Predicting declines in physical function in persons with multiple chronic medical conditions: what we can learn from the medical problem list
UMass Chan Affiliations
Department of Quantitative Health SciencesDocument Type
Journal ArticlePublication Date
2004-09-09Keywords
Activities of Daily LivingAdult
Aged
Boston
Chicago
Chronic Disease
*Comorbidity
Fee-for-Service Plans
Female
Health Maintenance Organizations
Humans
Hypertension
Longitudinal Studies
Los Angeles
Male
Medicine
Middle Aged
Outcome Assessment (Health Care)
Primary Health Care
Psychometrics
Quality of Life
Regression Analysis
*Sickness Impact Profile
Specialization
Biostatistics
Epidemiology
Health Services Research
Metadata
Show full item recordAbstract
BACKGROUND: Primary care physicians are caring for increasing numbers of persons with comorbid chronic illness. Longitudinal information on health outcomes associated with specific chronic conditions may be particularly relevant in caring for these populations. Our objective was to assess the effect of certain comorbid conditions on physical well being over time in a population of persons with chronic medical conditions; and to compare these effects to that of hypertension alone. METHODS: We conducted a secondary analysis of 4-year longitudinal data from the Medical Outcomes Study. A heterogeneous population of 1574 patients with either hypertension alone (referent) or one or more of the following conditions: diabetes, coronary artery disease, congestive heart failure, respiratory illness, musculoskeletal conditions and/or depression were recruited from primary and specialty (endocrinology, cardiology or mental health) practices within HMO and fee-for-service settings in three U.S. cities. We measured categorical change (worse vs. same/better) in the SF-36(R) Health Survey physical component summary score (PCS) over 4 years. We used logistic regression analysis to determine significant differences in longitudinal change in PCS between patients with hypertension alone and those with other comorbid conditions and linear regression analysis to assess the contribution of the explanatory variables. RESULTS: Specific diagnoses of CHF, diabetes and/or chronic respiratory disease; or 4 or more chronic conditions, were predictive of a clinically significant decline in PCS. CONCLUSIONS: Clinical recognition of these specific chronic conditions or 4 or more of a list of chronic conditions may provide an opportunity for proactive clinical decision making to maximize physical functioning in these populations.Source
Health Qual Life Outcomes. 2004 Sep 7;2:47. Link to article on publisher's siteDOI
10.1186/1477-7525-2-47Permanent Link to this Item
http://hdl.handle.net/20.500.14038/47458PubMed ID
15353000Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1186/1477-7525-2-47