scholarly journals Varicella healthcare resource utilization in middle income countries: a pooled analysis of the multi-country MARVEL study in Latin America & Europe

2019 ◽  
Vol 15 (4) ◽  
pp. 932-941 ◽  
Author(s):  
Lara J. Wolfson ◽  
Maria Esther Castillo ◽  
Norberto Giglio ◽  
Zsofia Meszner ◽  
Zsuzsanna Molnar ◽  
...  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Ying Li ◽  
Tai-Yu Lin ◽  
Yung-Ho Chiu

Abstract Background Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations. Methods The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013–2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated. Results It was found that: (1) the annual average overall efficiency in China’s eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper–middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities’ respiratory disease and mortality rate efficiencies were higher than in the upper–middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies. Conclusions First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO2 efficiencies. However, the high-income cities had lower average CO2 emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi’an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities.


Author(s):  
Ajay Sharma ◽  
Paula J Alvarez ◽  
Steven D Woods ◽  
Jeanene Fogli ◽  
Dingwei Dai

Abstract Background Hyperkalemia is a serious metabolic condition and can lead to life-threatening cardiac arrhythmias and sudden death. Guideline-directed medications that affect the renin-angiotensin-aldosterone axis can increase serum potassium and may limit their use. Hyperkalemia has been shown to drive healthcare resource utilization (HRU) and costs for patients with cardiorenal conditions. Objectives To describe hyperkalemic patient characteristics and quantify patient HRU and costs relative to normokalemic patients from a large US health plan. Methods A retrospective cohort study that identified and evaluated a hyperkalemic patient population from a large administrative claims database. The observation period was 1 January 2015 to 31 May 2018, with a 1-year follow-up period after the index date (the earliest service/claim with evidence of hyperkalemia). Primary patient outcomes included inpatient admissions, emergency department (ED) visits, primary care physician (PCP)/specialist visits, length of stay (LOS) and associated medical and pharmacy costs. This hyperkalemic cohort was stratified by renin-angiotensin-aldosterone system inhibitor (RAASi) utilization and chronic kidney disease (CKD) stage for the economic analysis. Key findings 86,129 adult patients with hyperkalemia were evaluated in the study cohort (median age: 69 years). There were more males [45,155 (52%)], with the majority of patients located in the Southern United States [45,541 (51%)] and a 70/30 split of Medicare to a commercial health plan. Most patients had CKD, hypertension and hyperlipidemia; ≥80% of the patients had ≥4 comorbidities. Over 40% of patients were not receiving RAASi therapy, and potassium binder use was low (<5%). Patients using optimal-dose RAASi with proportion of days covered ≥80% were observed to have the lowest HRU for inpatient admissions, ED and PCP visits and LOS days. Conclusions Hyperkalemia is associated with substantial HRU and costs. The development of a quality improvement program structured around the management of hyperkalemia in individuals with heart failure, diabetes and/or CKD may be necessary.


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