Non-specific pain and 30-day readmission in acute coronary syndromes: findings from the TRACE-CORE prospective cohort.
Ontology highlight
ABSTRACT: Background
Patients with acute coronary syndromes often experience non-specific (generic) pain after hospital discharge. However, evidence about the association between post-discharge non-specific pain and rehospitalization remains limited.Methods
We analyzed data from the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education (TRACE-CORE) prospective cohort. TRACE-CORE followed patients with acute coronary syndromes for 24 months post-discharge from the index hospitalization, collected patient-reported generic pain (using SF-36) and chest pain (using the Seattle Angina Questionnaire) and rehospitalization events. We assessed the association between generic pain and 30-day rehospitalization using multivariable logistic regression (N = 787). We also examined the associations among patient-reported pain, pain documentation identified by natural language processing (NLP) from electronic health record (EHR) notes, and the outcome.Results
Patients were 62 years old (SD = 11.4), with 5.1% Black or Hispanic individuals and 29.9% women. Within 30 days post-discharge, 87 (11.1%) patients were re-hospitalized. Patient-reported mild-to-moderate pain, without EHR documentation, was associated with 30-day rehospitalization (odds ratio [OR]: 2.03, 95% confidence interval [CI]: 1.14-3.62, reference: no pain) after adjusting for baseline characteristics; while patient-reported mild-to-moderate pain with EHR documentation (presumably addressed) was not (OR: 1.23, 95% CI: 0.52-2.90). Severe pain was also associated with 30-day rehospitalization (OR: 3.16, 95% CI: 1.32-7.54), even after further adjusting for chest pain (OR: 2.59, 95% CI: 1.06-6.35).Conclusions
Patient-reported post-discharge generic pain was positively associated with 30-day rehospitalization. Future studies should further disentangle the impact of cardiac and non-cardiac pain on rehospitalization and develop strategies to support the timely management of post-discharge pain by healthcare providers.
SUBMITTER: Chen J
PROVIDER: S-EPMC8351351 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The National Association of Children's Hospitals (NACHRI) and the Centers for Medicare and Medicaid Services (CMS) recently introduced 30-day hospital readmission rate as a quality care indicator in children with sickle cell disease (SCD). Based on previous research identifying risk factors for 30-day readmission in our patient population, we designed and implemented a multi-modal intervention to reduce 30-day readmission rate in children with SCD and pain.A before-and-after study design was performed to evaluate an intervention containing three components: (1) standardized SCD-pain admission orders; (2) monthly SCD-pain in-service for house physicians for the first 6-months; and (3) continuous patient/caregiver education. Following order implementation, we prospectively collected data on all children admitted for SCD-pain over a 6-month period. We compared the 30-day readmission rate after the intervention to the rate during the same 6-month interval in the previous calendar year prior to the availability of pre-specified SCD-pain orders.A total of 89 admissions, in 68 individuals, were eligible for the standardized orders during the prospective time period and were compared to 85 admissions in 56 individuals during the control period. Pre-specified SCD-pain orders were used in 93% of eligible admissions during the intervention. Readmission rate within 30 days was lower for the intervention cohort than the control cohort, 11% (10/89) versus 28% (24/85), P = 0.007, 95% CI 0.1-0.7.A multi-modal intervention was successful in decreasing 30-day hospital readmission rate for children with SCD and pain. Provider education was the most important component of the multi-modal intervention.
