Severity of illness within DRGs: impact on prospective payment.

This study compares the financial impact of a Diagnosis Related Group (DRG) prospective payment system with that of a Severity of Illness-adjusted DRG prospective payment system. The data base of about 106,000 discharges is from 15 hospitals, all of which had a Health Care Financing Administration (HCFA) DRG case mix index greater than 1. In order to pool the data over the 15 hospitals, all charges were converted to costs, normalized to Fiscal Year 1983, and adjusted for medical education and wage levels. The findings showed that, for the study population as a whole, DRGs explained 28 per cent of the variability in resource use per case while Severity of Illness-adjusted DRGs explained 61 per cent of the variability in resource use per case. When we simulated prospective payment systems based on DRGs and on Severity-adjusted DRGs, we found that the financial impact of the two systems differed by very little in some hospitals and by as much as 35 per cent of total operating costs in other hospitals. Thus, even with a data set that is relatively homogeneous (with respect to the HCFA DRG case mix index definition of hospitals), we found substantial inequities in payment when DRGs were not adjusted for Severity of Illness. These findings suggest that, with a more representative set of hospitals, the difference between unadjusted and Severity-adjusted DRG-based prospective payment could be greater than 35 per cent of a hospital's total operating costs.     

Trauma case mix and hospital payment: the potential for refining DRGs.

Uniform hospital discharge abstract data from Maryland were used to examine the homogeneity of trauma-related DRGs with respect to a well-established measure of injury severity, the Injury Severity Score (ISS). Thirty DRGs were identified as including trauma cases with a wide range of severity; for each of these DRGs, ISS explains a significant amount of variation in length of stay. By applying statistical techniques similar to those used to create the original DRG groupings, these 30 DRGs were subdivided by severity and age categories to create a new set of severity-modified DRGs. The potential effects of using DRGs and modified DRGs to pay for inpatient care within the Maryland state regionalized system of trauma care were examined. Payments based on regional averages per DRG and per modified DRG were compared to actual hospital charges regulated by the state's Health Services Cost Review Commission. Using average charges per DRG as a basis of payment, approximately !1.4 million (11 percent of total hospital charges) would be shifted from trauma centers to nontrauma centers. This shift represents an 18 percent loss in revenues to trauma centers and a 30 percent gain in revenues to nontrauma centers. Using a payment system based on severity-modified DRGs, trauma centers would still experience a net loss in revenues and the nontrauma centers a net gain, but the total amount of the shift would be reduced from $11.4 million to $9.8 million. The results argue for the need to explore alternative payment systems not strictly based on current DRGs. Because of DRGs do not adequately reflect severity differences, using them to pay hospitals will create financial incentives that discourage regionalization of trauma care.     

基于DRG的医疗服务质量与绩效评价干预模式研究

目的基于疾病诊断相关组(DRG)的上海市嘉定区某二级综合性医院的医疗服务质量与绩效评价干预模式进行分析,为建立公立医院绩效考核评价机制提供参考依据。方法本组以"DRG住院医疗服务监测与分析系统"等为研究平台,通过在线上报的病案首页信息,对某二级综合性医院2018—2019年基于DRG的住院患者入组病例数、CMI值、DRG组数和总权重等指标进行比较,同时对区域病种难度、区域手术难度以及MDC医疗服务能力、效率和安全进行比较,并从三个维度进行综合分析。结果2018年总病例数12464例,入组病例数12398例,入组率为99.47%;2019年总病例数12301例,入组病例数13037例,入组率为99.51%。其中DRG组数上升了7.94%,CMI值上升了9.64%,呈良好发展态势。产能、效率、安全和综合得分均呈上升趋势,其中安全得分上升了12.66%,综合得分上升了6.12%。MDC医疗服务能力、效率和安全和去年同期相比也呈上升趋势。结论基于DRG的医疗服务绩效评价具有科学性、客观性和可比性的特点,可以帮助医疗机构发现医疗行为存在的问题,有的放矢地进行干预,通过DRGs这个管理工具在费用控制、质量管理、安全控制、学科评估和绩效评价等方面发挥其综合作用。     

One DRG, One Price? The Effect of Patient Condition on Price Variation Within DRGs and Across Hospitals

