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This article examined the past performance of 36 Israeli child development account funds from 12 provident funds managers over three levels of risk for each manager. The results revealed that at times there was a large gap between the fund’s stated level of risk and the actual returns. In most cases, an increase in risk was accompanied by an increase in returns, except for medium-risk managers. Two managers failed to achieve above-average returns in any of their funds, regardless of their levels of risk. Finally, the managers who tended to be successful during periods of negative returns were generally those who sought average returns rather than those who tried for outsized returns. This study’s findings should provide parents with some insights to consider when choosing the child development accounts in which they want to invest. [ABSTRACT FROM AUTHOR]

Abstract Background Intensive care unit (ICU) length of stay (LOS) and the risk adjusted equivalent (RALOS) have been used as quality metrics. The latter measures entail either ratio or difference formulations or ICU random effects (RE), which have not been previously compared. Methods From calendar year 2016 data of an adult ICU registry-database (Australia & New Zealand Intensive Care Society (ANZICS) CORE), LOS predictive models were established using linear (LMM) and generalised linear (GLMM) mixed models. Model fixed effects quality-metric formulations were estimated as RALOSR for LMM (geometric mean derived from log(ICU LOS)) and GLMM (day) and observed minus expected ICU LOS (OMELOS from GLMM). Metric confidence intervals (95%CI) were estimated by bootstrapping; random effects (RE) were predicted for LMM and GLMM. Forest-plot displays of ranked quality-metric point-estimates (95%CI) were generated for ICU hospital classifications (metropolitan, private, rural/regional, and tertiary). Robust rank confidence sets (point estimate and 95%CI), both marginal (pertaining to a singular ICU) and simultaneous (pertaining to all ICU differences), were established. Results The ICU cohort was of 94,361 patients from 125 ICUs (metropolitan 16.9%, private 32.8%, rural/regional 6.4%, tertiary 43.8%). Age (mean, SD) was 61.7 (17.5) years; 58.3% were male; APACHE III severity-of-illness score 54.6 (25.7); ICU annual patient volume 1192 (702) and ICU LOS 3.2 (4.9). There was no concordance of ICU ranked model predictions, GLMM versus LMM, nor for the quality metrics used, RALOSR, OMELOS and site-specific RE for each of the ICU hospital classifications. Furthermore, there was no concordance between ICU ranking confidence sets, marginal and simultaneous for models or quality metrics. Conclusions Inference regarding adjusted ICU LOS was dependent upon the statistical estimator and the quality index used to quantify any LOS differences across ICUs. That is, there was no “one best model”; thus, ICU “performance” is determined by model choice and any rankings thereupon should be circumspect.

Background: Intensive care unit (ICU) length of stay (LOS) and the risk adjusted equivalent (RALOS) have been used as quality metrics. The latter measures entail either ratio or difference formulations or ICU random effects (RE), which have not been previously compared. Methods: From calendar year 2016 data of an adult ICU registry-database (Australia & New Zealand Intensive Care Society (ANZICS) CORE), LOS predictive models were established using linear (LMM) and generalised linear (GLMM) mixed models. Model fixed effects quality-metric formulations were estimated as RALOSR for LMM (geometric mean derived from log(ICU LOS)) and GLMM (day) and observed minus expected ICU LOS (OMELOS from GLMM). Metric confidence intervals (95%CI) were estimated by bootstrapping; random effects (RE) were predicted for LMM and GLMM. Forest-plot displays of ranked quality-metric point-estimates (95%CI) were generated for ICU hospital classifications (metropolitan, private, rural/regional, and tertiary). Robust rank confidence sets (point estimate and 95%CI), both marginal (pertaining to a singular ICU) and simultaneous (pertaining to all ICU differences), were established. Results: The ICU cohort was of 94,361 patients from 125 ICUs (metropolitan 16.9%, private 32.8%, rural/regional 6.4%, tertiary 43.8%). Age (mean, SD) was 61.7 (17.5) years; 58.3% were male; APACHE III severity-of-illness score 54.6 (25.7); ICU annual patient volume 1192 (702) and ICU LOS 3.2 (4.9). There was no concordance of ICU ranked model predictions, GLMM versus LMM, nor for the quality metrics used, RALOSR, OMELOS and site-specific RE for each of the ICU hospital classifications. Furthermore, there was no concordance between ICU ranking confidence sets, marginal and simultaneous for models or quality metrics. Conclusions: Inference regarding adjusted ICU LOS was dependent upon the statistical estimator and the quality index used to quantify any LOS differences across ICUs. That is, there was no "one best model"; thus, ICU "performance" is determined by model choice and any rankings thereupon should be circumspect. [ABSTRACT FROM AUTHOR]

