Faculty of Management and Medical Information, Kerman University of Medical Sciences, Kerman, Iran *Corresponding Author’s e-mail: emohsenbeigi@gmail.com التحدايت والنتائج السلبية لتنفيذ آليات للتعويض بناًء على نظام تصنيف اجملموعة املرتبط ابلتشخيص مراجعة منهجية حم�سن باروين، ليلى �أحمديان، ح�سني �سابري �أناري، �إلهام حم�سن بيكي abstract: In health insurance, a reimbursement mechanism refers to a method of third-party repayment to offset the use of medical services and equipment. This systematic review aimed to identify challenges and adverse outcomes generated by the implementation of reimbursement mechanisms based on the diagnosis-related group (DRG) classification system. All articles published between 1983 and 2017 and indexed in various databases were reviewed. Of the 1,475 articles identified, 36 were relevant and were included in the analysis. Overall, the most frequent challenges were increased costs (especially for severe diseases and specialised services), a lack of adequate supervision and technical infrastructure and the complexity of the method. Adverse outcomes included reduced length of patient stay, early patient discharge, decreased admissions, increased re-admissions and reduced services. Moreover, DRG-based reimbursement mechanisms often resulted in the referral of patients to other institutions, thus transferring costs to other sectors. Keywords: Health Insurance; Third-Party Payments; Reimbursement Mechanisms; Diagnosis-Related Groups; Quality of Health Care; Patient Outcome Assessment; Systematic Review. امللخ�ص: يف نظام �لتاأمني �ل�سحي، ت�سري �آلية �ل�سد�د �إىل طريقة �ل�سد�د لطرف ثالث لتعوي�ض ��ستخد�م �خلدمات و�ملعد�ت �لطبية. تهدف هذه �ملر�جعة �ملنهجية �إىل حتديد �لتحديات و�لنتائج �ل�سلبية �لناجتة عن تنفيذ �آليات �ل�سد�د على �أ�سا�ض نظام ت�سنيف �ملجموعة �ملرتبطة بالت�سخي�ض. متت مر�جعة جميع �ملقاالت �ملن�سورة بني عامي 1983 و 2017 و�ملفهر�سة يف قو�عد �لبيانات �ملختلفة. من بني 1,475 مقالة مت حتديدها، كانت 36 مقالة ذ�ت �سلة ومت ت�سمينها يف �لتحليل. ب�سكل عام، كانت �لتحديات �الأكرث �سيوًعا هي �لتكاليف �ملتز�يدة )خا�سة �لنتائج �سملت �لطريقة. وتعقيد �لتقنية �لتحتية و�لبنية �ملنا�سب �الإ�رش�ف ونق�ض �ملتخ�س�سة(، و�خلدمات �ل�سديدة للأمر��ض بالن�سبة �ل�سلبية تقليل مدة �إقامة �ملري�ض، و�خلروج �ملبكر للمري�ض، و�نخفا�ض معدل �الإدخال، وزيادة حاالت �إعادة �الإدخال وتقليل �خلدمات. علوة على ذلك، غالًبا ما �أدت �آليات �ل�سد�د �مل�ستندة �إىل �ملجموعة �ملرتبطة بالت�سخي�ض �إىل �إحالة �ملر�سى �إىل موؤ�س�سات �أخرى، وبالتايل حتويل �لتكاليف �إىل قطاعات �أخرى. الكلمات املفتاحية: �لتاأمني �ل�سحي؛ مدفوعات �لطرف �لثالث؛ �آليات �ل�سد�د؛ �ملجموعات ذ�ت �ل�سلة بالت�سخي�ض؛ جودة �لرعاية �ل�سحية؛ تقييم نتائج �ملري�ض؛ مر�جعة منهجية. Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari, *Elham Mohsenbeigi Sultan Qaboos University Med J, August 2020, Vol. 20, Iss. 3, pp. e260–270, Epub. 5 Oct 20 Submitted 21 Nov 19 Revision Req. 20 Jan 20; Revisions Recd. 25 Feb 20 Accepted 16 Apr 20 https://doi.org/10.18295/squmj.2020.20.03.004 review This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License. The diagnosis-related group (drg) classif- ication system is a method of categorising patients for health insurance purposes in order to control costs and facilitate repayment by third party providers for the use of medical services and equipment.1 Using this system, patients are classified according to a range of variables, including primary and secondary diagnoses, age, gender, the presence of comorbidities/complications and treatment(s) prov- ided. The intention behind this type of system is to classify patients into a limited number of groups in order to form clinically meaningful yet relatively homogeneous resource consumption patterns.2 A DRG-based reimbursement mechanism was first introduced in the USA in 1983 as a component of the Medicare programme, before being adopted by other countries around the world soon thereafter.3 Although the primary goals of DRG-based reim- bursement mechanisms vary worldwide, most aim to increase transparency and efficiency, especially in https://creativecommons.org/licenses/by-nd/4.0/ Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari and Elham Mohsenbeigi Review | 261 European countries.4–6 Indeed, increasing transparency, providing effective care, controlling costs and impr- oving the quality of care are some of the advantages reported for this method of reimbursement in hospital settings.7 However, this type of system is also subject to various challenges and adverse outcomes, for instance by unintentionally encouraging hospitals to preferentially admit more cost-effective patients.8 It has also been claimed that this type of payment system inspires a shift from traditional inpatient to outpatient care as a cost-saving measure.9 Researchers have previously evaluated the effects of implementing DRG-based repayment systems.10 However, to the best of the authors’ knowledge, none have yet sought to systematically evaluate the challenges and potential negative effects of this type of system. Therefore, the objective of this article was to systematically review the challenges and adverse outcomes generated by the implementation of DRG- based reimbursement mechanisms. Methods This systematic review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.11 A literature search was conducted to identify all English-language articles assessing the challenges and adverse outcomes of DRG- based reimbursement mechanisms published between January 1983 and February 2017 and indexed in the Scopus® (Elsevier, Amsterdam, the Netherlands), MEDLINE® (National Library of Medicine, Bethesda, Maryland, USA) or Embase® (Elsevier) databases. Search terms related to challenges and DRG- based reimbursement mechanisms were combined using Boolean operators (i.e. “challenge”, “barrier”, “problem”, “difficulty”, “disadvantage” OR “weakness” AND “DRG”, “diagnosis-related groups”, “case-mix” OR “case mix”) in order to identify relevant articles in which these terms appeared in the publication title, keywords and/or abstract. Following the literature search, identified articles were reviewed and the abstracts assessed by two evaluators to determine if they were fit for inclusion in the analysis. In cases of inter-evaluator disagreement, the full text of the articles was assessed in order to come to a consensus. Articles were selected for further full-text review if they explored the challenges and adverse outcomes generated by the implementation of a DRG-based reimbursement mechanism. All types of articles except reviews and letter to editors were included in the analysis. Articles focusing on other mechanisms of reimbursement, such as fee-for-service or global budget systems, were excluded. In addition, articles focusing on the measurement, calculation, development and structure of the mechanism and those solely examining positive or beneficial