Self-Report of Healthcare Utilization among Community-Dwelling Older Persons: A Prospective Cohort Study

Abstract

BackgroundSelf-reported data are often used for estimates on healthcare utilization in cost-effectiveness studies.ObjectiveTo analyze older adults’ self-report of healthcare utilization compared to data obtained from the general practitioners’ (GP) electronic medical record (EMR) and to study the differences in healthcare utilization between those who completed the study, those who did not respond, and those lost to follow-up.MethodsA prospective cohort study was conducted among community-dwelling persons aged 70 years and above, without dementia and not living in a nursing home. Self-reporting questionnaires were compared to healthcare utilization data extracted from the EMR at the GP-office.ResultsOverall, 790 persons completed questionnaires at baseline, median age 75 years (IQR 72–80), 55.8% had no disabilities in (instrumental) activities of daily living. Correlations between self-report data and EMR data on healthcare utilization were substantial for ‘hospitalizations’ and ‘GP home visits’ at 12 months intraclass correlation coefficient 0.63 (95% CI; 0.58–0.68). Compared to the EMR, self-reported healthcare utilization was generally slightly over-reported. Non-respondents received more GP home visits (p<0.05). Of the participants who died or were institutionalized 62.2% received 2 or more home visits (p<0.001) and 18.9% had 2 or more hospital admissions (p<0.001) versus respectively 18.6% and 3.9% of the participants who completed the study. Of the participants lost to follow-up for other reasons 33.0% received 2 or more home visits (p<0.01) versus 18.6 of the participants who completed the study.ConclusionsSelf-report of hospitalizations and GP home visits in a broadly ‘healthy’ community-dwelling older population seems adequate and efficient. However, as people become older and more functionally impaired, collecting healthcare utilization data from the EMR should be considered to avoid measurement bias, particularly if the data will be used to support economic evaluation.

Nursing Home Use Across The Spectrum of Cognitive Decline: Merging Mayo Clinic Study of Aging With CMS MDS Assessments

“…All NH days were captured, including multiple admissions and short stays. Resulting estimates address limitations recognized in the literature, 14,15,[19][20][21][22] and afford information on NH activity beyond cross-sectional estimates of the proportion of NH residents with cognitive impairment, which can be biased toward long-term residents, as well as findings limited to any NH use (yes/no) or time to NH admission.…”

“…Presently, source data for such models have ascertained cognitive status using discharge diagnosis codes or screening instruments and/or estimated utilization/costs using self‐report or single‐source administrative data that fail to include all payers (i.e., Medicare, Medicaid, commercial insurance, and private pay). The serious limitations of these approaches for estimating associations between healthcare utilization and cognitive impairment are demonstrated . The need for objective, complete measures of utilization by persons carefully characterized for cognition across the spectrum of cognitive decline is increasingly recognized …”

“…The serious limitations of these approaches for estimating associations between healthcare utilization and cognitive impairment are demonstrated. 14,[19][20][21][22] The need for objective, complete measures of utilization by persons carefully characterized for cognition across the spectrum of cognitive decline is increasingly recognized. 6,14,15,18 We endeavored to partially address this need in a previous study 23 and in the present study.…”

Economic burden of relapsed or refractory multiple myeloma: Results from an international trial

“…Recommendations to increase the accuracy of patient medical utilization questionnaires have been developed, many of which were included in this study, such as shorter recall periods, emphasis on key and intense medical experiences such as hospitalization and emergency care services, as well as distinguishing between family physician and specialists when reporting ambulatory visits . The time to follow‐up, from baseline to Cycle 2 and Cycle 4, nicely fits the recall period stipulated in the economic questionnaire and thereby minimized the potential threat of overlapping healthcare counts during recall and data analysis: The mean and median days to the first post‐baseline economic questionnaire assessment, covering a 3 month period, were both 96 days.…”

“…The economic questionnaire was interviewer-administered by study staff and was previously used in immunology clinical trials. [9][10][11][12][13][14] Patient-level baseline concomitant medication, demographic, clinical, economic, and HRQoL data that was available from the study dataset were collected from either the screening visit or the day of the first treatment administration ( 15 Severity thresholds have been established for the FACIT-Fatigue: mild to none (>40), moderate (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40), and severe (<30). 16,17 Similarly, pain severity thresholds for the BPI have been published: none to mild (0-4), moderate (5,6), and severe (7-10).…”