Costs and prices per patient admission vary greatly across patients and across hospitals. The variance across hospitals is due in part to institutional differences--hospital size, teaching status, local labor costs, and so on--but also to differences in different hospitals' patients' conditions. For purposes of reimbursement under the Medicare program, differences in patients' conditions are typically accounted for by nothing more than noting their different DRGs, without regard to intra-DRG patient differences. My results, which are based on 3.6 million individual patients, show that differences in individual patient DRGs and in observable indicators of their conditions are more than just relevant or important: They are nearly dispositive, explaining over 80% of the total variation in net price per patient admission. Moreover, cross-DRG differences explain only half of that price variation, with the other half explained by patient-level intra-DRG differences in patient condition that are not accounted for by patients' DRG classifications. Further analysis shows that those hospitals that tend to attract the more complex DRGs tend also to attract those patients who are more expensive to treat within each of their DRGs.     

Case mix and charges for inpatient and outpatient chemotherapy.

Case mix and charges for chemotherapy treatment were examined by an analysis of the inpatient discharges for DRG 410 (chemotherapy) from eight teaching hospitals and of outpatient visits from two teaching hospitals. Discharges for ovarian cancer were the most common and the least expensive, costing $1,600 or half as much as the most costly, less common conditions (leukemia and testicle cancer). Diagnosis explained 13 percent of the inpatient charge variation; metastasis explained less than 1 percent. Outpatient chemotherapy overlapped with inpatient among only 3 of the 10 most common diagnoses. The implication is that the two settings are complementary with regard to chemotherapy administration.     

运用DRGs工具对老年医院诊治能力及效率进行评价的探讨

目的 应用DRGs评价系统对老年医院诊治能力及效率进行评价,提升医院的管理水平。方法 以2018年15 096份住院病案首页数据为研究对象,使用“北京版诊断相关组(BJ-DRGs)”作为风险调整工具,从病例组合指数（CMI）、时间消耗指标、费用消耗指标、住院例均费用和医疗安全等方面进行分析,探讨DRGs工具对老年医院诊治能力及效率的评价效果。结果 老年医院MDC为22个,DRGs组数为437组, CMI、时间消耗指数和费用消耗指数分别超过老年病专业和北京市医院平均水平,低风险死亡率为0,中高组和高风险组病例数占比高于全市水平,死亡率低于全市水平。结论 通过DRGs数据分析能够发现老年医院、老年医学专业与综合医院专业科室在收治常见疾病上的差异,优化老年医院资源配置,改进医疗服务质量和水平。建议在使用DRG工具评价老年医学专业时,应考虑老年患者年龄、多病共存等因素影响,完善老年医学专业的医疗效率绩效指标个性化设定。     

Case-mix adjustment using objective measures of severity: the case for laboratory data.

OBJECTIVE. We evaluate the use of routinely gathered laboratory data to subclassify surgical and nonsurgical major diagnostic categories into groups homogeneous with respect to length of stay (LOS). DATA SOURCES AND STUDY SETTING. The source of data is the Combined Patient Experience database (COPE), created by merging data from computerized sources at the University of California San Francisco (UCSF) Medical Center and Stanford University Medical Center for a total sample size of 73,117 patient admissions. STUDY DESIGN. The study is cross-sectional and retrospective. All data were extracted from COPE consecutive admissions; the unit of analysis is an admission. The outcome variable LOS proxies hospital resource utilization for an inpatient stay. Nine (candidate) predictor variables were derived from seven lab tests (WBC, Na, K, C02, BUN, ALB, HCT) by recording the whole-stay minimum or maximum test result. DATA COLLECTION/EXTRACTION METHODS. Patient groups were formed by first assigning to major diagnostic categories (MDCs) all 73,117 admissions. Each MDC was then partitioned into medical and surgical subgroups (sub-MDCs). The 13 sub-MDCs selected for study define a study population of 32,599 patients that represents approximately 45 percent of inpatients. Within each of the 13 sub-MDCs, patients were randomly assigned to one of two data sets in a ratio of 2:1. The first set was used to create, the second to validate, three different LOS predictors. Predictive accuracies of individual DRG classes were compared with those of two alternative classification schemes, one formed by recursive partitioning (the sub-MDC) using only lab test results, the other by partitioning with both lab test results and individual DRGs. PRINCIPAL FINDINGS. For the eight largest sub-MDCs (81 percent of study population), individual DRGs explained 23 percent of the within sub-MDC variance in LOS, laboratory data classes explained 31 percent, and classes derived by considering individual DRGs and laboratory data explained 37 percent. (Each result is a weighted average R2. The average number of LOS classes into which the eight largest sub-MDCs were partitioned were 20, 10, and 10, respectively. Within six of the eight, partitioning on the basis of laboratory data alone explained more within sub-MDC variance than did partitioning into individual DRGs. CONCLUSIONS. Routine lab test data improve the accuracy of LOS prediction over that possible using DRG classes. We note that the improvements do not result from overfitting the data, since the numbers of LOS classes we use to predict LOS are considerably fewer than the numbers of individual DRGs.     

