Abstract
Background: Most data on mortality and prognostic factors of universal healthcare waiting lists come from North America, Australasia, and Europe, with little information from South America. We aimed to determine the relationship between medical center-specific waiting time and waiting list mortality in Chile. Methods: Using data from all new patients listed in medical specialist waitlists for non-prioritized health problems from 2008 to 2015 in three geographically distant regions of Chile, we constructed hierarchical multivariate survival models to predict mortality risk at two years after registration for each medical center. Kendall rank correlation analysis was used to measure the association between medical center-specific mortality hazard ratio and waiting times. Findings: There were 987,497 patients waiting for care at 77 medical centers, including 33,546 (3‧ 40%) who died within two years after registration. Male gender (hazard ratio [HR]=1‧ 17, 95% confidence interval [CI] 1‧ 1-1‧ 24), older age (HR=2‧ 88, 95% CI 2‧ 72-3‧ 05), urban residence (HR=1‧ 19, 95% CI 1‧ 09-1‧ 31), tertiary care (HR=2‧ 2, 95% CI 2‧ 14-2‧ 26), oncology (HR=3‧ 57, 95% CI 3‧ 4-3‧ 76), and hematology (HR=1‧ 6, 95% CI 1‧ 49-1‧ 73) were associated with higher risk of mortality at each medical center with large region-to-region variations. There was a statistically significant association between prolonged waiting and death (Z = 2‧ 16, P = 0‧ 0308). Interpretation: Patient wait time for non-prioritized health conditions was associated with increased mortality in Chilean hospitals. Funding Statement: The work was supported by the Johns Hopkins Alliance for a Healthier World. DM is also supported by the U.S. Centers for Disease Control and Prevention, U.S. Agency for Healthcare Research and Quality, and the Emergency Medicine Foundation. DP is also supported by the U.S. National Science Foundation. FF is also supported by the Comision Nacional de Investigacion Cientifica y Tecnologica de Chile. JH is also supported by the U.S. National Institutes of Health, U.S. Agency for Healthcare Research and Quality, and the Emergency Medicine Foundation. SL is also supported by the U.S. National Science Foundation, U.S. National Institutes of Health, and the U.S. Agency for Healthcare Research and Quality. Declaration of Interests: FF is the founder and co-owner of a start-up company with a focus on data analytics for process improvement. SL is the founder and co-owner of a start-up company with a focus on data-driven improvement of emergency department and hospital operations. DM, DP, HZ, JH, JD, MB, and RM have no competing interests.
Highlights
Most data on mortality and prognostic factors of universal healthcare waiting lists come from North America, Australasia, and Europe, with little information from South America
Male gender, older age (HR = 2.88, 95% CI 2.72–3.05), urban residence (HR = 1.19, 95% CI 1.09–1.31), tertiary care (HR = 2.2, 95% CI 2.14–2.26), oncology (HR = 3.57, 95% CI 3.4–3.76), and hematology (HR = 1.6, 95% CI 1.49–1.73) were associated with higher risk of mortality at each medical center with large region-to-region variations
Patient wait time for non-prioritized health conditions was associated with increased mortality in Chilean hospitals
Summary
Most data on mortality and prognostic factors of universal healthcare waiting lists come from North America, Australasia, and Europe, with little information from South America. To optimize allocation and distribution of spending, countries have implemented large reforms that build capacity, prioritize resources, and set explicit waiting time targets for conditions defined through cost-benefit analysis [5]. Results of such health-system strengthening efforts and their effects on the health of people suffering non-prioritized health problems in South America are relevant for other lowand middle-income countries advancing towards universal healthcare [6, 7]. Since 2005, the public system guarantees access to care with limited waiting time and out-of-pocket payment for a specific set of health problems under the Health Explicit Guarantees (GES) Act (previously named “Plan AUGE”) [15,16,17].
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