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Statistical Quality Control Methods in Infection Control and Hospital Epidemiology, Part I Introduction and Basic Theory

Published online by Cambridge University Press:  02 January 2015

James C. Benneyan
James C. Benneyan*
Affiliation:
Northeastern University, Boston, Massachusetts
*
Mechanical, Industrial, and Manufacturing Department, 334 Snell Engineering Center, Northeastern University, Boston, MA 02115
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Abstract

This article is the first in a two-part series discussing and illustrating the application of statistical process control (SPC) to processes often examined by hospital epidemiologists. The basic philosophical and theoretical foundations of statistical quality control and their relation to epidemiology are emphasized in order to expand mutual understanding and cross-fertilization between these two disciplines. Part I provides an overview of quality engineering and SPC, illustrates common types of control charts, and provides references for further information or statistical formulae. Part II discusses statistical properties of control charts, issues of chart design and optimal control limit widths, alternate possible SPC approaches to infection control, some common misunderstandings, and more advanced issues. The focus of both articles is mostly non-mathematical, emphasizing important concepts and practical examples rather than academic theory and exhaustive calculations

Type
Statistics for Hospital Epidemiology
Information
Infection Control & Hospital Epidemiology , Volume 19 , Issue 3 , March 1998 , pp. 194 - 214
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1998

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References

1. Benneyan, JC. Statistical quality control in infection control methods and hospital epidemiology, part II: chart use, statistical properties, and research issues. Infect Control Hosp Epidemiol. In press.Google Scholar
2. Sellick, JA. The use of statistical process control charts in hospital epidemiology. Infect Control Hosp Epidemiol 1993;14:649–656.CrossRefGoogle ScholarPubMed
3. Lee, JT. Statistical process control charts. Infect Control Hosp Epidemiol 1994;15:223, 224. Letter.CrossRefGoogle ScholarPubMed
4. Burnett, L, Chesher, D. Applications of CQI tools to the reduction in risk of needlestick injury. Infect Control Hosp Epidemiol 1995;16:503–505.CrossRefGoogle Scholar
5. Mylotte, JM, White, D, McDermott, C, Hodan, C. Nosocomial bloodstream infection at a veterans hospital: 1979 to 1987. Infect Control Hosp Epidemiol 1989;10:455–464.CrossRefGoogle Scholar
6. Benneyan, JC. Using statistical process control (SPC) to improve health care. Quality Management in Health Care. In press.Google Scholar
7. Koska, MT. Using CQI methods to lower post-surgical wound infection rate. Hospitals 1992;66:62–64.Google Scholar
8. Birnbaum, D. Measuring health care quality. Quality Progress 1994;27:108–112.Google Scholar
9. Benneyan, JC, Kaminsky, FC. Another view on how to measure health care quality. Quality Progress 1995;28:120–124.Google Scholar
10. Benneyan, JC. Applications of statistical process control (SPC) to improve health care. Proceedings of the 1995 Healthcare Information and Management Systems Society Annual Conference. Chicago, IL: Healthcare Information and Management Systems Society; 1995;2:289–301.Google Scholar
11. Finison, LJ, Finison, KS, Bliersback, CM. The use of control charts to improve healthcare quality. Journal for Healthcare Quality 1993;15(1):9–23.CrossRefGoogle ScholarPubMed
12. Plesk, P. Tutorial: introduction to control charts. Quality Management in Health Care 1992;1(1):65–73.CrossRefGoogle Scholar
13. Reinke, WA. Applicability of industrial sampling techniques to epidemiologic investigations: examination of an underutilized resource. Am J Epidemiol 1991;134:1222–1232.CrossRefGoogle ScholarPubMed
