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Anesthesiology Nov 2010
Topics: Anesthesia; Databases, Factual; Humans; Risk; Risk Adjustment; Risk Factors
PubMed: 20966658
DOI: 10.1097/ALN.0b013e3181f7ab17 -
Journal of Health Economics Dec 2017I develop a model of insurer price-setting and consumer welfare under risk-adjustment, a policy commonly used to combat inefficient sorting due to adverse selection in...
I develop a model of insurer price-setting and consumer welfare under risk-adjustment, a policy commonly used to combat inefficient sorting due to adverse selection in health insurance markets. I use the model to illustrate graphically that risk-adjustment causes health plan prices to be based on costs not predicted by the risk-adjustment model ("residual costs") rather than total costs, either weakening or exacerbating selection problems depending on the correlation between demand and costs predicted by the risk-adjustment model. I then use a structural model to estimate the welfare consequences of risk-adjustment, finding a welfare gain of over $600 per person-year.
Topics: Algorithms; Economic Competition; Female; Humans; Insurance Selection Bias; Insurance, Health; Male; Models, Theoretical; Risk Adjustment
PubMed: 29248056
DOI: 10.1016/j.jhealeco.2017.04.004 -
Medicine Apr 2018Renal angiomyolipoma (AML) is a common benign tumor of the kidney. The main complication of AML is retroperitoneal hemorrhage caused by AML rupture, which can be severe... (Review)
Review
BACKGROUND
Renal angiomyolipoma (AML) is a common benign tumor of the kidney. The main complication of AML is retroperitoneal hemorrhage caused by AML rupture, which can be severe and life threatening. The risk of AML rupture used to be determined by tumor size. However, these criteria have been challenged by series of clinical studies and case reports, suggesting prediction AML rupture based on tumor size is not always reliable.
METHODS
The authors searched PubMed using "angiomyolipoma," "AML," and "rupture" and reviewed relevant studies. The authors investigated the risk factors of AML rupture using the retrieved literature. The authors also summarized current modalities to evaluate and manage AML.
RESULTS
It is established that risk of AML rupture is associated with lesion size. However, genetic abnormality, aneurysm formation, and pregnancy are also risk factors for tumor rupture. Thus, the prediction of AML rupture should be based on a more comprehensive risk assessment system. The management of renal AML and tumor rupture was also discussed in the present paper.
CONCLUSION
The risk of AML rupture is associated with but not exclusive to lesion size. Any decision to intervene AML must be based on multiple factors including risk, symptoms, and auxiliary findings.
Topics: Angiomyolipoma; Hemorrhage; Humans; Kidney Neoplasms; Retroperitoneal Space; Risk Adjustment; Risk Assessment; Risk Factors; Rupture, Spontaneous
PubMed: 29668633
DOI: 10.1097/MD.0000000000010497 -
Circulation Jan 2017
Review
Topics: Benchmarking; Cardiology Service, Hospital; Health Personnel; Hospitals; Humans; Outcome Assessment, Health Care; Risk Adjustment; Risk Assessment
PubMed: 28115411
DOI: 10.1161/CIRCULATIONAHA.116.025653 -
Deutsches Arzteblatt International Feb 2021
Topics: Colorectal Neoplasms; Digestive System Surgical Procedures; Humans; Morbidity; Risk Adjustment
PubMed: 33835008
DOI: 10.3238/arztebl.m2021.0055 -
Infection Control and Hospital... Aug 2021To determine whether electronically available comorbidities and laboratory values on admission are risk factors for hospital-onset Clostridioides difficile infection...
OBJECTIVE
To determine whether electronically available comorbidities and laboratory values on admission are risk factors for hospital-onset Clostridioides difficile infection (HO-CDI) across multiple institutions and whether they could be used to improve risk adjustment.
PATIENTS
All patients at least 18 years of age admitted to 3 hospitals in Maryland between January 1, 2016, and January 1, 2018.
METHODS
Comorbid conditions were assigned using the Elixhauser comorbidity index. Multivariable log-binomial regression was conducted for each hospital using significant covariates (P < .10) in a bivariate analysis. Standardized infection ratios (SIRs) were computed using current Centers for Disease Control and Prevention (CDC) risk adjustment methodology and with the addition of Elixhauser score and individual comorbidities.
