exact branch-and-price approach. Comput. Oper. Res. 36(9):2660–2669, 2009.MATHCrossRef

31.

Arenas, M., Bilbao, A., Caballero, R., Gómez, T., Rodríguez, M. V., and Ruiz, F., Analysis via goal programming of the minimum achievable stay in surgical waiting lists. J. Oper. Res. Soc. 53(4):387–396, 2002.MATHCrossRef

32.

Lee, S. M., AB:QM. Allyn & Bacon, Boston, 1996.

33.

Anderson, D. R., Sweeney, D. J., and Williams, T. A., The management scientist V 6.0. West Publication, St. Paul, 2004.

Titel: Strategic Enterprise Resource Planning in a Health-Care System Using a Multicriteria Decision-Making Model
verfasst von: Chang Won Lee
N. K. Kwak
Publikationsdatum: 01.04.2011
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 2/2011
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-009-9362-x

Springer Medizin

Abstract

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