کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6239125 | 1278986 | 2016 | 8 صفحه PDF | دانلود رایگان |
- We analyzed a health insurance claims database including 1.24 million insured people.
- The prevalence of duplicative prescriptions in Japan was low (less than 10%).
- The prevalence of duplicative prescription was correlated with its frequency of prescription.
- Social network analysis revealed clusters of facilities connected via duplicative prescriptions.
- Using a social network approach helps to understand duplicative prescription practices.
ObjectivesDuplicative prescriptions refer to situations in which patients receive medications for the same condition from two or more sources. Health officials in Japan have expressed concern about medical “waste” resulting from this practices. We sought to conduct descriptive analysis of duplicative prescriptions using social network analysis and to report their prevalence across ages.MethodsWe analyzed a health insurance claims database including 1.24 million people from December 2012. Through social network analysis, we examined the duplicative prescription networks, representing each medical facility as nodes, and individual prescriptions for patients as edges.ResultsThe prevalence of duplicative prescription for any drug class was strongly correlated with its frequency of prescription (r = 0.90). Among patients aged 0-19, cough and colds drugs showed the highest prevalence of duplicative prescriptions (10.8%). Among people aged 65 and over, antihypertensive drugs had the highest frequency of prescriptions, but the prevalence of duplicative prescriptions was low (0.2-0.3%). Social network analysis revealed clusters of facilities connected via duplicative prescriptions, e.g., psychotropic drugs showed clustering due to a few patients receiving drugs from 10 or more facilities.ConclusionOverall, the prevalence of duplicative prescriptions was quite low - less than 10% - although the extent of the problem varied by drug class and age group. Our approach illustrates the potential utility of using a social network approach to understand these practices.
Journal: Health Policy - Volume 120, Issue 3, March 2016, Pages 334-341