RESULTS
At hospital 1, 314 of 48,057 patient admissions (0.65%) had a HO-CDI; 41 of 8,791 patient admissions (0.47%) at community hospital 2 had a HO-CDI; and 75 of 29,211 patient admissions (0.26%) at community hospital 3 had a HO-CDI. In multivariable regression, Elixhauser score was a significant risk factor for HO-CDI at all hospitals when controlling for age, antibiotic use, and antacid use. Abnormal leukocyte level at hospital admission was a significant risk factor at hospital 1 and hospital 2. When Elixhauser score was included in the risk adjustment model, it was statistically significant (P < .01). Compared with the current CDC SIR methodology, the SIR of hospital 1 decreased by 2%, whereas the SIRs of hospitals 2 and 3 increased by 2% and 6%, respectively, but the rankings did not change.
CONCLUSIONS
Electronically available patient comorbidities are important risk factors for HO-CDI and may improve risk-adjustment methodology.
Topics: Clostridioides; Clostridioides difficile; Clostridium Infections; Comorbidity; Cross Infection; Electronic Health Records; Hospitals; Humans; Risk Adjustment
PubMed: 33327970
DOI: 10.1017/ice.2020.1344 -
Cardiac Risk Assessment in Liver Transplant Candidates: Current Controversies and Future Directions.Hepatology (Baltimore, Md.) Jun 2021In the changing landscape of liver transplantation (LT), we are now evaluating older and sicker patients with more cardiovascular comorbidities, and the spectrum of... (Review)
Review
In the changing landscape of liver transplantation (LT), we are now evaluating older and sicker patients with more cardiovascular comorbidities, and the spectrum of cardiovascular disease is uniquely physiologically impacted by end-stage liver disease. Cardiac complications are now the leading cause of morbidity and mortality in LT recipients, and the pretransplant risk is exacerbated immediately during the transplant operation and continues long term under the umbrella of immunosuppression. Accurate risk estimation of cardiac complications before LT is paramount to guide allocation of limited health care resources and to improve both short-term and long-term clinical outcomes for patients. Current screening and diagnostic testing are limited in their capacity to accurately identify early coronary disease and myocardial dysfunction in persons with end-stage liver disease physiology. Furthermore, a number of testing modalities have not been evaluated in patients with end-stage liver disease. As a result, there is wide variation in cardiac risk assessment practices across transplant centers. In this review, we propose a definition for defining cardiac events in LT, evaluate the current evidence for surgery-related, short-term and long-term cardiac risk assessment in LT candidates, propose an evidence-based testing algorithm, and highlight specific gaps in knowledge and current controversies, identifying areas for future research.
Topics: Cardiovascular Diseases; End Stage Liver Disease; Humans; Liver Transplantation; Postoperative Complications; Risk Adjustment
PubMed: 33219576
DOI: 10.1002/hep.31647 -
Health Affairs (Project Hope) Jun 2016Under the Affordable Care Act, the risk-adjustment program is designed to compensate health plans for enrolling people with poorer health status so that plans compete on...
Under the Affordable Care Act, the risk-adjustment program is designed to compensate health plans for enrolling people with poorer health status so that plans compete on cost and quality rather than the avoidance of high-cost individuals. This study examined health plan incentives to limit covered services for mental health and substance use disorders under the risk-adjustment system used in the health insurance Marketplaces. Through a simulation of the program on a population constructed to reflect Marketplace enrollees, we analyzed the cost consequences for plans enrolling people with mental health and substance use disorders. Our assessment points to systematic underpayment to plans for people with these diagnoses. We document how Marketplace risk adjustment does not remove incentives for plans to limit coverage for services associated with mental health and substance use disorders. Adding mental health and substance use diagnoses used in Medicare Part D risk adjustment is one potential policy step toward addressing this problem in the Marketplaces.
