Comparative analysis of infertility healthcare utilization before and after insurance coverage of assisted reproductive technology: A cross-sectional study using National Patient Sample data.
Han-Sol LeeYu-Cheol LimDong-Il KimKyoung-Sun ParkYoon Jae LeeIn Hyuk HaYe-Seul LeePublished in: PloS one (2023)
This study aims to analyze the types and cost of infertility care provided in a clinical setting to examine the changes of healthcare utilization for infertility after the 2017 launch of assisted reproductive technology (ART) health insurance coverage in South Korea. Health Insurance Review Assessment-National Patient Sample data from 2016 and 2018 were analyzed comparatively. Data related to receiving medical service under the International Classification of Diseases 10th revision code N97 (female infertility) or N46 (male infertility) at least once were analyzed, including patients' characteristics and healthcare utilization (type of healthcare facility and treatment approach). Between 2016 and 2018, the percentage of patients aged 30-34 receiving infertility care dropped; the percentages of patients in older age groups increased. The number of female patients remained comparable, whereas the number of male patients increased by 23%. Average visits per patient increased by about 1 day from 2016 to 2018. Total annual infertility care claim cost increased from $665,391.05 to $3,214,219.48; the per-patient annual cost increased from $114.76 to $522.38. The number of claims and cost of treatment and surgery increased markedly, as did the number of claims and cost of gonadotropins. With its focus on health insurance coverage of ART and results demonstrating increases in medical services, medications, cost, and patient utilization, this study reveals the significant effects of national health policies on the treatment, cost, and management of infertility.
Keyphrases
- healthcare
- health insurance
- affordable care act
- end stage renal disease
- chronic kidney disease
- ejection fraction
- newly diagnosed
- case report
- prognostic factors
- peritoneal dialysis
- metabolic syndrome
- quality improvement
- total knee arthroplasty
- polycystic ovary syndrome
- type diabetes
- machine learning
- patient reported outcomes
- big data
- electronic health record
- adipose tissue
- insulin resistance
- hiv infected
- artificial intelligence
- acute coronary syndrome
- data analysis
- combination therapy
- deep learning
- long term care