Predicting charges for inpatient medical rehabilitation using severity, DRG, age, and function.

We examined the effectiveness of using diagnosis related groups (DRGs), Severity of Illness Index (SII), age and function at admission to predict inpatient charges for medical rehabilitation. Data from our sample of 199 indicate that DRGs alone explained approximately 12 per cent of the variation in charges for inpatient rehabilitation while SII explained 26 per cent of the variation. SII, DRG, and age together yielded the highest regression coefficient, accounting for nearly 39 per cent of the variation in total charges; SII and age accounted for 36 per cent of the variation. Within DRG categories, SII was the only important predictor of inpatient charges accounting for 23 per cent of the variation in charges among stroke patients (DRG 014) and 28 per cent of the variation in charges among hip fracture patients (DRG 210). Function at admission was not a useful predictor of inpatient rehabilitation charges within DRGs. These results suggest that SII and age may be useful in developing a DRG-based prospective payment system for inpatient medical rehabilitation.     

Could distance be a proxy for severity-of-illness? A comparison of hospital costs in distant and local patients.

OBJECTIVE. We test the hypothesis that hospital costs, after adjusting for DRG mix, are higher in distant patients than in local patients. DATA SOURCES AND STUDY SETTING. Data were obtained from the Washington State Commission Hospital Abstract Reporting System (CHARS) and included all patients discharged from 15 metropolitan hospitals in the state of Washington during fiscal year 1987 (N = 181,072). STUDY DESIGN. Distant patients were initially defined as those patients residing outside a 15-mile radius of the hospital from which they were discharged; all other patients were considered local. Distance was determined using the patient's residence zip code. Hospital charge, calculated for all patients regardless of payer, served as a proxy for cost and was adjusted using the DRG weight. PRINCIPAL FINDINGS. Average charge (adjusted for DRG weight) was higher for distant patients in all but two hospitals. Overall adjusted charge for distant patients was 15 percent higher (p < .001). This finding persisted when different distances were used to dichotomize distant and local patients. When the 20 most common DRGs were examined individually, little charge difference was found in surgical DRGs that require tertiary center services (tertiary DRGs) and in those DRGs with both moderate and predictable resource use (routine DRGs); the charge difference seemed most prominent in those DRGs with a wide array of possible resource use (heterogeneous DRGs). CONCLUSIONS. Results suggest that patients traveling long distances use more resources and incur higher hospital charges than local patients. This is not accounted for in prospective payment. We postulate that distance might serve in part as a proxy for severity-of-illness.     

A study of the relationship between severity of illness and hospital cost in New Jersey hospitals.

In response to concerns over the equity of diagnosis-related group (DRG)-based prospective payment, the New Jersey Department of Health conducted a Severity of Illness evaluation study in which severity of illness, DRG, and uniform cost information were collected for 76,798 patients in 25 hospitals. Severity of illness was measured using the Computerized Severity Index (CSI) and was found to be a significant determinant of hospital cost in 76 DRGs that accounted for 41.4 percent of the total direct hospital patient care costs and 27 percent of the patients. The addition of CSI severity levels to the 76 DRGs reduced the coefficient of variation of cost in these DRGs by 17.4 percent and improved the overall reduction in variance of cost within the 76 DRGs by 38.2 percent. The change in total hospital payments due to the addition of severity for the 76 DRGs varied from a positive 5.71 percent to a negative 5.48 percent. These results demonstrate that a severity adjustment to this subset of DRGs would result in a more equitable DRG-based prospective payment system.     

An evaluation of diagnosis-related group severity and complexity refinement

In 1988, an ambitious and extensive project was undertaken in New Jersey to evaluate severity class adjustment of the all-payer prospective payment system. Another project objective was to evaluate alternative strategies for refining diagnosis-related groups (DRGs). The evaluation presented here includes a comparison of DRG refinement using Computerized Severity Index classes and Yale University complexity classes. Statistical methods and payment simulations are used to assess the impact of DRG refinement and consequent revenue changes. When a high volume subset of DRGs is refined, simulated payment shifts between hospitals on the order of 5 percent of total hospital costs are indicated by this analysis.     

A comparison of the resource intensity of inpatients in urban and rural nonteaching hospitals

PL 98-21 mandated a prospective payment system based on diagnosis related groups (DRGs) for all Medicare inpatients. The predetermined payment for each DRG is intended to reflect the resources used to treat patients within the DRG. Eventually, the system will allow for one payment level for each DRG in rural hospitals and a higher payment level for the same DRG in urban hospitals. This represents an equitable approach, provided there is not a predominance of high severity cases in rural hospitals and that higher costs in urban hospitals are reflective of higher priced exogenous factors beyond the control of the hospital. Equitability also requires that DRGs capture the resource intensity of treatment for a given classification of patients, equally for urban and rural patients. This work compares the pediatric population of urban hospitals without a pediatric residency program with that of rural hospitals in terms of major diagnostic category, DRG, disease severity, length of stay, and charges. It also compares the capacity of DRGs to explain the variation in resource consumption in urban and rural hospitals. A sample of 116,721 discharges from 130 urban hospitals and a sample of 54,073 discharges from 97 rural hospitals are used in this work. The results indicate that there is no difference in the patient populations of these two hospital groups. The results also indicate that DRGs explain only 50 percent of the variance in the resource variables, but this obtains equally for both populations.     