14. Schnelle, JF, Newman, DR, Fogarty, T. Statistical quality control in nursing homes: assessment and management of chronic urinary incontinence. Health Serv Res 1990;25:627–637.Google ScholarPubMed
15. Plume, SK. Outcomes data: publishing the right stuff. The Quality Letter for Healthcare Leaders 1993;5(6):20–24.Google ScholarPubMed
16. VanderVeen, LM. Statistical process control: a practical application for hospitals. Journal for Healthcare Quality 1992;14(2):20–29.CrossRefGoogle ScholarPubMed
17. Birnbaum, DW. Analysis of hospital surveillance data. Infect Control 1984;5:332–338.CrossRefGoogle Scholar
18. Birnbaum, DW. CQI tools: sentinel events, warning, and action limits. Infect Control Hosp Epidemiol 1993;14:537–539.CrossRefGoogle ScholarPubMed
19. Birnbaum, DW. Nosocomial infection surveillance programs. Infect Control Hosp Epidemiol 1987;8:474–479.CrossRefGoogle ScholarPubMed
20. McGuckin, MB, Abrutyn, E. A surveillance method for early detection of nosocomial outbreaks. Am J Infect Control 1979;7:18–21.Google ScholarPubMed
21. Berwick, DM. Controlling variation in health care: a consultation from Walter Shewhart. Med Care 1991;29:1212–1225.CrossRefGoogle ScholarPubMed
22. Laffel, G, Blumenthal, D. The case for using industrial quality management science in health care organizations. JAMA 1989;262:2869–2873.CrossRefGoogle ScholarPubMed
23. Blumenthal, D. Total quality management and physicians clinical decisions. JAMA 1993;269:2775–2778.CrossRefGoogle ScholarPubMed
24. Jacquez, GM, Waller, LA, Grimson, R, Wartenberg, D. The analysis of disease clusters, part I: state of the art. Infect Control Hosp Epidemiol. 1996;17:319–327.CrossRefGoogle ScholarPubMed
25. Mylotte, JM. Analysis of infection surveillance data in a long-term care facility: use of threshold settings. Infect Control Hosp Epidemiol 1996;17:101–107.CrossRefGoogle Scholar
26. Childress, JA, Childress, JD. Statistical tests for possible infection outbreaks. Infect Control Hosp Epidemiol 1981;2:247–249.CrossRefGoogle Scholar
27. Hillier, FS, Lieberman, GJ. Introduction to Operations Research. 3rd ed. San Francisco, CA: Holden-Day, Inc; 1980.Google Scholar
28. Revelle, CS, Feldman, F, Lynn, W. An optimization model of tuberculosis epidemiology. Management Science 1969;16(4):B190–B211.CrossRefGoogle Scholar
29. Waller, W, Geser, A, Anderson, S. The use of mathematical models in the study of the epidemiology of tuberculosis. Am J Public Health 1962;52:1002–1013.CrossRefGoogle Scholar
30. Bush, JW, Chen, MM, Zaremba, J. Estimating health program outcomes using a Markov equilibrium analysis of disease control. Am J Public Health 1971;61:2362–2375.CrossRefGoogle Scholar
31. Gilberth, FB. Motion study in surgery. Canadian Journal of Medical Surgery 1916;40(1):22–31.Google Scholar
32. Fetter, RB, Shin, Y, Freeman, JL, Averill, RF, Thompson, JD. Case mix definition by diagnosis related groups. Med Care 1980:18(2):1–53.Google ScholarPubMed
33. Fetter, RB. Hospital payment based on diagnosis-related groups. J Soc Health Syst 1992;3(4):4–15.Google ScholarPubMed
34. Sahney, VK. Evolution of hospital industrial engineering: from scientific management to total quality management. J Soc Health Syst 1992;3(4):3–17.Google Scholar
35. Fries, BE. Bibliography of operations research in health-care systems. Operations Research: Special Health Care Issue (Pierskalla, WP, Urban, GL, eds.) 1976;24:801–814.CrossRefGoogle Scholar
36. Flagle, CD, Young, JP. Applications of operations research and industrial engineering to problems of hospitals. Journal of Industrial Engineering 1966;17:609–614.Google Scholar
37. Smalley, HE. Industrial engineering in hospitals. Journal of Industrial Engineering 1959;10:171–175.Google Scholar
38. Goldman, J, Knappenberger, HA, eds. Issue focus: IE contributions. J Soc Health Syst 1992;3(4).Google Scholar
