Introducing Diagnosis-Related Groups in Kazakhstan: Evolution, achievements, and challenges

A Bibliometric Analysis of Diagnosis Related Groups from 2013 to 2022

Purpose

As an important management method of the global healthcare system, diagnosis related groups (DRGs) classify patients into different cost groups and pay more attention to the equitable distribution of medical resources and the quality of medical services. At present, most countries have used DRGs to help medical institutions and doctors to treat patients more accurately, avoid the waste of medical resources, and improve treatment efficiency.

Methods

The Web of Science database was searched to collect all relevant literature on DRGs from 2013 to 2022. The literature information was imported into CiteSpace, Vosviewer, and Histcite for data analysis and visualization of the results. Analyze the cooperative relationship among the countries, institutions, journals, and authors. The usage trend of keywords; Highlight the content of the cited articles.

Results

The number of articles published in this decade was stable, and the number of citations in 2014 was the highest. The United States and Germany, as the first countries to use the DRGs system, are ahead of other countries in terms of the number and quality of articles. We have carried out content research on the articles with high citations, and summarized the application range of DRGs; classification method; advantages and disadvantages of the application. In general, the development trend of DRGs in foreign countries is to continuously optimize the classification method, expand the scope of application, and improve the application effect. These provide support and reference for the improvement of medical services and the perfection of the medical insurance system.

Conclusion

The application of DRGs can improve the quality and efficiency of medical services, and reduce the waste of medical expenses. It can also promote the rational allocation of medical resources and the equity of medical services. In the future, DRGs will pay more attention to the personalized diagnosis and treatment and fine management of patients, and the sharing and standardization of medical data, to promote the development of medical informatization.

Challenges of implementing diagnostic-related groups and healthcare promotion in Iran: A strategic applied research

Background and Aim

Implementing the diagnostic-related groups (DRGs) promotes the efficiency of healthcare. Therefore, the present study aimed to identify the challenges facing implementing the DRGs in Iran.

Methods

The present study is a strategic applied research conducted in two phases. In the first phase, the challenges facing DRGs were extracted through a literature review. Then the collected data is entered into a checklist consisting of five sections including technological, cultural, organizational, strategic, and natural challenges. In the second phase, data were collected by purposive sampling and semistructured interviews with 10 managers of the Medical Services Organization of Tehran, Iran. Data analysis was performed by conventional content analysis using MAXQDA software and descriptive using SPSS software version 19.

Results

The challenges facing the implementing DGRs from the experts' perspective included technological, organizational, nature, strategic, and cultural in order of priority. The three main fundamental challenges were reported; lack of integrating the DGRs with health information system (70%), frequent changes of management (70%), reducing the quality of care following early patient discharge (60%).

Conclusion

The results of the present study showed that the DRG system faced with challenges and healthcare officials should apply policies and guidelines to reform the system before changing the reimbursement system in Iran. By considering the leading countries experiences in the nationalizing the DRG system field, the problems and solutions of the system can be identified and aid in the more successful implementation of these systems.

DRG grouping by machine learning: from expert-oriented to data-based method

Background

Diagnosis-related groups (DRGs) are a payment system that could effectively solve the problem of excessive increases in healthcare costs which are applied as a principal measure in the healthcare reform in China. However, expert-oriented DRG grouping is a black box with the drawbacks of upcoding and high cost.

Methods

This study proposes a method of data-based grouping, designed and updated by machine learning algorithms, which could be trained by real cases, or even simulated cases. It inherits the decision-making rules from the expert-oriented grouping and improves performance by incorporating continuous updates at low cost. Five typical classification algorithms were assessed and some suggestions were made for algorithm choice. The kappa coefficients were reported to evaluate the performance of grouping.

Results

Based on tenfold cross-validation, experiments showed that data-based grouping had a similar classification performance to the expert-oriented grouping when choosing suitable algorithms. The groupings trained by simulated cases had less accuracy when they were tested by the real cases rather than simulated cases, but the kappa coefficients of the best model were still higher than 0.6. When the grouping was tested in a new DRGs system, the average kappa coefficients were significantly improved from 0.1534 to 0.6435 by the update; and with enough computation resources, the update process could be completed in a very short time.

Conclusions

As a new potential option, the data-based grouping meets the requirements of the DRGs system and has the advantages of high transparency and low cost in the design and update process.

Effects of a DRG-based hospital reimbursement on the health care utilization and costs in Swiss primary care: A retrospective "quasi-experimental" analysis

Introduction

In Switzerland, a nationwide Swiss Diagnosis related Groups (Swiss DRG) system for hospital reimbursement was introduced in 2012. However, the impact of DRG systems on primary care is still unclear with respect to number of consultations and costs. The aim of this study was to investigate the effect of the implementation of DRG on costs and volumes in the primary care sector, on a nationwide basis in Switzerland.

