Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/30009
Title: Optimal Measures for Primary Care Physician Encounters after Stroke and Association with Survival: A Data Linkage Study.
Austin Authors: Ung, David;Wang, Yun;Sundararajan, Vijaya;Lopez, Derrick;Kilkenny, Monique F;Cadilhac, Dominique A;Thrift, Amanda G;Nelson, Mark R;Andrew, Nadine E
Affiliation: The Florey Institute of Neuroscience and Mental Health
Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
Peninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia
Department of Public Health, School of Psychology and Public Health, La Trobe University, Bundoora, Victoria, Australia
School of Pharmacy, Chapman University, Irvine, California, USA
Department of Epidemiology and Preventative Medicine, Monash University, Melbourne, Victoria, Australia
Menzies Institute for Medical Research, Hobart, Tasmania, Australia
School of Population and Global Health, The University of Western Australia, Perth, Washington, Australia
Issue Date: 2022
Date: 2021-12-22
Publication information: Neuroepidemiology 2022; 56(2): 90-96
Abstract: Primary care physicians (PCPs) provide ongoing management after stroke. However, little is known about how best to measure physician encounters with reference to longer term outcomes. We aimed to compare methods for measuring regularity and continuity of PCP encounters, based on survival following stroke using linked healthcare data. Data from the Australian Stroke Clinical Registry (2010-2014) were linked with Australian Medicare claims from 2009 to 2016. Physician encounters were ascertained within 18 months of discharge for stroke. We calculated three separate measures of continuity of encounters (consistency of visits with primary physician) and three for regularity of encounters (distribution of service utilization over time). Indices were compared based on 1-year survival using multivariable Cox regression models. The best performing measures of regularity and continuity, based on model fit, were combined into a composite "optimal care" variable. Among 10,728 registrants (43% female, 69% aged ≥65 years), the median number of encounters was 17. The measures most associated with survival (hazard ratio [95% confidence interval], Akaike information criterion [AIC], and Bayesian information criterion [BIC]) were the Continuity of Care Index (COCI, as a measure of continuity; 0.88 [0.76-1.02], p = 0.099, AIC = 13,746, BIC = 13,855) and our persistence measure of regularity (encounter at least every 6 months; 0.80 [0.67-0.95], p = 0.011, AIC = 13,742, BIC = 13,852). Our composite measure, persistent plus COCI ≥80% (24% of registrants; 0.80 [0.68-0.94], p = 0.008, AIC = 13,742, BIC = 13,851), performed marginally better than our persistence measure alone. Our persistence measure of regularity or composite measure may be useful when measuring physician encounters following stroke.
URI: https://ahro.austin.org.au/austinjspui/handle/1/30009
DOI: 10.1159/000520700
ORCID: 0000-0002-3375-287X
0000-0001-8162-682X
Journal: Neuroepidemiology
PubMed URL: 34937038
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/34937038/
Type: Journal Article
Subjects: Continuity of care
Primary care physician
Regularity
Stroke
Survival
Appears in Collections:Journal articles

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