39. Pasternack, A, ed. Guide to Effective Health Care Management Engineering. Chicago, IL: Healthcare Information and Management Systems Society; 1995.Google Scholar
40. Rising, EJ. Ambulatory Care Systems, I: Design for Improved Patient Flow. Lexington, MA: Lexington Books; 1977.Google Scholar
41. Mahachek, AR. An introduction to patient flow simulation for healthcare managers. J Soc Health Syst 1992;3:73–81.Google Scholar
42. Benneyan, JC. An introduction to using computer simulation in healthcare. J Soc Health Syst 1997;5:1–15.Google ScholarPubMed
43. Kennedy, OG, Davis, GM, Heda, S. Clinical information systems: 25-year history and the future. J Soc Health Syst 1992;3:49–60.Google ScholarPubMed
44. Duncan, IB, Norwich, HS. Opportunity costs and elementary inventory theory in the hospital service. Operational Research Quarterly 1973;24:27–34.CrossRefGoogle Scholar
45. Reed, R, Stanley, WE. Optimizing control of hospital inventories. Journal of Industrial Engineering 1965;16(1):48–51.Google Scholar
46. Gilberth, LM. Motion and time study. Modern Hospital 1945;65(3):53, 54.Google Scholar
47. Gilberth, LM. Management engineering and nursing. Am J Nurs 1950;50:780, 781.Google Scholar
48. Rising, EJ, Baron, R, Averill, B. A systems analysis of a university health service outpatient clinic. Operations Research 1973;21:1030–1047.CrossRefGoogle Scholar
49. Griffith, JR, Wellman, BT. Forecasting bed needs and recommending plans for community hospitals: a review of past performance. Med Care 1979;17:293–303.CrossRefGoogle ScholarPubMed
50. Schmitz, HH, Kwak, NK. Monte Carlo simulation of operating room and recovery-room usage. Operations Research 1972;20:1171–1180.CrossRefGoogle Scholar
51. Giglio, RJ, ed. Issue focus: resource scheduling. J Soc Health Syst 1991;2(2).Google Scholar
52. Kolesar, P. A Markovian model for hospital admission scheduling. Management Science 1970;16(6):B384–B396.CrossRefGoogle Scholar
53. Warner, DM, Prawda, J. A mathematical programming model for scheduling nursing personnel in a hospital. Management Science 1972;19:411–422.CrossRefGoogle Scholar
54. Trivedi, VM, Warner, DM. A branch and bound algorithm for optimum allocation of float nurses. Management Science 1976;22:972–981.CrossRefGoogle Scholar
55. Goldman, J, Knappenberger, HA, Moore, EW. An evaluation of operating room scheduling policies. Hospital Management 1969;110:40–51.Google Scholar
56. Gitlow, HS. A methodology for determining the optimal design of a free standing abortion clinic. Management Science 1976;22:1289–1298.CrossRefGoogle ScholarPubMed
57. Coope, JK, Corcovan, TM. Estimating bed needs by means of queueing theory. N Engl J Med 1974;291:404, 405.Google Scholar
58. Davies, R, Johnson, D, Farrow, S. Planning patient care with a Markov model. Operational Research Quarterly 1975;26:599–607.CrossRefGoogle Scholar
59. Meredith, J. A Markovian analysis of a geriatric ward. Management Science 1973;19:604–612.CrossRefGoogle Scholar
60. Kao, EPC. A semi-Markov model to predict recovery progress of coronary patients. Health Serv Res 1972;7:192–208.Google ScholarPubMed
61. Shuman, LJ, Wolfe, H, Speas, RD. The role of operations research in regional health planning. Operations Research 1974;22:234–248.CrossRefGoogle Scholar
62. Dokmeci, VF. A qualitative model to plan regional health facility systems. Management Science 1977;24:411–419.CrossRefGoogle Scholar
63. Reisman, A, Dean, BV, Esogbue, AO, Aggornal, V, Kauja, LG, Lewy, P, et al. Physician supply and surgical demand forecasting: a regional manpower study. Management Science 1973;19:1345–1359.CrossRefGoogle Scholar
64. McKenna, JV. The standardization of surgical services. Journal of Industrial Engineering 1960;11(1):3–7.Google Scholar
65. McCarty, FB. Motion study in surgery. Am J Surg 1944;65:197–209.CrossRefGoogle Scholar
