Efficient evaluation of center-level emergency surgery performance using a high-yield procedure set: A step towards an EGS registry.

BACKGROUND: Emergency general surgery (EGS) lacks mechanisms to compare performance between institutions. Focusing on higher-risk procedures may efficiently identify outliers. METHODS: EGS patients were identified from the 2016 State Inpatient Databases of Florida, New York, and Kentucky. Risk-adjusted mortality was calculated as an O:E ratio, generating expected mortality from a model including demographic and procedural factors. Outliers were centers whose 90% confidence intervals excluded 1. This was repeated in several subsets, to determine if these yielded outliers similar to the overall dataset. RESULTS: We identified 45,430 EGS patients. Overall, 3 high performing centers and 5 low performing centers were identified. Exclusion of appendectomies and cholecystectomies resulted in a remaining data set of 13,569 patients (29.9% of the overall data set), with 2 high performers and 5 low performers. One low performer in the limited data set was not identified in the overall set. CONCLUSION: Evaluation of 5 procedures, making up less than a third of EGS, identifies most outliers. A streamlined monitoring procedure may facilitate maintenance of an EGS registry.

Organisational and financial consequences of the early discharge of patients treated for acute bacterial skin and skin structure infection and osteomyelitis in infectious disease departments in Greece, Italy and Spain: a scenario analysis.

OBJECTIVE: The aim of the analysis is to assess the organisational and economic consequences of adopting an early discharge strategy for the treatment of acute bacterial skin and skin structure infection (ABSSSI) and osteomyelitis within infectious disease departments. SETTING: Infectious disease departments in Greece, Italy and Spain. PARTICIPANTS: No patients were involved in the analysis performed. INTERVENTIONS: An analytic framework was developed to consider two alternative scenarios: standard hospitalisation care or an early discharge strategy for patients hospitalised due to ABSSSI and osteomyelitis, from the perspective of the National Health Services of Greece, Italy and Spain. The variables considered were: the number of annual hospitalisations eligible for early discharge, the antibiotic treatments considered (ie, oral antibiotics and intravenous long-acting antibiotics), diagnosis-related group (DRG) reimbursements, number of days of hospitalisation, incidence and costs of hospital-acquired infections, additional follow-up visits and intravenous administrations. Data were based on published literature and expert opinions. PRIMARY AND SECONDARY OUTCOME MEASURES: Number of days of hospitalisation avoided and direct medical costs avoided. RESULTS: The total number of days of hospitalisation avoided on a yearly basis would be between 2216 and 5595 in Greece (-8/-21 hospital beds), between 15 848 and 38 444 in Italy (-57/-135 hospital beds) and between 7529 and 23 520 in Spain (-27/-85 hospital beds). From an economic perspective, the impact of the early discharge scenario is a reduction between €45 036 and €149 552 in Greece, a reduction between €182 132 and €437 990 in Italy and a reduction between €292 284 and €884 035 in Spain. CONCLUSIONS: The early discharge strategy presented would have a positive organisational impact on National Health Services, leading to potential savings in beds, and to a reduction of hospital-acquired infections and costs.

Comparison of Epithor clinical national database and medico-administrative database to identify the influence of case-mix on the estimation of hospital outliers.