神经系统疾病诊断相关分组研究——以河南省某三甲医院为例

目的 分析神经系统疾病患者的住院费用影响因素,建立该疾病的诊断相关分组（DRGs）模型,为DRGs实施和细化分组提供参考。方法 以河南省某三甲医院2013—2019年43 198例神经系统疾病患者住院病案首页数据为研究对象,分别用非参数检验、人工神经网络进行单因素、多因素分析,用决策树CHAID算法构建分组模型,用变异系数（CV）、ROC曲线和非参数检验对分组结果评价。结果 以是否手术（0.5090）、病例分型（0.2799）、有无其他诊断（0.1702）、入院途径（0.0217）4个重要因素作为分类截点,分成15个DRG组;模型评价结果是ROC曲线下面积均＞0.5,变异系数（CV）最大为0.98, P值均＜0.05,分组效果良好。结论 是否手术、病情危重、有无其他诊断、入院途径是神经系统疾病患者分组的重要因素,人工神经网络和CHAID算法相结合,建立的分组方案合理。     

Time trends in inpatient physician spending.

OBJECTIVE. Despite falling admissions and declining lengths of stay, Medicare expenditures for inpatient physician services have continued to climb; this article seeks to understand this trend by examining the expenditures on a per admission basis. DATA SOURCES AND STUDY SETTING. One hundred percent Medicare claims data were available from nine states for the 1985-1988 time period. STUDY DESIGN. Because Medicare's prospective payment system encourages hospitals to shift some services outside the inpatient setting, we examined trends in episodes of care, encompassing some time both before and after the inpatient stay itself. Trends were also examined at the individual DRG level in order to partially control for case-mix shifts and increased surgical use. Allowed charges were purged of both Medicare fee updates and geographic price variation in order to derive estimates of real spending growth. DATA COLLECTION/EXTRACTION METHODS. Hospital and physician claims were merged to form inpatient episodes that included seven days prior to admission as well as 30 days following discharge. PRINCIPAL FINDINGS. Physician spending per episode increased 27 percent just over this four-year time period, but with considerable variation by DRG ranging from only 2 percent for transurethral prostatectomies (TURPs) to 56 percent for uncomplicated acute myocardial infarctions (AMIs). Changes in case severity and hospital and physician characteristics were all found to be important contributors to the increase in physician inpatient spending. Most important seemed to be the growth in the number of physicians associated with the inpatient stay (and the subsequent increase in diagnostic tests and other procedures). CONCLUSIONS. The findings suggest that control of technology and control of the number of physicians involved in the care of a patient are both critical to constraining the rate of increase in physician inpatient expenditures.     

Cost-variance analysis by DRGs; a technique for clinical budget analysis

In this article it is shown how a cost accounting system based on DRGs can be valuable in determining changes in clinical practice and explaining alterations in expenditure patterns from one period to another. A cost-variance analysis is performed using data from the orthopedic department from the fiscal years 1993 and 1994. Differences between predicted and observed cost for medical care, such as diagnostic procedures, therapeutic procedures and nursing care are analyzed into different components: changes in patient volume, case-mix differences, changes in resource use and variations in cost per procedure. Using a DRG cost accounting system proved to be a useful technique for clinical budget analysis. Results may stimulate discussions between hospital managers and medical professionals to explain cost variations integrating medical and economic aspects of clinical health care.     

