Predictors for shorter and longer length of hospital stay outliers: a retrospective case-control study of 8247 patients at a university hospital trauma department.

BACKGROUND: Providing efficient healthcare is important for hospitals. Shorter and longer length of hospital stay (LOS) outliers influence financial results and reimbursement. The objective of this study was to identify independent diagnosis related group (DRG)-related risk factors for shorter and longer LOS outlier status. METHODS: A retrospective case-control study was conducted at a Swiss level 1 trauma centre between January 2012 and December 2014. The study included all patients with available information on LOS based on DRG. Many predictor variables were tested. The outcome variable was the DRG-based LOS. Logistic regression models were fitted for shorter and longer LOS outliers, with a significance level of <1%. RESULTS: A total of 8247 patients were analysed, of whom inliers were more frequent than shorter and longer LOS outliers (n = 5838 [70.8%] vs n = 1996 [24.2%] vs n = 413 [5.0%]). Predictors for shorter LOS outliers were death (odds ratio [OR] 4.89, 95% confidence interval [CI] 3.27-7.31), concussion (OR 4.87, 95% CI 4.20-5.63) and psychiatric disease (OR 1.85, 95% CI 1.46-2.34). Predictors for longer LOS outliers were age ≥65 years (OR 1.74, 95% CI 1.31-2.30), number of diagnoses ≥5 (OR 2.07, 95% CI 1.52-2.81), comorbidity (OR 1.75, 95% CI 1.28-2.40), number of surgical procedures (OR 1.76, 95% CI 1.36-2.28), complication perioperatively (OR 1.69, 95% CI 1.24-2.30), infection (OR 2.66, 95% CI 1.57-4.49]), concussion (OR 1.52, 95% CI 1.14-2.01) and urinary tract infection (OR 2.34, 95% CI 1.61-3.41). CONCLUSION: This large study showed that LOS outliers, especially shorter LOS outliers, are relatively common. Patients who died, or had concussion or psychiatric disease were more commonly discharged early. Patients weremore often discharged late if they were aged ≥65 years, had more diagnoses, were comorbid, had more surgical procedures, complications perioperatively, infection, concussion and urinary tract infection. For hospitals, this can help raise awareness and lead to better management of specific diagnoses in order to avoid monetary deficits. For the public health sector, this information may be considered in future revisions of the DRG.

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.

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.

Rationale and design of GISSI OUTLIERS VAR Study in bicuspid aortic valve patients: prospective longitudinal, multicenter study to investigate correlation between surgical, echo distinctive features, histologic and genetic findings in phenotypically homogeneous outlier cases.

BACKGROUND/OBJECTIVES: Bicuspid aortic valve (BAV) is the most common congenital heart disorder, affecting up to 2% of the population. Involvement of aortic root and ascending aorta (aneurysm or, eventually, dissection) is frequent in patients with pathologic or normal functioning BAV. Unfortunately, there are no well-known correlations between valvular and vascular diseases. In VAR protocol, with a new strategy of research, we analysemultiple aspects of BAV disease through correlation between surgical, echo, histologic and genetic findings in phenotypically homogeneous outlier cases. METHODS: VAR protocol is a prospective, longitudinal, multicenter study. It observes 4 homogeneous small groups of BAV surgical patients (15 patients each): isolated aortic regurgitation, isolated ascending aortic aneurysm, aortic regurgitation associated with aortic aneurysm, isolated aortic stenosis in older patients (>60years). Echo analysis is extended to first-degree relatives and, in case of BAV, genetic test is performed. Patients and relatives are enrolled in 10 cardiac surgery/cardiologic centers throughout Italy. CONCLUSIONS: The aim of the study is to identify predictors of favorable or unfavorable evolution of BAV in terms of valvular dysfunction and/or aortic aneurysm. Correlations between different features could help in identification of various BAV risk groups, rationalizing follow-up and treatment.

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.

[Are extra costs generated by patients justifiable? Methodology and results from a study carried out in a Belgian general hospital]. / Les surcoûts engendrés par certains patients sont-ils justifiables? Méthodologie et résultats d'une étude réalisée dans un hôpital général belge.

