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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 -
Cardiology Clinics Feb 2021Women with congenital heart disease are pursuing pregnancy in increasing numbers. Counseling about genetic transmission, medication management, maternal and fetal risks,... (Review)
Review
Women with congenital heart disease are pursuing pregnancy in increasing numbers. Counseling about genetic transmission, medication management, maternal and fetal risks, and maternal longevity should be initiated well before pregnancy is considered. Although preconception medical and surgical optimization as well as coordinated multidisciplinary care throughout pregnancy decrease maternal and fetal risks, the rate of complications remains increased compared with the general population. Lesion-specific risk stratification and care throughout pregnancy further improve outcomes and decrease unnecessary interventions.
Topics: Female; Heart Defects, Congenital; Humans; Patient Care Team; Preconception Care; Pregnancy; Pregnancy Complications, Cardiovascular; Risk Adjustment
PubMed: 33222814
DOI: 10.1016/j.ccl.2020.09.004 -
Archives of Physical Medicine and... May 2020To develop a patient risk adjustment model for experience of care (EOC) quality measures for long-term care hospitals (LTCHs) that includes mode of survey...
OBJECTIVES
To develop a patient risk adjustment model for experience of care (EOC) quality measures for long-term care hospitals (LTCHs) that includes mode of survey administration. To assess presence of nonresponse bias in the adjusted facility-level scores.
DESIGN
We tested 3 modes of collecting the EOC data: mail-only, mixed (ie, mail with telephone follow-up), and in-facility. This study used sequential modeling and impact analysis, specified a risk and mode adjustment model, and evaluated presence of nonresponse after adjustment.
SETTING
LTCHs.
PARTICIPANTS
Patients (N=1364) and 69 LTCHs.
INTERVENTION
Not applicable.
MAIN OUTCOME MEASURES
Risk and mode adjusted responses to 28 survey questions and 6 facility-level scores derived from survey responses.
RESULTS
Mode of data collection and patient risk variables (age, sex, overall health, overall mental health, marital status, education, race, and whether a proxy responded) were included in the model. Clinical variables were not significant. The in-facility mode was associated with significantly higher performance scores than the other modes. When the recommended risk and mode adjustment model was applied, nonresponse bias was not observed in any mode.
CONCLUSIONS
LTCH EOC data should be adjusted for patient risk variables including mode of data collection.
Topics: Adolescent; Adult; Age Factors; Aged; Bias; Data Collection; Female; Health Care Surveys; Hospitals, Urban; Humans; Length of Stay; Long-Term Care; Male; Middle Aged; Quality of Health Care; Regression Analysis; Risk Adjustment; Sex Factors; United States; Young Adult
PubMed: 31904343
DOI: 10.1016/j.apmr.2019.11.016 -
The Journals of Gerontology. Series A,... Jul 2021
Topics: Aged; Clinical Decision-Making; Geriatric Assessment; Humans; Neoplasms; Patient Care Management; Patient Selection; Population Dynamics; Quality of Life; Risk Adjustment; Survivorship
PubMed: 34156074
DOI: 10.1093/gerona/glab126 -
Archives of Physical Medicine and... Jun 2022To describe the exclusion criteria and risk-adjustment model developed for the quality measure Change in Self-Care. The exclusion criteria and risk adjustment model are...
OBJECTIVE
To describe the exclusion criteria and risk-adjustment model developed for the quality measure Change in Self-Care. The exclusion criteria and risk adjustment model are used to calculate Change in Self-Care scores, allowing scores to be compared across inpatient rehabilitation facilities (IRFs).
DESIGN
This national cohort study examined admission demographic and clinical factors associated with IRF patients' self-care change scores using standardized self-care data for Medicare patients discharged in calendar year 2017.
SETTING
A total of 1129 IRFs in the United States.
PARTICIPANTS
A total of 493,209 (N=493,209) Medicare Fee-for-Service and Medicare Advantage IRF patient stays INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURES
Self-care change scores using admission and discharge standardized assessment data elements from the Inpatient Rehabilitation Facility-Patient Assessment Instrument.
RESULTS
Approximately 53% of patients were female, and 67% were between 65 and 84 years old. The final risk-adjustment model contained 93 clinically relevant risk adjusters and explained 23.1% of variance in self-care change scores. Risk adjusters that had the greatest effect on change scores and included IRF primary diagnosis group (ie, binary risk adjusters representing 13 diagnoses), prior self-care functioning, and age older than 90 years. When split by deciles of expected scores, the ratio of the average expected and observed change scores was within 2% of 1.0 across 8 groups and within 8% at the extremes, showing good predictive accuracy.
CONCLUSIONS
The risk adjustment model quantifies the relationship between IRF patients' demographic and clinical characteristics and their self-care score changes. The exclusion criteria and model are used to risk-adjust the IRF Change in Self-Care quality measure.
