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International Journal of Environmental... May 2021Quality indicators (QIs) based on the Resident Assessment Instrument-Home Care (RAI-HC) offer the opportunity to assess home care quality and compare home care...
Quality indicators (QIs) based on the Resident Assessment Instrument-Home Care (RAI-HC) offer the opportunity to assess home care quality and compare home care organizations' (HCOs) performance. For fair comparisons, providers' QI rates must be risk-adjusted to control for different case-mix. The study's objectives were to develop a risk adjustment model for worsening or onset of urinary incontinence (UI), measured with the RAI-HC QI bladder incontinence, using the database HomeCareData and to assess the impact of risk adjustment on quality rankings of HCOs. Risk factors of UI were identified in the scientific literature, and multivariable logistic regression was used to develop the risk adjustment model. The observed and risk-adjusted QI rates were calculated on organization level, uncertainty addressed by nonparametric bootstrapping. The differences between observed and risk-adjusted QI rates were graphically assessed with a Bland-Altman plot and the impact of risk adjustment examined by HCOs tertile ranking changes. 12,652 clients from 76 Swiss HCOs aged 18 years and older receiving home care between 1 January 2017, and 31 December 2018, were included. Eight risk factors were significantly associated with worsening or onset of UI: older age, female sex, obesity, impairment in cognition, impairment in hygiene, impairment in bathing, unsteady gait, and hospitalization. The adjustment model showed fair discrimination power and had a considerable effect on tertile ranking: 14 (20%) of 70 HCOs shifted to another tertile after risk adjustment. The study showed the importance of risk adjustment for fair comparisons of the quality of UI care between HCOs in Switzerland.
Topics: Aged; Female; Home Care Services; Humans; Quality Indicators, Health Care; Quality of Health Care; Risk Adjustment; Switzerland
PubMed: 34063743
DOI: 10.3390/ijerph18115502 -
Postgraduate Medicine Aug 2021Cancer is a leading cause of venous thromboembolism (VTE), which contributes to significant morbidity and mortality in these patients. Increased thrombotic risk in... (Review)
Review
Cancer is a leading cause of venous thromboembolism (VTE), which contributes to significant morbidity and mortality in these patients. Increased thrombotic risk in cancer patients is modified by tumor-specific biology, disease-directed interventions, and individual comorbidities. Risk stratification for prophylaxis and treatment requires regular reevaluation of these factors, which can be facilitated by validated prediction tools. This review also discusses large clinical trial data (SELECT-D, HOKUSAI-VTE, ADAM VTE, CARAVAGGIO) demonstrating that direct oral anticoagulants (DOACs) are effective in the treatment of cancer-associated VTE, with comparable efficacy to the traditional choice of low molecular weight heparin. In the prophylactic setting derived from patients with cancer with increased VTE risk, DOACs also reduced the incidence of VTE with only modest increases in bleeding risk. The ease of DOAC administration and acceptable risk profile in the carefully selected patient make them an appealing choice for anticoagulation. In instances where the risk of gastrointestinal bleeding is of concern, apixaban, in particular, may still be a suitable option in place of LMWH. These improvements in our anticoagulation approach to cancer-associated VTE are well-timed to accompany the recent advances in disease-directed therapies that are enabling patients to live longer with cancer and therefore at increased risk of complications such as VTE.
Topics: Anticoagulants; Chemoprevention; Humans; Neoplasms; Patient Selection; Risk Adjustment; Risk Assessment; Treatment Outcome; Venous Thromboembolism
PubMed: 34255597
DOI: 10.1080/00325481.2021.1955542 -
Deutsches Arzteblatt International Feb 2021
Topics: Colorectal Neoplasms; Digestive System Surgical Procedures; Humans; Morbidity; Risk Adjustment
PubMed: 33835008
DOI: 10.3238/arztebl.m2021.0055 -
Journal of Health Care For the Poor and... 2022Health care providers are often evaluated on patient health outcomes and quality of care measures. The social determinants of health play an outsized role in determining...
Health care providers are often evaluated on patient health outcomes and quality of care measures. The social determinants of health play an outsized role in determining patient outcomes regardless of the quality of care delivered. As a result, providers caring for poor and underserved patients tend to receive lower value-adjusted payments, which exacerbates disparities in access to care. We conducted semi-structured interviews with 30 researchers, health policy constituents, and Medicaid payer and practice leaders in Oregon to better assess how to use social factors in risk adjustment modeling. While all 30 respondents agreed with the importance of social risk adjustment, we find that the experts have divergent perspectives on how to approach individual and community social risk. Moreover, many respondents felt dismayed because the data required are plagued by fragmentation and outdated privacy protection frameworks. Our findings suggest that alternative payment models must be better developed for low-income and underserved communities.
Topics: Health Policy; Humans; Medicaid; Oregon; Risk Adjustment; United States
PubMed: 35153206
DOI: 10.1353/hpu.2022.0007 -
Journal of the American College of... Dec 2023Congenital heart surgery (CHS) encompasses a heterogeneous population of patients and surgeries. Risk standardization models that adjust for patient and procedural...
