scholarly journals Measuring the Relative Contribution of Social Risk Factors in an Enhanced Risk‐Adjustment Model for Unplanned Hospital Readmissions

2020 ◽  
Vol 55 (S1) ◽  
pp. 108-109
Author(s):  
C. Nwachukwu ◽  
H. Trieu ◽  
T. Land ◽  
W. Li ◽  
Z. Zhang
Keyword(s):  
Risk Factors ◽  
Risk Adjustment ◽  
Hospital Readmissions ◽  
Social Risk ◽  
Social Risk Factors ◽  
Relative Contribution ◽  
Adjustment Model ◽  
Risk Adjustment Model

scholarly journals Adjusting Client-Level Risks Impacts on Home Care Organization Ranking

2021 ◽  
Vol 18 (11) ◽  
pp. 5502
Author(s):  
Aylin Wagner ◽  
René Schaffert ◽  
Julia Dratva
Keyword(s):  
Risk Factors ◽  
Home Care ◽  
Risk Adjustment ◽  
Care Quality ◽  
Assessment Instrument ◽  
Care Organization ◽  
Discrimination Power ◽  
Adjustment Model ◽  
Risk Adjustment Model ◽  
The Impact

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.

scholarly journals Adjusting for social risk factors impacts performance and penalties in the hospital readmissions reduction program

2019 ◽  
Vol 54 (2) ◽  
pp. 327-336 ◽  
Author(s):  
Karen E. Joynt Maddox ◽  
Mat Reidhead ◽  
Jianhui Hu ◽  
Amy J. H. Kind ◽  
Alan M. Zaslavsky ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hospital Readmissions ◽  
Social Risk ◽  
Social Risk Factors ◽  
Reduction Program

An Approach to Selecting Single or Multiple Social Risk Factors for Clinic-Based Screening

2021 ◽  
Author(s):  
John F. Steiner ◽  
Glenn K. Goodrich ◽  
Kelly R. Moore ◽  
Spero M. Manson ◽  
Laura M. Gottlieb ◽  
...  
Keyword(s):  
Risk Factors ◽  
Social Risk ◽  
Social Risk Factors

Comorbidity and severity-of-illness risk adjustment for hospital-onset Clostridioides difficile infection using data from the electronic medical record

2020 ◽  
pp. 1-7
Author(s):  
Stephanie M. Cabral ◽  
Katherine E. Goodman ◽  
Natalia Blanco ◽  
Surbhi Leekha ◽  
Larry S. Magder ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Risk Adjustment ◽  
Community Hospital ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Bivariate Analysis ◽  
Patient Admissions ◽  
Clostridioides Difficile ◽  
Risk Adjustment Model

Abstract 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.

СОСТОЯНИЕ ПРОБЛЕМЫ НАРКОЛОГИЧЕСКИХ РАССТРОЙСТВ В КУРСКОЙ ОБЛАСТИ И СОПРЕДЕЛЬНЫХ ТЕРРИТОРИЯХ В 2014-2019 ГОДАХ

Innova ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 33-38
Author(s):  
Владимир Игоревич Тимошилов ◽  
◽  
Альберт Генрихович Ластовецкий
Keyword(s):  
Risk Factors ◽  
Drug Addiction ◽  
Epidemiological Data ◽  
Drug Prevention ◽  
Social Risk ◽  
Social Risk Factors ◽  
Social Instability ◽  
Lower Incidence Rate ◽  
Kursk Region ◽  
Active Substances

Period 2014-2019 characterized by a certain increase in social instability in Russia, which led to an increase of social risk factors for drug addiction. In the Kursk region, at the same time, there have been changes in the regulation of anti-drug prevention, a large number of specialists have been trained, and a movement of competent volunteers has developed. In this regard, the epidemiological data for 2014-2019 are of particular interest. For the period from 2005 to 2019 the primary incidence of alcohol use disorders in Russia decreased from 147.4 to 48.3, in the Kursk region – from 106 to 53.5 cases per 100 000 population per year. Of the adjacent regions in 2019, a lower incidence rate than in the Kursk region was noted only in the Belgorod region – 39.4 cases per 100,000 population. Primary incidence of disorders associated with the use of narcotic active substances, during 2014-2019 in Russia as a whole decreased from 15 to 9.8, in the Kursk region – from 11.3 to 4 new cases per 100 000 inhabitants per year. In 2019, the detection rate of primary incidence of drug addiction and substance abuse was significantly higher than in the Kursk region in Bryansk and Lipetsk. Despite favorable trends, it was noted that the coronavirus pandemic and the restrictions introduced to combat it can have a significant impact on the risk factors for drug addiction, which requires the adaptation of preventive programs to new conditions.

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