Pitfalls in assessing the quality of care for patients with cardiovascular disease.

DiSalvo TG, Normand SL, Hauptman PJ, Guadagnoli E, Palmer RH, McNeil BJ
Am J Med. 2001 111 (4): 297-303

PMID: 11583014 · DOI:10.1016/s0002-9343(01)00842-7

PURPOSE - There are no clinical performance measures for cardiovascular diseases that span the continuum of hospital through postdischarge ambulatory care. We tested the feasibility of developing and implementing such measures for patients with acute myocardial infarction, congestive heart failure, or hypertension.

SUBJECTS AND METHODS - After reviewing practice guidelines and the medical literature, we developed potential measures related to therapy, diagnostic evaluation, and communication. We tested the feasibility of implementing the selected measures for 518 patients with myocardial infarction, 396 with heart failure, and 601 with hypertension who were enrolled in four major U.S. managed care plans at six geographic sites, using data from administrative claims, medical records, and patient surveys.

RESULTS - Difficulties in obtaining timely data and small numbers of cases adversely affected measurement. We encountered 6- to 12-month delays, disagreement between principal discharge diagnosis as coded in administrative and records data (for 9% of myocardial infarction and 21% of heart failure patients), missing medical records (20% for both myocardial infarction and heart failure patients), and problems in identifying physicians accountable for care. Low rates of performing key diagnostic tests (e.g., ejection fraction) excluded many cases from measures of appropriate therapy that were conditional on test results. Patient survey response rates were low.

CONCLUSIONS - Constructing meaningful clinical performance measures is straightforward, but implementing them on a large scale will require improved data systems. Lack of standardized data captured at the point of clinical care and low rates of eligibility for key measures hamper measurement of quality of care.

MeSH Terms (11)

Algorithms Cardiovascular Diseases Chronic Disease Cohort Studies Continuity of Patient Care Feasibility Studies Humans Process Assessment, Health Care Quality of Health Care Reproducibility of Results Risk Factors

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