美国诊断相关组的引进

诊断相关组是美国医疗保险医院补偿系统预付费的依据,目的是将医院的病例组合与所需的资源和花费相联系.各组的定义与划分应有共同的组织系统或病因学,且有共同的临床特性又有相近的资源消耗.根据主要诊断、主要手术、重要的合并症和并发症、年龄(以17岁区别成年人和未成年人)、性别、新生儿体重等进行分组.按照美国第18版分组定义编制程序,对北京二级以上医院病案首页数据进行分组,根据分组情况、分组的合理性及各组的权重分析,采用美国的分组结构是可行的,但应根据我国情况进行适当的变更.     

Are rural referral centers as costly as urban hospitals?

This article evaluates the claim that rural referral centers (RRCs), identified by HCFA criteria for special treatment under Medicare's prospective payment system, have average costs similar to urban hospitals. Multivariate analysis led us to conclude that RRC Medicare costs were 13 percent higher than those of other rural hospitals in 1984, holding constant Medicare case mix, teaching activity, and relative wages. However, RRCs were 9 percent ($200) less costly per case than urban hospitals. Outliers explained most of the cost difference between RRCs and urban hospitals, while transfers were more important in explaining differences between RRCs and other rural hospitals. Given that bed size alone explained all of the RRC-other rural cost difference, paying RRCs the urban rate results in an indirect way of paying them based on bed size. It also gives them an average excess of payment over Medicare cost well above the national rural and urban average.     

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.     

Refinement of the Medicare diagnosis-related groups to incorporate a measure of severity

This article presents a system under consideration by the Health Care Financing Administration (HCFA) for incorporating a measure of severity of illness into the Medicare diagnosis-related groups (DRGs). DRG assignment is one of the main factors in determining the payment made for hospital inpatient services furnished to Medicare beneficiaries. Specifically, the formula used to calculate payment for a single Medicare hospital inpatient case takes an average payment rate for a typical case and multiplies it by the relative weight of the DRG to which it is assigned. Thus, it is easy to see that the DRG relative weights have a large impact on the payment a hospital receives. In this article, we describe the Medicare DRG prospective payment system (PPS), evaluate the various classification elements available for assessing severity of illness, describe the analyses used in formulating this proposal, and present the proposed DRG severity system.     

Description of case-mix adjusters by the Severity of Illness Working Group of the Society of Hospital Epidemiologists of America (SHEA)

Hospitals, insurance companies, and federal and state governments are increasingly concerned about reducing patient cost expenditures while maintaining high quality patient care. One method of reducing expenditures has been to tie hospital reimbursement with a prospective payment system based on diagnosis-related groups (DRGs). However, reimbursement under the DRG system is not acceptable for all patients in all hospitals because it is neither an accurate predictor of costs nor of clinical outcome. This deficiency poses significant problems for hospitals because DRGs are used nationwide as the prospective payment system for inpatients covered by Medicare. Several case-mix adjusters have been proposed to modify DRGs to improve their accuracy in predicting costs and outcome. We reviewed five of the most widely available indices: Acute Physiologic and Chronic Health Evaluation (APACHE II), Coded Disease Staging, Computerized Severity Index (CSI), Medical Illness Severity Group System (MEDISGROUPS), and Patient Management Categories (PMC). Recommendations for the use of a single case-mix adjuster cannot be made at this time because all indices have not been compared in sufficiently diverse settings and because some are better predictors of costs while others are better predictors of clinical outcome. Hospital epidemiologists and other infection control practitioners should be informed about these indices and their potential applications as they expand their role beyond infection control problems to issues concerning cost containment, quality assurance, and reimbursement.     

Shifting costs from high-cost to low-cost diagnosis-related groups?

Hospitals are commonly compared with each other within diagnosis-related group (DRG) categories. Administrators infer that hospitals with a higher cost per case within a DRG are less efficient than hospitals with a lower cost per case after case mix and severity adjustment. The authors assess whether hospitals that carry a heavy load of high-cost DRGs potentially distribute the added expenses of treating these patients onto their lower cost DRGs using data gathered from the 47 hospitals in the University Hospital Consortium database between January 1994 and December 1995. The results indicate that given standard hospital allocation practices, some of the costs associated with high-cost patients were likely shifted downward, thereby inflating the cost per case for less expensive patients. As researchers adopt more benchmarking methodologies, it is important to recognize that standard accounting practices in which cost shifting from one class of patient to another may impair the ability to understand the actual cost structure for classes of patients.     

