Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 61 lotted 90 minutes and sent us additional materials. Some who were interrupted by urgent clinical business rescheduled time to complete the interviews. Although this was a selectedânot a randomly sampledâgroup, and there was clearly great enthusiasm and of innovative work going on at the grass-roots level. Many of those in- terviewed expressed clear ideas about how they were reorganizing practices, their principles for doing so, and their commitment to an ongoing process. Respondents described their early limited successes or outright failures. We heard what had and had not been successful as they tried to disseminate their practices throughout their organizations. We believe there is much that could profitably learned and shared beyond the individual sites that has not been yet been pulled together by a unifying conceptual framework or effective mechanism for de- ploying what is being learned. We were struck by two findings in particular: First, the importance of leadership at the macro-system as well as clinical level; and second, the general lack of information infrastruc- ture in these practices. Micro-system leaders repeatedly stressed the importance of executive and governance-level support. This support was singled out repeatedly as a sine qua non to their ability to succeed. It was also apparent that although some steps have been taken to in- corporate the explosion of information technologies that are being deployed for managing pa- tient information, free-standing practices as well as much of clinical practice within hospitals have only begun to integrate data systems, use them for real-time clinical practice, or as in- formation tools for improving the quality of care for a patient population. The potential is enormous, but as yet, almost untapped. They appear to be at a threshold of incorporating in- formation technologies into daily practice. The potential created by the development of knowledge servers, decision support tools, consumer informatics32 continuous electronic pa- tient-clinician communication, and computer-based electronic health records puts most of these micro-systems almost at âtime zeroâ for what will likely be dramatic changes in the in- tegration of information for real-time patient care and a strong baseline for future comparison. As research on micro-systems moves forward, it will be important to transfer what has been learned from research on teams and organizations to new research that will be con- ducted on micro-systems. For example, research that will be helpful includes information about the different stages of development and maturity of the organization, creating the or- ganizational environment to support teams, socializing new members (clinicians and staff) to the team, environments that support micro-systems, the characteristics of effective leader- ship, and how micro-systems can build linkages that result in well-coordinated care within and across organizational boundaries. IOM Quality of Care Study This study was intended to provide more than a database for research, however. It was undertaken to provide an evidence base for the IOM Committee on the Quality of Health Care in America in formulating its conclusions and recommendations. Because that commit- tee was charged with the formulation of recommendations about changes that can lead to threshold improvement in the quality of care in this country, its members believed that it was extremely important to draw not only on their expertise and the literature but also on the best evidence it could find of excellent performance and to do so in a systematic way as exempli-
62 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS fied by this study. As that study was not limited by type of health care, the goals of such a project necessitated drawing from a wide range of sites serving a variety of patient popula- tions. It also suggests a sample size that for qualitative analytic methods was quite broad but not unwieldy. The number of sites interviewedï£§43ï£§served these purposes well. We had several of each âkindâ of micro-system (e.g., primary care, critical care) but they varied in location, composition, and in their own approaches to organizing and delivering care, thus providing a very rich database of observation. That report, which is expected to be published in early 2001, will use the responses and analysis described in this technical report to under- pin its recommendations about how health care micro-systems, macro-systems, and other or- ganizational forms that have not yet emerged, can improve their performance. REFERENCES 1. Bertalanffy, Ludwig von. General System Theory.â Pp 1â10 in General Systems: Yearbook of the Society for the Advancement of General Systems Theory, 1. Ludwig von Bertalanffy and Anatol Rapoport, eds., 1956. 2. Institute of Medicine. To Err is Human. Building a Safer Health System. LT Kohn, JM Corrigan, MS Donaldson, eds. Washington, DC: National Academy Press, 2000. 3. Scott, Richard W. Organizations: Rational, Natural, and Open Systems. Englewood Cliffs, NJ: Prentice Hall, 1981. 4. Boulding, Kenneth. General Systems Theory: The Skeleton of Science. Management Science 2:197â208, 1956. 5. Quinn, James B. Intelligent Enterprise. New York: Free Press, 1992. 6. Frontiers of Health Services Management 15(1), 1998, passim. 7. Nelson, Eugene C., Batalden, Paul B., Mohr, Julie J., et al. Building a Quality Future. Frontiers of Health Services Management 15:3â32, 1998. 8. Nelson, Eugene C., Batalden, Paul B., Mohr Julie J., et al. âBuilding a Quality Future.â Frontiers of Health Services Management 15: 3â32, 1998. 9. Kaluzny, Arnold D. âDesign and Management of Disciplinary and Interdisciplinary Groups in Health Services: Review and Critique.â Medical Care Review 42(1): 77â112, 1985. 10. Cebul, Randall D. âRandomized, Controlled Trials Using the Metro Firm System.â Medical Care 29: JS9âJS18, 1991. 11. Neuhauser, Duncan. âParallel Providers, Ongoing Randomization, and Continuous Improve- ment.â Medical Care 29: JS5âJS8, 1991. 12. Neuhauser, Duncan. âProgress on Firms Research.â International Journal of Technology Assess- ment in Health Care 8: 321â324, 1992. 13. Patton, Michael Q. Qualitative Evaluation and Research Methods. Newbury Park: Sage Publica- tions, 1994. 14. Center for the Evaluative Clinical Sciences. Dartmouth Medical School. The Quality of Medical Care in the United States: A Report on the Medicare Program. Dartmouth Atlas of Helath Care, 1999. 15. Guba, Egon G. Toward a Methodology of Naturalistic Inquiry in Educational Evaluation. Los Angeles, University of California, Los Angeles, Center for the Study of Evaluation, 1978. 16. Guba, Egon G. and Lincoln, Yvonna S. Effective Evaluation: Improving the Usefulness of Evaluation Results Through Responsive and Naturalistic Approaches. San Francisco, Jossey- Bass, 1981. 17. Denzin, Norman K. Interpretive Interactionism. Newbury Park, Sage Publications, 1989. 18. Patton, Michael Q. Qualitative Evaluation and Research Methods. Newbury Park: Sage Publica- tions, 1994.