| S-EPMC2722244 | biostudies-literature
Project description:BACKGROUND:Restrictive transfusion strategies supported by large randomized trials are resulting in decreased blood utilization in cardiac surgery. What remains to be determined, however, is the impact of lower discharge hemoglobin (Hb) levels on readmission rates. We assessed patients with higher versus lower Hb levels on discharge to compare 30-day readmission rates after coronary artery bypass grafting (CABG). METHODS:We retrospectively evaluated 1552 patients undergoing isolated CABG at our institution from January 2013 to May 2016. We evaluated 2 Hb cohorts: "high" (above) and "low" (below) the mean discharge Hb level of 9.4 g/dL, comparing patient characteristics, blood utilization, and clinical outcomes including 30-day readmission rates. We further evaluated the effects of the lowest (<8 g/dL) discharge Hb levels on 30-day readmission rates by dividing the patients into 4 anemia cohorts based on discharge Hb levels: "no anemia" (>12 g/dL), "mild anemia" (10-11.9 g/dL), "moderate anemia" (8-9.9 g/dL), and "severe anemia" (<8 g/dL). Risk adjustment accounted for age, sex, Charlson comorbidity index, preoperative comorbidities, revision sternotomy, and patient blood management program implementation. RESULTS:The "high" and "low" groups had similar patient characteristics except for Hb levels (mean discharge Hb was 10.4 ± 0.9 vs 8.5 ± 0.6 g/dL, respectively). Notably, no evidence for a difference in 30-day readmission rates was noted between the "high" (76/746; 10.2%) and "low" (97/806; 12.0%) (P = .25) Hb cohorts. The 4 anemia cohorts had differences in age, revision sternotomy incidence, Hb levels, certain patient comorbidities, and time to readmission. On multivariable analysis, the risk-adjusted odds of readmission in the "low" Hb cohort (odds ratio, 1.16; 95% confidence interval, 0.84-1.61; P = .36) was not significant compared to the "high" Hb cohort. Compared to patients with discharge Hb ?8 g/dL, patients with Hb <8 g/dL had a higher incidence of readmission (22/129; 17.1% vs 151/1423; 10.6%; P = .036). On multivariable analysis, Hb <8 g/dL on discharge was predictive of readmission (odds ratio, 1.77; 95% confidence interval, 1.05-2.88; P = .03). The most common reason for readmission was volume overload, followed by infection and arrhythmias. CONCLUSIONS:A discharge Hb level below the institution mean for CABG patients does not provide evidence for an association with an increased 30-day readmission rate. In the small number of patients discharged with Hb <8 g/dL, there is a suggestion of increased risk for readmission and larger more controlled studies are needed to verify or refute this finding.
| S-EPMC6533067 | biostudies-literature
Project description:BackgroundReadmission following COPD exacerbation is a common and challenging clinical problem. New approaches to predicting readmissions are required to help mitigate risk and develop novel interventions.MethodsWe conducted a prospective cohort study in 82 COPD patients admitted due to an exacerbation of COPD. Lung function measures [spirometry, forced oscillation technique (FOT) indices and peak inspiratory flow rate (PIFR)], inflammatory biomarkers and patient-reported outcomes including previous exacerbation history, breathlessness, quality of life and frailty were measured at admission and discharge. We prospectively followed patients for 30 and 90 days to identify predictors for readmission.ResultsThe readmission rate within 30 days was 38%, and 56% within 90 days. Previous exacerbations, higher COPD Assessment Test score at discharge, frailty, reduced PIFR and increased length of stay were significantly associated with 30-day readmission. PIFR at discharge and frailty had the highest predictive ability for 30-day readmission using area under receiver operating characteristic curves (AUC 0.86, 95% CI 0.78-0.95, p < 0.001 and AUC 0.81, 95% CI 0.71-0.90, p < 0.001, respectively). Ninety-day readmissions were significantly associated with previous exacerbations and hospitalisations, higher CAT score at discharge, frailty, depression, lower PIFR and greater expiratory flow limitation (EFL) in the supine position. The best predictive variable in multivariable analysis for both 30- and 90-day readmission was PIFR at discharge.ConclusionPIFR, CAT score, frailty, and EFL were found to be associated with 30- and 90-day readmission following COPD exacerbation. These findings help identify those at highest risk and to optimise care prior to discharge.