BACKGROUND
Congenital heart surgery (CHS) encompasses a heterogeneous population of patients and surgeries. Risk standardization models that adjust for patient and procedural characteristics can allow for collective study of these disparate patients and procedures.
OBJECTIVES
We sought to develop a risk-adjustment model for CHS using the newly developed Risk Stratification for Congenital Heart Surgery for ICD-10 Administrative Data (RACHS-2) methodology.
METHODS
Within the Kids' Inpatient Database 2019, we identified all CHSs that could be assigned a RACHS-2 score. Hierarchical logistic regression (clustered on hospital) was used to identify patient and procedural characteristics associated with in-hospital mortality. Model validation was performed using data from 24 State Inpatient Databases during 2017.
RESULTS
Of 5,902,538 total weighted hospital discharges in the Kids' Inpatient Database 2019, 22,310 pediatric cardiac surgeries were identified and assigned a RACHS-2 score. In-hospital mortality occurred in 543 (2.4%) of cases. Using only RACHS-2, the mortality mode had a C-statistic of 0.81 that improved to 0.83 with the addition of age. A final multivariable model inclusive of RACHS-2, age, payer, and presence of a complex chronic condition outside of congenital heart disease further improved model discrimination to 0.87 (P < 0.001). Discrimination in the validation cohort was also very good with a C-statistic of 0.83.
CONCLUSIONS
We created and validated a risk-adjustment model for CHS that accounts for patient and procedural characteristics associated with in-hospital mortality available in administrative data, including the newly developed RACHS-2. Our risk model will be critical for use in health services research and quality improvement initiatives.
Topics: Child; Humans; Infant; Cardiac Surgical Procedures; Heart Defects, Congenital; Risk Adjustment; Hospital Mortality; Logistic Models; Risk Factors; Retrospective Studies
PubMed: 38030351
DOI: 10.1016/j.jacc.2023.09.826 -
Medical Care Aug 2023To risk-adjust the Potential Inpatient Complication (PIC) measure set and propose a method to identify large deviations between observed and expected PIC counts.
OBJECTIVE
To risk-adjust the Potential Inpatient Complication (PIC) measure set and propose a method to identify large deviations between observed and expected PIC counts.
DATA SOURCES
Acute inpatient stays from the Premier Healthcare Database from January 1, 2019 to December 31, 2021.
STUDY DESIGN
In 2014, the PIC list was developed to identify a broader set of potential complications that can occur as a result of care decisions. Risk adjustment for 111 PIC measures is performed across 3 age-based strata. Using patient-level risk factors and PIC occurrences, PIC-specific probabilities of occurrence are estimated through multivariate logistic regression models. Poisson Binomial cumulative mass function estimates identify deviations between observed and expected PIC counts across levels of patient-visit aggregation. Area under the curve (AUC) estimates are used to demonstrate PIC predictive performance in an 80:20 derivation-validation split framework.
DATA COLLECTION/EXTRACTION METHODS
We used N=3,363,149 administrative hospitalizations between 2019 and 2021 from the Premier Healthcare Database.
PRINCIPAL FINDINGS
PIC-specific model predictive performance was strong across PICs and age strata. Average area under the curve estimates across PICs were 0.95 (95% CI: 0.93-0.96), 0.91 (95% CI: 0.90-0.93), and 0.90 (95% CI: 0.89-0.91) for the neonate and infant, pediatric, and adult strata, respectively.
CONCLUSIONS
The proposed method provides a consistent quality metric that adjusts for the population's case mix. Age-specific risk stratification further addresses currently ignored heterogeneity in PIC prevalence across age groups. Finally, the proposed aggregation method identifies large PIC-specific deviations between observed and expected counts, flagging areas with a potential need for quality improvements.
Topics: Adult; Infant; Infant, Newborn; Humans; Child; Risk Adjustment; Inpatients; International Classification of Diseases; Hospitalization; Risk Factors
PubMed: 37219083
DOI: 10.1097/MLR.0000000000001865 -
Annals of Surgery Mar 2020We hypothesize the Distressed Communities Index (DCI), a composite socioeconomic ranking by ZIP code, will predict risk-adjusted outcomes after surgery.
OBJECTIVE
We hypothesize the Distressed Communities Index (DCI), a composite socioeconomic ranking by ZIP code, will predict risk-adjusted outcomes after surgery.
SUMMARY OF BACKGROUND DATA
Socioeconomic status affects surgical outcomes; however, the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) database does not account for these factors.
METHODS
All ACS NSQIP patients (17,228) undergoing surgery (2005 to 2015) at a large academic institution were paired with the DCI, which accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies. Developed by the Economic Innovation Group, DCI scores range from 0 (no distress) to 100 (severe distress). Multivariable regressions were used to evaluate ACS NSQIP predicted risk-adjusted effect of DCI on outcomes and inflation-adjusted hospital cost.
