Is Family Care Associated with Reduced Health Care expenditures?

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Original Research

Is Family Care Associated with Reduced Health Care expenditures?

J Fam Pract. 1999 August;48(8):608-614

References

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Measures

Family Care. As reported previously,²⁶ family care was assessed by measuring intergenerational personal physician congruence. Data from the Rand Health Insurance Experiment28 showed that personal physicians represented generalists who provided 87% to 93% of visits for selected primary care problems. A national study²⁹ showed that 79% of Americans could identify a “regular” personal physician by name, and 76% of those physicians were believed to be FPs, GPs, internists, or pediatricians.

Presence of intergenerational personal physician congruence was defined as at least 1 parent and 1 child sharing the same personal physician. Other patterns of congruence were considered and rejected. Spousal personal physician congruence would have limited the study to married families. Moreover, in the preponderance of families with spousal congruence by a shared FP or GP, intergenerational family care also occurred. Physician congruence across all family members would have excluded families where some members did not identify a personal physician. For example, in several families personal physician congruence occurred, but the male head of household did not identify a personal physician.

The following 2 intergenerational personal physician congruence categories were compared: (1) family care, which included all families in which there was personal physician congruence between at least 1 parent and at least 1 child, and (2) individual care, which included all families in which there was a personal physician for at least 1 parent and at least 1 child, but there was no intergenerational congruence. Two previously reported categories,²⁶ in which no personal physician was reported for either the parents, the children, or both generations, were not included in this study.

Sociodemographic Factors. Several variables available in the NMES were examined to adjust for potential confounding. Categorical variables included health insurance during the survey period (any private insurance, any Medicaid but no private insurance, or no insurance), level of education for adults (less than high school, high school, or greater than high school), household income as percent of poverty level (poor = < 100%; near poor = 100% to < 125%; low income = 125% to < 200%; middle-income = 200% to 400%; and high income = > 400%), race/ethnicity (white or nonwhite), residence location (metropolitan or nonmetropolitan), census division (Northeast, Midwest, South, or West), and marital status for adults (married or unmarried but living with a partner, or single). Continuous variables included age and for family-level analyses, family size. Age was also examined categorically and age-sex interactions were evaluated, but these did not materially affect the findings.

Case Mix/Disease Severity. Subjective health status was measured using items that comprise subscales of the Medical Outcomes Study (MOS) General Short-Form Health Survey (SF-20), a reliable and valid measure.³⁰ The MOS general health survey is a useful measure of the health effects of chronic disease; the subscales exhibit distinct profiles for several diseases.³¹ For example, hypertension was associated with a decrement of 3.5 in the health perceptions scale (scored from 0 to 100), compared with a decrement of 13 for persons with chronic lung disease.³¹ The subscales exhibited excellent internal reliability in the NMES and included 5 questions each on health perceptions (Cronbach’s a = .90), mental health (a = .88), and physical functioning (a = .85). Although the NMES did not record the MOS survey items for children, an item assessing overall health status (excellent, good, fair, or poor) was included. Because “poor” was recorded for very few children, we collapsed overall health status into 3 levels: excellent, good, and fair or poor. Each subject’s baseline smoking status was classified as current smoker, former smoker, or never smoker. Body mass index (BMI) was calculated for each subject from self-reported weight and height, and categorized to reflect extremes that have been associated with excess mortality in other studies^32,33 (ie, BMI ·19 kg/m² or Ž30 kg/m²). An index of unhealthy behaviors was developed by summing the responses to the following categories: (1) getting less than 7 hours of sleep per night; (2) eating breakfast only rarely or sometimes; (3) using a seatbelt sometimes, at most; and (4) not getting regular physical exercise. Summary indexes have been shown to be predictive of health status, morbidity, and mortality, thus suggesting predictive validity.^34-37 This index was used as a measure of orientation toward health behaviors among adult subjects. Ten health attitude questions, derived from a 1970 Center for Health Administration Studies/National Opinion Research Center study,³⁸ were included in the NMES. For this report, 5 questions that contributed to reliability (Cronbach’s a = .62) were selected to form a unidimensional scale to measure the adult respondents’ “medical skepticism” about health insurance and health care. Increasing medical skepticism has been shown to be associated with increasing mortality in the NMES.³⁹