Cost outliers account for 6 to 8% of hospital inpatient stays and concentrate 22 to 30% of inpatient costs. Explanatory factors were highlighted in various studies. They are the lenght of stay, an intensive care unit stay, the severity of illness index related to DRG and social factors. Patients are not always explained by these factors. The objective of this study is to analyse cases not explained by those factors, through a detailed analysis of medical files. In the studied hospital, there are 6,3% high cost outliers and 1,1% low cost outliers. These stays were isolated on the basis of a rule based on percentiles. Extra costs generated by high cost outliers are 6.999 euro per stay. The extra lenght of stay for these patients is 20,42 days. Among the 454 patients high cost outliers, 334 patients are explained by factors extracted from a statistical analysis based on a logistic regression (intensive care unit stay, severity of illness index, lenght of stay and social factors). The analysis of medical files of the 120 not explained inpatient stays highlights new explanatory factors (coding errors, heterogeneity of DRGs, etc.). At the end of this study, the conclusion is that a statistical analysis combined with a precise analysis of medical files allowed to explain the majority of cost outliers. An explanation is however not necessarily synonymous with medical justification.

Trialling diagnosis-related groups classification in the Iranian health system: a case study examining the feasibility of introducing casemix.

This paper examines the quality of routinely collected information in an Iranian hospital in a trial of casemix classification. Australian Refined Diagnosis Related Groups (AR-DRG) were used to classify patient episodes. There were 327 DRGs identified, of which 20% had only 1 case. The grouper program identified invalid records for 4% of total separations. Approximately 4.5% of cases were classified into error DRGs and 3.4% were ungroupable. No complication and comorbidity effects were identified with 93% of total cases. R2 (variance in length of stay explained) was 44% for untrimmed cases, increasing to 63%, 57% and 58% after trimming by L3H3, IQR and 10th-95th percentile methods respectively.

Non-therapeutic omission of medications in acutely ill patients.

AIMS AND OBJECTIVES: To examine documentation of medication administration in medical and surgical patients. STUDY OBJECTIVES: (1) Determine the point prevalence of non-therapeutic medication omissions; (2) identify documented reasons for non-therapeutic medication omissions; (3) examine the relationship between length of stay and medication omissions; and (4) explore the impact of outlier status (e.g. medical patients managed on surgical wards) on medication administration. BACKGROUND: Acutely ill patients are particularly sensitive to health care errors. We previously identified a 26% rate of non-therapeutic medication omissions in patients admitted unexpectedly to intensive care unit (ICU) from medical and surgical wards. DESIGN: A point prevalence survey of 162 medical and surgical patients across four sites in the South West of England. METHOD: Data collected included: all instances of, and reasons for, non-therapeutic medication omission. We also recorded whether the patient was an 'outlier' and examined nursing documentation where no reason for medication omission was given on the drug chart. RESULTS: The number of patients who missed at least one medication was high across all sites (n = 129/162; 79.6%, range 60-88%), with a total of 1077 doses omitted. Patients who were outliers (e.g. surgical patients on a medical ward) were more likely to miss medications (100% versus 74%, p < 0.001). The most common missed medications were analgesia and anti-inflammatory drugs (28%, 299/1077); 203 of these were due to patient refusal. CONCLUSIONS: The extent of medications omitted for non-therapeutic reasons in medical and surgical patients is of concern. None were recorded as an adverse drug event; however, the extent of omitted or refused medications suggests the need for a review of prescribing and drug administration processes. These findings have important implications for the role of ICU outreach and liaison services, for example, including medication management in the monitoring of patients pre/post-ICU admission and support/education provided for ward staff. RELEVANCE TO CLINICAL PRACTICE: Detailed analysis of medication records suggests a number of areas of medication administration that would benefit from review.

Putting it altogether: improving performance in heart failure outcomes, part 2.

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 10th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. As follow-up to the case study in this column's June 2009 article, this article highlights the interventions and outcomes of the study.

Effects of the Premier Hospital Quality Incentive Demonstration on Medicare patient mortality and cost.