Topics: Adult; Chronic Disease; Computer Simulation; Female; Health Insurance Exchanges; Humans; Insurance Coverage; Insurance, Health; Male; Mental Disorders; Motivation; Patient Protection and Affordable Care Act; Risk Adjustment; Substance-Related Disorders; United States
PubMed: 27269018
DOI: 10.1377/hlthaff.2015.1668 -
BMJ Open Aug 2021Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes....
OBJECTIVES
Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes. Current risk adjustment models are not optimal in terms of the number and nature of predictor variables included in the model and the treatment of missing data. We propose a statistically robust and parsimonious risk adjustment model for the purpose of benchmarking.
SETTING
This study analysed data from the multicentre Australia New Zealand Trauma Registry from 1 July 2016 to 30 June 2018 consisting of 31 trauma centres.
OUTCOME MEASURES
The primary endpoints were inpatient mortality and length of hospital stay. Firth logistic regression and robust linear regression models were used to study the endpoints, respectively. Restricted cubic splines were used to model non-linear relationships with age. Model validation was performed on a subset of the dataset.
RESULTS
Of the 9509 patients in the model development cohort, 72% were male and approximately half (51%) aged over 50 years . For mortality, cubic splines in age, injury cause, arrival Glasgow Coma Scale motor score, highest and second-highest Abbreviated Injury Scale scores and shock index were significant predictors. The model performed well in the validation sample with an area under the curve of 0.93. For length of stay, the identified predictor variables were similar. Compared with low falls, motor vehicle occupants stayed on average 2.6 days longer (95% CI: 2.0 to 3.1), p<0.001. Sensitivity analyses did not demonstrate any marked differences in the performance of the models.
CONCLUSION
Our risk adjustment model of six variables is efficient and can be reliably collected from registries to enhance the process of benchmarking.
Topics: Aged; Australia; Hospitals; Humans; Length of Stay; Male; Registries; Risk Adjustment
PubMed: 34426470
DOI: 10.1136/bmjopen-2021-050795 -
Circulation. Cardiovascular Quality and... Oct 2021Health status outcomes are increasingly being promoted as measures of health care quality, given their importance to patients. In heart failure (HF), an American College...
BACKGROUND
Health status outcomes are increasingly being promoted as measures of health care quality, given their importance to patients. In heart failure (HF), an American College of Cardiology/American Heart Association Task Force proposed using the proportion of patients with preserved health status as a quality measure but not as a performance measure because risk adjustment methods were not available.
METHODS
We built risk adjustment models for alive with preserved health status and for preserved health status alone in a prospective registry of outpatients with HF with reduced ejection fraction across 146 US centers between December 2015 and October 2017. Preserved health status was defined as not having a ≥5-point decrease in the Kansas City Cardiomyopathy Questionnaire Overall Summary score at 1 year. Using only patient-level characteristics, hierarchical multivariable logistic regression models were developed for 1-year outcomes and validated using data from 1 to 2 years. We examined model calibration, discrimination, and variability in sites' unadjusted and adjusted rates.
RESULTS
Among 3932 participants (median age [interquartile range] 68 years [59-75], 29.7% female, 75.4% White), 2703 (68.7%) were alive with preserved health status, 902 (22.9%) were alive without preserved health status, and 327 (8.3%) had died by 1 year. The final risk adjustment model for alive with preserved health status included baseline Kansas City Cardiomyopathy Questionnaire Overall Summary, age, race, employment status, annual income, body mass index, depression, atrial fibrillation, renal function, number of hospitalizations in the past 1 year, and duration of HF (optimism-corrected C statistic=0.62 with excellent calibration). Similar results were observed when deaths were ignored. The risk standardized proportion of patients alive with preserved health status across the 146 sites ranged from 62% at the 10th percentile to 75% at the 90th percentile. Variability across sites was modest and changed minimally with risk adjustment.
CONCLUSIONS
Through leveraging data from a large, outpatient, observational registry, we identified key factors to risk adjust sites' proportions of patients with preserved health status. These data lay the foundation for building quality measures that quantify treatment outcomes from patients' perspectives.
Topics: Aged; Female; Health Status; Heart Failure; Humans; Male; Quality of Life; Registries; Risk Adjustment; Stroke Volume; United States
PubMed: 34615366
DOI: 10.1161/CIRCOUTCOMES.121.008072