scholarly journals The Influence of Physician's Assistants on National Health Insurance Revenue and Number of Patients in Clinic

2007 ◽  
Vol 17 (2) ◽  
pp. 18-32
Keyword(s):  
Health Insurance ◽  
National Health Insurance ◽  
National Health ◽  
Number Of Patients

scholarly journals How was cognitive behavioural therapy for mood disorder implemented in Japan? A retrospective observational study using the nationwide claims database from FY2010 to FY2015

BMJ Open ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. e033365 ◽  
Author(s):  
Yuta Hayashi ◽  
Naoki Yoshinaga ◽  
Yosuke Sasaki ◽  
Hiroki Tanoue ◽  
Kensuke Yoshimura ◽  
...  
Keyword(s):  
Health Insurance ◽  
Observational Study ◽  
National Health Insurance ◽  
National Health ◽  
National Health Insurance Scheme ◽  
Behavioural Therapy ◽  
Health Insurance Scheme ◽  
Insurance Scheme ◽  
Cognitive Behavioural ◽  
Number Of Patients

ObjectivesTo clarify the dissemination status of cognitive behavioural therapy (CBT) in Japan under the national health insurance scheme.DesignRetrospective observational study.SettingNational Database of Health Insurance Claims and Specific Health Checkups of Japan.ParticipantsPatients who received CBT under the national health insurance scheme from fiscal years (FY) 2010 to 2015.Primary and secondary outcome measuresWe estimated the change rate and the standardised claim ratio (SCR) for the number of patients receiving CBT and analysed the association between the CBT status and several regional factors.ResultsWe found that (a) a total of 60 304 patients received CBT during the study period; (b) the number of patients receiving CBT was highest in the first year (−1.8% from FY2010 to FY2015); (c) the number of patients who received CBT per 100 000 population decreased (or remained at zero) in most prefectures (32 out of 47); (d) there was a maximum 424.7-fold difference between prefectures in the standardised claim ratio for CBT and (e) the number of registered CBT institutions was significantly associated with the number of patients who received CBT.ConclusionsThe provision of CBT did not increase in the first 6 years (FY2010–2015) after its coverage in Japan’s national health insurance scheme. Further studies including a questionnaire survey of registered CBT institutions are required to get more detailed information on the dissemination of CBT in Japan.

scholarly journals BACK-REFERRAL PROGRAM IN THE ERA OF NATIONAL HEALTH INSURANCE AT BALUNG DISTRICT GENERAL HOSPITAL OF JEMBER IN 2017

2019 ◽  
Vol 7 (1) ◽  
pp. 33
Author(s):  
Christyana Sandra
Keyword(s):  
Health Insurance ◽  
Social Security ◽  
General Hospital ◽  
National Health Insurance ◽  
National Health ◽  
Access To Health Care ◽  
Neurological Diseases ◽  
District General Hospital ◽  
Stable Conditions ◽  
Number Of Patients

Background: In 2014, National Health Insurance Program (BPJS Kesehatan) implemented Back-Referral Program (BRP) to facilitate access to health care for patients with chronic diseases in stable conditions. However, the program did not run well at District General Hospital of Balung which had the lowest back-referral program (6 participants) in 2015-2016.Aim: The study aims to examine the BRP at Balung District General Hospital of Jember in 2017.Methods: This study is designed as qualitative case study. The informants consisted of head of treasury verification, secretary of JKN service controlling, officers of local government’s free care scheme, coordinator of internal and neurological disease, specialists in internal and neurological diseases, officers of Social Security Agency for Health, officers of patient eligibility verification, and participants of Back-Referral Program. The study was conducted from October to December 2017.Results: Results show that the attendance of BPJS Kesehatan officers has no contribution to the services of BPJS Kesehatan in the hospital. Participants also find it difficult to follow the steps of BRP due to unavailability of drugs at primary healthcare centers. Moreover, neurologists have not written any referral recommendation since 2016, so there was no patient admittance.Conclusions: The BRP at Balung District General Hospital did not achieve its target (<5 cases/week). In the contrary, the average number of patients referred to the hospital was 86 patients per week. Balung District General Hospital should implement Standard Operating Procedure for letters signed by responsible physician for patients and evaluate the BRP. Keywords: National Health Insurance, Back-referral program, Hospital, Social security.

