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.
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.
| Original language | English |
|---|---|
| Publication status | Published - Dec 2019 |
| Event | 11th Health Services and Policy Research Conference - Pullman Hotel Auckland, Auckland, New Zealand Duration: 4 Dec 2019 → 6 Dec 2019 Conference number: 11 http://www.healthservicesconference.com.au/hsraanz2019/ |
Conference
| Conference | 11th Health Services and Policy Research Conference |
|---|---|
| Abbreviated title | HSRAANZ 2019 |
| Country/Territory | New Zealand |
| City | Auckland |
| Period | 4/12/19 → 6/12/19 |
| Internet address |