66. Ross, JP. The scientific approach to surgery. BMJ 1959;5140:26–29.CrossRefGoogle Scholar
67. Jennings, JB. Blood bank inventory control. Management Science 1973;19:637–645.CrossRefGoogle Scholar
68. Rockwell, TH, Barnum, RA, Griffin, WC. Inventory analysis as applied to hospital whole blood supply and demand. Journal of Industrial Engineering 1962;13:109–114.Google Scholar
69. Benneyan, JC. The importance of modeling discrete data in SPC. Proceedings of the Tenth International Conference of the Israel Society for Quality. Jerusalem, Israel: Israel Society for Quality; 1994:640–646.Google Scholar
70. Benneyan, JC, Kaminsky, FC. Statistical and economic models for analysis and optimal design of laboratory screening policies for cervical cancer. Annals of Operations Research 1996;67:235–285.CrossRefGoogle Scholar
71. Eddy, DM. Screening for Cancer: Theory, Analysis, and Design. Englewood Cliffs, NJ: Prentice-Hall Inc; 1980.Google Scholar
72. David, I, Yechiali, U. A time-dependent stopping problem with application to live organ transplants. Operations Research 1985;33:491–504.CrossRefGoogle ScholarPubMed
73. Kent, DL, Shachter, R, Sox, HC, Hui, NS, Shortliffe, LD, Moynihan, S, et al. Optimal scheduling of cystoscopies in monitoring for recurrent bladder cancer. Med Decis Making 1989;9:26, 27.CrossRefGoogle Scholar
74. Deming, WE. Quality, Productivity, and Competitive Position. Cambridge, MA: Massachusetts Institute of Technology Center for Advanced Engineering Studies; 1982.Google Scholar
75. Al-Assaf, AF, Schmele, JA, eds. The Textbook of Total Quality in Healthcare. Delray Beach, FL: St Lucie Press; 1993.CrossRefGoogle Scholar
76. Neave, HR. The Deming Dimension. Knoxville, TN: SPC Press Inc; 1990.Google Scholar
77. Berwick, DM. Continuous improvement as an ideal in health care. N Engl J Med 1989;320:53–56.CrossRefGoogle ScholarPubMed
78. Deming, WE. Notes on management in a hospital. 09 20, 1987. Reprinted in: Kilian CS. Observations on medical care and hospital management. In: The World of W. Edwards Deming, 2nd ed. Knoxville, TN: SPC Press; 1992.Google Scholar
79. Martone, WJ, Gaynes, RP, Horan, TC, Emori, TG, Jarvis, WR, Bennett, ME, et al. Nosocomial infection rates for interhospital comparison: limitations and possible solutions. Infect Control Hosp Epidemiol 1991;12:609–621.Google Scholar
80. Juran, JM, Gryna, FM, eds. Juran's Quality Control Handbook, 4th ed. New York, NY: McGraw-Hill Book Co; 1988.Google Scholar
81. Benneyan, JC. The Role of Quality Engineering, Statistical Quality Management, and TQM for Improving Health Care. Technical Report. University of Massachusetts: Industrial Engineering and Operations Research; 1995.Google Scholar
82. Benneyan, JC. Improving healthcare systems using SPC and quality engineering: billing and laboratory case studies. Proceedings of the 1996 Healthcare Information and Management Systems Society Annual Conference. Chicago, IL: Healthcare Information and Management Systems Society;1996;(2):31–40.Google Scholar
83. Montgomery, DC. Introduction to Statistical Quality Control. 2nd ed. New York, NY: John Wiley and Sons, Inc; 1991.Google Scholar
84. Duncan, AJ. Quality Control and Industrial Statistics. 5th ed. Homewood, IL: Richard D. Irwin, Inc; 1986.Google Scholar
85. Benneyan, JC, Kaminsky, FC. Modeling discrete data in SPC: the gand h control charts. ASQC Annual Quality Congress Transactions 1994:32–42.Google Scholar
86. Brewer, JH, Gasser, CS. The affinity between continuous quality improvement and epidemic surveillance. Infect Control Hosp Epidemiol 1993;14:95–98.CrossRefGoogle ScholarPubMed
87. Kritchevsky, SB, Simmons, BP. The tools of quality improvement: CQI versus epidemiology. Infect Control Hosp Epidemiol 1995;16:499–502.CrossRefGoogle ScholarPubMed
88. Larson, EA. A comparison of methods for surveillance of nosocomial infections. Infect Control 1980;6:377–380.CrossRefGoogle Scholar
