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Journal of Medical Systems

, Volume 35, Issue 5, pp 1039–1062 | Cite as

Data Envelopment Analysis Model for the Appraisal and Relative Performance Evaluation of Nurses at an Intensive Care Unit

  • Ibrahim H. Osman
  • Lynn N. Berbary
  • Yusuf Sidani
  • Baydaa Al-Ayoubi
  • Ali Emrouznejad
ORIGINAL PAPER

Abstract

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

Keywords

Data envelopment analysis Health care services Nursing appraisal Performance evaluation Ratio pitfalls of units to measures Talent management 

Notes

Acknowledgment

The authors would like to thank the director of nursing services at Hospital G for cooperation and allowing access to their confidential data without such the project would not have been achieved.

References

  1. 1.
    Andes, S., Metzger, L. M., Kralewski, J., and Gans, D., Measuring efficiency of physician practices using data envelopment analysis. Manag. Care 11(11):48–54, 2002.Google Scholar
  2. 2.
    Ashton, M. C., Personality and job performance: The importance of narrow traits. J. Organ. Behav. 19(3):289–303, 1998.CrossRefGoogle Scholar
  3. 3.
    Banker, R. D., Charnes, A., and Cooper, W. W., Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage. Sci. 30(9):1078–1092, 1984.zbMATHCrossRefGoogle Scholar
  4. 4.
    Banker, R. D., Charnes, A., Cooper, W. W., Swarts, W., and Thomas, D., An introduction to data envelopment analysis with some of its models and their uses. Res. Gov. Non-profit Account. 5:125–163, 1989.Google Scholar
  5. 5.
    Bannigan, K., To serve better: Addressing poor performance in occupational therapy. Br. J. Occup. Ther. 63(11):523–528, 2000.Google Scholar
  6. 6.
    Bernardin, H. J., and Beatty, R. W., Performance appraisal: Assessing human behavior at work. Kent Pub. Co., Boston, 1984.Google Scholar
  7. 7.
    Blumenfield, S., and Epstein, I., Promoting and maintaining a reflective professional staff in a hospital-based social work department. Soc. Work Health Care 33(3–4):1–13, 2001.Google Scholar
  8. 8.
    Boles, J., Donthu, N., and Lohtia, R., Salesperson evaluation using relative performance efficiency: The application of data envelopment analysis. J. Pers. Sell. Sales Manage. 15(3):31–49, 1995.Google Scholar
  9. 9.
    Bowers, S. J., and Jinks, A. M., Issues surrounding professional portfolio development for nurses. Br. J. Nurs. 13(3):155–159, 2004.Google Scholar
  10. 10.
    Bowlin, W., Renner, C., and Rives, J., A DEA study of gender equity in executive compensation. J. Oper. Res. Soc. 54(7):751–757, 2003.zbMATHCrossRefGoogle Scholar
  11. 11.
    Bradley, D., and Huseman, S., Validating competency at the bedside. J. Nurses Staff Dev. 19(4):165–173, 2003.CrossRefGoogle Scholar
  12. 12.
    Brahm, M. M., and de Magalhaes, A. M., Nursing team opinion concerning the performance evaluation process. Acta Paul Enferm 20(4):415–421, 2007.CrossRefGoogle Scholar
  13. 13.
    Castle, N. G., An instrument to measure job satisfaction of nursing home administrators. BMC Med. Res. Methodol. 47(6):1–11, 2006.Google Scholar
  14. 14.
    Chandra, A., and Frank, Z. D., Utilization of performance appraisal systems in health care organizations and improvement strategies for supervisors. Health Care Manager 23(1):25–30, 2004.Google Scholar
  15. 15.
    Charnes, A., Cooper, W. W., and Rhodes, E., Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2(6):429–444, 1978.zbMATHMathSciNetCrossRefGoogle Scholar
  16. 16.