outcomes were also excluded. Subsequently, the studies were assessed to determine their quality based on criteria proposed by Kmet et al.12 Depending on the design of the study, two evaluators independently ranked the studies using different sets of criteria for qualitative and quantitative studies. Any disagreements were discussed until a consensus was reached. Implementation challenges were categorised as either leadership-related, managerial, organisational, technical or personnel- related according to a previously described template.13 Adverse outcomes were classified as per the model developed by Fourie et al.9 Overall, a total of 1,475 articles were identified during the literature search, of which 343 were duplicates. After reviewing the titles and abstracts, 892 non-relevant articles were also excluded. Subsequently, 240 articles underwent further full-text review; of these, 55 articles were excluded due to lack of access to the full text, 75 articles were review articles or letters to the editor and 44 were written in languages other than English. Furthermore, 29 articles were removed due to their lack of relevance and one qualitative article was excluded due to its low quality (i.e. a quality score of <50%). The final analysis therefore included 36 articles [Figure 1]. A standardised data collection form was developed and completed by two researchers. The data collected included bibliographic information, the study setting, the country in which the study was performed and any challenges and adverse Figure 1: Flowchart showing the search strategy used to identify articles for inclusion in the systematic review. Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review 262 | SQU Medical Journal, August 2020, Volume 20, Issue 3 Table 1: Quality analysis* of studies assessing the implementation of reimbursement mechanisms based on the diagnosis-related group classification system14–49 Criteria Score Quantitative studies Qualitative studies Mixed-method studies† Question/objective sufficiently described? 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 + 2 1 + 2 1 + 2 2 + 2 Study design evident and appropriate? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 + 2 2 + 2 2 + 2 2 + 2 Context for the study clear? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2 2 1 2 2 2 2 Connection to a theoretical framework/wider body of knowledge? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2 2 1 2 2 2 2 Sampling strategy described, relevant and justified? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2 N/A 2 2 2 2 2 Data collection methods clearly described and systematic? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2 2 1 2 2 2 2 Data analysis clearly described and systematic? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 2 2 2 2 2 2 2 Use of verification procedure(s) to establish credibility? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 0 0 1 2 0 2 2 Reflexivity accounted for? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 0 0 0 0 0 0 0 Method of subject/comparison group selection or source of information/ input variables described and appropriate? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 N/A N/A N/A 2 2 2 2 Subject (and comparison group, if applicable) characteristics sufficiently described? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 N/A N/A N/A 2 2 2 2 If interventional and random allocation was possible, was it described? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A If interventional and blinding of investigators was possible, was it reported? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A If interventional and blinding of subjects was possible, was it reported? N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A Outcome and (if applicable) exposure measure(s) well-defined and robust for measurement/misclassification bias? Means of assessment reported? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 N/A N/A N/A 2 2 2 2 Sample size appropriate? N/A N/A 2 1 2 N/A 2 1 N/A N/A N/A 2 2 1 N/A N/A N/A 2 2 N/A N/A Analytic methods described/justified and appropriate? 2 1 2 1 2 2 2 2 2 2 2 2 2 2 N/A N/A N/A 2 2 2 2 Some estimate of variance is reported for the main results? 2 1 0 0 2 0 0 2 0 2 2 1 2 1 N/A N/A N/A 2 0 2 0 Controlled for confounding? N/A N/A N/A N/A 0 N/A N/A N/A N/A 1 0 1 1 1 N/A N/A N/A N/A 0 0 N/A Results reported in sufficient detail? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 N/A N/A N/A 2 2 2 2 Conclusions supported by the results? 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 + 2 2 + 2 1 + 2 1 + 2 Total score out of maximum 18/ 18 16/ 18 18/ 20 16/ 20 20/ 22 16/ 18 18/ 20 19/ 20 15/ 18 19/ 20 18/ 20 20/ 22 21/ 22 19/ 22 16/ 20 14/ 18 14/ 20 37/ 40 33/ 42 34/ 40 33/ 38 N/A = not applicable. *As per criteria adapted from Kmet et al.12 Each criterion was assessed based on compliance, with scores of zero indicating no, 1 indicating partial compliance and 2 indicating full compliance. †For mixed-method studies, the qualitative and quantitative components were assessed separately, as indicated by plus signs (+) for criteria spanning both categories. M ul ti pl e s tu di es 14 ,1 7, 34 –3 7, 40 ,4 2– 46 H en se n et a l.4 7 ( 20 05 ) Z ha n et a l.3 2 ( 20 07 ) R oe de r e t a l.2 6 ( 20 01 ) R og er s e t a l.1 5 ( 19 90 ) M ul ti pl e st ud ie s1 6, 31 Pa te l48 (1 98 8) H or n et a l.3 8 ( 19 86 ) Sa nd er so n et a l.2 7 ( 19 89 ) M ul ti pl e st ud ie s2 4, 28 ,3 9 M ul ti pl e st ud ie s1 9, 23 H ur le y et a l.2 1 ( 19 90 ) W ol fe a nd D et m er 49 (1 98 8) M en ke e t a l.2 2 ( 19 98 ) B ul l41 (1 98 8) N ot m an e t a l.2 9 ( 19 87 ) W is en sa le a nd W al dr on 33 (1 99 1) So dz i-T et te y et a l.2 5 ( 20 12 ) G ol db er g an d Es te s1 8 ( 19 90 ) Ly le s2 0 (1 98 6) B ra y et a l.3 0 ( 19 94 ) Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari and Elham Mohsenbeigi Review | 263 outcomes identified regarding the implementation of DRG-based reimbursement mechanisms. In cases of disagreement, a third researcher was contacted to provide the deciding vote. Data analysis was performed using an Excel spreadsheet, Version 2013 (Microsoft Corp., Redmond, Washington, USA). The results were presented using descriptive statistics. Results A total of 36 articles assessing the challenges and adverse outcomes of DRG-based reimbursement mechanisms were included in the final analysis.14–49 Of these, the majority (n = 28; 77.8%) were published in 1990 or before.15–21,23,24,27–29,31,34,35,37–46,48,49 Most studies (n = 31; 86.1%) were set in the USA.15–24,28–46,48,49 Data collection strategies included observation (n = 2; 5.6%), in-person (n = 4; 11.1%) or telephone (n = 2; 5.6%) interviews, paper-based (n = 2; 5.6%) or electronic (n = 1; 2.8%) questionnaires, checklists (n = 1; 2.8%) and reviews of patient/hospital records (n = 26; 72.2%), annual reports (n = 8; 22.2%) and transcripts (n = 1; 2.8%).14–49 Almost two-thirds (n = 23; 63.9%) of the studies were set in hospitals, with the rest set in medical centres (n = 6; 16.7%), nursing homes (n = 2; 5.6%), trauma centres (n = 2; 5.6%), home health agencies (n = 2; 5.6%) or rehabilitation centres (n = 1; 2.8%).14–49 A total of 29 studies (80.6%) were quantitative in nature.14–17,19,21–24,26–28,31,32,34–40,42–49 In addition, there were three qualitative (8.3%) and four mixed-method (11.1%) studies.18,20,25,29,30,33,41 In terms of quality assessment, qualitative, quantitative and mixed- method studies received scores of >70%, >80% and >85%, respectively; however, quantitative studies were generally higher in quality compared to qualitative and mixed-method studies [Table 1].14–49 Table 2 summarises the studies which ident- ified challenges in the implementation of DRG-based reimbursement mechanisms.25–49 Overall, 15 studies (41.7%) reported managerial challenges.25,30,32,34–36,38–40, 42–47 Of these, 12 (80%) indicated that DRG-based reimbursement mechanisms were not suitable for certain services due to the high cost involved and the likelihood of financial loss, including skin care, trauma, fibrocystic disease, heart surgery, rare diseases, urology disorders, mental disorders, intensive care and the care of elderly and paediatric patients.34–36,38–40,42–47 The remaining three studies (20%) reported delayed reimbursement of hospital fees, increased expenses in educational hospitals (especially at baseline and in rural areas), poor medical recordkeeping and a lack of coding rules and standards.25,30,32 Two studies (5.6%) examined organisation environment challenges, including poor compliance with guidelines, the misfiling and potential loss of patients records and physicians being pressured to discharge patients prematurely.25,33 Technical challenges were reported by nine studies (25%), particularly data coding and misclassification issues and DRG creeping (i.e. upgrading or upcoding patients).25–28,31,32,37,42,47 Personnel-related challenges were also reported by eight studies (22%); of these, one of the most important was a lack of familiarity among physicians with the DRG classification system and misconceptions regarding the objectives of the mechanism.25,29,30,33,34,41,42,48,49 No leadership challenges were reported by any of the studies. Studies assessing adverse outcomes resulting from the implementation of DRG-based reimbursement mechanisms are described in Table 3.14–24,32–49 Overall, 11 studies (30.6%) examined the rate of early discharge, all of which noted an increase following implementation of the mechanism.15,17–20,22,23,33,41,47,48 The motivation for this was due to awareness on the part of both physicians and hospital administrators of patients’ costs and the desire to reduce the length of hospital stay and increase efficiency. Five studies (13.9%) evaluated readmission rates; of these, four (80%) observed that the implementation of DRG-based reimbursement mechanisms resulted in increased re- admission due to the low quality of services provided initially and premature discharge.14,19,22,23 In contrast, the remaining study revealed no change in the rate of re-admission.17 Nine studies (25%) measured length of patient stay.14,16,17,19,22–24,37,38 The majority (n = 8; 88.9%) found that the duration of hospital stay was reduced following the implementation of DRG-based reim- bursement mechanisms; reasons for this included preserving resources, reducing costs and improving efficiency.14,17,19,22–24,37,38 Only one indicated that the average length of stay increased.16 Two studies (5.6%) examined the number of services provided to patients; in the first, there was no change in the number of services provided to patients after implementation of the reimbursement mechanism, while the second found that access to certain services or technologies was restricted after implementation of the reimbursement mechanism since the system increased performance monitoring.17,23 Mortality rate was assessed as an outcome in four studies (11.1%).14,15,20,23 One study showed that the mortality rate increased following implementation of a DRG-based reimbursement mechanism.20 In contrast, two studies showed a reduction in mortality rate.14,23 Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review 264 | SQU Medical Journal, August 2020, Volume 20, Issue 3 Table 2: Challenges in the implementation of reimbursement mechanisms based on the diagnosis-related group classification system25–49 Author and year of study Setting Type of study Type of challenges Management process Organisation environment Technical systems Personnel Sodzi-Tettey et al.25 (2012) Ghana Mixed-method • Delays in reimbursement • Poor compliance with guidelines • Inadequate filing system • Classification problems • Severe personnel shortage • Lack of familiarity with DRG among physicians Roeder et al.26 (2001) Germany Quantitative N/A N/A • DRG variants differed in degree and detail • Questionable grouping of cases • Inaccuracies in diagnostic coding • Classification problems N/A Sanderson et al.27 (1989) UK Quantitative N/A N/A • Irregularities in diagnostic and operative coding • Inaccuracies in diagnostic coding N/A Horn et al.28 (1985) USA Quantitative N/A N/A • Failure to account for illness severity N/A Notman et al.29 (1987) USA Qualitative N/A N/A N/A • Lack of familiarity with DRG among physicians • Misconceptions regarding DRG among physicians Bray et al.30 (1994) USA Mixed-method • Increased costs per discharge in rural hospitals N/A N/A • Less effort made by physicians to improve the hospital’s financial performance Bredenberg and Lagoe31 (1987) USA Quantitative N/A N/A • Lack of sensitivity to different types of procedures N/A Zhan et al.32 (2007) USA Quantitative • Low-quality medical recordkeeping • Lack of rules and standards for coding N/A • DRG creeping N/A Wisensale and Waldron33 (1991) USA Qualitative N/A • Pressure on doctors to discharge patients prematurely N/A • Reduction of nurses and other support staff Muñoz et al.34 (1989) USA Quantitative • Financial loss N/A N/A • Refusal to admit patients Muñoz et al.35 (1988) USA Quantitative • Financial loss N/A N/A N/A Zwanziger et al.36 (1991) USA Quantitative • Financial loss N/A N/A N/A Vollertsen et al.37 (1988) USA Quantitative N/A N/A • Classification problems • DRG creeping N/A Horn et al.38 (1986) USA Quantitative • Financial loss N/A N/A N/A Thomas et al.39 (1988) USA Quantitative • Financial loss N/A N/A N/A Pasternak et al.40 (1986) USA Quantitative • Financial loss N/A N/A N/A Bull41 (1988) USA Qualitative N/A N/A N/A • Guiding patients to outpatient departments Joy and Yurt42 (1990) USA Quantitative • Financial loss N/A • Failure to account for illness severity N/A Muñoz et al.43 (1988) USA Quantitative • Financial loss N/A N/A N/A Munoz et al.44 (1989) USA Quantitative • Financial loss N/A N/A N/A Munoz et al.45 (1989) USA Quantitative • Financial loss N/A N/A N/A Muñoz et al.46 (1989) USA Quantitative • Financial loss N/A N/A N/A N/A = not available; DRG = diagnosis-related group. Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari and Elham Mohsenbeigi Review | 265 However, none of these studies reported a significant link between this outcome and the reimbursement mechanism. No change in mortality rate was observed in the final study.15 Nine studies (25%) evaluated the number of admissions.14,15,18,23,33,34,38,42,49 Of these, all but one (n = 8; 88.9%) indicated that the admission rate was reduced following implementation of the DRG-based reimbursement mechanisms in order to preserve resources.14,15,23,33,34,38,42,49 Hospital efficiency was assessed as an outcome in 14 studies (38.9%), all of which observed an increase in inefficiency.16,32,34–36,38–40,42–49 A total of 13 studies (36%) examined the impact of the reimbursement methods on transferring costs by directing patients to other healthcare institutions or centres.14,15,17–24,35,37,41 Only one of these indicated that implementation of the reimbursement mechanism did not lead to the transfer of costs to other institutions.14 The other studies found that patient costs were often transferred to other institutions in order to help reduce costs, especially for patients requiring rehabilitation services and those ≥65 years old. In particular, patients were often transferred to nursing homes or nursing care centres (n = 6; 46.2%), outpatient departments (n = 3; 23.1%), non-therapeutic sections (n = 1; 7.7%) and home-based services (n = 1; 7.7%).15,17–24,35,37,41 Discussion Prospective reimbursement mechanisms, particularly those based on the DRG classification system, are usually implemented by healthcare policymakers in order to improve efficiency, ensure the optimal allocation of resources and control costs.50,51 Such mechanisms are also viewed favourably by insurance agencies as they allow for the distribution of financial risk between customers and service providers.52 However, the current review indicated that the implementation of these systems can be subject to various challenges, the most important of which was increased costs, especially for patients with severe diseases and those requiring specialised services.34–36,38–40,42–47 Other challenges included the failure to follow necessary guidelines, inadequate supervision, poor knowledge of the system among healthcare personnel (especially physicians and nurses), lack of technical infrastructure and the complexity of the method in question.25–27,29,32 Several studies noted that DRG-based reimbursement mechanisms failed to appropriately calculate disease severity and the cost of certain services.28,42,47 According to Leister and Stausberg, neglecting to consider disease risk and appropriate diagnostic classifications based on disease severity can cause hospitals to lose valuable resources when delivering care to high-risk patients and those with severe illnesses.53 In such cases, hospitals utilising these systems may choose not to admit such patients or to discharge them earlier in order to increase efficiency and cut costs. As such, DRG classification systems should be set up based on the number, type and severity of disease in each case and allow users to modify the assigned group based on these factors; this would ensure the more equitable calculation of fees and improve accessibility to healthcare and the quality of services rendered.28,34,35 Roeder et al. deemed the establishment of standard DRG units and different types of DRGs to be especially challenging.26 Another systematic review similarly highlighted this to be a major hindrance to the implementation of DRG-based reimbursement mechanisms in mainland China.54 Variations in the lifestyles and types of patients attending hospitals in different geographical regions can often result in differences in treatment patterns, medical costs, demand for services and the overall burden of disease. These represent major barriers to the data collection necessary to establish appropriate classification groups that reflect the actual economic and clinical situation.54 However, only one of the studies included in the current review referred to this problem.36 Other studies highlighted various organisational and technical challenges related to DRG-based Table 2 (cont’d): Challenges in the implementation of reimbursement mechanisms based on the diagnosis-related group classification system25–49 Author and year of study Setting Type of study Type of challenges Management process Organisation environment Technical systems Personnel Patel48 (1988) USA Quantitative N/A N/A N/A • Early discharge of patients • Restricted access to certain products, technologies and services • Conflict between physicians Wolfe and Detmer49 (1988) USA Quantitative N/A N/A N/A • Motivation among surgeons for patient selection N/A = not available; DRG = diagnosis-related group. Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review 266 | SQU Medical Journal, August 2020, Volume 20, Issue 3 Table 3: Adverse outcomes resulting from the implementation of reimbursement mechanisms based on the diagnosis-related group classification system14–24,32–49 Author and year of study Setting Type of study Outcome Quality of care Access to care Efficiency of care Early discharge Readmission rate Length of stay Service provision Mortality rate Admission rate Efficiency Transfer of costs Busato and von Below14 (2010) Switzerland Quantitative N/A Increased Decreased N/A Decreased Decreased N/A No effect Rogers et al.15 (1990) USA Quantitative Increased N/A N/A N/A No effect No effect N/A Increased Vulgaropulos et al.16 (1990) USA Quantitative N/A N/A Increased N/A N/A N/A Inefficient N/A Evans et al.17 (1990) USA Quantitative Increased No effect Decreased No effect N/A N/A N/A Increased Goldberg and Estes18 (1990) USA Mixed- method Increased N/A N/A N/A N/A Decreased N/A Increased Tresch et al.19 (1988) USA Quantitative Increased Increased Decreased N/A N/A N/A N/A Increased Lyles20 (1986) USA Mixed-method Increased N/A N/A N/A Increased N/A N/A Increased Hurley et al.21 (1990) USA Quantitative N/A N/A N/A N/A N/A N/A N/A Increased Menke et al.22 (1998) USA Quantitative Increased Increased Decreased N/A N/A N/A N/A Increased Gay and Kronenfeld23 (1990) USA Quantitative Increased Increased Decreased N/A Decreased Decreased N/A Increased Morrisey et al.24 (1988) USA Quantitative N/A N/A Decreased N/A N/A N/A N/A Increased Zhan et al.32 (2007) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Wisensale and Waldron33 (1991) USA Qualitative Increased N/A N/A N/A N/A Decreased N/A N/A Muñoz et al.34 (1989) USA Quantitative N/A N/A N/A N/A N/A Decreased Inefficient N/A Muñoz et al.35 (1988) USA Quantitative N/A N/A N/A N/A N/A Decreased Inefficient Increased Zwanziger et al.36 (1991) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Vollertsen et al.37 (1988) USA Quantitative N/A N/A Decreased N/A N/A N/A N/A Increased Horn et al.38 (1986) USA Quantitative N/A N/A Decreased N/A N/A Decreased Inefficient N/A Thomas et al.39 (1988) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Pasternak et al.40 (1986) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Bull41 (1988) USA Qualitative Increased N/A N/A N/A N/A N/A N/A Increased Joy and Yurt42 (1990) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Muñoz et al.43 (1988) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Munoz et al.44 (1989)USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Munoz et al.45 (1989) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Muñoz et al.46 (1989) USA Quantitative N/A N/A N/A N/A N/A N/A Inefficient N/A Hensen et al.47 (2005) Germany Quantitative Increased N/A N/A N/A N/A N/A Inefficient N/A Patel48 (1988) USA Quantitative Increased N/A N/A Decreased N/A N/A N/A N/A Wolfe and Detmer49 (1988) USA Quantitative N/A N/A N/A N/A N/A Decreased N/A N/A N/A = not available. Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari and Elham Mohsenbeigi Review | 267 reimbursement mechanisms, including inadequate filing systems, poor recordkeeping, the misclassification of diseases, irregularities in the coding of procedures and diagnoses and an overall lack of coding rules and standards.25–27,32 Indeed, some studies showed that classification problems led to the possibility of DRG creeping, which refers to a tendency to upgrade or upcode patients to allow for the hospital to receive higher reimbursements.32,37 In a study of 239 hospitals under the Medicare programme, Hsia et al. identified the rate of DRG coding errors to be 20.8%, of which 61.7% significantly favoured the hospital.55 In order to avoid this problem, coding standards and rules should be established and enforced in every hospital to ensure the correct codes are utilised. Several studies in the current systematic review identified misconceptions among physicians and nurses regarding the DRG-based system, compounded by a lack of familiarity with the system.25,29 In some cases, healthcare personnel were uninterested in controlling costs.30 However, Wild et al. noted that sharing profits with physicians and encouraging them to help balance the budget would intensify conflict between physicians; moreover, they might feel torn between their commitments to providing the best care to the patient and controlling costs.7 One of the studies included in the current review noted that the DRG-based reimbursement mechanism increased costs, particularly in the year of implementation and in rural healthcare settings and educational hospitals.30 This finding may be due to several reasons, including a larger number of patients with severe illness presenting to educational hospitals, the lack of involvement of the physicians in improving the hospital’s financial performance, poor financial management and primary productivity control processes.30 On the other hand, DRG-based reimbursement mechanisms were deemed unsuitable in certain circumstances by other studies due to the lack of appropriate moderators, resulting in financial loss for the institution.38–40 Although most DRG-based reimbursement systems are introduced as cost-controlling measures, this can lead to undesirable outcomes that can affect the quality of the health services provided.4,56,57 This type of system results in a clear incentive for healthcare providers to preferentially admit patients with lower costs or restrict the provision of expensive services, leading to an unfair access to healthcare.58 In particular, vulnerable patient groups such as the elderly, children, immigrants and those suffering from chronic illness, heart failure or multiple illnesses may be disproportionately affected.34,48,49 Hospitals should therefore commit to providing an equal level of care to all patients by monitoring the performance of physicians. Additionally, providing standard protocols and guidelines for clinical decision-making may also be helpful to ensure a set level of quality of care while still controlling costs. In the current review, DRG-based reimbursement systems also led to other alarming outcomes, such as reducing essential services and admissions, encouraging early discharge, reducing length of stay, increasing re-admission and transferring costs to other sectors by directing patients to other healthcare institutions.14–24,32–49 Other researchers have similarly shown that the implementation of this type of system often results in a reduction in length of stay in order to cut costs and improve hospital efficiency.54,59–61 In a two-year study conducted in the UK, Farrar et al. found that the length of stay among patients with pelvic fractures increased following implementation of a DRG-based reimbursement mechanism.62 Likewise, the implementation of such mechanisms have resulted in increased rates of early discharge and subsequent emergency visits.54,63–65 However, others noted no significant differences in readmission, mortality and admission rates following implementation of the system.60,66,67 It is as yet unfeasible to conclude that DRG- based reimbursement mechanisms are directly linked to substantial changes in quality of care for various reasons. First, none of the studies included in the present review could unequivocally attribute care outcomes to the implementation of the system, particularly since long-term effects can only be determined over years or even decades. Therefore, continuous quality monitoring is crucial at all hospitals. Second, while certain measurable clinical indicators like mortality and infection rates are important indicators of quality of care, other indirect factors also play a large role, including determinants of nursing care, interaction time between patients and physicians and the level of training received by healthcare professionals. Third, observed changes in the quality of care may not be explicitly related to the reimbursement mechanism in question, but to other factors, such as competition between hospitals or increased transparency. This research was subject to several limitations. First, the full text of some articles was not available due to the date of publication; furthermore, several more recent articles available on this topic were published in languages other than English. Second, the majority of the included studies were from high-income countries; therefore, developing countries were not adequately represented, a fact which may limit the generalisability of the results. Third, the number of