Drug utilization study and cost analysis of adult β-thalassemia major patient therapy at Dr. Soetomo General Hospital Surabaya

2021 ◽  
Vol 32 (4) ◽  
pp. 611-616
Author(s):  
Hasna Qatrunnada ◽  
Suharjono ◽  
Siprianus Ugroseno Yudho Bintoro ◽  
Siti Wahyuni
Keyword(s):  
Health Insurance ◽  
General Hospital ◽  
Drug Utilization ◽  
Serum Ferritin ◽  
National Health Insurance ◽  
National Health ◽  
Thalassemia Major ◽  
Drug Utilization Study ◽  
Number Of Patients ◽  
Health Insurance Claims

Abstract Objectives The main therapy of β-thalassemia major are blood transfusion and iron chelation drugs. However, those therapies also have some adverse effects and problems such as iron overload, transfusion reactions, nutritional deficiencies, and patient compliance problems. Those arising problems also have an impact on therapy cost. Hence, this study was designed to analyze drug utilization study and cost of therapy in β-thalassemia major adult patients at Dr. Soetomo General Hospital Surabaya. Methods This research was conducted in descriptive observational-retrospective design using secondary data obtained from patient’s medical records and billing registrations from January 1–December 31, 2019. Results There were 18 patients out of 233 patients that were analyzed. Deferasirox was the most administered drug with doses between 500 mg/day–1,500 mg/day while deferiprone was ranged between 1,500 and 4,500 mg/day. Patients also received transfusion reaction drugs with dexamethasone injection 5 mg/ml which was administered the most. The most administered supplement was folic acid 1 mg. Patients had an increase in serum ferritin due to low compliance. Deferasirox had the most adherence number of patients with decrease of serum ferritin. The two highest costs of direct medical components were top-up medicines and consumable medical supplies. Overall, the hospital gained profit from national health insurance claims. Conclusions The most administered chelating agent was deferasirox. Deferasirox also had the most adherence number of patients with decreased number of serum ferritin. However, deferasirox also yielded the highest cost. Yet, overall, the hospital gained profit from national health insurance claims.

scholarly journals The Associations of Tonsillectomy with Adenoidectomy with Pneumonia and Appendicitis Based on National Sample Cohort Data from the Korean National Health Insurance Service

2021 ◽  
Author(s):  
Junhui Jeong ◽  
Jung Kyu Choi ◽  
Hyun Seung Choi ◽  
Chang Eui Hong ◽  
Hyang Ae Shin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Insurance ◽  
National Health Insurance ◽  
National Health ◽  
Significant Risk ◽  
National Sample ◽  
Population Based ◽  
Control Group ◽  
Number Of Patients ◽  
Korean National Health Insurance

Abstract Introduction The association between tonsillectomy with adenoidectomy (T&A) with appendicitis is controversial, and the association of T&A with pneumonia has not been investigated. Objective To investigate the associations of T&A with pneumonia and appendicitis using data from the Korean National Health Insurance Service National Sample Cohort. Methods We selected patients between the ages of 3 and 10 years who had undergone T&A in 2005 and were monitored since the performance of the T&A until 2013. The control group was established to have similar propensities for demographic characteristics compared to the T&A group. For eight years after the T&A, the number of patients with a diagnosis of pneumonia, patients who were admitted due to pneumonia, and those who underwent appendectomy were analyzed. The risk factors for pneumonia and appendectomy were analyzed. Results The number of pneumonia diagnoses was significantly higher in the T&A group than in the control group (p = 0.023), but there were no significant differences in the number of admissions due to pneumonia between the 2 groups (p = 0.155). Younger age and T&A were significant risk factors for the development of pneumonia. There were no significant differences in the number of appendectomies between the T&A and the control groups (p = 0.425), neither were there significant risk factors for appendectomy. Conclusion Tonsillectomy with adenoidectomy was associated with an increase in pneumonia diagnoses, but it was not associated with the number of appendectomies. The associations of T&A with pneumonia and appendicitis were analyzed in this population-based study.