Control charts play an effective role in monitoring and controlling the performance of health care. It helps to determine the strategy to improve the process and identify the causes of variations. In recent years, the risk adjusted memory type control charts have received reasonable attention in monitoring surgical outcomes. In this research, we used the concept of an adaptive exponentially weighted moving average (AEWMA) control chart and proposed a new adaptive risk adjusted exponentially weighted moving average (ARAEWMA) control chart by using the accelerated failure time (AFT) regression. A real data set of the cardiac surgery patients is used for analysis and the patient condition is counted by personnet score method. The proposed ARAEWMA control chart is fitted by using the AFT model and run length profiles are computed at different shifts. The proposed ARAEWMA chart is better in shift detection and showed efficient results than the risk adjusted exponentially weighted moving average control chart. [ABSTRACT FROM AUTHOR]

The fnancial stability cyclical behavior is analyzed in this study which is seen as the risk taken by the Islamic banks for the period of 2013 to 2018. For this research study, researcher have used the dynamic panel data of 20 Islamic banks evaluated by the GMM (GMM) technique to investigate that whether the procyclicality in the fnancial stability of Islamic banks exist or not. The study found that there is no procyclicality or countercyclicality existing in the fnancial stability of Islamic banks which means that the risk taking behavior of Islamic banks is not infuenced either by the upturns or the downturns of the economy. In addition, the borrowing activities of the Islamic banks also have no infuence on the fnancial stability. Study found few signifcant results i.e. the proxy of insolvency risk i.e. Z sore of return on equity is found to be infuenced by the capitalization ratio and asset growth rate, risk adjusted asset returns is found to be infuenced by business cycle, capital measure i.e. CAPTA, BC*C and asset growth rate and risk adjusted market returns is infuenced by the capitalization ratio ETA and capital measure (CAPR). Study conclude that out of these three, asset growth rate affect the bank’s insolvency risk as compared to the others. This study is unique in nature and provide comprehensive model and added value to the previous researches. Study is helpful for the policymakers to understand the procyclicality testing and fnancial stability of Islamic banking sector. [ABSTRACT FROM AUTHOR]

Existing literature on market seasonality focuses mainly on returns anomalies with little or no attention to risk adjustment. This study investigates risk-adjusted, and Bonferroni adjusted day-of-the-week anomalies in nine emerging Asian stock markets. The data consist of the daily prices of nine stock indices from January 1997 to September 2019. The MSCI emerging market index was employed as a proxy of time-varying risk. Findings/originality: The results confirm the presence of day-of-the-week anomalies in emerging Asian markets, and the addition of the market risk proxy has failed to fade these patterns. Finally, after consideration of time-varying risk premium and applying Bonferroni Correction type adjustment, several market anomalies remain. However, both adjustments partially eliminate the significance of these patterns. The presence of these anomalies suggests that little of this can be accounted for the MSCI-EM stock price index. The results also confirm that systematic risk level varies from Monday to Friday.

The American College of Surgeons Committee on Trauma revised the Resources for Optimal Care of the Injured Patient to include the criteria for trauma centers to participate in a risk-adjusted benchmarking system. Trauma Quality Improvement Program is currently the risk-adjusted benchmarking program sponsored by the American College of Surgeons, which will be required of all trauma centers to participate in early 2017. Prior to this, there were no risk-adjusted programs for Level III verified trauma centers. The Ohio Society of Trauma Nurse Leaders is a collaborative group made up of trauma program managers, coordinators, and other trauma leaders who meet 6 times a year. Within this group, a Level III Subcommittee was formed initially to provide a place for the Level III centers to discuss issues specific to the Level III centers. When the new requirement regarding risk-adjustment became official, the subcommittee agreed to begin reporting simple data points with the idea to risk adjust in the future. [ABSTRACT FROM AUTHOR]

