Measuring Quality of Care in Patients With Multiple Clinical Conditions: Summary of a Conference Conducted by the Society of General Internal Medicine
- 128 Downloads
Performance measurement has been widely advocated as a means to improve health care delivery and, ultimately, clinical outcomes. However, the evidence supporting the value of using the same quality measures designed for patients with a single clinical condition in patients with multiple conditions is weak. If clinically complex patients, defined here as patients with multiple clinical conditions, present greater challenges to achieving quality goals, providers may shun them or ignore important, but unmeasured, clinical issues. This paper summarizes the proceedings of a conference addressing the challenge of measuring quality of care in the patient with multiple clinical conditions with the goal of informing the implementation of quality measurement systems and future research programs on this topic. The conference had three main areas of discussion. First, the potential problems caused by applying current quality standards to patients with multiple conditions were examined. Second, the advantages and disadvantages of three strategies to improve quality measurement in clinically complex patients were evaluated: excluding certain clinically complex patients from a given standard, relaxing the performance target, and assigning a greater weight to some measures based on the expected clinical benefit or difficulty of reaching the performance target. Third, the strengths and weaknesses of potential novel measures such change in functional status were considered. The group concurred that, because clinically complex patients present a threat to the implementation of quality measures, high priority must be assigned to a research agenda on this topic. This research should evaluate the impact of quality measurement on these patients and expand the range of quality measures relevant to the care of clinically complex patients.
KEY WORDSperformance measurement quality measures clinically complex patients
The authors gratefully acknowledge Greg Pawlson for his assistance as a conference leader and Robert Centor for his comments on an earlier draft of this manuscript. Funding was provided by the American Board of Internal Medicine (ABIM) Foundation and the Commonwealth Fund.
Conflict of Interest
Dr. Greenfield has received grants for research from Pfizer and Novo-nordisk and honoraria from Pfizer. Dr. Fung has received research support from a grant from Pfizer. Dr. Turner has received a grant for research from Pfizer.
- 2.Joint Commision on Accreditation of Healthcare Organizations. Public Policy: Principles for the Construct of Pay-for-Performance Programs. http://www.jointcommission.org/PublicPolicy/pay.htm. Accessed June 5, 2006.
- 3.Centers for Medicare and Medicaid Services. Hospital Quality Initiative http://www.cms.hhs.gov/HospitalQualityInits/downloads/HospitalOverview200512.pdf. Accessed June 5, 2006.
- 10.Anderson G, Horvarth J. Chronic Conditions: Making the Case for Ongoing Care. Baltimore, MD: Johns Hopkins Press; 2002.Google Scholar
- 11.Greenfield S, Apolone G, McNeil BJ, Cleary PD. The importance of co-existent disease in the occurrence of postoperative complications and one-year recovery in patients undergoing total hip replacement. Comorbidity and outcomes after hip replacement. Med Care. 1993;31:141–54.PubMedCrossRefGoogle Scholar
- 25.Iezzoni L. Risk Adjustment for Measuring Healthcare Outcomes. 2nd ed. Chicago, IL: Health Administration Press; 1997.Google Scholar
- 26.Litwin MS, Greenfield S, Elkin EP, Lubeck D, Broering JM, Kaplan SH. Mortality is predicted by a comorbidity measure in men with prostate cancer. Cancer. 2007 (in press).Google Scholar
- 31.Agency For Healthcare Research and Quality. CAHPS Surveys and Tools. http://www.cahps.ahrq.gov Accessed May 9, 2007.
- 34.American Board of Internal Medicine. Practice Improvement Module. http://www.abim.org/online/pim/demo.aspx.