Measurement of optimal general practitioner encounters following stroke using linked data from the Australian Stroke Clinical Registry
Year: 2019
Type: conference-paper
Abstract: Objective We aimed to compare methods for measuring general practitioner (GP) encounters following stroke using routinely collected data. Methods Patient data from the Australian Stroke Clinical Registry (AuSCR; 2010-2014) were linked with Medicare (2009-2015) and death data (2009-2016). GP contacts were identified for the 0-18 months following the first event in AuSCR (exposure period) using Medicare codes among adults who survived to 21 months. Continuity (extent to which a patient sees a given provider) was calculated using a modified continuity index and continuity-of-care index. Regularity(distribution of GP use) was ascertained using the variance method (variance between visits) and a modified standard deviation method (standard deviation between visits). We regressed the indices against the total frequency of visits using negative binomial regressions, and all-cause death, for deaths that occurred between 21-33 months, using Cox regressions adjusted for demographic/clinical variables. Akaike information criterion (AIC)/Bayesian information criterion(BIC) were used to determine the best model (lower=better). Lessons learned Ninety-five percent of the cohort were linked to Medicare(n=7502 eligible). Median frequency was 6 visits/person/year and 51.3% saw the same GP 80% of the time. Models using the modified regularity index were consistently better than for the original index for both models: (AIC 52069.94 (modified), 54666.3 (original); BIC 52090.65 (modified), 54687 (original)) and survival models (AIC 9041.393 (modified), 9042.321 (original); BIC 9109.708 (modified), 9110.635 (original)). There was no difference in continuity of care indices. Implications Few researchers have explored GP continuity and regularity of care following stroke. Using optimal methods to calculate these variables is likely to better inform recommendations for research/clinical practice.
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W3095461579