BACKGROUND: The national Epithor database was initiated in 2003 in France. Fifteen years on, a quality assessment of the recorded data seemed necessary. This study examines the completeness of the data recorded in Epithor through a comparison with the French PMSI database, which is the national medico-administrative reference database. The aim of this study was to demonstrate the influence of data quality with respect to identifying 30-day mortality hospital outliers. METHODS: We used each hospital's individual FINESS code to compare the number of pulmonary resections and deaths recorded in Epithor to the figures found in the PMSI. Centers were classified into either the good-quality data (GQD) group or the low-quality data (LQD) group. To demonstrate the influence of case-mix quality on the ranking of centers with low-quality data, we used 2 methods to estimate the standardized mortality rate (SMR). For the first (SMR1), the expected number of deaths per hospital was estimated with risk-adjustment models fitted with low-quality data. For the second (SMR2), the expected number of deaths per hospital was estimated with a linear predictor for the LQD group using the coefficients of a logistic regression model developed from the GQD group. RESULTS: Of the hospitals that use Epithor, 25 were classified in the GQD group and 75 in the LQD group. The 30-day mortality rate was 2.8% (n = 300) in the GQD group vs. 1.9% (n = 181) in the LQD group (P <0.0001). The between-hospital differences in SMR1 appeared substantial (interquartile range (IQR) 0-1.036), and they were even higher in SMR2 (IQR 0-1.19). SMR1 identified 7 hospitals as high-mortality outliers. SMR2 identified 4 hospitals as high-mortality outliers. Some hospitals went from non-outlier to high mortality and vice-versa. Kappa values were roughly 0.46 and indicated moderate agreement. CONCLUSION: We found that most hospitals provided Epithor with high-quality data, but other hospitals needed to improve the quality of the information provided. Quality control is essential for this type of database and necessary for the unbiased adjustment of regression models.

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.

Are Case Volume and Facility Complexity Level Associated With Postoperative Complications After Hip Fracture Surgery in the Veterans Affairs Healthcare System?

BACKGROUND: Hospital-related factors associated with mortality and morbidity after hip fracture surgery are not completely understood. The Veterans Health Administration (VHA) is the largest single-payer, networked healthcare system in the country serving a relatively homogenous patient population with facilities that vary in size and resource availability. These characteristics provide some degree of financial and patient-level controls to explore the association, if any, between surgical volume and facility resource availability and hospital performance regarding postoperative complications after hip fracture surgery. QUESTIONS/PURPOSES: (1) Do VHA facilities with the highest complexity level designation (Level 1a) have a disproportionate number of better-than-expected performance outliers for major postoperative complications compared with lower-complexity level facilities? (2) Do VHA facilities with higher hip fracture surgical volume have a disproportionate number of better-than-expected performance outliers for major postoperative complications compared with lower-volume facilities? METHODS: We explored the Veterans Affairs Surgical Quality Improvement Project (VASQIP) database from October 2001 to September 2012 for records of hip fracture surgery performed. Data reliability of the VASQIP database has been previously validated. We excluded nine of the 98 VHA facilities for contributing fewer than 30 records. The remaining 89 VHA facilities provided 23,029 records. The VHA designates a complexity level to each facility based on multiple criteria. We labeled facilities with a complexity Level 1a (38 facilities)-the highest achievable VHA designated complexity level-as high complexity; we labeled all other complexity level designations as low complexity (51 facilities). Facility volume was divided into tertiles: high (> 277 hip fracture procedures during the sampling frame), medium (204 to 277 procedures), and low (< 204 procedures). The patient population treated by low-complexity facilities was older, had a higher prevalence of severe chronic obstructive pulmonary disease (26% versus 22%, p < 0.001), and had a higher percentage of patients having surgery within 2 days of hospital admission (83% versus 76%, p < 0.001). High-complexity facilities treated more patients with recent congestive heart failure exacerbation (4% versus 3%, p < 0.001). We defined major postoperative complications as having at least one of the following: death within 30 days of surgery, cardiac arrest requiring cardiopulmonary resuscitation, new q-wave myocardial infarction, deep vein thrombosis and/or pulmonary embolism, ventilator dependence for at least 48 hours after surgery, reintubation for respiratory or cardiac failure, acute renal failure requiring renal replacement therapy, progressive renal insufficiency with a rise in serum creatinine of at least 2 mg/dL from preoperative value, pneumonia, or surgical site infection. We used the observed-to-expected ratio (O/E ratio)-a risk-adjusted metric to classify facility performance-for major postoperative complications to assess the performance of VHA facilities. Outlier facilities with 95% confidence intervals (95% CI) for O/E ratio completely less than 1.0 were labeled "exceed expectation;" those that were completely greater than 1.0 were labeled "below expectation." We compared differences in the distribution of outlier facilities between high and low-complexity facilities, and between high-, medium-, and low-volume facilities using Fisher's exact test. RESULTS: We observed no association between facility complexity level and the distribution of outlier facilities (high-complexity: 5% exceeded expectation, 5% below expectation; low-complexity: 8% exceeded expectation, 2% below expectation; p = 0.742). Compared with high-complexity facilities, the adjusted odds ratio for major postoperative complications for low-complexity facilities was 0.85 (95% CI, 0.67-1.09; p = 0.108).We observed no association between facility volume and the distribution of outlier facilities: 3% exceeded expectation and 3% below expectation for high-volume; 10% exceeded expectation and 3% below expectation for medium-volume; and 7% exceeded expectation and 3% below expectation for low-volume; p = 0.890). The adjusted odds ratios for major postoperative complications were 0.87 (95% CI, 0.73-1.05) for low- versus high-volume facilities and 0.89 (95% CI, 0.79-1.02] for medium- versus high-volume facilities (p = 0.155). CONCLUSIONS: These results do not support restricting facilities from treating hip fracture patients based on historical surgical volume or facility resource availability. Identification of consistent performance outliers may help health care organizations with multiple facilities determine allocation of services and identify characteristics and processes that determine outlier status in the interest of continued quality improvement. LEVEL OF EVIDENCE: Level III, therapeutic study.

