Medicare Program; Explanation of FY 2004 Outlier Fixed-Loss Threshold as Required by Court Rulings. Clarification.

In accordance with court rulings in cases that challenge the federal fiscal year (FY) 2004 outlier fixed-loss threshold rulemaking, this document provides further explanation of certain methodological choices made in the FY 2004 fixed-loss threshold determination.

Development of a methodology for the detection of hospital financial outliers using information systems.

Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers.

Summary of prospective quantification of reimbursement recovery from inpatient acute care outliers.

The purpose of this study is to identify and quantify inpatient acute care hospital cases that are eligible for additional financial reimbursement. Acute care hospitals are reimbursed by third-party payers on behalf of their patients. Reimbursement is a fixed amount dependent primarily upon the diagnostic related group (DRG) of the case and the service intensity weight of the individual hospital. This method is used by nearly all third-party payers. For a given case, reimbursement is fixed (all else being equal) until a certain threshold level of charges, the cost outlier threshold, is reached. Above this amount the hospital is partially reimbursed for additional charges above the cost outlier threshold. Hospital discharge information has been described as having an error rate of between 7 and 22 percent in attribution of basic case characteristics. It can be expected that there is a significant error rate in the attribution of charges as well. This could be due to miscategorization of the case, misapplication of charges, or other causes. Identification of likely cases eligible for additional reimbursement would alleviate financial pressure where hospitals would have to absorb high expenses for outlier cases. Determining predicted values for total charges for each case was accomplished by exploring associative relationships between charges and case-specific variables. These variables were clinical, demographic, and administrative. Year-by-year comparisons show that these relationships appear stable throughout the five-year period under study. Beta coefficients developed in Year 1 are applied to develop predictions for Year 3 cases. This was also done for year pairs 2 and 4, and 3 and 5. Based on the predicted and actual value of charges, recovery amounts were calculated for each case in the second year of the year pairs. The year gap is necessary to allow for collection and analysis of the data of the first year of each pair. The analysis was performed in two parts. First, cases of myocardial infarction were examined to prove feasibility and then a sample of strata of all cases were subjected to the same analytical procedure to provide support for the postulation of universal applicability. Approximately 85,000 cases could be audited annually in New York State, and possibly 1.3 million in the entire United States. Estimated recovery from all inpatient cases is approximately $230 million per year in New York State and roughly $3.6 billion per year from these payers on a national basis. The cost-benefits ratio was estimated at 3.6:1. These are considered to be conservative estimates.

Medicare program; end-stage renal disease prospective payment system. Final rule.

This final rule implements a case-mix adjusted bundled prospective payment system (PPS) for Medicare outpatient end-stage renal disease (ESRD) dialysis facilities beginning January 1, 2011 (ESRD PPS), in compliance with the statutory requirement of the Medicare Improvements for Patients and Providers Act (MIPPA), enacted July 15, 2008. This ESRD PPS also replaces the current basic case-mix adjusted composite payment system and the methodologies for the reimbursement of separately billable outpatient ESRD services.

Speaking the same language: underestimating financial impact when using diagnosis-related group versus ICD-9-based definitions for trauma inclusion criteria.

BACKGROUND: Hospital accounting methods use diagnosis-related group (DRG) data to identify patients and derive financial analyses and reports. The National Trauma Data Bank and trauma programs identify patients with trauma by International Classification of Diseases, Ninth Edition (ICD-9)-based definitions for inclusion criteria. These differing methods of identifying patients result in economic reports that vary significantly and fail to accurately identify the financial impact of trauma services. METHODS: Routine financial data were collected for patients admitted to our Trauma Service from July 1, 2005 to June 30, 2006 using two methods of identifying the cases; by trauma DRGs and by trauma registry database inclusion criteria. The resulting data were compared and stratified to define the financial impact on hospital charges, reimbursement, costs, contribution to margin, downstream revenue, and estimated profit or loss. The results also defined the impact on supporting services, market share and total revenue from trauma admissions, return visits, discharged trauma alerts, and consultations. RESULTS: A total of 3,070 patients were identified by the trauma registry as meeting ICD-9 inclusion criteria. Trauma-associated DRGs accounted for 871 of the 3,070 admissions. The DRG-driven data set demonstrated an estimated profit of $800,000 dollars; the ICD-9 data set revealed an estimated 4.8 million dollar profit, increased our market share, and showed substantial revenue generated for other hospital service lines. CONCLUSIONS: Trauma DRGs fail to account for most trauma admissions. Financial data derived from DRG definitions significantly underestimate the trauma service line's financial contribution to hospital economics. Accurately identifying patients with trauma based on trauma database inclusion criteria better defines the business of trauma.

The variance of length of stay and the optimal DRG outlier payments.

Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

[Health economic effects after DRG-implementation--a systematic overview]. / Gesundheitsökonomische Auswirkungen der DRG-Einführung in Deutschland--eine systematische Ubersicht.

BACKGROUND: Since 1 January 2004, inpatient treatment services in German hospitals have been reimbursed using a prospective payment method based on diagnosis-related groups (DRGs) rather than daily rates. The aim of the payment system reform was to decrease the length of inpatient stays and reduce overall healthcare expenditure, the latter of which had increased markedly during previous decades. OBJECTIVE: The primary objective of our study was to analyse and describe the health-economic consequences of implementing a DRG-based system of prospective payment in Germany. METHODS: A systematic search of the literature was performed on MEDLINE. Inclusion criteria were a focus on health economic variables from the German perspective and a publication date after 1 January 2004. The search was supplemented by a manual review of references, as well as internet-based hand search. The main health-economic conclusions were subsequently extracted from all of the included studies. RESULTS: A total of 19 quantitative and qualitative studies were included. There were substantial differences between them in terms of medical focus and hospital characteristics. The most common health-economic variables analysed were revenue generated by patient treatment, and length of inpatient stay. As expected, both variables showed a decreasing trend following the introduction of DRGs. The included studies also investigated the development of case numbers, the proportion of outpatient services provided, the number of diagnoses per case, and the homogeneity of case groups. For these variables, the studies showed a wide range of results. CONCLUSION: Similar to the experience with DRGs in many other countries, the introduction of DRGs in Germany has led to a reduction in the length of inpatient stay and a decrease in hospital revenues. The effects on other health-economic parameters are inconsistent. Additional studies in this area are needed.

Center Variation in Medicare Spending for Durable Left Ventricular Assist Device Implant Hospitalizations.

Importance: Hospitalizations for durable left ventricular assist device (LVAD) implants are expensive and increasingly common. Insights into center-level variation in Medicare spending for these hospitalizations are needed to inform value improvement efforts. Objective: To examine center-level variation in Medicare spending for durable LVAD implant hospitalizations and its association with clinical outcomes. Design, Setting, and Participants: Retrospective cohort study of linked Medicare administrative claims and Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) clinical data comprising 106 centers in the United States providing durable LVAD implant. Centers were grouped into quartiles based on the mean price-standardized Medicare spending of their patients. The study included Medicare beneficiaries receiving primary durable LVAD implant between January 2008 and December 2014. Data were analyzed between November 2017 and October 2018. Main Outcomes and Measures: Price-standardized Medicare payments and clinical outcomes. Overall and component (facility diagnosis-related group payments, outlier payments, physician services) payments and clinical outcomes (postimplant length of stay and adverse events) were compared across payment quartiles. Results: The study sample included 4442 hospitalized patients, with mean (SD) age of 63.0 (10.8) years, 18.7% female, 27.2% nonwhite, and 6.1% Hispanic ethnicity. Among 4442 hospitalizations, the mean (SD) price-standardized Medicare payment was $176 825 ($60 286) and ranged from $122 953 to $271 472 across 106 centers. The difference in price-standardized payments between lowest and highest spending quartiles was $55 446 ($152 714 vs $208 160; 36%; P < .001), with outlier payments making up most of the difference ($42 742; 77%), followed by DRG ($6929; 13%) and physician services ($5774; 10%). After risk standardization, there was a modest decline in the difference in payments between quartiles ($53 221; 35%), with outlier payments accounting for a larger proportion of the difference (84%). After adjusting for patient characteristics, higher price-standardized payment quartiles were associated with longer postimplant length of stay but were not associated with any adverse events. Conclusions and Relevance: Medicare payments for durable LVAD implant hospitalizations vary widely across centers; this was not well explained by prices or case mix. While associated with longer postimplant length of stay, increased spending was not associated with adverse events. As the supply and demand for durable LVAD therapy continues to rise, identifying opportunities to reduce variation in spending from both explained and unexplained sources will ensure high-value use.

Supply-side risk adjustment and outlier payment policy.

In most health care systems where a prospective payment system is implemented, an outlier payment is used to cover the hospitals' unusually high costs. When the hospital chooses its cost reduction effort before observing a patient's severity, we show that the best outlier payment is based on the realized cost when the hospital exerts the first best level of effort, for any level of severity.

Complexities in transplant revenue management.