Methods

The study retrospectively analysed yearly data, from 2008 to 2014, of almost 60 Swiss health insurers that covered almost all Swiss general practitioners, with a total number of patients which represented approximately 76% of the Swiss population. GP consultations, total numbers and rates, and the relative costs reimbursed (TARMED tariff values) in the Swiss federal states, cantons, which already introduced a DRG-like system before 2012 (AP-DRG), were compared to the GP consultations and costs reimbursed in the other cantons (DRG-naive). Regression discontinuity design analysis and mixed regression models, at cantonal level, were performed to evaluate the effect of the nationwide implementation of the Swiss DRG on health care demand and costs in the primary care setting. Change in outcome level and yearly trend pattern difference between groups (AP-DRG vs. DRG-naive) were examined.

Results

Overall, the total number of GP consultations and the relative TARMED values increased from 2008 to 2014. In the DRG naive, 15 cantons: in 2008, the number of GP consultations were 13,114,126, with a TARMED value of 1,194,957,157 CHF, and in 2014, the GP consultation were 13,752,511, with a TARMED value of 1,513,861,260 CHF. In the AP-DRG group, 11 cantons, the total number of GP consultations increased from 8,787,646, in 2008, to 9,347,168 in 2014 and the TARMED value increased from 896,673,657 CHF in 2008, to 1,100,203,508 CHF in 2014. The yearly trend pattern of GP consultations and TARMED values, in the AP-DRG group, were not significantly different from the respective trends in the DRG- naive and, overall, no significant change was detected in consultations and costs trends before and after 2012.

Discussion/Conclusion

This study found no evidence of any effect of the introduction of the SwissDRG on the yearly trend of primary care consultations and costs. Nevertheless, potential negative impacts on vulnerable patients, as chronically ill patients, could not be excluded and further investigation is required.

The impact of improving the quality of coding in the utilities of Diagnosis Related Groups system in a private healthcare institution. 14-year experience

BACKGROUND AND PROJECT AIM

The American British Cowdray Medical Center is a private healthcare institution in Mexico City. One of the many tools that we use and help us to achieve a high standard of quality and recognition worldwide is the clinical coding and Diagnosis Related Groups (DRG). To help the readers to improve the process of clinical coding, we will share the challenges, changes and different applications of the generation of DRG in the private healthcare institution.

METHODS AND RESULTS

A retrospective, descriptive study to demonstrate the changes on the process of coding and measure the outcome of clinical coding, precision of data and better quality in the generations of DRGs. Initially, less than 2 diagnoses and 1 procedure were coded per discharge, using partial medical records. By the second half of 2007, a different coding procedure was implemented, and the complete medical records started being used; also, comorbid conditions were included in coding. Nowadays, the average number of coded diagnoses is 5.4 and the average number of coded procedures is 4.2, with a coding error rate of 0.68% and a DRG outliers' rate of 0.45%.

DISCUSSION AND CONCLUSIONS

While many countries use DRG for reimbursement, we exploit the clinical data registration and the DRGs for the economic and organizational. Through more efficient and accurate coding, DRGs are useful within the institution to generate indicators on resources, cost, length of stay and goals for each service. Having better quality clinical data has allowed for improved service line management, which has translated into patient-oriented services. Prospective studies are necessary to keep evaluating in a objective way the utilities of the DRG in healthcare private institutions.

Implementation of provider payment system reforms in the age of universal health coverage: a realist review of evidence from Asian developing countries

Objective

Launched to assist in achieving universal health coverage, provider payment reform (PPR) is one of the most important policy tools deployed to transform incentives within a health system that is plagued with allocative inefficiency and high out-of-pocket payments to one that is able to deliver basic services and be cost-efficient. However, the black box of such reform – that is, the contexts in which reform operates, the mechanisms by which it changes health systems and behaviour within health systems, and the outcome patterns that arise from – remains unexplored. This review aims to examine the implementation mechanisms underlying PPR in Asian developing countries.

Methods

A realist synthesis approach was employed to tease out the configurative elements of PPR in developing countries. A multimethod and retrospective search was conducted to locate the evidence. A programme theory and data extraction framework were developed. Data were analysed using thematic synthesis to inform an overarching realist synthesis, expressed as a set of synthesized context-mechanism-outcome configurations.

Results

This review found that the policy design of PPR, policy capacity, willingness of policy adoption at the local government level and provider autonomy are critical contextual factors that could trigger different policy mechanisms leading to either intended theoretical outcomes or perverse incentives.

Conclusions

Our findings, demonstrating the PPR implementation contexts and mechanisms that have worked in Asian countries, have implications in terms of policy learning for most developing countries that are contemplating rolling out similar reforms in the future.