Drivers of high-cost persistence in rural China: A population-based retrospective study

Abstract

PurposeHigh-cost patients account for over 70% of total health expenditures in rural China and have become a key focus of health insurers. Persistently high-cost patients constitute a substantial proportion of medical resources. Hence, exploring high-cost persistence (HCP) and what drives it is considered meaningful and necessary.Patients and methodsA population-based retrospective study was carried out. The annual healthcare utilization data of Dangyang New Rural Cooperative Medical Scheme from 2012 to 2017 were analyzed. Patients in the top 10% of spending in a given year were considered high-cost patients. Persistence level was estimated using Markov matrices. A total of 19,405 patients categorized as high-cost patients in 2016 were divided into two groups according to whether or not they kept high-cost status in 2017. Finally, a multilevel logistic regression model was used in examining the determinants of HCP.ResultsOn average, about 31.48% of high-cost patients each year still maintained high-cost status in the subsequent year from 2012 to 2017. The elderly (OR = 2.150), families with more non-labor members (OR = 2.307), families applying for subsistence allowances (OR = 1.245), and patients with blood and immune diseases (OR = 2.614) or malignant tumors (OR = 2.077) were more likely to maintain high-cost status. Hospitalization frequency was found to be a mediator.ConclusionAbout one-third of high-cost patients in a given year had persistently high cost status in the subsequent year. Health status and family support were considered the main drivers of HCP. High inpatient service utilization as a mediator was a prominent manifestation of persistently high-cost patients. The accurate identification of persistently high-cost patients is the basis for our management.

Residents’ willingness towards first-contact with primary health care under uncertainty in healthcare: a cross-sectional study in rural China

“…We conducted a cross-sectional study in Dangyang, a typical rural area in Hubei Province in central China, with a rural population of 331 349 and a gross domestic product per capita higher than the national average. 25 We used the stratified sampling method to randomly Open access select three villages from each of the 10 townships in Dangyang. The household survey was conducted in each selected village.…”