| S-EPMC8504869 | biostudies-literature
Project description:BackgroundLowering hospital readmission rates has become a primary target for the Centers for Medicare & Medicaid Services, but studies of the relationship between adherence to the recommended hospital care processes and readmission rates have provided inconsistent and inconclusive results.ObjectiveTo examine the association between hospital performance on Medicare's Hospital Compare process quality measures and 30-day readmission rates for patients with acute myocardial infarction (AMI), heart failure and pneumonia, and for those undergoing major surgery.Design, setting and participantsWe assessed hospital performance on process measures using the 2007 Hospital Inpatient Quality Reporting Program. The process measures for each condition were aggregated in two separate measures: Overall Measure (OM) and Appropriate Care Measure (ACM) scores. Readmission rates were calculated using Medicare claims.Main outcome measureRisk-standardized 30-day all-cause readmission rate was calculated as the ratio of predicted to expected rate standardized by the overall mean readmission rate. We calculated predicted readmission rate using hierarchical generalized linear models and adjusting for patient-level factors.ResultsAmong patients aged ≥ 66 years, the median OM score ranged from 79.4 % for abdominal surgery to 95.7 % for AMI, and the median ACM scores ranged from 45.8 % for abdominal surgery to 87.9 % for AMI. We observed a statistically significant, but weak, correlation between performance scores and readmission rates for pneumonia (correlation coefficient R = 0.07), AMI (R = 0.10), and orthopedic surgery (R = 0.06). The difference in the mean readmission rate between hospitals in the 1st and 4th quartiles of process measure performance was statistically significant only for AMI (0.25 percentage points) and pneumonia (0.31 percentage points). Performance on process measures explained less than 1 % of hospital-level variation in readmission rates.ConclusionsHospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.
| S-EPMC3579957 | biostudies-literature
Project description:BackgroundReadmission in older adults is typically complex with multiple contributing factors. We aim to examine how two prevalent and potentially modifiable geriatric conditions - depressive symptoms and malnutrition - relate to other geriatric syndromes and 30-day readmission in hospitalized older adults.MethodsConsecutive admissions of patients ≥ 65 years to a general medical department were recruited over 16 months. Patients were screened for depression, malnutrition, delirium, cognitive impairment, and frailty at admission. Medical records were reviewed for poor oral intake and functional decline during hospitalization. Unplanned readmission within 30-days of discharge was tracked through the hospital's electronic health records and follow-up telephone interviews. We use directed acyclic graphs (DAGs) to depict the relationship of depressive symptoms and malnutrition with geriatric syndromes that constitute covariates of interest and 30-day readmission outcome. Multiple logistic regression was performed for the independent associations of depressive symptoms and malnutrition with 30-day readmission, adjusting for variables based on DAG-identified minimal adjustment set.ResultsWe recruited 1619 consecutive admissions, with mean age 76.4 (7.9) years and 51.3% females. 30-day readmission occurred in 331 (22.0%) of 1,507 patients with follow-up data. Depressive symptoms, malnutrition, higher comorbidity burden, hospitalization in the one-year preceding index admission, frailty, delirium, as well as functional decline and poor oral intake during the index admission, were more commonly observed among patients who were readmitted within 30 days of discharge (P < 0.05). Patients with active depressive symptoms were significantly more likely to be frail (OR = 1.62, 95% CI 1.22-2.16), had poor oral intake (OR = 1.35, 95% CI 1.02-1.79) and functional decline during admission (OR = 1.58, 95% CI 1.11-2.23). Malnutrition at admission was significantly associated with frailty (OR = 1.53, 95% CI 1.07-2.19), delirium (OR = 2.33, 95% CI 1.60-3.39) cognitive impairment (OR = 1.88, 95% CI 1.39-2.54) and poor oral intake during hospitalization (OR = 2.70, 95% CI 2.01-3.64). In minimal adjustment set identified by DAG, depressive symptoms (OR = 1.38, 95% CI 1.02-1.86) remained significantly associated with 30-day readmission. The association of malnutrition with 30-day readmission was no longer statistically significant after adjusting for age, ethnicity and depressive symptoms in the minimal adjustment set (OR = 1.40, 95% CI 0.99-1.98).ConclusionThe observed causal associations support screening and targeted interventions for depressive symptoms and malnutrition during admission and in the post-acute period.