scholarly journals Machine Learning Prediction Models for Chronic Kidney Disease using National Health Insurance Claim Data in Taiwan

2020 ◽  
Author(s):  
Surya Krishnamurthy ◽  
Kapeleshh KS ◽  
Erik Dovgan ◽  
Mitja Luštrek ◽  
Barbara Gradišek Piletič ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chronic Kidney Disease ◽  
Health Insurance ◽  
Kidney Disease ◽  
National Health Insurance ◽  
National Health ◽  
Performance Metrics ◽  
Prediction Models ◽  
Research Database ◽  
Number Of Patients

ABSTRACTBackground and ObjectiveChronic kidney disease (CKD) represent a heavy burden on the healthcare system because of the increasing number of patients, high risk of progression to end-stage renal disease, and poor prognosis of morbidity and mortality. The aim of this study is to develop a machine-learning model that uses the comorbidity and medication data, obtained from Taiwan’s National Health Insurance Research Database, to forecast whether an individual will develop CKD within the next 6 or 12 months, and thus forecast the prevalence in the population.MethodsA total of 18,000 people with CKD and 72,000 people without CKD diagnosis along with the past two years of medication and comorbidity data matched by propensity score were used to build a predicting model. A series of approaches were tested, including Convoluted Neural Networks (CNN). 5-fold cross-validation was used to assess the performance metrics of the algorithms.ResultsBoth for the 6 month and 12-month models, the CNN approach performed best, with the AUROC of 0.957 and 0.954, respectively. The most prominent features in the tree-based models were identified, including diabetes mellitus, age, gout, and medications such as sulfonamides, angiotensins which had an impact on the progression of CKD.ConclusionsThe model proposed in this study can be a useful tool for the policy-makers helping them in predicting the trends of CKD in the population in the next 6 to 12 months. Information provided by this model can allow closely monitoring the people with risk, early detection of CKD, better allocation of resources, and patient-centric management

scholarly journals Trend of Status Epilepticus Statistics in Korea: An Epidemiologic Study Based on National Health Insurance Database

2020 ◽  
Vol 38 (4) ◽  
pp. 253-259
Author(s):  
Hyun Kyung Kim ◽  
Sungchan Kang ◽  
Seo-Young Lee
Keyword(s):  
Growth Rate ◽  
Health Insurance ◽  
Status Epilepticus ◽  
National Health Insurance ◽  
National Health ◽  
Age Groups ◽  
National Health Insurance Database ◽  
Number Of Patients ◽  
Health Insurance Database ◽  
Insurance Database

Background: Status epilepticus is a severe neurologic emergency comprising significant morbidity and mortality. This study investigated the epidemiologic features of status epilepticus in Korea from 2010 to 2019.Methods: We used the Healthcare Bigdata Hub of the Korea National Health Insurance Database to identify records with principal diagnostic codes for status epilepticus (G41) using the 10th revision of the International Statistical Classification of Diseases and Related Health Problems from January 2010 to December 2019. This database only included patients with health insurance and not those with medical aid. The annual number of patients, costs, and regional differences were evaluated. The patients hospitalized under the principal diagnostic code for status epilepticus were considered as incident cases.Results: The total number of patients with a diagnosis of status epilepticus increased annually from 3,110 in 2010 to 5,840 in 2019 at a compound annual growth rate of 7.3%. The incidence of status epilepticus per 100,000 population increased steadily from 2.21 in 2010 to 5.33 in 2019. Health care expenditures showed continued growth at a faster rate of 18.4%. When categorized by age groups, the growth rate was markedly higher in age groups >60 years.Conclusions: In Korea, the incidence and cost of status epilepticus have increased from 2010 to 2019. Considering a possible underestimation of the incidence owing to data characteristics, the real incidence of status epilepticus may be higher. This trend in the incidence of status epilepticus can be mostly attributed to the increase of status epilepticus in the older population.

scholarly journals Evaluasi Implementasi Pelayanan Jaminan Kesehatan Nasional pada Balai Kesehatan Paru Masyarakat (BKPM) Wilayah Semarang Terikat Kerjasama Dengan Badan Penyelenggara Jaminan Sosial (BPJS) Kesehatan