Rural Implications of Medicare''s Post-Acute-Care Transfer Payment Policy

CONTEXT: Under the Medicare post-acute-care (PAC) transfer policy, acute-care hospitals are reimbursed under a per-diem formula whenever beneficiaries are discharged from selected diagnosis-related groups (DRGs) to a skilled nursing facility, home health care, or a prospective payment system (PPS)-excluded facility. Total per-diem payments are below the full DRG payment only when the patient's length of stay (LOS) is short relative to the geometric mean LOS for the DRG; otherwise, the full DRG payment is received. This policy originally applied to 10 DRGs beginning in fiscal year 1999 and was expanded to additional DRGs in FY2004. The Secretary may include other DRGs and types of PAC settings in future expansions. PURPOSE: This article examines how the initial policy change affected rural and urban hospitals and investigates the likely impact of the FY2004 expansion and other possible future expansions. METHODS: The authors used 1998-2001 Medicare Provider Analysis and Review (MEDPAR) data to investigate changes in hospital discharge patterns after the original policy was implemented, compute the change in Medicare revenue resulting from the payment change, and simulate the expected revenue reductions under expansions to additional DRGs and swing-bed discharges. FINDINGS: Neither rural nor urban hospitals appear to have made a sustained change in their discharge behavior so as to limit their exposure to the transfer policy. Financial impacts from the initial policy were similar in relative terms for both types of hospitals and would be expected to be fairly similar for an expansion to additional DRGs. On average, including swing-bed discharges in the transfer policy would have a very small financial impact on small rural hospitals; only hospitals that make extensive use of swing beds after a short inpatient stay might expect large declines in total Medicare revenue. CONCLUSION: Rural hospitals are not disproportionately harmed by the PAC transfer policy. An expanded policy may even benefit rural hospitals by recognizing their lower use of post-acute-care and readjusting DRG weights so that they are paid more appropriately when providing the full course of inpatient care.     

Do Diagnosis‐Related Group‐Based Payments Incentivise Hospitals to Adjust Output Mix?

This study investigates whether the diagnosis‐related group (DRG)‐based payment method motivates hospitals to adjust output mix in order to maximise profits. The hypothesis is that when there is an increase in profitability of a DRG, hospitals will increase the proportion of that DRG (own‐price effects) and decrease those of other DRGs (cross‐price effects), except in cases where there are scope economies in producing two different DRGs. This conjecture is tested in the context of the case payment scheme (CPS) under Taiwan's National Health Insurance programme over the period of July 1999 to December 2004. To tackle endogeneity of DRG profitability and treatment policy, a fixed‐effects three‐stage least squares method is applied. The results support the hypothesised own‐price and cross‐price effects, showing that DRGs which share similar resources appear to be complements rather substitutes. For‐profit hospitals do not appear to be more responsive to DRG profitability, possibly because of their institutional characteristics and bonds with local communities. The key conclusion is that DRG‐based payments will encourage a type of ‘product‐range’ specialisation, which may improve hospital efficiency in the long run. However, further research is needed on how changes in output mix impact patient access and pay‐outs of health insurance. Copyright © 2014 John Wiley & Sons, Ltd.     

DRGs and specialized nutrition support. Prospective payment and nutritional support: the need for reform

The Medicare Prospective Payment System does not recognize the use of parenteral and enteral nutrition services as an explicit factor to be used in determination of DRG payment rates. When the DRGs were originally created, the use of parenteral and enteral nutrition services (PENS) was not coded in discharge data sets. As a result, it was impossible to determine whether patients who received PENS were more expensive to treat. Data we have collected indicate that patients who receive PENS tend to have high hospital costs--costs that often exceed the DRG payments established by the Health Care Financing Administration (HCFA). The potential for a hospital to incur a financial loss as a result of treating patients who require PENS could make such patients less attractive to hospitals and thus could adversely affect patients requiring these services. In order to minimize this possibility, we suggest several alternative modifications to the DRG payment system. The modifications would provide higher payments for patients who require PENS, thereby reducing the possibility of discrimination against these patients. By readjusting the DRG prices for patients who do not require PENS, the entire payment modification can be made budget-neutral.     