search terms and databases may not have been sufficiently Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review 268 | SQU Medical Journal, August 2020, Volume 20, Issue 3 comprehensive to retrieve all relevant articles on this topic. Finally, most studies retrieved during the literature search reported both positive and adverse outcomes of DRG-based reimbursement mechanisms, with few focusing on administrative challenges. Future research is recommended to evaluate administrative challenges generated by the implementation of DRG- based reimbursement mechanisms, especially with regards to leadership. Conclusion Reimbursement mechanisms based on the DRG classification system are gradually replacing fee-for- service systems in many countries. However, the implementation of such mechanisms can face certain challenges, such as a lack of familiarity with the system among physicians, poor medical recordkeeping and issues with data coding. Recommended solutions include revising DRG classifications based on disease complexity, severity and complications and the number and type of illnesses, establishing new DRGs for patients with severe diseases, establishing moderators for vulnerable patient groups and incorporating an increased budget for particularly unusual or complex cases. Moreover, hospitals should implement extensive training at different levels, ensure effective communication with physicians and develop standard protocols for clinical decision-making. a c k n o w l e d g e m e n t s The preliminary version of this research was submitted as part of a PhD thesis in the field of healthcare management at the Kerman University of Medical Sciences, Kerman, Iran, in 2017. c o n f l i c t o f i n t e r e s t The authors declare no conflicts of interest. f u n d i n g This research was funded with the aid of a grant from the Kerman University of Medical Sciences (grant #96000524). References 1. Witter S, Ensor T, Jowett M, Thompson R. Health Economics for Developing Countries: A practical guide. London, UK: MacMillan Education, 2000. 2. Fetter RB. Diagnosis related groups: Understanding hospital performance. Interfaces (Providence) 1991; 21:6–26. https:// doi.org/10.1287/inte.21.1.6. 3. Wiley M. From the origins of DRGs to their implementation in Europe. In: Busse R, Geissler A, Quentin W, Wiley M, Eds. Diagnosis-Related Groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Berkshire, UK: Open University Press, 2011. Pp. 3–7. 4. Or Z, Häkkinen U. DRGs and quality: For better or worse? In: Busse R, Geissler A, Quentin W, Wiley M, Eds. Diagnosis- Related Groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Berkshire, UK: Open University Press, 2011. Pp. 141–55. 5. Quentin W, Scheller-Kreinsen D, Blümel M, Geissler A, Busse R. Hospital payment based on diagnosis-related groups differs in Europe and holds lessons for the United States. Health Aff (Millwood) 2013; 32:713–23. https://doi.org/10.1377/hlthaff.20 12.0876. 6. Tan SS, Serdén L, Geissler A, Van Ineveld M, Redekop K, Heurgren M, et al. DRGs and cost accounting: Which is driving which? In: Busse R, Geissler A, Quentin W, Wiley M, Eds. Diagnosis-Related Groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Berkshire, UK: Open University Press, 2011. Pp. 85–100. 7. Wild V, Carina F, Frouzakis R, Clarinval C, Fässler M, Elger B, et al. Assessing the impact of DRGs on patient care and prof- essional practice in Switzerland (IDoC): A potential model for monitoring and evaluating healthcare reform. Swiss Med Wkly 2015; 145:w14034. https://doi.org/10.4414/smw.2015.14034. 8. Langenbrunner JC, Cashin CS, O’Dougherty S. Designing and implementing health care provider payment systems: How-to manuals. Washington DC, USA: World Bank, 2009. 9. Fourie C, Biller-Andorno N, Wild V. Systematically evaluating the impact of diagnosis-related groups (DRGs) on health care delivery: A matrix of ethical implications. Health Policy 2014; 115:157–64. https://doi.org/10.1016/j.healthpol.2013.11.014. 10. Koné I, Maria Zimmermann B, Nordström K, Simone Elger B, Wangmo T. A scoping review of empirical evidence on the impacts of the DRG introduction in Germany and Switzerland. Int J Health Plann Manage 2019; 34:56–70. https://doi.org/10.1002/ hpm.2669. 11. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta- analyses: The PRISMA statement. BMJ 2009; 339:b2535. https://doi.org/10.1136/bmj.b2535. 12. Kmet LM, Lee RC, Cook LS. Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Edmonton, Canada: Alberta Heritage Foundation for Medical Research, 2004. 13. Beaumaster S. Information technology implementation issues: An analysis. Ph.D. Thesis, 1999, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. 14. Busato A, von Below G. The implementation of DRG-based hospital reimbursement in Switzerland: A population-based perspective. Health Res Policy Syst 2010; 8:31. https://doi. org/10.1186/1478-4505-8-31. 15. Rogers WH, Draper D, Kahn KL, Keeler EB, Rubenstein LV, Kosecoff J, et al. Quality of care before and after implementation of the DRG-based prospective payment system: A summary of effects. JAMA 1990; 264:1989–94. https://doi.org/10.1001/ jama.1990.03450150089037. 16. Vulgaropulos SP, Lyle CB, Sessions JT. Potential economic impact of applying DRG-based prospective payment categories to inflammatory bowel disease patients. Dig Dis Sci 1990; 35:577–81. https://doi.org/10.1007/BF01540404. 17. Evans RL, Halar EM, Hendricks RD, Lawrence KV, Kirk C, Bishop DS. Effects of prospective payment financing on rehabilitation outcome. Int J Rehabil Res 1990; 13:27–35. https://doi.org/10.1097/00004356-199003000-00003. https://doi.org/10.1287/inte.21.1.6 https://doi.org/10.1287/inte.21.1.6 https://doi.org/10.1377/hlthaff.2012.0876 https://doi.org/10.1377/hlthaff.2012.0876 https://doi.org/10.4414/smw.2015.14034 https://doi.org/10.1016/j.healthpol.2013.11.014 https://doi.org/10.1002/hpm.2669 https://doi.org/10.1002/hpm.2669 https://doi.org/10.1136/bmj.b2535 https://doi.org/10.1186/1478-4505-8-31 https://doi.org/10.1186/1478-4505-8-31 https://doi.org/10.1001/jama.1990.03450150089037 https://doi.org/10.1001/jama.1990.03450150089037 https://doi.org/10.1007/BF01540404 https://doi.org/10.1097/00004356-199003000-00003 Mohsen Barouni, Leila Ahmadian, Hossein Saberi Anari and Elham Mohsenbeigi Review | 269 18. Goldberg SC, Estes CL. Medicare DRGs and post-hospital care for the elderly: Does out of the hospital mean out of luck? J Appl Gerontol 1990; 9:20–35. https://doi.org/10.11 77/073346489000900103. 19. Tresch DD, Duthie EH Jr, Newton M, Bodin B. Coping with diagnosis related groups: The changing role of the nursing home. Arch Intern Med 1988; 148:1393–6. https://doi.org/10.1 001/archinte.1988.00380060157028. 