Topics: Aged; Aged, 80 and over; Cohort Studies; Female; Humans; Inpatients; Length of Stay; Male; Medicare; Patient Discharge; Quality Indicators, Health Care; Rehabilitation Centers; Retrospective Studies; Risk Adjustment; Self Care; United States
PubMed: 35278465
DOI: 10.1016/j.apmr.2022.02.009 -
Clinical Obstetrics and Gynecology Jun 2020If it is medically necessary to perform nonobstetrical abdominal surgery in pregnancy, a minimally invasive approach should be considered. The benefits of laparoscopy... (Review)
Review
If it is medically necessary to perform nonobstetrical abdominal surgery in pregnancy, a minimally invasive approach should be considered. The benefits of laparoscopy are well known and current studies promote the safety of laparoscopy in pregnancy, when certain guidelines are followed. This article will review the safety of surgery in pregnancy, maternal physiology, fetal considerations, maternal obesity, laparoscopic cerclage, large adnexal mass, and complications. Guidelines for surgery will be reviewed as well.
Topics: Abdominal Cavity; Female; Humans; Minimally Invasive Surgical Procedures; Obesity; Postoperative Complications; Pregnancy; Pregnancy Complications; Risk Adjustment; Risk Assessment
PubMed: 32195684
DOI: 10.1097/GRF.0000000000000527 -
Cardiology Clinics Feb 2021Cardiovascular disease is a major contributor to maternal morbidity and mortality and frequently preventable. Women with known cardiovascular disease should undergo... (Review)
Review
Cardiovascular disease is a major contributor to maternal morbidity and mortality and frequently preventable. Women with known cardiovascular disease should undergo cardiac evaluation before pregnancy. Many women with pregnancy-associated cardiac complications are not previously known to have cardiac disease. Women at high risk or who have signs or symptoms suggestive of heart failure, angina, or arrhythmias should undergo prompt evaluation. This article describes various diagnostic imaging modalities that can be used in pregnancy, including indications, strengths, and limitations.
Topics: Cardiac Imaging Techniques; Female; Heart Diseases; Humans; Pregnancy; Pregnancy Complications, Cardiovascular; Risk Adjustment
PubMed: 33222812
DOI: 10.1016/j.ccl.2020.09.003 -
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 -
The Annals of Thoracic Surgery May 2020
Topics: Humans; Models, Statistical; Quality Indicators, Health Care; Risk Adjustment; United States
PubMed: 31604091
DOI: 10.1016/j.athoracsur.2019.09.010 -
The Journal of Arthroplasty Mar 2021Under bundled payment models, gainsharing presents an important mechanism to ensure engagement and reward innovation. We hypothesized that metric selection, metric...
BACKGROUND
Under bundled payment models, gainsharing presents an important mechanism to ensure engagement and reward innovation. We hypothesized that metric selection, metric targets, and risk adjustment would impact surgeons' performance in gainsharing models.
METHODS
Patients undergoing total joint arthroplasty at an urban health system from 2017 to September 2018 were included. Gainsharing metrics included the following: length of stay, % discharge-to-home, 90-day readmission rate, % of patients with episode spend under target price, and % of patients with patient-reported outcomes (PROs) collected. Four scenarios were created to evaluate how metric selection/adjustment impacted surgeons' performance designation: scenario 1 used "aspirational targets" (>60th percentile), scenario 2 used "acceptable targets" (>50th percentile), scenario 3 risk-adjusted surgeon performance prior to comparing aspirational targets, and scenario 4 included a PRO collection metric. Number of metrics achieved determined performance tier, with higher tiers getting a greater share of the gainsharing pool.
RESULTS
In total, 2776 patients treated by 12 surgeons met inclusion criteria (mean length of stay 3.0 days, readmission rate 4.0%, discharge-to-home 74%, episode spend under target price 85%, PRO collection 56%). Lowering of metric targets (scenario 1 vs. 2) resulted in a 75% increase in the number of high performers and 98% of the gainsharing pool being eligible for distribution. Risk adjustment (scenario 3) caused 50% of providers to move to higher performance tiers and potential payments to increase by 28%. Adding the PRO metric did not change performance.
CONCLUSION
Quality metric/target selection and risk adjustment profoundly impact surgeons' performance in gainsharing contracts. This impacts how successful these contracts can be in driving innovation and dis-incentivizing the "cherry picking" of patients.
LEVEL OF EVIDENCE
Level III.
Topics: Arthroplasty, Replacement, Hip; Arthroplasty, Replacement, Knee; Humans; Patient Care Bundles; Patient Discharge; Risk Adjustment; United States
PubMed: 33199096
DOI: 10.1016/j.arth.2020.10.007