A time-duration measure of continuity of care to optimise utilisation of primary health care: A threshold effects approach among people with diabetes - Ha, N.T.; Harris, Mark; Preen, D.; Robinson, S.; Moorin, Rachael (2019)
© 2019 The Author(s). Background: Literature highlighted the importance of timely access and ongoing care provided at primary care settings in reducing hospitalisation and health care resource uses. However, the effect of timely access to primary care has not been fully captured in most of the current continuity of care indices. This study aimed to develop a time-duration measure of continuity of primary care ("cover index") capturing the proportion of time an individual is under the potentially protective effect of primary health care contacts. Methods: An observational study was conducted on 36,667 individuals aged 45 years or older with diabetes mellitus extracted from Western Australian linked administrative data. Threshold effect models were used to determine the maximum time interval between general practitioner (GP) visits that afforded a protective effect against avoidable hospitalisation across complication cohorts. The optimal maximum time interval was used to compute a cover index for each individual. The cover was evaluated using descriptive statistics stratified by population socio-demographic characteristics. Results: The optimal maximum time between GP visits was 9-13 months for people with diabetes with no complication, 5-11 months for people with diabetes with 1-2 complications, and 4-9 months for people with diabetes with 3+ complications. The cover index was lowest among those aged 75+ years, males, Indigenous people, socio-economically disadvantaged and those in very remote areas. Conclusions: This study developed a new measure of continuity of primary care that adds a time parameter to capturing longitudinal continuity. Cover has the potential to better capture underuse of primary care and will significantly contribute to the sparsely available methods for analysis of linked administrative data in evaluating continuity of care for people with chronic conditions.