Diagnosis related groups (DRGs): efficiency and/or quality producing? Some evidence from surgical patients.

Hospital charges and length of stay for inguinal hernia and acute appendicitis patients were examined in a university hospital to determine the degree of variation with DRGs. Evidence presented here suggests that DRGs may lead to a reduction in medical care costs without a reduction in patient outcomes. Mode/year DRGs to take account of source of admission and maintaining outliers payments may be desirable to avoid patient selectivity and incentives for lowering quality of care of the most severely ill patients.     

Hospital costs estimation and prediction as a function of patient and admission characteristics

The present work analyzed the association between hospital costs and patient admission characteristics in a general public hospital in the city of Rio de Janeiro, Brazil. The unit costs method was used to estimate inpatient day costs associated to specific hospital clinics. With this aim, three "cost centers" were defined in order to group direct and indirect expenses pertaining to the clinics. After the costs were estimated, a standard linear regression model was developed for correlating cost units and their putative predictors (the patients gender and age, the admission type (urgency/elective), ICU admission (yes/no), blood transfusion (yes/no), the admission outcome (death/no death), the complexity of the medical procedures performed, and a risk-adjustment index). Data were collected for 3100 patients, January 2001-January 2003. Average inpatient costs across clinics ranged from (US$) 1135 [Orthopedics] to 3101 [Cardiology]. Costs increased according to increases in the risk-adjustment index in all clinics, and the index was statistically significant in all clinics except Urology, General surgery, and Clinical medicine. The occupation rate was inversely correlated to costs, and age had no association with costs. The (adjusted) per cent of explained variance varied between 36.3% [Clinical medicine] and 55.1% [Thoracic surgery clinic]. The estimates are an important step towards the standardization of hospital costs calculation, especially for countries that lack formal hospital accounting systems.     

Investigating DRG cost weights for hospitals in middle income countries

Identifying the cost of hospital outputs, particularly acute inpatients measured by Diagnosis Related Groups (DRGs), is an important component of casemix implementation. Measuring the relative costliness of specific DRGs is useful for a wide range of policy and planning applications. Estimating the relative use of resources per DRG can be done through different costing approaches depending on availability of information and time and budget. This study aims to guide costing efforts in Iran and other countries in the region that are pursuing casemix funding, through identifying the main issues facing cost finding approaches and introducing the costing models compatible with their hospitals accounting and management structures. The results show that inadequate financial and utilisation information at the patient's level, poorly computerized 'feeder systems'; and low quality data make it impossible to estimate reliable DRGs costs through clinical costing. A cost modelling approach estimates the average cost of 2.723 million Rials (Iranian Currency) per DRG. Using standard linear regression, a coefficient of 0.14 (CI = 0.12-0.16) suggests that the average cost weight increases by 14% for every one-day increase in average length of stay (LOS).We concluded that calculation of DRG cost weights (CWs) using Australian service weights provides a sensible starting place for DRG-based hospital management; but restructuring hospital accounting systems, designing computerized feeder systems, using appropriate software, and development of national service weights that reflect local practice patterns will enhance the accuracy of DRG CWs.     

What accounts for the regional differences in the utilisation of hospitals in Germany?

There are huge regional variations in the utilisation of hospital services in Germany. In 2007 and 2008 the states of Hamburg and Baden-Württemberg had on average just under 38 % fewer hospitalisations per capita than Saxony-Anhalt. We use data from the DRG statistics aggregated at the county level in combination with numerous other data sources (e.g. INKAR Database, accounting data from the National Association of Statutory Health Insurance Physicians (KBV), Federal Medical Registry, Germany Hospital Directory, population structure per county) to establish the proportion of the observed regional differences that can be explained at county and state levels. Overall we are able to account for 73 % of the variation at state level in terms of observable factors. By far the most important reason for the regional variation in the utilisation of in-patient services is differences in medical needs. Differences in the supply of medical services and the substitutability of outpatient and inpatient treatment are also relevant, but to a lesser extent.     