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.

Canadian Clinical Practice Guidelines for Rosacea.

Rosacea is a chronic facial inflammatory dermatosis characterized by background facial erythema and flushing and may be accompanied by inflammatory papules and pustules, cutaneous fibrosis and hyperplasia known as phyma, and ocular involvement. These features can have adverse impact on quality of life, and ocular involvement can lead to visual dysfunction. The past decade has witnessed increased research into pathogenic pathways involved in rosacea and the introduction of novel treatment innovations. The objective of these guidelines is to offer evidence-based recommendations to assist Canadian health care providers in the diagnosis and management of rosacea. These guidelines were developed by an expert panel of Canadian dermatologists taking into consideration the balance of desirable and undesirable outcomes, the quality of supporting evidence, the values and preferences of patients, and the costs of treatment. The 2015 Cochrane review "Interventions in Rosacea" was used as a source of clinical trial evidence on which to base the recommendations.

Feasibility of Report Cards for Measuring Anesthesiologist Quality for Cardiac Surgery.

BACKGROUND: In creating the Merit-Based Incentive Payment System, Congress has mandated pay-for-performance (P4P) for all physicians, including anesthesiologists. There are currently no National Quality Forum-endorsed risk-adjusted outcome metrics for anesthesiologists to use as the basis for P4P. METHODS: Using clinical data from the New York State Cardiac Surgery Reporting System, we conducted a retrospective observational study of 55,436 patients undergoing cardiac surgery between 2009 and 2012. Hierarchical logistic regression modeling was used to examine the variation in in-hospital mortality or major complications (Q-wave myocardial infarction, renal failure, stroke, and respiratory failure) among anesthesiologists, controlling for patient demographics, severity of disease, comorbidities, and hospital quality. RESULTS: Although the variation in performance among anesthesiologists was statistically significant (P = 0.025), none of the anesthesiologists in the sample was classified as a high- or low-performance outliers. The contribution of anesthesiologists to outcomes represented 0.51% of the overall variability in patient outcomes (intraclass correlation coefficient [ICC] = 0.0051; 95% confidence interval [CI], 0.002-0.014), whereas the contribution of hospitals to patient outcomes was 2.90% (ICC = 0.029; 95% CI, 0.017-0.050). The anesthesiologist median odds ratio (MOR) was 1.13 (95% CI, 1.08-1.24), suggesting that the variation between anesthesiologist was modest, whereas the hospital MOR was 1.35 (95% CI, 1.25-1.48). In a separate analysis, the contribution of surgeons to overall outcomes represented 1.76% of the overall variability in patient outcomes (ICC = 0.018, 95% CI, 0.010-0.031), and the surgeon MOR was 1.26 (95% CI, 1.19-1.37). Twelve of the surgeons were identified as performance outliers. CONCLUSIONS: The impact of anesthesiologists on the total variability in cardiac surgical outcomes was probably about one-fourth as large as the surgeons' contribution. None of the anesthesiologists caring for cardiac surgical patients in New York State over a 3+ year period were identified as performance outliers. The use of a performance metric based on death or major complications for P4P may not be feasible for cardiac anesthesiologists.