    Chen, Y., Gregoriou, G., and Rouah, F., Efficiency persistence of bank and thrift CEOs using data envelopment analysis. Comput. Oper. Res. 36:1554–1561, 2009.zbMATHCrossRefGoogle Scholar
  17. 17.
    Cooper, W. W., Seiford, L. M., and Tone, K., Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software, 2nd edition. Springer, New York, 2007.zbMATHGoogle Scholar
  18. 18.
    Dowling, A. F., Nursing information systems. J. Med. Syst. 9(1-2), 1985.Google Scholar
  19. 19.
    Dyson, R., Allen, R., Camanho, A., Podinovski, V., Sarrico, C., and Shale, E., Pitfalls and protocols in DEA. Eur. J. Oper. Res. 132(2):245–259, 2001.zbMATHCrossRefGoogle Scholar
  20. 20.
    Emden, C., Hutt, D., and Bruce, M., Portfolio learning assessment in nursing and midwifery: An innovation in progress. Contemp. Nurse 16(1–2):124–132, 2003.Google Scholar
  21. 21.
    Emrouznejad, A., Parker, B., and Tavares, G., Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. J. Socio-Econ. Plann. Sci. 42(3):151–157, 2008.CrossRefGoogle Scholar
  22. 22.
    Finucane, P. M., Bourgeois-Law, G. A., Ineson, S. L., and Kaigas, T. M., A comparison of performance assessment programs for medical practitioners in Canada, Australia, New Zealand, and the United Kingdom. Acad. Med. 78(8):837–843, 2003.CrossRefGoogle Scholar
  23. 23.
    Gray, G., Performance Appraisals do not work. Industrial Management, 15-17, March/April 2002.Google Scholar
  24. 24.
    Golany, B. A., and Roll, Y., An application procedure for data envelopment analysis. Omega 17(3):237–250, 1989.CrossRefGoogle Scholar
  25. 25.
    Grussing, P. G., Valuck, R. J., and Williams, R. G., Development and validation of behaviorally-anchored rating scales for student evaluation of pharmacy instruction. Am. J. Pharm. Educ. 58(Winter Supplement):25–37, 1994.Google Scholar
  26. 26.
    Hamilton, K. E., Coates, V., Kelly, B., Boore, J. P., Cundell, J. H., Gracey, J., Mcfetridge, B., Mcgonigle, M., and Sinclair, M., Performance assessment in health care providers: A critical review of evidence and current practice. J. Nurs. Manage. 15:773–791, 2007.CrossRefGoogle Scholar
  27. 27.
    Hedley, B., A fundamental approach to strategy development. Long Range Plann. 9(6):2–11, 1976.CrossRefGoogle Scholar
  28. 28.
    Henderson, R.I. 1980. Performance Appraisal: Theory to practice. Virginia: Reston Publishing Company.Google Scholar
  29. 29.
    Hollingsworth, B., Dawson, P. J., and Maniadakis, N., Efficiency measurement of health care: A review of non-parametric methods and applications. Health Care Manage. Sci. 2(3):161–72, 1999.CrossRefGoogle Scholar
  30. 30.
    Homburg, C., Using data envelopment analysis to benchmark activities. Int. J. Prod. Econ. 73(1):51–58, 2001.CrossRefGoogle Scholar
  31. 31.
    Hoogestraat, T. L., Validation of PMG’s 360-degree feedback process. George Fox University, USA, 2007.Google Scholar
  32. 32.
    Islam, R., and Rasad, S. B. M., Employee performance evaluation by AHP: A case study. Proceedings of the 8th International Symposium on Analytic Hierarchy Process. July 8–10, 2005, Honolulu, Hawaii, USA. 2005.Google Scholar
  33. 33.
    Johnson, S. A., and Zhu, J., Identifying best applicants in recruiting using data envelopment analysis. Socio-econ. Plann. Sci. 37(2):125–139, 2003.CrossRefGoogle Scholar
  34. 34.
    Kemppainen, J. K., The critical incident technique and nursing care quality research. J. Adv. Nurs. 32(5):1264–1271, 2000.CrossRefGoogle Scholar
  35. 35.