20. Lyles YM. Impact of Medicare diagnosis-related groups (DRGs) on nursing homes in the Portland, Oregon Metropolitan Area. J Am Geriatr Soc 1986; 34:573–8. https://doi.org/10.1111/j.153 2-5415.1986.tb05762.x. 21. Hurley J, Linz D, Swint E. Assessing the effects of the Medicare prospective payment system on the demand for VA inpatient services: An examination of transfers and discharges of problem patients. Health Serv Res 1990; 25:239–55. 22. Menke TJ, Ashton CM, Petersen NJ, Wolinsky FD. Impact of an all-inclusive diagnosis-related group payment system on inpatient utilization. Med Care 1998; 36:1126–37. https://doi. org/10.1097/00005650-199808000-00003. 23. Gay EG, Kronenfeld JJ. Regulation, retrenchment--The DRG experience: Problems from changing reimbursement practice. Soc Sci Med 1990; 31:1103–18. https://doi.org/10.1016/0277- 9536(90)90232-h. 24. Morrisey MA, Sloan FA, Valvona J. Medicare prospective pay- ment and posthospital transfers to subacute care. Med Care 1988; 26:685–98. https://doi.org/10.1097/00005650-19880700 0-00004. 25. Sodzi-Tettey S, Aikins M, Awoonor-Williams JK, Agyepong IA. Challenges in provider payment under the Ghana National Health Insurance Scheme: A case study of claims management in two districts. Ghana Med J 2012; 46:189–99. 26. Roeder N, Rochell B, Juhra C, Mueller M. Empirical comparison of DRG variants using cardiovascular surgery data: Initial results of a project at 18 German hospitals. Aust Health Rev 2001; 24:57–80. https://doi.org/10.1071/ah010057. 27. Sanderson HF, Storey A, Morris D, McNay RA, Robson MP, Loeb J. Evaluation of diagnosis-related groups in the National Health Service. Community Med 1989; 11:269–78. 28. Horn SD, Bulkley G, Sharkey PD, Chambers AF, Horn RA, Schramm CJ. Interhospital differences in severity of illness. Problems for prospective payment based on diagnosis-related groups (DRGs). N Engl J Med 1985; 313:20–4. https://doi. org/10.1056/NEJM198507043130105. 29. Notman M, Howe KR, Rittenberg W, Bridgham R, Holmes MM, Rovner DR. Social policy and professional self-interest: Phy- sician responses to DRGs. Soc Sci Med 1987; 25:1259–67. https://doi.org/10.1016/0277-9536(87)90124-9. 30. Bray N, Carter C, Dobson A, Watt JM, Shortell S. An examination of winners and losers under Medicare’s prospective payment system. Health Care Manage Rev 1994; 19:44–55. https://doi. org/10.1097/00004010-199424000-00007. 31. Bredenberg PA, Lagoe RJ. Mastectomies for malignancy: A DRG-based hospital utilization analysis. J Surg Oncol 1987; 35:19–23. https://doi.org/10.1002/jso.2930350105. 32. Zhan C, Elixhauser A, Friedman B, Houchens R, Chiang YP. Modifying DRG-PPS to include only diagnoses present on admi- ssion: Financial implications and challenges. Med Care 2007; 45:288–91. https://doi.org/10.1097/01.mlr.0000256969.34461.cf. 33. Wisensale SK, Waldron RJ. Applying the family impact statement to DRGs: Implications for future policymaking. Lifestyles 1991; 12:89–102. https://doi.org/10.1007/BF00987299. 34. Muñoz E, Luber J, Birnbaum E, Mulloy K, Cohen JR, Wise L. Hospital costs and resource characteristics for cardiothoracic surgical hospital deaths. Ann Thorac Surg 1989; 47:735–40. https://doi.org/10.1016/0003-4975(89)90129-x. 35. Muñoz E, Angus G, Calabro S, Mulloy K, Wise L. DRGs, costs, and outcome for plastic surgical patients. Plast Reconstr Surg 1988; 82:116–24. https://doi.org/10.1097/00006534-198882010-00021. 36. Zwanziger J, Davis L, Bamezai A, Hosek SD. Using DRGs to pay for inpatient substance abuse services: An assessment of the CHAMPUS reimbursement system. Med Care 1991; 29:565–77. https://doi.org/10.1097/00005650-199106000-00015. 37. Vollertsen RS, Nobrega FT, Michet CJ Jr, Hanson TJ, Naessens JM. Economic outcome under Medicare prospective payment at a tertiary-care institution: The effects of demographic, clinical, and logistic factors on duration of hospital stay and part A charges for medical back problems (DRG 243). Mayo Clin Proc 1988; 63:583–91. https://doi.org/10.1016/s0025-6196(12)64888-5. 38. Horn SD, Horn RA, Sharkey PD, Beall RJ, Hoff JS, Rosenstein BJ. Misclassification problems in diagnosis-related groups: Cystic fibrosis as an example. N Engl J Med 1986; 314:484–7. https:// doi.org/10.1056/NEJM198602203140805. 39. Thomas F, Clemmer TP, Larsen KG, Menlove RL, Orme JF Jr, Christison EA. The economic impact of DRG payment policies on air-evacuated trauma patients. J Trauma 1988; 28:446–52. https://doi.org/10.1097/00005373-198804000-00005. 40. Pasternak LR, Dean JM, Gioia FR, Rogers MC. Lack of validity of diagnosis-related group payment systems in an intensive care population. J Pediatr 1986; 108:784–9. https://doi.org/10.1016/ s0022-3476(86)81069-1. 41. Bull MJ. Influence of diagnosis-related groups on discharge planning, professional practice, and patient care. J Prof Nurs 1988; 4:415–21. https://doi.org/10.1016/s8755-7223(88)80092-9. 42. Joy SA, Yurt RW. An all-payor prospective payment system (PPS) based on diagnosis-related-groups (DRG): Financial imp- act on reimbursement for trauma care and approaches to mini- mizing loss. J Trauma 1990; 30:866–73. https://doi.org/10.10 97/00005373-199007000-00017. 43. Muñoz E, Rosner F, Chalfin D, Goldstein J, Margolis IB, Wise L. Financial risk and hospital cost for elderly patients: Age- and non-age-stratified medical diagnosis related groups. Arch Intern Med 1988; 148:909–12. https://doi.org/10.1001/archi nte.1988.00380040149021. 44. Munoz E, Barrios E, Johnson H, Goldstein J, Mulloy K, Chalfin D, et al. Pediatric patients, race, and DRG prospective hospital pay- ment. Am J Dis Child 1989; 143:612–16. https://doi.org/10.100 1/archpedi.1989.02150170114035. 45. Munoz E, Lory M, Josephson J, Goldstein J, Brewster J, Wise L. Pediatric patients, DRG hospital payment, and comorbidities. J Pediatr 1989; 115:545–8. https://doi.org/10.1016/s0022-3476 (89)80278-1. 46. Muñoz E, Wilkins S, Mallet E, Goldstein J, Sterman H, Wise L. Financial risk and hospital cost for elderly patients in non-age stratified urology DRGs. Urology 1989; 33:445–8. https://doi. org/10.1016/0090-4295(89)90048-4. 47. Hensen P, Fürstenberg T, Luger TA, Steinhoff M, Roeder N. Case mix measures and diagnosis-related groups: Opportunities and threats for inpatient dermatology. J Eur Acad Dermatol Venereol 2005; 19:582–8. https://doi.org/10.1111/j.1468-3083.2 005.01258.x. 48. Patel K. Physicians and DRGs: Hospital management alter- natives. Eval Health Prof 1988; 11:487–505. https://doi.org/10.1 177/016327878801100405. 49. Wolfe BL, Detmer DE. Diagnosis related groups (DRGs): Efficiency and/or quality producing? Some evidence from surgical patients. Health Serv Manag Res 1988; 1:19–28. https://doi.org/10.1177/095148488800100103. 