Background: Single-incision laparoscopic colectomy (SILC) has emerged as a viable minimally invasive surgical approach with benefits and limitations yet to be fully elucidated. Although shown to be safe and feasible, characterization of the learning curve has not been addressed. Our aim was to identify a learning curve for SILC right hemicolectomy and to determine the incidence of operative failure and complication rates during this phase. Methods: Over a 2-year period, data from 54 consecutive SILC cases performed by the same surgeon were tabulated in an institutional review board—approved database. A learning curve was generated utilizing cumulative sum (CUSUM) methodology to assess changes in total operative time (OT) across the case sequence. A separate learning curve was generated utilizing risk-adjusted CUSUM analysis, taking into account patient risk factors (i.e., age, American Society of Anesthesiologists score, body mass index, prior abdominal surgeries, and tumor size for malignant cases) and operative failure (i.e., prolonged OT, conversion to open surgery, intraoperative and 30-day postoperative complications, prolonged length of stay, reoperation, readmission, and mortality). Results: Patients had a mean age of 63.6 ± 11.5 years, mean body mass index of 27.3 ± 3.9 kg/m 2, and median American Society of Anesthesiologists score of 2. Mean OT and length of stay were 123.5 ± 28.9 min and 3.9 ± 2.4 days, respectively. There were no conversions or oncologic failures. Six patients developed 30-day postoperative complications. CUSUM analysis of OT identified achievement of the learning phase after 30 cases. When taking into account both analyses, the rate of operative failure was not statistically different between the initial 30 and the final 24 cases. Conclusions: In our experience, the learning curve is achieved between 30 to 36 cases. Offering this minimally invasive surgical approach does not result in increased complications or harmful results even in the early phases of the learning curve. [ABSTRACT FROM AUTHOR]

Purpose: The goal of this research was to estimate 12-month survival rates for a large sample of elderly veterans after hip fracture with a risk-adjusted model and to compare the results of men to those of women. Methods: The study design was a retrospective, secondary data analysis of national Veterans Health Administration (VHA) Medicare beneficiaries. The study population was 43,165 veterans with hip fracture first admitted to a Medicare-eligible facility during our specified enrollment period of 1999–2002. Measurement was a Cox proportional hazard model or survival analysis of hip fracture patients with an outcome of death over a 1 year period after discharge controlled by age, gender, and selected Elixhauser comorbidities. Results: The unadjusted, 1 year mortality rates (30 days = 9.7%, 90 days = 17.5%, 180 days = 24%, 365 days = 32.2%) were slightly higher than the adjusted rates (30 days = 8.9%, 90 days = 15.6%, 180 days = 21.8%, 1 year = 29.9%). The mortality odds for women 12 months after hip fracture were 18%, compared with 32% for men. The comorbidity adjustment suggested that the presence of metastatic cancer increased the risk of death by almost 4 times compared with those patients without this diagnosis. Other particularly high-risk conditions included congestive heart failure, renal failure, liver disease, lymphoma, and weight loss, each of which increased the 1 year mortality risk by approximately two-fold. Conclusions: One in 3 elderly male veterans who sustain a hip fracture dies within 1 year. Our work represents the first large study of hip fractures with a predominantly male sample and confirms that men have a higher mortality risk than women, as reported by previous researchers who used smaller samples that were mostly female. Fracture patients with metastatic cancer, renal failure, lymphoma, weight loss, and liver disease have higher mortality risks. The adverse outcomes associated with hip fracture argue for clinical intervention strategies, such as gait and balance testing, and osteoporosis diagnosis that may prevent fractures in both genders. [Copyright &y& Elsevier]

Most experts certainly agree that the health care payment systems of today lead to a lot of over-and misuse as well as underuse of health care services on the other side. The author argues to balance overtreatment-inducing payment systems for the individual practice (partly budgeted fee-for-service) with population based and risk adjusted shared savings for a certain regional population. He describes the model he developed with two sickness funds in Germany (AOK and LKK Baden-Wuerttemberg) and its promising results over several years. Three basic requirements are extracted out of the experiences in Kinzigtal: * The need for a balance of ethical and financial incentives to stimulate the professional pride in those who are delivering care * The need for a comprehensive set of health care utilization data for the population * The need for an entrepreneurial but health sciences based management company to reach highest efficiency rates [ABSTRACT FROM AUTHOR]