OBJECTIVE: To evaluate the effects of the Premier Inc. and Centers for Medicare and Medicaid Services Hospital Quality Incentive Demonstration (PHQID), a public quality reporting and pay-for-performance (P4P) program, on Medicare patient mortality, cost, and outlier classification. DATA SOURCES: The 2000-2006 Medicare inpatient claims, Medicare denominator files, and Medicare Provider of Service files. STUDY DESIGN: Panel data econometric methods are applied to a retrospective cohort of 11,232,452 admissions from 6,713,928 patients with principal diagnoses of acute myocardial infarction (AMI), heart failure, pneumonia, or a coronary-artery bypass grafting (CABG) procedure from 3,570 acute care hospitals between 2000 and 2006. Three estimators are used to evaluate the effects of the PHQID on risk-adjusted (RA) mortality, cost, and outlier classification in the presence of unobserved selection, resulting from the PHQID being voluntary: fixed effects (FE), FE estimated in the subset of hospitals eligible for the PHQID, and difference-in-difference-in-differences. DATA EXTRACTION METHODS: Data were obtained from CMS. Principal Findings. This analysis found no evidence that the PHQID had a significant effect on RA 30-day mortality or RA 60-day cost for AMI, heart failure, pneumonia, or CABG and weak evidence that the PHQID increased RA outlier classification for heart failure and pneumonia. CONCLUSIONS: By not reducing mortality or cost growth, this study suggests that the PHQID has made little impact on the value of inpatient care purchased by Medicare.

[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.

Detecting outlier samples in microarray data.

In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to explore underlying experimental or biological problems and remove erroneous data. We propose an outlier detection method based on principal component analysis (PCA) and robust estimation of Mahalanobis distances that is fully automatic. We demonstrate that our outlier detection method identifies biologically significant outliers with high accuracy and that outlier removal improves the prediction accuracy of classifiers. Our outlier detection method is closely related to existing robust PCA methods, so we compare our outlier detection method to a prominent robust PCA method.

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.

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.

Impact of the present-on-admission indicator on hospital quality measurement: experience with the Agency for Healthcare Research and Quality (AHRQ) Inpatient Quality Indicators.

BACKGROUND: The Agency for Healthcare Research and Quality (AHRQ) has constructed Inpatient Quality Indicator (IQI) mortality measures to measure hospital quality using routinely available administrative data. With the exception of California, New York State, and Wisconsin, administrative data do not include a present-on-admission (POA) indicator to distinguish between preexisting conditions and complications. The extent to which the lack of a POA indicator biases quality assessment based on the AHRQ mortality measures is unknown. OBJECTIVE: To examine the impact of the POA indicator on hospital quality assessment based on the AHRQ mortality measures using enhanced administrative data from California, which includes a POA indicator. METHODS: Retrospective cohort study based on 2.07 million inpatient admissions between 1998 and 2000 in the California State Inpatient Database. The AHRQ IQI software was used to calculate risk-adjusted mortality rates using either (1) routine administrative data that included all the International Classification of Diseases (ICD)-9-CM codes or (2) enhanced administrative data that included only the ICD-9-CM codes representing preexisting conditions. RESULTS: The inclusion of the POA indicator frequently results in changes in the quality ranking of hospitals classified as high-quality or low-quality using routine administrative data. Twenty-seven percent (stroke) to 94% (coronary artery bypass graft) of hospitals classified as high-quality using routine administrative data were reclassified as intermediate- or low-quality hospitals using the enhanced administrative data. Twenty-five percent (congestive heart failure) to 76% (percutaneous coronary intervention) of hospitals classified as low-quality hospitals using enhanced administrative data were misclassified as intermediate-quality hospitals using routine administrative data. CONCLUSIONS: Despite the fact that the AHRQ IQIs were primarily intended to serve as a screening tool, they are being increasingly used to publicly report hospital quality. Our findings emphasize the need to improve the "quality" of administrative data by including a POA indicator if these data are to serve as the information infrastructure for quality reporting.

Acuity and case management: a healthy dose of outcomes, part III.