Hospital cost control in Norway: a decade's experience with prospective payment

Under Norway's prospective payment system, which was in existence from 1972 to 1980, hospital costs increased 15.8 percent annually, compared with 15.3 percent in the United States. In 1980 the Norwegian national government started paying for all institutional services according to a population-based, morbidity-adjusted formula. Norway's prospective payment system provides important insights into problems of controlling hospital costs despite significant differences, including ownership of medical facilities and payment and spending as a percent of GNP. Yet striking similarities exist. Annual real growth in health expenditures from 1972 to 1980 in Norway was 2.2 percent, compared with 2.4 percent in the United States. In both countries, public demands for cost control were accompanied by demands for more services. And problems of geographic dispersion of new technology and distribution of resources were similar. Norway's experience in the 1970s demonstrates that prospective payment is no panacea. The annual budget process created disincentives to hospitals to control costs. But Norway's changes in 1980 to a population-based methodology suggest a useful approach to achieve a more equitable distribution of resources. This method of payment provides incentives to control variations in both admissions and cost per case. In contrast, the Medicare approach based on Diagnostic Related Groups (DRGs) is limited, and it does not affect variations in admissions and capital costs. Population-based methodologies can be used in adjusting DRG rates to control both problems. In addition, the DRG system only applies to Medicare payments; the Norwegian experience demonstrates that this system may result in significant shifting of costs onto other payors.     

Have DRG-based prospective payment systems influenced the number of secondary diagnoses in health care administrative data?

Diagnosis-related groups (DRGs) are secondary patient classification systems based on primary classified medical data, in which single events of care are grouped into larger, economically and medically consistent groups. The main primary classified medical data are diagnoses and surgery codes. In Sweden, the number of secondary diagnoses per case increased during the 1990s. In the early 1990s some county councils introduced DRG systems. The present study investigated whether the introduction of such systems had influenced the number of secondary diagnoses. The nation-wide Hospital Discharge Register from 1988 to 2000 was used for the analyses. All regional hospitals were included, giving a database of 5,355,000 discharges. The hospitals were divided into those that had introduced prospective payment systems during the study period and those that had not. Among all regional hospitals, there was an increase in the number of coded secondary diagnoses, but also in the number of secondary diagnoses per case. Hospitals with prospective payment systems had a larger increase, starting after the system was introduced. Regional hospitals without prospect payment systems had a more constant increase, starting later and coinciding with the introduction of their DRG-based management systems. It is concluded that introduction of DRG-based systems, irrespective of use, focuses on recording diagnoses and therefore increases the number of diagnoses. Other reasons may also have contributed to the increase. It was found that the changes in the speciality mix, during the study period, have impact on the increase of secondary diagnoses.     

Medicaid prospective payment: case-mix increase

South Carolina Medicaid implemented prospective payment by diagnosis-related group (DRG) for inpatient care. The rate of complications among newborns and deliveries doubled immediately. The case-mix index for newborns increased 66.6 percent, which increased the total Medicaid hospital expenditure 5.5 percent. Outlier payments increased total expenditure further. DRG distribution change among newborns has a large impact on spending because newborn complication DRGs have high weights. States adopting a DRG-based payment system for Medicaid should anticipate a greater increase in case mix than Medicare experienced.     

试论病例组合 DRGs与临床质量管理

病例组合是通过一定原则对病人进行分类管理的一种工具。DRGs根据临床相似性、资源消耗相似性对急性住院病人进行分类,可用于住院筹资和补偿、住院资源配置和调整、住院预付制(即DRG-PPS)、绩效评价和比较研究等方面。各国DRG内部分组的粗细不一,各医院收治的疾病种类和病人的构成也存在一定的差异,DRG分组也应该根据情况。在开展支付制度改革的时候必须有质量监测、评价和控制措施相配套。DRG分组和支付标准的研究和建立是一个繁杂的系统工程,必须在国家层面上,统一开发,形成国家标准,统一实施。     

DRG reimbursement in New Jersey: some initial results

New Jersey hospitals' experience with the DRG method of case mix reimbursement leads to the following conclusions: (1) the number of DRGs should be reduced; (2) all patients should not be charged the same payment rate; (3) a method is needed to adjust for intra-DRG shifts; and (4) hospitals need more information to manage efficiently.     

Comparing in-patient classification systems: A problem of non-nested regression models

Since 1983, hospitals in the United States have been receiving prospective payment for their in-hospital patient admissions covered under Medicare. Under such schemes each patient is placed in a group by a classification system, known as the Diagnosis Related Groups (DRG), and the hospital is reimbursed by the Health Care Financing Administration according to some predetermined group average, adjusted for hospital level characteristics, such as size, location and teaching activity. Recent interest has focused on refining the DRG system or considering totally different systems of classification. Studies designed to compare the ability of different systems to account for between-patient variability in resource consumption in the same dataset lead to the problem of model selection between large non-nested regressions, where resource consumption, measured by length of hospital stay or costs, is regressed on dummy-indicator variables representing different patient groups. We use a simple measure of fit to develop a symmetric test of the null hypothesis that the two systems account equally well for variability in resource consumption. With this method, unlike methods such as Akaike's AIC criterion, we can quantify the probability of a false positive, and thereby limit the probability of choosing one system over another when it is no better at accounting for variability in resource consumption.