Predicting the cost of hospital stay for stroke patients: the use of diagnosis related groups

In order to provide tailor-made care, governments are considering the implementation of output-pricing based on hospital case-mix measures, such as diagnosis related groups (DRG). The question is whether the current DRG classification system can provide a satisfactory prediction of the variance of costs in stroke patients and if not, in what way other variables may enhance this prediction. In this study, data from 731 stroke patients hospitalized at University Hospital Maastricht during 1996-1998 are used in the cost analysis. The DRG classification for this group uses information--in addition to the DRG classification operation or no operation--on the patient's age combined with discharge status. The results of regression analysis show that using DRGs, the variance explained in the costs amounts to 34%. Adding other variables to the DRGs, the variance explained increases to about 61%. Additional factors highly correlating with inpatient costs are the level of functioning after stroke, comorbidity, complications, and 'days of stay for non-medical reasons'. Costs decreased for stroke patients discharged during the latter part of the years studied, and if stroke patients happened to die during their hospital stay. The results do suggest that future implementation of output-pricing based on the DRG case-mix measures is feasible for stroke patients only if it is enhanced with information on complications and the level of functioning.     

How well do diagnosis-related groups for appendectomy explain variations in resource use? An analysis of patient-level data from 10 European countries

Appendectomy is a common and relatively simple procedure to remove an inflamed appendix, but the rate of appendectomy varies widely across Europe. This paper investigates factors that explain differences in resource use for appendectomy. We analysed 106,929 appendectomy patients treated in 939 hospitals in 10 European countries. In stage 1, we tested the performance of three models in explaining variation in the (log of) cost of the inpatient stay (seven countries) or length of stay (three countries). The first model used only the diagnosis-related groups (DRGs) to which patients were coded, the second model used a core set of general patient-level and appendectomy-specific variables, and the third model combined both sets of variables. In stage two, we investigated hospital-level variation. In classifying appendectomy patients, most DRG systems take account of complex diagnoses and comorbidities but use different numbers of DRGs (range: 2 to 8). The capacity of DRGs and patient-level variables to explain patient-level cost variation ranges from 34% in Spain to over 60% in England and France. All DRG systems can make better use of administrative data such as the patient's age, diagnoses and procedures, and all countries have outlying hospitals that could improve their management of resources for appendectomy.     

Predicting length of stay for Medicare patients at a teaching hospital.

This research examines how the patients' characteristics and clinical indicators affect length of stay for the top five Diagnosis-Related-Groups (DRGs) for Medicare patients at a teaching hospital in the United States. The top DRGs were selected on the basis of volume per year. Teaching hospitals in the United States devote a significant amount of their resources to research and teaching, while providing treatment for patients. The ability to predict length of stay can substantially improve a teaching hospital's capacity utilization, while ensuring that resources are available to meet the health care needs of the Medicare population. Multiple regression models are developed to predict the length of stay using the patients' characteristics and clinical indicators as independent variables. The results indicate that approximately 60 percent (R(2)) of the variance in the length of stay is explained by the patients' characteristics and clinical indicators for these DRGs. The Mortality and Severity indices are found to be the strongest predictors for length of stay in all DRGs. Other patients' characteristics and clinical indicators such as age, gender, race/ethnicity, marital status, admission type and admission source are also significant predictors for some DRGs. In addition, most of these variables affect the length of stay in the same manner as shown in previous studies, even though the previous studies do not have the DRG specificity of this study.     

DRG calculation and utilization patterns: a review of method and policy

This paper examines methodological and policy issues of interest to medical geographers who use diagnosis-related groups (DRGs) in their research. Methodological issues are studied in terms of the calculation of DRGs and variation in the utilization of surgical and medical DRGs. It is argued that a shift to a single DRG price system should first address the (i) regional disparities that currently exist and the need for large-scale indices of medical wages and labor costs; (ii) severity of illness measurements other than the present nominal ones; and (iii) wide variation among medical versus surgical procedures. The Department of Commerce's Economic Analysis Area is recommended to remedy the problem of geographic scale. Policy issues of interest to medical geographers center around the shift to greater hospital specialization which is likely to continue across the country. Inner-city, rural and teaching hospitals may continue to be inadequately reimbursed by DRGs, treat more medically indigent, or both. Medical geographers should be aware of the policy and methodological issues involved not only in DRGs, but in proposed prospective payment systems for ambulatory and long-term care.