Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
3.
Health Care Financ Rev ; 25(4): 75-91, 2004.
Article in English | MEDLINE | ID: mdl-15493445

ABSTRACT

This research examines the predictors of 2-year declines in physical and mental health for beneficiaries surveyed in the Medicare Health Outcomes Survey (HOS). Regression results indicate that age, arthritis of the hip/knee, sciatica, and pulmonary diseases, comorbidity at baseline, and increased comorbidity between baseline and followup were predictors of decline in physical health; however, these account for very small amounts of variance. The number of newly diagnosed chronic conditions and depression predicted decline in mental health. Beneficiaries deceased at followup were of lower socioeconomic status, and had lower physical and mental health scores than the analytic sample.


Subject(s)
Data Collection/instrumentation , Medicare , Outcome Assessment, Health Care/statistics & numerical data , Aged , Aged, 80 and over , Chronic Disease , Female , Humans , Male , United States
4.
Health Qual Life Outcomes ; 1: 47, 2003 Sep 18.
Article in English | MEDLINE | ID: mdl-14570594

ABSTRACT

BACKGROUND: This research examined the use of the propensity score method to compare proxy-completed responses to self-completed responses in the first three baseline cohorts of the Medicare Health Outcomes Survey, administered in 1998, 1999, and 2000, respectively. A proxy is someone other than the respondent who completes the survey for the respondent. METHODS: The propensity score method of matched sampling was used to compare proxy and self-completed responses. A propensity score is a value that equals the estimated probability of a given individual belonging to a treatment group given the observed background characteristics of that individual. Proxy and self-completed responses were compared on demographics, the SF-36, chronic conditions, activities of daily living, and depression-screening questions. For each individual survey respondent, logistic regression was used to calculate the probability that this individual belonged to the proxy respondent group (propensity score). Pre and post adjustment comparisons were tested by calculating effect sizes. RESULTS: Differences between self and proxy-completed responses were substantially reduced with the use of the propensity score method. However, differences were still found in the SF-36, several demographics, several impaired activities of daily living, several chronic conditions, and one depression-screening question. CONCLUSION: The propensity score method helped to reduce differences between proxy-completed and self-completed survey responses, thereby providing an approximation to a randomized controlled experiment of proxy-completed versus self-completed survey responses.


Subject(s)
Data Collection/methods , Health Surveys , Medicare , Proxy , Psychometrics/methods , Quality of Life , Activities of Daily Living , Adult , Aged , Aged, 80 and over , Chronic Disease , Cohort Studies , Depression/diagnosis , Female , Health Status , Humans , Logistic Models , Male , Mental Health , Middle Aged , Outcome Assessment, Health Care , United States
SELECTION OF CITATIONS
SEARCH DETAIL
...