The ANZROD model: better benchmarking of ICU outcomes and detection of outliers.

OBJECTIVE: To compare the impact of the 2013 Australian and New Zealand Risk of Death (ANZROD) model and the 2002 Acute Physiology and Chronic Health Evaluation (APACHE) III-j model as risk-adjustment tools for benchmarking performance and detecting outliers in Australian and New Zealand intensive care units. METHODS: Data were extracted from the Australian and New Zealand Intensive Care Society Adult Patient Database for all ICUs that contributed data between 1 January 2010 and 31 December 2013. Annual standardised mortality ratios (SMRs) were calculated for ICUs using the ANZROD and APACHE III-j models. They were plotted on funnel plots separately for each hospital type, with ICUs above the upper 99.8% control limit considered as potential outliers with worse performance than their peer group. Overdispersion parameters were estimated for both models. Overall fit was assessed using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Outlier association with mortality was assessed using a logistic regression model. RESULTS: The ANZROD model identified more outliers than the APACHE III-j model during the study period. The numbers of outliers in rural, metropolitan, tertiary and private hospitals identified by the ANZROD model were 3, 2, 6 and 6, respectively; and those identified by the APACHE III-j model were 2, 0, 1 and 1, respectively. The degree of overdispersion was less for the ANZROD model compared with the APACHE III-j model in each year. The ANZROD model showed better overall fit to the data, with smaller AIC and BIC values than the APACHE III-j model. Outlier ICUs identified using the ANZROD model were more strongly associated with increased mortality. CONCLUSION: The ANZROD model reduces variability in SMRs due to casemix, as measured by overdispersion, and facilitates more consistent identification of true outlier ICUs, compared with the APACHE III-j model.

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.

[Medical and economic evaluation of oncological inpatients in 14 Belgian hospitals]. / Analyse médico-économique de la patientèle oncologique de 14 hôpitaux belges.

INTRODUCTION: A prospective payment system per DRG is announced in Belgium. Is this kind of financing system adequate for oncology? Objectives of this study are: to analyze medical and economical characteristics of oncological inpatients and evaluate the homogeneity of costs and length of stay per DRG. METHODS: The study was realized in 14 Belgian hospitals, with 2010 data. Inpatients with primary diagnosis of neoplasms were selected in medical and administrative databases. Characteristics of patients as well as length of stay and cost (hospital perspective) were analyzed. The homogeneity of costs and length of stay is measured by calculating the coefficient of variation (standard deviation divided by the mean). RESULTS: The length of stay (standard deviation) is 9.72 days (12.64). The variation is high per DRG. The average cost (standard deviation) is 7689.28€ (10,418) and is also variable from one DRG to another one. There are 5% of high-length of stay outliers and 0.2% of low-length of stay outliers. There are 4.7% of high-cost outliers and 0.2% of low-cost outliers. The withdrawal of outliers improves the homogeneity of cost and length of stay per APR-DRG. DISCUSSION AND CONCLUSION: There is a homogeneity of costs and length of stay per DRG and per severity of illness. A prospective payment system per DRG would probably be applicable for these patients. It is however necessary to plan an appropriate and additional financing of all elements susceptible to stimulate innovation in the management of oncology and to stimulate the quality of care by adding financial stimulants.

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.

Devising outlier-based alerts for medication orders.