RESULTS
A total of 4522 (26.2%) patients came from severely distressed communities (top quartile). These patients had higher rates of medical comorbidities, transfer from outside hospital, emergency status, and higher ACS NSQIP predicted risk scores (all P < 0.05). In addition, these patients had greater resource utilization, increased postoperative complications, and higher short- and long-term mortality (all P < 0.05). Risk-adjustment with multivariate regression demonstrated that DCI independently predicts postoperative complications (odds ratio 1.1, P = 0.01) even after accounting for ACS NSQIP predicted risk score. Furthermore, DCI independently predicted inflation-adjusted cost (+$978/quartile, P < 0.0001) after risk adjustment.
CONCLUSIONS
The DCI, an established metric for socioeconomic distress, improves ACS NSQIP risk-adjustment to predict outcomes and hospital cost. These findings highlight the impact of socioeconomic status on surgical outcomes and should be integrated into ACS NSQIP risk models.
Topics: Female; Healthcare Disparities; Humans; Male; Middle Aged; Postoperative Complications; Poverty Areas; Quality Improvement; Risk Adjustment; Social Class; Surgical Procedures, Operative; Survival Analysis; United States
PubMed: 30741732
DOI: 10.1097/SLA.0000000000002997 -
The Journal of Thoracic and... Oct 2021Both congestive heart failure (HF) and atrial fibrillation (AF) are important and increasingly common forms of cardiovascular disease in the 21 century. Heart failure is...
Both congestive heart failure (HF) and atrial fibrillation (AF) are important and increasingly common forms of cardiovascular disease in the 21 century. Heart failure is often complicated by AF, and AF can exacerbate and, in some cases, cause HF, also known as tachycardia-induced cardiomyopathy (TIC). Restoration and maintenance of sinus rhythm in the majority of AF patients with TIC can lead to an improvement in left ventricular function and dramatic symptomatic relief. This can be accomplished by surgical ablation; specifically, the Cox-Maze IV procedure (CMP IV), in those refractory to medical and catheter-based ablation, and those patients undergoing concomitant cardiac operation. However, many surgeons are reluctant to perform stand-alone or concomitant CMP IV in this high-risk cohort of patients. In this review, the over three decades of experience with surgical ablation will be reviewed along with the essential information that surgeons need to be aware of as they participate in the team-based care of patients with AF and HF.
Topics: Atrial Fibrillation; Catheter Ablation; Heart Failure; Humans; Outcome Assessment, Health Care; Patient Selection; Prognosis; Quality of Life; Randomized Controlled Trials as Topic; Risk Adjustment; Stroke Volume; Ventricular Dysfunction, Left
PubMed: 32948298
DOI: 10.1016/j.jtcvs.2020.05.125 -
BMJ (Clinical Research Ed.) Jan 2021
Topics: Female; Humans; Infant, Newborn; Maternal Health; Maternal Health Services; Maternal Mortality; Pregnancy; Pregnancy, High-Risk; Quality Improvement; Risk Adjustment; Safety Management; United Kingdom
PubMed: 33436374
DOI: 10.1136/bmj.n45 -
The Canadian Journal of Cardiology Jan 2022Numerous studies have identified the association of socioeconomic factors with outcomes of cardiac surgical procedures. Most have focused on easily measured demographic...
BACKGROUND
Numerous studies have identified the association of socioeconomic factors with outcomes of cardiac surgical procedures. Most have focused on easily measured demographic factors or on socioeconomic characteristics of patients' 5-digit zip codes. The impact of socioeconomic information that is derived from smaller geographic regions has rarely been studied.
METHODS
The association of the Area Deprivation Index (ADI) with short-term mortality and readmissions was tested for patients undergoing percutaneous coronary intervention (PCI) in New York while adjusting for numerous patient risk factors, including race, ethnicity, and payer. Changes in hospitals' risk-adjusted outcomes and outlier status with the addition of socioeconomic factors were examined.
RESULTS
After adjustment, patients in the 2 most deprived ADI quintiles were more likely to experience in-hospital and 30-day mortality after PCI (adjusted odds ratios [95% confidence intervals] 1.39 [1.18-1.65] and 1.24 [1.03-1.49], respectively), than patients in the first quintile (least deprived). Also, patients in the second and fifth ADI quintiles had higher 30-day readmissions rates than patients in the first quintile (1.12 [1.01-1.25] and 1.17 [1.04-1.32], respectively). Medicare patients had higher mortality and readmission rates, Hispanics had lower mortality, and Medicaid patients had higher readmission rates.
CONCLUSIONS
Patients with the most deprived ADIs are more likely to experience short-term mortality and readmissions after PCI. Ethnicity and payer are significantly associated with adverse outcomes even after adjusting for ADI. This information should be considered when identifying patients who are at the highest risk for adverse events after PCI and when risk-adjusting hospital outcomes and assessing quality of care.
Topics: Aged; Female; Humans; Male; Middle Aged; Outcome Assessment, Health Care; Percutaneous Coronary Intervention; Retrospective Studies; Risk Adjustment; Risk Factors; Socioeconomic Factors; United States
PubMed: 34610383
DOI: 10.1016/j.cjca.2021.09.029