| S-EPMC9344637 | biostudies-literature
Project description:BackgroundThirty-day hospital readmissions are common among maintenance dialysis patients. Prior studies have evaluated easily measurable readmission risk factors such as comorbid conditions, laboratory results, and hospital discharge day. We undertook this prospective study to investigate the associations between hospital-assessed depression, health literacy, social support, and self-rated health (separately) and 30-day hospital readmission among dialysis patients.MethodsParticipants were recruited from the University of North Carolina Hospitals, 2014-2016. Validated depression, health literacy, social support, and self-rated health screening instruments were administered during index hospitalizations. Multivariable logistic regression models with 30-day readmission as the dependent outcome were used to examine readmission risk factors.ResultsOf the 154 participants, 58 (37.7%) had a 30-day hospital readmission. In unadjusted analyses, individuals with positive screening for depression, lower health literacy, and poorer social support were more likely to have a 30-day readmission (vs. negative screening). Positive depression screening and poorer social support remained significantly associated with 30-day readmission in models adjusted for race, heart failure, admitting service, weekend discharge day, and serum albumin: adjusted OR (95% CI) 2.33 (1.02-5.15) for positive depressive symptoms and 2.57 (1.10-5.91) for poorer social support. The area under the receiver operating characteristic curve (AUC) of the multivariable model adjusted for social support status was significantly greater than the AUC of the multivariable model without social support status (test for equality; p value = 0.04).ConclusionPoor social support and depressive symptoms identified during hospitalizations may represent targetable readmission risk factors among dialysis patients. Our findings suggest that hospital-based assessments of select psychosocial factors may improve readmission risk prediction.
| S-EPMC5483850 | biostudies-literature
Project description:ObjectiveTo assess the reliability of risk-standardized readmission rates (RSRRs) for medical conditions and surgical procedures used in the Hospital Readmission Reduction Program (HRRP).Data sourcesState Inpatient Databases for six states from 2011 to 2013 were used to identify patient cohorts for the six conditions used in the HRRP, which was augmented with hospital characteristic and HRRP penalty data.Study designHierarchical logistic regression models estimated hospital-level RSRRs for each condition, the reliability of each RSRR, and the extent to which socioeconomic and hospital factors further explain RSRR variation. We used publicly available data to estimate payments for excess readmissions in hospitals with reliable and unreliable RSRRs.Principal findingsOnly RSRRs for surgical procedures exceeded the reliability benchmark for most hospitals, whereas RSRRs for medical conditions were typically below the benchmark. Additional adjustment for socioeconomic and hospital factors modestly explained variation in RSRRs. Approximately 25 percent of payments for excess readmissions were tied to unreliable RSRRs.ConclusionsMany of the RSRRs employed by the HRRP are unreliable, and one quarter of payments for excess readmissions are associated with unreliable RSRRs. Unreliable measures blur the connection between hospital performance and incentives, and threaten the success of the HRRP.
| S-EPMC5134200 | biostudies-literature
Project description:OBJECTIVE:To explore the influence of contextual factors on health-related quality of life (HRQoL), which is sometimes used as an indicator of quality of care, we examined the association of neighborhood socioeconomic status (NSES) and trajectories of HRQoL after hospitalization for acute coronary syndromes (ACS). METHODS:We studied 1481 patients hospitalized with acute coronary syndromes in Massachusetts and Georgia querying HRQoL via the mental and physical components of the 36-item short-form health survey (SF-36) (MCS and PCS) and the physical limitations and angina-related HRQoL subscales of the Seattle Angina Questionnaire (SAQ) during hospitalization and at 1-, 3-, and 6-month postdischarge. We categorized participants by tertiles of the neighborhood deprivation index (a residence-census tract-based measure) to examine the association of NSES with trajectories of HRQoL after adjusting for individual socioeconomic status (SES) and clinical characteristics. RESULTS:Participants had mean age 61.3 (SD, 11.4) years; 33% were female; 76%, non-Hispanic white; 11.2% had household income below the federal poverty level. During 6 months postdischarge, living in lower NSES neighborhoods was associated with lower mean PCS scores (1.5 points for intermediate NSES; 1.8 for low) and SAQ scores (2.4 and 4.2 points) versus living in high NSES neighborhoods. NSES was more consequential for patients with lower individual SES. Individuals living below the federal poverty level had lower average MCS and SAQ physical scores (3.7 and 7.7 points, respectively) than those above. CONCLUSIONS:Neighborhood deprivation was associated with worse health status. Using HRQoL to assess quality of care without accounting for individual SES and NSES may unfairly penalize safety-net hospitals.