PURPOSE OF STUDY: This is the third of a 3-part series presenting 2 effective applications--acuity and dosage--that describe how the business case for case management (CM) can be made. In Part I, dosage and acuity concepts were explained as client need-severity, CM intervention-intensity, and CM activity-dose prescribed by amount, frequency, duration, and breadth of activities. Concepts were presented that related the practice of CM to the use of evidence-based practice (EBP), knowledge, and methods and the development of instruments that measure and score pivotal CM actions. Part I also featured a specific exemplar, the CM Acuity Tool, and described how to use acuity to identify and score the complexity of a CM case. Part II further explained dosage and 2 acuity instruments, the Acuity Tool and AccuDiff. Part III presents linkage to EBP and practical applications. PRIMARY PRACTICE SETTING(S): The information contained in the 3-part series applies to all CM practice settings and contains ideas and recommendations useful to CM generalists, specialists, supervisors, and business and outcomes managers. The Acuity Tools Project was developed from frontline CM practice in one large, national telephonic CM company. METHODOLOGY AND SAMPLE: Dosage: A literature search failed to find research into dosage of a behavioral intervention. The Huber-Hall model was developed and tested in a longitudinal study of CM models in substance abuse treatment and reported in the literature. Acuity: A structured literature search and needs assessment launched the development of the suite of acuity tools. A gap analysis identified that an instrument to assign and measure case acuity specific to CM activities was needed. Clinical experts, quality specialists, and business analysts (n = 7) monitored the development and testing of the tools, acuity concepts, scores, differentials, and their operating principles and evaluated the validity of the acuity tools' content related to CM activities. During the pilot phase of development, interrater reliability testing of draft and final tools for evaluator concordance, b testing for content accuracy and appropriateness, and representative sample size testing were done. Expert panel reviews occurred at multiple junctures along the development pathway, including the 5 critical points after initial tool draft and both before and after b-test (n = 5) and pilot-test (n = 28) evaluations. The pilot testing body (n = 33) consisted of a team of case managers (n = 28) along with quality analysts (n = 2), supervisory personnel (n = 2), and the lead product analyst (the developer). Product evaluation included monitoring weekly reports of open cases for the 28 case managers for 3 months (June-August 2000). RESULTS: The Acuity Tools Suite was used to calculate individual case acuity, overall caseload acuity profiles, case length, and acuity differentials. Normal distributions and outliers were analyzed and the results were used for internal quality improvement and outcomes monitoring. IMPLICATIONS FOR CM PRACTICE: To show value, case managers need to access the evidence base for practice, use tools to capture quantities of intervention intensity, and precisely specify the activities that produce better outcomes. Acuity and dosage can help case managers explore and fully describe their own practice in ways that can be measured, and thus provide data and evidence that contributes to the accumulating body of definitive proof regarding the exceptional worth of CM. Proving business and professional worth in CM through EBP is a clarion call that case managers must heed and an innovation that all case managers can practice.

New approaches to reimbursement schemes based on patient classification systems and their comparison.

We propose reimbursement schemes based on patient classification systems (PCSs) that include adjustments for length of stay (LOS) and exceptional costs and are designed to minimize undesirable effects of economic incentives. In addition, a statistical approach to compare the schemes and the underlying PCSs is proposed, where costs and LOSs for two successive years are used. The first year data provides estimates of the class cost means and the next year's reimbursements which are compared with the second year's costs. This method focuses on the predictive power of a PCS and differs from the usual retrospective analyses based on the proportion of explained variance for single year data. The approach is applied to discharge data of Swiss hospitals where stays are grouped according to five PCSs: All Patient Diagnosis-Related Groups (AP-DRGs), All Patient Refined Diagnosis-Related Groups (APR-DRGs), International Refined Diagnosis-Related Groups (IR-DRGs), Australian Refined Diagnosis-Related Groups (AR-DRGs), and SQLape. When adjusting for LOS and outliers, these systems do not differ substantially in their ability to predict cost of stay. Therefore, increasing the number of classes does not necessarily improve cost predictions. However, the payment of a fixed amount per diem (not exceeding the marginal cost) and correcting the reimbursements for exceptional costs substantially reduces the average discrepancy between costs and reimbursements.

[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.

[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.