ABSTRACT
Background@#On October 1, 2017, a new coinsurance reduction policy for children under 15 was introduced to minimize the lack of inpatient medical services for economic reasons and secure children’s access to medical care. @*Methods@#This study analyzes the effect of this coinsurance reduction policy on healthcare utilization using data from the National Health Insurance Service-National Sample Cohort between 2015 and 2019. Groups were classified by 3 case groups and a control group according to age. The dependent variables were inpatient cost, admission, length of hospitalization, outpatient cost and visit, and total cost. The difference-in-differences method was used to examine changes in healthcare utilization among the case and control groups after policy implementation. @*Results@#Children of the age group 1–5 exhibited an increase in inpatient services and a decrease in outpatient services. There was a 16.17% increase in inpatient cost, 8.55% increase in inpatient admission, 10.67% increase in inpatient length of hospitalization, −9.14% decline in outpatient cost, and −6.79% decline in outpatient visits. Regarding children in the age groups of 6–10 and 11–15, the effect of the policy was inconclusive. @*Conclusion@#The reduction in coinsurance rate policy in hospitalization among children has increased inpatient services and reduced outpatient services for 1–5-year-olds—a substitute effect was observed in this group. There is need for further research to examine the longterm effects of the coinsurance reduction policy.
ABSTRACT
Objectives@#The aim of this study was to identify the association between cohabitation status and sleep quality in family members of people with dementia (PwDs). @*Methods@#Data of 190 365 participants aged ≥19 years from the 2018 Korea Community Health Survey were analyzed. Participants were categorized according to their cohabitation status with PwDs. Multiple logistic regression and ordinal logistic regression analyses were performed to evaluate the relationship between the cohabitation status of PwDs’ relatives and sleep quality measured using the Pittsburgh Sleep Quality Index (PSQI) and PSQI subscales. @*Results@#Compared to participants without PwDs in their families, both cohabitation and non-cohabitation with PwDs were associated with poor sleep quality (cohabitation, male: odds ratio [OR],1.28; 95% confidence interval [CI], 1.08 to 1.52; female: OR, 1.40; 95% CI, 1.20 to 1.64; non-cohabitation, male: OR, 1.14; 95% CI, 1.05 to 1.24; female: OR, 1.23; 95% CI, 1.14 to 1.33). In a subgroup analysis, non-cohabiting family members showed the highest odds of experiencing poor sleep quality when the PwD lived alone (male: OR, 1.48; 95% CI, 1.14 to 1.91; female: OR, 1.58; 95% CI, 1.24 to 2.01). Cohabiting male and female participants had higher odds of poor subjective sleep quality and use of sleeping medications than non-cohabiting male and female participants, respectively. @*Conclusions@#The residence of PwDs and cohabitation status may contribute to poor sleep quality among PwDs’ family members. The circumstances faced by cohabiting and non-cohabiting family members should be considered when evaluating sleep quality in family members of PwDs, and appropriate interventions may be needed to improve sleep quality in both cohabiting and non-cohabiting family members.
ABSTRACT
Objectives@#The aim of this study was to identify the association between cohabitation status and sleep quality in family members of people with dementia (PwDs). @*Methods@#Data of 190 365 participants aged ≥19 years from the 2018 Korea Community Health Survey were analyzed. Participants were categorized according to their cohabitation status with PwDs. Multiple logistic regression and ordinal logistic regression analyses were performed to evaluate the relationship between the cohabitation status of PwDs’ relatives and sleep quality measured using the Pittsburgh Sleep Quality Index (PSQI) and PSQI subscales. @*Results@#Compared to participants without PwDs in their families, both cohabitation and non-cohabitation with PwDs were associated with poor sleep quality (cohabitation, male: odds ratio [OR],1.28; 95% confidence interval [CI], 1.08 to 1.52; female: OR, 1.40; 95% CI, 1.20 to 1.64; non-cohabitation, male: OR, 1.14; 95% CI, 1.05 to 1.24; female: OR, 1.23; 95% CI, 1.14 to 1.33). In a subgroup analysis, non-cohabiting family members showed the highest odds of experiencing poor sleep quality when the PwD lived alone (male: OR, 1.48; 95% CI, 1.14 to 1.91; female: OR, 1.58; 95% CI, 1.24 to 2.01). Cohabiting male and female participants had higher odds of poor subjective sleep quality and use of sleeping medications than non-cohabiting male and female participants, respectively. @*Conclusions@#The residence of PwDs and cohabitation status may contribute to poor sleep quality among PwDs’ family members. The circumstances faced by cohabiting and non-cohabiting family members should be considered when evaluating sleep quality in family members of PwDs, and appropriate interventions may be needed to improve sleep quality in both cohabiting and non-cohabiting family members.
ABSTRACT
OBJECTIVES: Recent advances in mobile technology have opened up possibilities to provide strongly integrated mobile-based services in healthcare and telemedicine. Although the number of mobile Electronic Health Record (EHR) applications is large and growing, there is a paucity of evidence demonstrating the usage patterns of these mobile applications by healthcare providers. This study aimed to illustrate the deployment process for an integrated mobile EHR application and to analyze usage patterns after provision of the mobile EHR service. METHODS: We developed an integrated mobile application that aimed to enhance the mobility of healthcare providers by improving access to patient- and hospital-related information during their daily medical activities. The study included mobile EHR users who accessed patient healthcare records between May 2013 and May 2014. We performed a data analysis using a web server log file analyzer from the integrated EHR system. Cluster analysis was applied to longitudinal user data based on their application usage pattern. RESULTS: The mobile EHR service named M-UMIS has been in service since May 2013. Every healthcare provider in the hospital could access the mobile EHR service and view the medical charts of their patients. The frequency of using services and network packet transmission on the M-UMIS increased gradually during the study period. The most frequently accessed service in the menu was the patient list. CONCLUSIONS: A better understanding regarding the adoption of mobile EHR applications by healthcare providers in patient-centered care provides useful information to guide the design and implementation of future applications.