    Kingstrom, P. O., and Bass, A. R., A critical analysis of studies comparing behaviorally anchored rating scales (bars) and other rating formats. Pers. Psychol. 34(2):211–449, 1981.CrossRefGoogle Scholar
  36. 36.
    Kleinsorge, I. K., and Karney, D. F., Management of nursing homes using data envelopment analysis. Socio-econ. Plann. Sci. 26(1):57–71, 1992.CrossRefGoogle Scholar
  37. 37.
    Lloyd, J., How to build a high-performance facility management organisation. J. Facil. Manage. 3(4):325–337, 2005.CrossRefGoogle Scholar
  38. 38.
    Lockyer, J., Multisource feedback in the assessment of physician competencies. J. Contin. Educ. Health Prof. 23(1):4–12, 2003.CrossRefGoogle Scholar
  39. 39.
    Longenecker, C. O., and Fink, L. S., Creative effective performance appraisals. Industrial Management 41(5):18–23, 1999.Google Scholar
  40. 40.
    Lopez-Cabrales, A., Valle, R., and Herrero, I., The contribution of core employees to organizational capabilities and efficiency. Hum. Resour. Manage. 45(1):81–109, 2006.CrossRefGoogle Scholar
  41. 41.
    Mani, B.G., Performance Appraisal Systems, Productivity, and Motivation: A Case Study, Public Personnel Management, 31(2): 141–159, 2002.Google Scholar
  42. 42.
    Marsland, D., and Gissane, C., Nursing evaluation: Purposes, achievements and opportunities. Int. J. Nursing Study 29(3):231–236, 1992.CrossRefGoogle Scholar
  43. 43.
    McCabe, T. J., and Garavan, T. N., A study of the drivers of commitment amongst nurses: The salience of training, development and career issues. J. Eur. Ind. Train. 32(7):528–568, 2008.CrossRefGoogle Scholar
  44. 44.
    McCarthy, J., How to conduct productive performance appraisals. J. Prop. Manage.: 22–25, 2000.Google Scholar
  45. 45.
    McCarthy, A., and Garavan, T., Understanding acceptance of multisource feedback for management development. Pers. Rev. 36(6):903–917, 2007.CrossRefGoogle Scholar
  46. 46.
    Meng, W., Zhang, D., Qi, L., and Liu, W., Two-level DEA approaches in research evaluation, 36(6):950–957, 2008.Google Scholar
  47. 47.
    Meyer, A., An employee evaluation tool that works. Nurs. Homes 44(2):14–17, 1995.Google Scholar
  48. 48.
    Nunamaker, T., Measuring routine nursing service efficiency: A comparison of cost per patient day and data envelopment analysis models. Health Serv. Res. 18(2 Pt 1):183, 1983.Google Scholar
  49. 49.
    Ogunyemi, D., Gonzalez, G., Fong, A., Alexander, C., Finke, D., Donnon, T., and Azziz, R., From the eye of the nurses: 360-degree evaluation of residents. J. Contin. Educ. Health Prof. 29(2):105–110, 2009.CrossRefGoogle Scholar
  50. 50.
    Osman, I. H., Hitti, A., and Al-Ayoubi, B., Data Envelopment Analysis: A Tool For Monitoring The Relative Efficiency Of Lebanese Banks. In: Irani, Z. et al. (Eds.), Online Proceedings of the European and Mediterranean on Information Systems Conference (ECMS2008) Late Breaking Papers, May 25–26th, 2008, Al-Bustan Rotana, Dubai, UAE, 2008.Google Scholar
  51. 51.
    Osman, I. H., Helou, M., and Al-Ayoubi, B., A Knowledge Value Chain Management Framework & Its Relative Performance Evaluation on Academics in Higher Education. Proceedings of the 10th ISAHP 2009 Symposium, July 29–August 1, 2009, Pittsburgh, Pennsylvania, USA, 2009.Google Scholar
  52. 52.
  53. 53.
    PAF-HG (2009). Performance Appraisal Form at the Nursing Services of the Hospital in Beirut Lebanon. Anonymous for confidentiality reason.Google Scholar
  54. 54.
    Paradi, J.C., Smith, S., Schaffnit-Chatterjee, C., Knowledge worker performance analysis using DEA: an application to engineering design teams at Bell Canada. IEEE Transactions on Engineering Management, 49(2):161–172, 2002.Google Scholar
