ANALYSIS OF CASE MIX COMPLEXITY USING INFORMATION-THEORY AND DIAGNOSTIC RELATED GROUPING

被引:22
作者
HORN, SD [1 ]
SCHUMACHER, DN [1 ]
机构
[1] JOHNS HOPKINS UNIV, SCH HYG & PUBL HLTH, DEPT MATH SCI, BALTIMORE, MD 21218 USA
关键词
D O I
10.1097/00005650-197904000-00006
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Case mix complexity measurements are essential to determine health care efficiency and effectiveness. Measures of patient care processes and outcomes must be adjusted for case mix before valid comparisons can be made. Hospital reimbursement, particularly prospective reimbursement, must take into account differences in case mix. In addition, a key variable for hospital classification is case mix. There are, however, no widely accepted easily computed case mix measures. Information theory measures of case mix have been developed but their acceptance has been limited by a lack of verification of their basic assumption that concentration of disease is related to clinical complexity. We discuss the rationale underlying the mathematical computation of information theory measures and demonstrate a statistically significant relationship between clinical measures of case mix complexity and information theory measures of case mix complexity. © J. B. Lippincott Co.
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页码:382 / 389
页数:8
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