Drugs are chemical substances, which can, on consumption and under certain conditions, be toxic and cause Adverse Drug Reactions (ADRs) in patients. This paper puts forth the proposition of generating a systemic alert to a clinician, at the time of placing a medication order for a patient, when the number of ADRs associated with the selected medication is significantly different from the number of ADRs associated with other drugs approved for the same therapeutic area.

Effects of the Ten Percent Cap in Medicare Home Health Care on Treatment Intensity and Patient Discharge Status.

OBJECTIVE: To estimate the effect of the 10 percent cap introduced to Medicare home health care on treatment intensity and patient discharge status. DATA SOURCES: Medicare Denominator, Medicare Home Health Claims, and Medicare Provider of Services Files from 2008 through 2010. STUDY DESIGN: We used agency-level variation in the proportion of outlier payments prior to the implementation of the 10 percent cap to identify how home health agencies adjusted the number of home health visits and patient discharge status under the new law. PRINCIPAL FINDINGS: Under the 10 percent cap, agencies dramatically decreased the number of service visits. Agencies also dropped relatively healthy patients and sent sicker patients to nursing homes. CONCLUSIONS: The drastic reduction in the number of service visits and discontinuation of relatively healthy patients from home health care suggest that the 10 percent cap improved the efficiency of home health services as intended. However, the 10 percent cap increased other types of health care expenditures by pushing sicker patients to use more expensive health services.

Influence of outliers on accuracy estimation in genomic prediction in plant breeding.

Outliers often pose problems in analyses of data in plant breeding, but their influence on the performance of methods for estimating predictive accuracy in genomic prediction studies has not yet been evaluated. Here, we evaluate the influence of outliers on the performance of methods for accuracy estimation in genomic prediction studies using simulation. We simulated 1000 datasets for each of 10 scenarios to evaluate the influence of outliers on the performance of seven methods for estimating accuracy. These scenarios are defined by the number of genotypes, marker effect variance, and magnitude of outliers. To mimic outliers, we added to one observation in each simulated dataset, in turn, 5-, 8-, and 10-times the error SD used to simulate small and large phenotypic datasets. The effect of outliers on accuracy estimation was evaluated by comparing deviations in the estimated and true accuracies for datasets with and without outliers. Outliers adversely influenced accuracy estimation, more so at small values of genetic variance or number of genotypes. A method for estimating heritability and predictive accuracy in plant breeding and another used to estimate accuracy in animal breeding were the most accurate and resistant to outliers across all scenarios and are therefore preferable for accuracy estimation in genomic prediction studies. The performances of the other five methods that use cross-validation were less consistent and varied widely across scenarios. The computing time for the methods increased as the size of outliers and sample size increased and the genetic variance decreased.

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.

Reforming reimbursement of public hospitals in Greece during the economic crisis: Implementation of a DRG system.

OBJECTIVES: Until recently, in-patient NHS hospital care in Greece was reimbursed via an anachronistic and under-priced retrospective per diem system, which has been held primarily responsible for continuous budget deficits. The purpose of this paper is to present the efforts of the Ministry of Health (MoH) to implement a new DRG-based payment system. METHODS: As in many countries, the decision was to adopt a patient classification from abroad and to refine it for use in Greece with national data. Pricing was achieved with a combination of activity-based costing with data from selected Greek hospitals, and "imported" cost weights. Data collection, IT support and monitoring are provided via ESY.net, a web-based facility developed and implemented by the MoH. RESULTS: After an initial pilot testing of the classification in 20 hospitals, complete DRG reimbursement data was reported by 113 hospitals (85% of total) for the fourth quarter of 2011. The recorded monthly increase in patient discharges billed with the new system and in revenue implies increasing adaptability by the hospitals. However, the unfavorable inlier vs. outlier distribution of discharges and revenue observed in some health regions signifies the need for corrective actions. CONCLUSIONS: The importance of this reimbursement reform is discussed in light of the current crisis faced by the Greek economy. There is yet much to be done and many projects are currently in progress to support this effort; however the first cost containment results are encouraging.