Defining the practice population in fee-for-service practice.
AUTOR(ES)
Hutchison, B G
RESUMO
OBJECTIVE: To develop and validate a technique for defining a practice population of discrete individuals based on multiyear family practice fee-for-service billings data. DATA SOURCES/STUDY SETTING: Nineteen family physicians in Ontario, Canada who converted from fee-for-service to capitation payment. Data sources were fee-for-service billings data for the three-year period prior to the conversion from fee-for-service to capitation payment and the rosters of enrolled patients for the first and third years after the change to capitation payment. STUDY DESIGN: The billings-based definition of the physician's practice population was compared against the Year 1 roster. We also compared the billings-based practice population and the Year 1 roster to the physician's Year 3 roster to identify patients who might have been missed during the roster development process. Our principal analyses were an assessment of the sensitivity of the billings-based definition of the practice population (EPP), the positive predictive value of EPP, and the agreement between EPP and the rostered patient population (RPP). We also examined the ratio between EPP and RPP to determine EPP's accuracy in estimating the practice denominator. DATA COLLECTION/EXTRACTION METHODS: The practice population for each physician at the time of conversion from fee-for-service to capitation payment was defined as (a) all persons for whom the physician billed the provincial health insurance plan for at least one visit during the year immediately prior to joining the capitation-funded program; and (b) all additional patients for whom the physician billed the plan for at least one service in each of the two preceding years. Data extraction was carried out within the Ministry of Health in order to preserve the anonymity of patients and physicians. Data were provided to the investigators stripped of patient and physician identifiers. PRINCIPAL FINDINGS: The mean sensitivity and positive predictive value of EPP were 95.3 percent and 87.4 percent, respectively. The level of agreement between EPP and RPP averaged 84.4 percent. The mean ratio of EPP to RPP was 1.21 (95 percent C.I. 1.030-1.213). Correction for roster false-negatives increased the sensitivity, positive predictive value, and agreement between EPP and the practice population, and reduced the mean ratio of EPP to the practice population to 1.068 (95 percent C.I. 1.010-1.127). CONCLUSIONS: The practice population can usefully be defined in fee-for-service family practice on the basis of multiyear fee-for-service billings data. Further research examining alternative encounter-based practice population definitions would be valuable.
