PREDICTING HEALTH SERVICE UTILIZATION WITH THE PCS AND MCS OF THE SF-36

Author(s)

Tianhui Chen, Dr, Researcher1, Lu Li, MPH, Professor, Director21Zhejiang University, Hangzhou, China; 2 Zhejiang University, Hangzhou, Zhejiang, China

OBJECTIVES: We aim to predict outpatient consultation and inpatient consultation with two summary scores of the SF-36, physical component summary (PCS) and mental component summary (MCS).  METHODS: A retrospective cross-sectional design was carried out among primary care patients in mainland China. Health-related quality of life (HRQOL) was measured by two summary score of the SF-36, PCS and MCS, Either the electronic or the paper version of validated Chinese SF-36 was used in the survey. Outpatient consultation was calculated by the monthly outpatient consultation rate and inpatient consultation was calculated by the annual hospitalization rate. Binary logistic regression for consultation and inpatient consultation was adopted in the analyses. A total of 733 valid subjects were eventually recruited in this study. RESULTS: For the monthly outpatient consultation rate, the odds ratios (OR) and 95% confidence interval (CI) were 0.919 (0.891, 0.947) for PCS and 0.995 (0.970, 1.021) for MCS. For the annual hospitalization rate, OR and 95% CI were 0.907(0.884, 0.930) for PCS and 0.951 (0.927, 0.975) for MCS.  CONCLUSIONS: PCS of the SF-36 can predict both outpatient consultation and inpatient consultation, whereas MCS of the SF-36 can predict inpatient consultation among primary care patients in mainland China.

Conference/Value in Health Info

2008-11, ISPOR Europe 2008, Athens, Greece

Value in Health, Vol. 11, No. 6 (November 2008)

Code

PMC26

Topic

Methodological & Statistical Research

Topic Subcategory

PRO & Related Methods

Disease

Multiple Diseases

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