2016 ◽  
Vol 4 (1) ◽  
pp. 74-82
Author(s):  
Agus Budiono ◽  
Sutopo Patria Jati ◽  
Chriswardani Suryawati
Keyword(s):  
Health Insurance ◽  
Health Center ◽  
National Health Insurance ◽  
National Health ◽  
Regional Cooperation ◽  
Unit Cost ◽  
Infrastructure Development ◽  
Real Cost ◽  
Number Of Patients ◽  
Lung Health

Provision of National Health Insurance (JKN) on Lung Health Center Society (BKPM) Region Semarang has not been implemented optimally. Increased patient visits JKN participants in 2014 only 1% compared to the era of Askes, the discrepancy rates with real cost incurred, inadequate infrastructure services, long waiting time queuing services and the lack of agreement among stakeholders define the classification status of BKPM. The aim of research to evaluate the implementation of national health insurance on Lung Health Center Society (BKPM) Region Semarang. The research was conducted by using a qualitative in-depth interviews and review of documentation to explore the phenomenon being evaluated. This study key informants from BKPM Territory Semarang is Semarang Regional Head of BKPM, Treasurer, 1 Medical Record officers, 2 doctors clinic, and 1 administrative manager of the Health Insurance. 1 person sexy informant triangulation financing and Public Health Insurance Central Java Provincial Health Office, 1 Main Branch Health BPJS staff Semarang. Quantitative data to support the triangulation of data with customer satisfaction survey using quota sampling technique to sample 45 participants JKN patients who seek treatment in Semarang Regional BKPM. Qualitative data analysis techniques and quantitative content analysis method with frequency table. The results showed that: 1) The number of patients more than Non PBI PBI, 2) Services BKPM Semarang according to the contents successor agreement Regional cooperation but still need to be developed and improved again. 79.03% patient satisfaction that includes a satisfactory category. 3) On the financing aspects still exist discrepancies BPJS service rates with real cost Semarang Regional BKPM expenses, 4) Coordination is not maximized at the management and executive levels in Semarang Regional BKPM in the implementation of Health Insurance in early 2014. Recommendations that can be given is necessary socialization and revamping procedures JKN referral, assessment manufacture unit cost as the basis tariff scheme, infrastructure development and improvement of health services in the implementation of labor discipline JKN in Semarang Regional BKPM.

scholarly journals Machine Learning Prediction Models for Chronic Kidney Disease Using National Health Insurance Claim Data in Taiwan

Healthcare ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 546
Author(s):  
Surya Krishnamurthy ◽  
Kapeleshh KS ◽  
Erik Dovgan ◽  
Mitja Luštrek ◽  
Barbara Gradišek Piletič ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chronic Kidney Disease ◽  
Health Insurance ◽  
Kidney Disease ◽  
National Health Insurance ◽  
National Health ◽  
Prediction Models ◽  
Research Database ◽  
Close Monitoring ◽  
Number Of Patients

Chronic kidney disease (CKD) represents a heavy burden on the healthcare system because of the increasing number of patients, high risk of progression to end-stage renal disease, and poor prognosis of morbidity and mortality. The aim of this study is to develop a machine-learning model that uses the comorbidity and medication data obtained from Taiwan’s National Health Insurance Research Database to forecast the occurrence of CKD within the next 6 or 12 months before its onset, and hence its prevalence in the population. A total of 18,000 people with CKD and 72,000 people without CKD diagnosis were selected using propensity score matching. Their demographic, medication and comorbidity data from their respective two-year observation period were used to build a predictive model. Among the approaches investigated, the Convolutional Neural Networks (CNN) model performed best with a test set AUROC of 0.957 and 0.954 for the 6-month and 12-month predictions, respectively. The most prominent predictors in the tree-based models were identified, including diabetes mellitus, age, gout, and medications such as sulfonamides and angiotensins. The model proposed in this study could be a useful tool for policymakers in predicting the trends of CKD in the population. The models can allow close monitoring of people at risk, early detection of CKD, better allocation of resources, and patient-centric management.

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