| S-EPMC5687991 | biostudies-literature
Project description:To examine racial variations in access to postacute care (PAC) and rehabilitation (Rehab) services following elective total knee arthroplasty and whether where patients go after surgery for PAC/Rehab is associated with 30-day readmission to acute care facility.Sample consisted of 129 522 patients discharged from 169 hospitals in the State of Pennsylvania between fiscal years 2008 and 2012. We used multinomial regression models to assess the relationship between patient race and discharge destination after surgery, for patients aged 18 to 64 years and for those aged 65 and older. We used multivariable (MV) regression and propensity score (PS) approaches to examine the relationship between patient discharge destination after surgery for PAC/Rehab and 30-day readmission, controlling for key individual- and facility-level factors.Lower proportions of younger patients compared to those older than 65 were discharged to inpatient rehabilitation facilities (IRFs; 5.8% vs 12.6%, respectively) and skilled nursing facilities (SNFs; 15.2% vs 32.7%, respectively) compared to home-based Rehab (self-care; 23.3% vs 14.2%, respectively). Compared to whites, African American patients had significantly higher odds of discharge to IRF (age < 65, odds ratio = 2.04; age ≥ 65, odds ratio = 1.64) and to SNF (age < 65, odds ratio = 2.86; age ≥ 65, odds ratio = 2.19) and discharge to home care in patients younger than 65 years (odds ratio = 1.31). The odds of 30-day readmission among patients discharged to an IRF (MV odds ratio = 7.76; PS odds ratio = 8.34) and SNF (MV odds ratio = 2.01; PS odds ratio = 1.83) were significantly higher in comparison to patients discharged home with self-care.African American patients with knee replacement are more likely to be discharged to inpatient Rehab settings following surgery. Inpatient Rehab is significantly associated with 30-day readmission to acute care facility.
| S-EPMC4647199 | biostudies-other
Project description:Background and Purpose: Hospital readmissions impose a substantial burden on the healthcare system. Reducing readmissions after stroke could lead to improved quality of care especially since stroke is associated with a high rate of readmission. The goal of this study is to enhance our understanding of the predictors of 30-day readmission after ischemic stroke and develop models to identify high-risk individuals for targeted interventions. Methods: We used patient-level data from electronic health records (EHR), five machine learning algorithms (random forest, gradient boosting machine, extreme gradient boosting-XGBoost, support vector machine, and logistic regression-LR), data-driven feature selection strategy, and adaptive sampling to develop 15 models of 30-day readmission after ischemic stroke. We further identified important clinical variables. Results: We included 3,184 patients with ischemic stroke (mean age: 71 ± 13.90 years, men: 51.06%). Among the 61 clinical variables included in the model, the National Institutes of Health Stroke Scale score above 24, insert indwelling urinary catheter, hypercoagulable state, and percutaneous gastrostomy had the highest importance score. The Model's AUC (area under the curve) for predicting 30-day readmission was 0.74 (95%CI: 0.64-0.78) with PPV of 0.43 when the XGBoost algorithm was used with ROSE-sampling. The balance between specificity and sensitivity improved through the sampling strategy. The best sensitivity was achieved with LR when optimized with feature selection and ROSE-sampling (AUC: 0.64, sensitivity: 0.53, specificity: 0.69). Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.
| S-EPMC8044392 | biostudies-literature