The effectiveness of the neonatal diagnosis-related group scheme

How much can we learn from each other? Polish and Hungarian good practices in financing ophthalmology care as a proposal for implementation in Ukraine

OBJECTIVES

The article aims to compare payment schemes for cataract, glaucoma, vitrectomy, cornea transplantations, DME, and AMD across Hungary, Poland, and Ukraine, and to identify implementable practices in Ukraine within the context of ongoing healthcare reforms.

METHODS

Researchers used mixed-method research-with legal documents and data analysis on utilisation of ophthalmology services between 2010 and 2019 and in-depth semi structured interviews with fifteen health experts from Hungary, Poland, and Ukraine. Interviewees, five from each country, were representatives from healthcare providers and payers with at least 10 years' experience in ophthalmology care and knowledge about financing schemes in each country of residence.

RESULTS

We identified significant differences in healthcare delivery and financing of ophthalmology services between Hungary and Poland, despite both countries rely on Diagnosis-Related Group (DRG) based systems for hospital care. Good practices for financing specific eye treatments like cataract, glaucoma, age-related macular degeneration (AMD), diabetic macular edema (DME), cornea transplantations, and vitrectomy are identified. The financing scheme, including financial products and incentives, can influence the volume of treatments. Access to ophthalmic care is a key concern, with differences in treatment schemes between Hungary (ambulatory care) and Poland (hospital care), leading to higher costs and the need for centralization of complex procedures like cornea transplantations.

CONCLUSIONS

The article highlights the importance of incentivizing quality improvements and removing financial barriers in Poland, while Hungary should focus on continuous monitoring of treatment methods and flexibility in reimbursement. For Ukraine, the research findings are significant due to ongoing healthcare reform, and the country seeks optimal practices while considering the experiences of other countries.

DRGKB: a knowledgebase of worldwide diagnosis-related groups' practices for comparison, evaluation and knowledge-guided application

As a prospective payment method, diagnosis-related groups (DRGs)'s implementation has varying effects on different regions and adopt different case classification systems. Our goal is to build a structured public online knowledgebase describing the worldwide practice of DRGs, which includes systematic indicators for DRGs' performance assessment. Therefore, we manually collected the qualified literature from PUBMED and constructed DRGKB website. We divided the evaluation indicators into four categories, including (i) medical service quality; (ii) medical service efficiency; (iii) profitability and sustainability; (iv) case grouping ability. Then we carried out descriptive analysis and comprehensive scoring on outcome measurements performance, improvement strategy and specialty performance. At last, the DRGKB finally contains 297 entries. It was found that DRGs generally have a considerable impact on hospital operations, including average length of stay, medical quality and use of medical resources. At the same time, the current DRGs also have many deficiencies, including insufficient reimbursement rates and the ability to classify complex cases. We analyzed these underperforming parts by domain. In conclusion, this research innovatively constructed a knowledgebase to quantify the practice effects of DRGs, analyzed and visualized the development trends and area performance from a comprehensive perspective. This study provides a data-driven research paradigm for following DRGs-related work along with a proposed DRGs evolution model. Availability and implementation: DRGKB is freely available at http://www.sysbio.org.cn/drgkb/. Database URL: http://www.sysbio.org.cn/drgkb/.

Prediction of Obstetric Patient Flow and Horizontal Allocation of Medical Resources Based on Time Series Analysis

Objective: Given the ever-changing flow of obstetric patients in the hospital, how the government and hospital management plan and allocate medical resources has become an important problem that needs to be urgently solved. In this study a prediction method for calculating the monthly and daily flow of patients based on time series is proposed to provide decision support for government and hospital management.

Methods: The historical patient flow data from the Department of Obstetrics and Gynecology of the First Hospital of Jilin University, China, from January 1, 2018, to February 29, 2020, were used as the training set. Seven models such as XGBoost, SVM, RF, and NNAR were used to predict the daily patient flow in the next 14 days. The HoltWinters model is then used to predict the monthly flow of patients over the next year.

Results: The results of this analysis and prediction model showed that the obstetric inpatient flow was not a purely random process, and that patient flow was not only accompanied by the random patient flow but also showed a trend change and seasonal change rule. ACF,PACF,Ljung_box, and residual histogram were then used to verify the accuracy of the prediction model, and the results show that the Holtwiners model was optimal. R2, MAPE, and other indicators were used to measure the accuracy of the 14 day prediction model, and the results showed that HoltWinters and STL prediction models achieved high accuracy.

Conclusion: In this paper, the time series model was used to analyze the trend and seasonal changes of obstetric patient flow and predict the patient flow in the next 14 days and 12 months. On this basis, combined with the trend and seasonal changes of obstetric patient flow, a more reasonable and fair horizontal allocation scheme of medical resources is proposed, combined with the prediction of patient flow.

The impact of diagnosis related group payment on the performance of public hospitals

OBJECTIVE

To investigate the practical value of diagnosis related groups (DRGs) according to payment for assessing the performance of public hospitals.

METHODS

According to a random number table, 2400 patients were chosen from 3928 inpatients admitted for treatment in our hospital. Based on nodes implemented in the DRGs, these patients were assigned to the control group and the experimental group (1200 patients in each group). In the control group, patients didn't receive assistance with DRG payment (a clinical performance management approach was carried out based on the type of disease and cost), while patients in the experimental group received DRG. Bed turnover rate, hospitalization time, average cost, mortality, and subjective satisfaction were obtained and compared between the two groups.

RESULTS

Compared with the control group, bed turnover rate, hospitalization time, average cost, and mortality in the experimental group were all significantly decreased (P<0.05), while subjective satisfaction was increased (P<0.05).

CONCLUSION

DRG payment is beneficial for reduced clinical hospitalization time, cost, and mortality, and improved bed utilization rate and subjective satisfaction, which is worthy of clinical promotion.