89. Benneyan, JC. Design of statistical g control charts for nosocomial infection and other alternatives. International Applied Statistics in Medicine Conference Transactions. In press.Google Scholar
90. Whitt, W. A review of L= λW and extensions. Queueing Systems 1991;9:235–268.CrossRefGoogle Scholar
91. Grant, EL, Leavenworth, RS. Statistical Quality Control. 6th ed. New York, NY: McGraw-Hill Book Co; 1988.Google Scholar
92. Friedman, DJ, Albin, SL. Clustered defects in IC fabrication: impact on process control charts. IEEE Transactions on Semiconductor Manufacturing 1991;4(1):36–42.CrossRefGoogle Scholar
93. Bisgaard, S. The importance of graphics in problem solving and detective work. Quality Engineering 1996;9(1):157–162.CrossRefGoogle Scholar
94. Shewhart, WA. Statistical Method from the Viewpoint of Quality Control. Washington, DC: Lancaster Press, Inc; 1939.Google Scholar
95. Latzko, WJ. Control charts in the board room. ASQC Quality Congress Transactions 1989:731–736.Google Scholar
96. Latzko, WJ. Quality and Productivity for Bankers and Financial Managers. New York, NY: Marcel Dekker, Inc; 1986.Google Scholar
97. Rosander, AC. Applications of Quality Control in the Service Industries. New York, NY: Marcel Dekker, Inc; 1985.CrossRefGoogle Scholar
98. Deming, WE, Geoffrey, L. On sample inspection in the processing of census returns. Journal of the American Statistical Association 1941;36:351–360.CrossRefGoogle Scholar
99. Philpot, JW. Monitoring administrative and service functions using statistical process control. Survey of Business 1984;20:7–10.Google Scholar
100. Benneyan, JC, Chute, AD. SPC, process improvement, and Deming's PDCA cycle in freight administration. Production and Inventory Management Journal 1993;34(11):35–40.Google Scholar
101. Bicking, CA. The application of quality control to administrative problems. Industrial Quality Control 1950;6(6):21–25.Google Scholar
102. Mandel, B. Statistical programs of the United States post office department. Industrial Quality Control 1967;23:535–538.Google Scholar
103. Selover, RB. Some applications of quality control techniques to clerical work. Industrial Quality Control 1955;12(8):5–8.Google Scholar
104. Anderson, EA, Diaz, J. Using process control chart techniques to analyze crime rates in Houston, Texas. Journal of the Operational Research Society 1996;47:871–881.CrossRefGoogle Scholar
105. Ramsey, LP, Cantrell, RS. Investigating cost variances using control charts. Healthcare Financial Management 1985;339:61–62.Google Scholar
106. D'Agostino, RB, Stephens, MA, eds. Goodness-of-Fit Techniques. New York, NY: Marcel Dekker, Inc; 1986.Google Scholar
107. Banks, J. Principles of Quality Control. New York, NY: John Wiley and Sons, Inc; 1981.Google Scholar
108. Benneyan, JC. Measuring health care quality: a statistical quality management perspective. In: Ahluwalia, JS, ed. Total Quality: Creating Individual and Corporate Success. New Delhi, India: Excel Books; 1996.Google Scholar
109. Benneyan, JC. Using statistical process control (SPC) to measure and improve health care quality. 8th Annual Quest for Quality and Productivity in Health Services Conference Proceedings. Norcross, GA: Institute of Industrial Engineers; 1996:143–150.Google Scholar
110. Benneyan, JC. On the Application and Interpretation of Control Charts With Unequal Subgroup Sizes With Application to Hospital Length of Stay Data. Technical Report. University of Massachusetts: Industrial Engineering and Operations Research; 1996.Google Scholar
111. Zimmerman, SM, Brown, LD, Brown, SS, Alexander, L. Human body function control charts for the physician. ASQC Quality Congress Transactions 1990:408–412.Google Scholar
112. Garlock, JH, Seley, GP. The use of sulfanilamide in surgery on the colon and rectum. preliminary report. Surgery 1939;5:787–790.Google Scholar