Numerous payment methodologies, contract types, and income reimbursement methods exist in the highly complex environment of transplantation. A fundamental understanding of the transplant environment and the various compensation schemes involved with transplant revenue management is necessary to stay viable in such a complicated system. Knowledge of resources such as Medicare, commercial insurance, Medicaid, and self-pay individuals will allow a program to fully optimize allowable revenue streams. This multiple payer mix can be challenging, with payment arrangements ranging from a single global case rate that must cover all transplant-related services to individual payment arrangements for each stage of the transplantation process. Transplant programs must track each agreement to ensure optimal payment, and must therefore become proficient with central fiscal operations such as Medicare cost reporting and managed care contract negotiations. Outlier protection and risk pool strategies can also be used to remain competitive and profitable. A transplant program must have a thorough understanding of all available payment schemes and reimbursement optimizing strategies to facilitate the realization of a strong financial outlook.

[DRG evaluation results--state comparisons: MDK Baden-Württemberg versus MDK Westfalen-Lippe]. / DRG-Prüfergebnisse im Ländervergleich: MDK Baden-Württemberg und MDK Westfalen-Lippe.

We report on the first detailed comparison of evaluation results regarding the correct billing in the G-DRG (German diagnosis-related group) system. For two Medical Review Boards of the Statutory Health Insurance Funds of comparable size (MDK Baden-Württemberg and MDK Westfalen-Lippe), we analysed consecutive expertises regarding correct billing according to section sign 275 SGB V, and the results were compared in terms of the frequency of DRG-relevant error codes, their relevance to revenue, and the question of error clustering (specific DRGs, primary diagnoses, etc.). The analysis comprised 51,010 individual expertises pertaining to billings of the year 2005 (admittance to hospital from January 1 to December 31, 2005). The proportion of disapproved cases was 38.5% in Baden-Württemberg and 44.6% in Westfalen-Lippe. Among these, errors to the disadvantage of the Health Insurance (incorrectly high) were 33.9% and 39.3%, respectively, and errors to the disadvantage of the hospitals (incorrectly low) were 4.6% and 5.3%, respectively. The resulting ratio (incorrectly high vs. low) was an identical 7.4 in both cases. Not only the most commonly rejected DRGs but also the primary and secondary diagnoses were similar in both cases, while the disapproved procedure codes showed a significant variability (analysis based on the respective 10 most common objections). We discuss the similarities and differences in these results and their possible causes, and demonstrate the cost relevance of this audit segment. Result comparisons of this type can yield insights into streamlining of the review practice of Medical Review Boards, as well as increase the efficiency and effectiveness of the selection of cases.

[Random sampling according to section 17 c KHG--report on the experience of maximal care hospitals in Hesse]. / Die Stichprobenprüfung nach 17 c KHG--Erfahrungsbericht aus Krankenhäusern der Maximalversorgung in Hessen.

Hospital billing converted to "German diagnosis-related groups" (G-DRG) for in-patient treatment in Germany is reviewed, except in psychiatry where per-diems are still in use. Currently thousands of bills are sent to the Medical Service for scrutiny. In addition, the law relating to Hospital Financing (Krankenhausfinanzierungsgesetz, para. 17 c) provides for systematic checks on a random sample of bills from a given hospital. The Medical Service of the Social Security Health Insurance reports on the experience in the State of Hessen. Present regulations exclude from the random sample those bills that have already been presented for a check on a case by case basis. Excluding these cases from the random sample introduces a bias in an avoidable way. The present rule is contrary to valid conclusions from the random sampling and should be abolished.

Are medical outliers associated with worse patient outcomes? A retrospective study within a regional NHS hospital using routine data.

OBJECTIVE: To explore the quality and safety of patients' healthcare provision by identifying whether being a medical outlier is associated with worse patient outcomes. A medical outlier is a hospital inpatient who is classified as a medical patient for an episode within a spell of care and has at least one non-medical ward placement within that spell. DATA SOURCES: Secondary data from the Patient Administration System of a district general hospital were provided for the financial years 2013/2014-2015/2016. The data included 71 038 medical patient spells for the 3-year period. STUDY DESIGN: This research was based on a retrospective, cross-sectional observational study design. Multivariate logistic regression and zero-truncated negative binomial regression were used to explore patient outcomes (in-hospital mortality, 30-day mortality, readmissions and length of stay (LOS)) while adjusting for several confounding factors. PRINCIPAL FINDINGS: Univariate analysis indicated that an outlying medical in-hospital patient has higher odds for readmission, double the odds of staying longer in the hospital but no significant difference in the odds of in-hospital and 30-day mortality. Multivariable analysis indicates that being a medical outlier does not affect mortality outcomes or readmission, but it does prolong LOS in the hospital. CONCLUSIONS: After adjusting for other factors, medical outliers are associated with an increased LOS while mortality or readmissions are not worse than patients treated in appropriate specialty wards. This is in line with existing but limited literature that such patients experience worse patient outcomes. Hospitals may need to revisit their policies regarding outlying patients as increased LOS is associated with an increased likelihood of harm events, worse quality of care and increased healthcare costs.