50. Turner-Stokes L, Sutch S, Dredge R, Eagar K. International casemix and funding models: Lessons for rehabilitation. Clin Rehabil 2012; 26:195–208. https://doi.org/10.1177/0269215511417468. https://doi.org/10.1177/073346489000900103 https://doi.org/10.1177/073346489000900103 https://doi.org/10.1001/archinte.1988.00380060157028 https://doi.org/10.1001/archinte.1988.00380060157028 https://doi.org/10.1111/j.1532-5415.1986.tb05762.x https://doi.org/10.1111/j.1532-5415.1986.tb05762.x https://doi.org/10.1097/00005650-199808000-00003 https://doi.org/10.1097/00005650-199808000-00003 https://doi.org/10.1016/0277-9536%2890%2990232-h https://doi.org/10.1016/0277-9536%2890%2990232-h https://doi.org/10.1097/00005650-198807000-00004 https://doi.org/10.1097/00005650-198807000-00004 https://doi.org/10.1071/ah010057 https://doi.org/10.1056/NEJM198507043130105 https://doi.org/10.1056/NEJM198507043130105 https://doi.org/10.1016/0277-9536%2887%2990124-9 https://doi.org/10.1097/00004010-199424000-00007 https://doi.org/10.1097/00004010-199424000-00007 https://doi.org/10.1002/jso.2930350105 https://doi.org/10.1097/01.mlr.0000256969.34461.cf https://doi.org/10.1007/BF00987299 https://doi.org/10.1016/0003-4975%2889%2990129-x https://doi.org/10.1097/00006534-198882010-00021 https://doi.org/10.1097/00005650-199106000-00015 https://doi.org/10.1016/s0025-6196%2812%2964888-5 https://doi.org/10.1056/NEJM198602203140805 https://doi.org/10.1056/NEJM198602203140805 https://doi.org/10.1097/00005373-198804000-00005 https://doi.org/10.1016/s0022-3476%2886%2981069-1 https://doi.org/10.1016/s0022-3476%2886%2981069-1 https://doi.org/10.1016/s8755-7223%2888%2980092-9 https://doi.org/10.1097/00005373-199007000-00017 https://doi.org/10.1097/00005373-199007000-00017 https://doi.org/10.1001/archinte.1988.00380040149021 https://doi.org/10.1001/archinte.1988.00380040149021 https://doi.org/10.1001/archpedi.1989.02150170114035 https://doi.org/10.1001/archpedi.1989.02150170114035 https://doi.org/10.1016/s0022-3476%2889%2980278-1 https://doi.org/10.1016/s0022-3476%2889%2980278-1 https://doi.org/10.1016/0090-4295%2889%2990048-4 https://doi.org/10.1016/0090-4295%2889%2990048-4 https://doi.org/10.1111/j.1468-3083.2005.01258.x https://doi.org/10.1111/j.1468-3083.2005.01258.x https://doi.org/10.1177/016327878801100405 https://doi.org/10.1177/016327878801100405 https://doi.org/10.1177/095148488800100103 https://doi.org/10.1177/0269215511417468 Challenges and Adverse Outcomes of Implementing Reimbursement Mechanisms Based on the Diagnosis-Related Group Classification System A systematic review 270 | SQU Medical Journal, August 2020, Volume 20, Issue 3 51. Tan SS, Chiarello P, Quentin W. Knee replacement and diag- nosis-related groups (DRGs): Patient classification and hospital reimbursement in 11 European countries. Knee Surg Sports Traumatol Arthrosc 2013; 21:2548–56. https://doi.org/10.1007/ s00167-013-2374-6. 52. Lüthi HJ, Widmer PK. DRG system design: A financial risk perspective. Oper Res Health Care 2017; 13–14:23–32. https:// doi.org/10.1016/j.orhc.2017.03.002. 53. Leister JE, Stausberg J. Comparison of cost accounting methods from different DRG systems and their effect on health care quality. Health Policy 2005; 74:46–55. https://doi.org/10.1016/j. healthpol.2004.12.001. 54. Gao F. Systematic review of the impacts of diagnosis related groups and the challenges of the implementation in Mainland China. Ph.D. Thesis, 2013, University of Hong Kong, Pokfulam, Hong Kong. 55. Hsia DC, Krushat WM, Fagan AB, Tebbutt JA, Kusserow RP. Accuracy of diagnostic coding for Medicare patients under the prospective-payment system. N Engl J Med 1988; 318:352–5. https://doi.org/10.1056/NEJM198802113180604. 56. Street A, O’Reilly J, Ward P, Mason A. DRG-based hospital payment and efficiency: Theory, evidence, and challenges. In: Busse R, Geissler A, Quentin W, Wiley M, Eds. Diagnosis- Related Groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Berkshire, UK: Open University Press, 2011. Pp. 119–40. 57. Cots F, Chiarello P, Salvador X, Castells X, Quentin W. DRG-based hospital payment: Intended and unintended consequences. In: Busse R, Geissler A, Quentin W, Wiley M, Eds. Diagnosis-Related Groups in Europe: Moving towards transparency, efficiency and quality in hospitals. Berkshire, UK: Open University Press, 2011. Pp. 101–18. 58. Mason A, Street A, Verzulli R. Private sector treatment centres are treating less complex patients than the NHS. J R Soc Med 2010; 103:322–31. https://doi.org/10.1258/jrsm.2010.100044. 59. Schwartz MH, Tartter PI. Decreased length of stay for patients with colorectal cancer: Implications of DRG use. J Healthc Qual 1998; 20:22–5. https://doi.org/10.1111/j.1945-1474.1998. tb00268.x. 60. Cheng SH, Chen CC, Tsai SL. The impacts of DRG-based payments on health care provider behaviors under a universal coverage system: A population-based study. Health Policy 2012; 107:202–8. https://doi.org/10.1016/j.healthpol.2012.03.021. 61. Louis DZ, Yuen EJ, Braga M, Cicchetti A, Rabinowitz C, Laine C, et al. Impact of a DRG-based hospital financing system on quality and outcomes of care in Italy. Health Serv Res 1999; 34:405–15. 62. Farrar S, Yi D, Sutton M, Chalkley M, Sussex J, Scott A. Has payment by results affected the way that English hospitals provide care? Difference-in-differences analysis. BMJ 2009; 339:b3047. https://doi.org/10.1136/bmj.b3047. 63. Castro J, Hector E. Diagnostic related groups (DRGS): Resourceful tools for financial crisis times? Rev Cienc Salud 2011; 9:73–82. 64. McCall N, Korb J, Petersons A, Moore S. Reforming Medicare payment: Early effects of the 1997 Balanced Budget Act on postacute care. Milbank Q 2003; 81:277–303. https://doi. org/10.1111/1468-0009.t01-1-00054. 65. Gillen R, Tennen H, McKee T. The impact of the inpatient rehabilitation facility prospective payment system on stroke program outcomes. Am J Phys Med Rehabil 2007; 86:356–63. https://doi.org/10.1097/PHM.0b013e31804a7e2f. 66. Kahn KL, Keeler EB, Sherwood MJ, Rogers WH, Draper D, Bentow SS, et al. Comparing outcomes of care before and after implementation of the DRG-based prospective payment system. JAMA 1990; 264:1984–8. https://doi.org/10.1001/ jama.1990.03450150084036. 67. Lave JR, Frank RG, Taube C, Goldman H, Rupp A. The early effects of Medicare’s prospective payment system on psychiatry. Inquiry 1988; 25:354–63. https://doi.org/10.1007/s00167-013-2374-6 https://doi.org/10.1007/s00167-013-2374-6 https://doi.org/10.1016/j.orhc.2017.03.002 https://doi.org/10.1016/j.orhc.2017.03.002 https://doi.org/10.1016/j.healthpol.2004.12.001 https://doi.org/10.1016/j.healthpol.2004.12.001 https://doi.org/10.1056/NEJM198802113180604 https://doi.org/10.1258/jrsm.2010.100044 https://doi.org/10.1111/j.1945-1474.1998.tb00268.x https://doi.org/10.1111/j.1945-1474.1998.tb00268.x https://doi.org/10.1016/j.healthpol.2012.03.021 https://doi.org/10.1136/bmj.b3047 https://doi.org/10.1111/1468-0009.t01-1-00054 https://doi.org/10.1111/1468-0009.t01-1-00054 https://doi.org/10.1097/PHM.0b013e31804a7e2f https://doi.org/10.1001/jama.1990.03450150084036 https://doi.org/10.1001/jama.1990.03450150084036