Yu-Chi Tung1, Guo-Hong Li2, Hsien-Yen Chang3,4,5. 1. Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan. yuchitung@ntu.edu.tw. 2. Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan. 3. Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. 4. Center for Drug Safety and Effectiveness, Johns Hopkins University, Baltimore, MD, USA. 5. Center for Population Health Information Technology, Johns Hopkins University, Baltimore, MD, USA.
Abstract
BACKGROUND: The Overuse Index (OI), previously called the Johns Hopkins Overuse Index, is developed and validated as a composite measure of systematic overuse/low-value care using United States claims data. However, no information is available concerning whether the external validation of the OI is sustained, especially for international application. Moreover, little is known about which supply and demand factors are associated with the OI. OBJECTIVE: We used nationwide population-based data from Taiwan to externally validate the OI and to examine the association of regional healthcare resources and socioeconomic factors with the OI. DESIGN AND PARTICIPANTS: We analyzed 1,994,636 beneficiaries randomly selected from all people enrolled in the Taiwan National Health Insurance in 2013. MAIN MEASURES: The OI was calculated for 2013 to 2015 for each of 50 medical regions. Spearman correlation analysis was applied to examine the association of the OI with total medical costs per capita and mortality rate. Generalized estimating equation linear regression analysis was conducted to examine the association of regional healthcare resources (number of hospital beds per 1000 population, number of physicians per 1000 population, and proportion of primary care physicians [PCPs]) and socioeconomic factors (proportion of low-income people and proportion of population aged 20 and older without a high school diploma) with the OI. RESULTS: Higher scores of the OI were associated with higher total medical costs per capita (ρ = 0.48, P < 0.001) and not associated with total mortality (ρ = - 0.01, P = 0.882). Higher proportions of PCPs and higher proportions of low-income people were associated with lower scores of the OI (β = - 0.022, P = 0.016 and β = - 0.224, P < 0.001, respectively). CONCLUSIONS: Our study supported the external validation of the OI by demonstrating a similar association within a universal healthcare system, and it showed the association of a higher proportion of PCPs and a higher proportion of low-income people with less overuse/low-value care.
BACKGROUND: The Overuse Index (OI), previously called the Johns Hopkins Overuse Index, is developed and validated as a composite measure of systematic overuse/low-value care using United States claims data. However, no information is available concerning whether the external validation of the OI is sustained, especially for international application. Moreover, little is known about which supply and demand factors are associated with the OI. OBJECTIVE: We used nationwide population-based data from Taiwan to externally validate the OI and to examine the association of regional healthcare resources and socioeconomic factors with the OI. DESIGN AND PARTICIPANTS: We analyzed 1,994,636 beneficiaries randomly selected from all people enrolled in the Taiwan National Health Insurance in 2013. MAIN MEASURES: The OI was calculated for 2013 to 2015 for each of 50 medical regions. Spearman correlation analysis was applied to examine the association of the OI with total medical costs per capita and mortality rate. Generalized estimating equation linear regression analysis was conducted to examine the association of regional healthcare resources (number of hospital beds per 1000 population, number of physicians per 1000 population, and proportion of primary care physicians [PCPs]) and socioeconomic factors (proportion of low-income people and proportion of population aged 20 and older without a high school diploma) with the OI. RESULTS: Higher scores of the OI were associated with higher total medical costs per capita (ρ = 0.48, P < 0.001) and not associated with total mortality (ρ = - 0.01, P = 0.882). Higher proportions of PCPs and higher proportions of low-income people were associated with lower scores of the OI (β = - 0.022, P = 0.016 and β = - 0.224, P < 0.001, respectively). CONCLUSIONS: Our study supported the external validation of the OI by demonstrating a similar association within a universal healthcare system, and it showed the association of a higher proportion of PCPs and a higher proportion of low-income people with less overuse/low-value care.
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