113. Classen, DC, Evans, RS, Pestotnik, SL, Horn, SD, Menlove, RL, Burke, JP. The timing of prophylactic administration of antibiotics and the risk of surgical-wound infection. N Engl J Med 1992;326:281–286.CrossRefGoogle ScholarPubMed
114. Wenzel, RP. Preoperative prophylactic antibiotics: brief historical note. Infect Control Hosp Epidemiol 1993;14:121.Google ScholarPubMed
115. Jackson, JE. All count distributions are not alike. Journal of Quality Technology 1972;4(2):86–92.CrossRefGoogle Scholar
116. Johnson, NL, Kotz, S, Kemp, AW. Univariate Discrete Distributions. 2nd ed. New York, NY: John Wiley and Sons, Inc; 1992.Google Scholar
117. Mendenhall, W, Scheaffer, RL, Wackerly, DD. Mathematical Statistical with Applications. 4th ed. Boston, MA: Duxbury Press; 1990.Google Scholar
118. Devore, JL. Probability and Statistics for Engineering and the Sciences. 2nd ed. Monterey, CA: Brooks/Cole Publishing Co; 1987.Google Scholar
119. Guttman, I, Wilks, SS, Hunter, JS. Introductory Engineering Statistics. 3rd ed. New York, NY: John Wiley and Sons, Inc; 1982.Google Scholar
120. Benneyan, JC. Statistical Control Charts Based on Geometric and Negative Binomial Distributions. University of Massachusetts, Amherst, MA; 1992. Thesis.Google Scholar
121. Kaminsky, FC, Benneyan, JC, Davis, RB, Burke, RJ. Statistical control charts based on a geometric distribution. Journal of Quality Technology 1992;24(2):63–69.CrossRefGoogle Scholar
122. Newell, DJ. Unusual frequency distributions. Biometrics 1965;21:159–168.CrossRefGoogle Scholar
123. Brawley, RL, Weber, DJ, Samsa, GP, Rutala, WA. Multiple nosocomial infections, an incidence study. Am J Epidemiol 1989;130:769–780.CrossRefGoogle ScholarPubMed
124. Benneyan, JC. An introduction to using statistical process control (SPC) within health care. International Applied Statistics in Medicine Conference Transactions. In press.Google Scholar
125. Benneyan, JC, Kaminsky, FC. Successfully applying SPC to improve health care: pitfalls and barriers to improving quality and reducing liability. Proceedings of the ASQC Annual Quality Congress Transactions. Milwaukee, WI: American Society for Quality, Inc; 1995:578–586.Google Scholar
126. Liu, MC, Fernandez, JE, Davis, PJ. A statistical process control approach to carpal tunnel syndrome risk evaluation. Quality Engineering 1993;5:375–392.CrossRefGoogle Scholar
127. Alemi, F, Rom, W, Eisenstein, E. Risk adjusted control charts for healthcare assessment. Annals of Operations Research 1996;67:45–60.CrossRefGoogle Scholar
128. Sloan, MD, ed. Success Stories on Lowering Health Care Costs by Improving Health Care Quality. Milwaukee, WI: ASQC Press; 1995.Google Scholar
129. Wernimont, G. Use of control charts in the analytic laboratory. Ind Eng Chem Anal Ed 1946;18:587–592.CrossRefGoogle Scholar
130. Levey, S, Jennings, ER. The use of control charts in clinical laboratories. Am J Clin Pathol 1950;20:1059–1066.CrossRefGoogle Scholar
131. Benneyan, JC. Statistical Quality Control in Clinical Laboratories. Technical Report. University of Massachusetts: Industrial Engineering and Operations Research; 1995.Google Scholar
132. Kaminsky, FC, Benneyan, JC, Andrzewski, C. Total Quality Management and Statistical Process Control in the Clinical Laboratory With Applications to EIA Testing for HIV-1/2 and Hepatitis Antibodies. Technical Report. Greenfield, MA: Productivity Sciences Inc; 1995 Google Scholar
133. Gentleman, RC, Hamada, MS, Matthews, DE, Wilson, AR. Statistical quality control of HIV-1 ELISA test performance. Journal of the American Statistical Association 1994;89:1200–1208.CrossRefGoogle Scholar
134. Carey, RG. Measuring Quality: Report Cards Get Low Grades. Parkridge, IL: Parkside Associates; 1995.Google ScholarPubMed
135. O'Leary, DS. Measurement and accountability: taking careful aim. Jt Comm Journal on Quality Improvement 1995;21:354–357.CrossRefGoogle ScholarPubMed