  55. 55.
    Patten, T., Pay: Employee compensation and incentive plans. Free, London, 1977.Google Scholar
  56. 56.
    Pedraja-Chaparro, F., Salinas-Jimenez, J., and Smith, P., On the quality of the data envelopment analysis model. J. Oper. Res. Soc. 50(6):636–644, 1999.zbMATHGoogle Scholar
  57. 57.
    PEF-UCB, Performance evaluation forms and resources. University of California, Berkeley. http:hrweb.berkeley.eduformspedescr.htm, 2009.
  58. 58.
    Ramanathan, R., Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process, Computers & Operations Research 33(5): 1289–1307, 2006.Google Scholar
  59. 59.
    Redfern, S. J., Norman, I. J., Calman, L., Watson, R., and Murrells, T., Assessing competence to practice in nursing: A review of the literature. Res. Pap. Educ. 17(1):55–84, 2002.Google Scholar
  60. 60.
    Roberts, G. E., Employee performance appraisal system participation: A technique that works. Public Pers. Manage. 32(1):89–98, 2003.Google Scholar
  61. 61.
    Rosenman, R., and Friesner, D., Scope and scale inefficiencies in physician practices. Health Econ. 13(11):1091–116, 2004.CrossRefGoogle Scholar
  62. 62.
    Schoessler, M. T., Aneshansley, P., Baffaro, C., Castellano, T., Goins, L., Largaespada, E., Payne, R., and Stinson, D., The performance appraisal as a developmental tool. J. Nurses Staff Dev. 24(3):12–18, 2008.CrossRefGoogle Scholar
  63. 63.
    Schwab, D. P., Heneman, H. G., III, and DeCotis, T. A., Behaviorally anchored rating scales: A review of the literature. Pers. Psychol. 28:549–562, 1975.CrossRefGoogle Scholar
  64. 64.
    Shimshak, D., Lenard, M., and Klimberg, R., Incorporating quality into Data Envelopment Analysis in nursing home performance: A case study. Omega 37:672–685, 2009.CrossRefGoogle Scholar
  65. 65.
    Somerick, N. M., Strategies for improving employee relations by using performance appraisals more effectively. Public Relat. Q. 38(3):37–39, 1993.Google Scholar
  66. 66.
    SPAF-PU. Staff performance appraisal form, at Princeton University. http:www.princeton.eduhrpoliciesconditionsperfappb.doc, 2009.
  67. 67.
    Thanassoulis, E., Assessing police forces in England and Wales using data envelopment analysis European Journal of Operational Research, 87(3): 641–657,1995.Google Scholar
  68. 68.
    Thanassoulis, E., Introduction to the theory and application of data envelopment analysis: A foundation text with integrated software. Kluwer, Norwell, 2001.Google Scholar
  69. 69.
    Timmreck, T. C., Developing successful performance appraisals through choosing appropriate words to effectively describe work. Health Care Manage. Rev. 23(3):48–57, 1998.Google Scholar
  70. 70.
    Tustin, J., Canham, G., Berridge, J., Braden, D., and Starke, T., Professional development and appraisal system for school nurses. J. Sch. Nurs. 18(4):229–236, 2002.CrossRefGoogle Scholar
  71. 71.
    Wagner, J.M., Shimshak. D.G., and Novak, M.A., Advances in physician profiling: the use of DEA Socio-Economic Planning Sciences, 37(2):141-163, 2003.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Ibrahim H. Osman
    • 1
  • Lynn N. Berbary
    • 1
  • Yusuf Sidani
    • 1
  • Baydaa Al-Ayoubi
    • 2
  • Ali Emrouznejad
    • 3
  1. 1.Olayan School of BusinessAmerican University of BeirutBeirutLebanon
  2. 2.Faculty of Science ILebanese UniversityBeirutLebanon
  3. 3.Aston Business SchoolAston UniversityBirminghamUK

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