Analysis of cost outliers within APR-DRGs in a Belgian general hospital: two complementary approaches.

CONTEXT AND OBJECTIVES: The objective of this study was to find factors that could explain high and low resource use outliers, by associating an explanatory analysis with a statistical analysis. METHOD: High resource use outliers were selected according to the following rule: 75th percentile + 1.5* inter-quartile range. Low resource use outliers were selected according to: 25th percentile - 1.5* inter-quartile range. The statistical approach was based on a multivariate analysis using logistic regression. A decision tree approach using predictors from this analysis (intensive care unit (ICU) stay, high severity of illness and social factors associated with longer length of stay) was also tested as a more intuitive tool for use by hospitals in focussing review efforts on "not explained" cost outliers. RESULTS: High resource use outliers accounted for 6.31% of the hospital stays versus 1.07% for low resource use outliers. The probability of a patient being a high resource use outlier was higher with an increase in the length of stay (odds ratios (OR) = 1.08), when the patient was treated in an intensive care unit (OR = 3.02), with a major or extreme severity of illness (OR=1.46), and with the presence of social factors (OR = 1.44). The probability of being a low outlier is lower for older patients (OR = 0.98). The probability of being a low outlier is also lower without readmission within the year (OR = 0.55). The more intuitive decision tree method identified 92.26% of the cases identified through residuals of the regression model. One quarter of the high cost outliers were flagged for additional review ("not justified" on the basis of the model), with nearly three-quarters "justified" by clinical and social factors. CONCLUSION: The analysis of cost outliers can meet different aims (financing of justifiable outliers, improvement of the care process for the outliers not justifiable on medical or social grounds). The two methods are complementary, by proposing a statistical and a didactic approach to achieve the goal of high quality care using fewer resources.

Economic profiling of physician specialists: use of outlier treatment and episode attribution rules.

This paper examines the influence of episode attribution methodology and cost outlier methodology on the accuracy of physicians' economic profiles. Four years of claims data from a mixed model HMO were processed using the leading episode grouper software. Episode grouped results then were applied to construct input distributions for a simulation model. For each of four specialties (cardiology, family practice, general surgery, and neurology), we employed sets of 18 simulations to investigate the effects of three alternative episode attribution methodologies and six alternative cost outlier methodologies on sensitivity, specificity, and positive predictive error in classifying cost-efficient and cost-inefficient physicians. For identification of cost-efficient physicians, the most accurate profiling results were obtained when Winsorizing outliers at 2% and 98% of episode-type cost distributions, and attributing responsibility for episode costs to physicians who accounted for at least 30% of associated professional and prescribing fees. No consistent combination of outlier methodology and episode attribution rule was found to be superior for identifying cost-inefficient physicians.

Prospective casemix-based funding, analysis and financial impact of cost outliers in all-patient refined diagnosis related groups in three Belgian general hospitals.

This study examined the impact of cost outliers in term of hospital resources consumption, the financial impact of the outliers under the Belgium casemix-based system, and the validity of two "proxies" for costs: length of stay and charges. The cost of all hospital stays at three Belgian general hospitals were calculated for the year 2001. High resource use outliers were selected according to the following rule: 75th percentile +1.5 xinter-quartile range. The frequency of cost outliers varied from 7% to 8% across hospitals. Explanatory factors were: major or extreme severity of illness, longer length of stay, and intensive care unit stay. Cost outliers account for 22-30% of hospital costs. One-third of length-of-stay outliers are not cost outliers, and nearly one-quarter of charges outliers are not cost outliers. The current funding system in Belgium does not penalize hospitals having a high percentage of outliers. The billing generated by these patients largely compensates for costs generated. Length of stay and charges are not a good approximation to select cost outliers.

Trends in Medicare disproportionate share (DSH) distribution in US hospitals: 1996-2003.

Implemented in 1986, Medicare's disproportionate share (DSH) adjustment is intended to recognize hospitals' additional resource investment in caring for low-income patients. This project analyzed changes in the DSH percentage between 1996 and 2003 and examined the association between selected hospital characteristics and such changes. Results obtained revealed some interesting findings. First, minimal changes in DSH percentage occurred during the period 1996-1999 with a hike in that ratio in 2000-2001. However, even with the absence of any legislative or executive changes to the DSH threshold or formula during 2002 and 2003, significant increases occurred during 2001-2003 (11 percent increase between 2001 and 2003). Such an increase may be caused by the nation's economic situation during that timeframe (i.e., more people depending on public programs for coverage).

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center.

PRINCIPLES: Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG. METHODS: 28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings. RESULTS: Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001). CONCLUSION: We suggest considering psychiatric diagnosis, admission as an emergency case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.