Simple Index to Predict Likelihood of Skilled Nursing Facility Admission After Coronary Artery Bypass Grafting Among Older Patients

Hospital Variation in Skilled Nursing Facility Use After Coronary Artery Bypass Graft Surgery

BACKGROUND

Over 20% of patients are discharged to a skilled nursing facility (SNF) after coronary artery bypass graft surgery, but little is known about specific drivers for postdischarge SNF use. The purpose of this study was to evaluate hospital variation in SNF use and its association with postoperative outcomes after coronary artery bypass graft.

METHODS AND RESULTS

A retrospective study design utilizing Medicare Provider Analysis and Review files was used to evaluate SNF use among 70 509 beneficiaries undergoing coronary artery bypass graft, with or without valve procedures, between 2016 and 2018. A total of 17 328 (24.6%) were discharged to a SNF, ranging from 0% to 88% across 871 hospitals. Multilevel logistic regression models identified significant patient-level predictors of discharge to SNF including increasing age, comorbidities, female sex, Black race, dual eligibility, and postoperative complications. After adjusting for patient and hospital factors, 15.6% of the variation in hospital SNF use was attributed to the discharging hospital. Compared with the lower quartile of hospital SNF use, hospitals in the top quartile of SNF use had lower risk-adjusted 1-year mortality (12.5% versus 8.6%, P<0.001) and readmission (59.9% versus 49.8%, P<0.001) rates for patients discharged to a SNF.

CONCLUSIONS

There is high variability in SNF use among hospitals that is only partially explained by patient characteristics. Hospitals with higher SNF utilization had lower risk-adjusted 1-year mortality and readmission rates for patients discharged to a SNF. More work is needed to better understand underlying provider and hospital-level factors contributing to SNF use variability.

Using phenotypic data from the Electronic Health Record (EHR) to predict discharge

BACKGROUND

Timely discharge to post-acute care (PAC) settings, such as skilled nursing facilities, requires early identification of eligible patients. We sought to develop and internally validate a model which predicts a patient's likelihood of requiring PAC based on information obtained in the first 24 h of hospitalization.

METHODS

This was a retrospective observational cohort study. We collected clinical data and commonly used nursing assessments from the electronic health record (EHR) for all adult inpatient admissions at our academic tertiary care center from September 1, 2017 to August 1, 2018. We performed a multivariable logistic regression to develop the model from the derivation cohort of the available records. We then evaluated the capability of the model to predict discharge destination on an internal validation cohort.

RESULTS

Age (adjusted odds ratio [AOR], 1.04 [per year]; 95% Confidence Interval [CI], 1.03 to 1.04), admission to the intensive care unit (AOR, 1.51; 95% CI, 1.27 to 1.79), admission from the emergency department (AOR, 1.53; 95% CI, 1.31 to 1.78), more home medication prescriptions (AOR, 1.06 [per medication count increase]; 95% CI 1.05 to 1.07), and higher Morse fall risk scores at admission (AOR, 1.03 [per unit increase]; 95% CI 1.02 to 1.03) were independently associated with higher likelihood of being discharged to PAC facility. The c-statistic of the model derived from the primary analysis was 0.875, and the model predicted the correct discharge destination in 81.2% of the validation cases.

CONCLUSIONS

A model that utilizes baseline clinical factors and risk assessments has excellent model performance in predicting discharge to a PAC facility.

Systematic review of prediction models for postacute care destination decision-making

OBJECTIVE

This article reports a systematic review of studies containing development and validation of models predicting postacute care destination after adult inpatient hospitalization, summarizes clinical populations and variables, evaluates model performance, assesses risk of bias and applicability, and makes recommendations to reduce bias in future models.

MATERIALS AND METHODS

A systematic literature review was conducted following PRISMA guidelines and the Cochrane Prognosis Methods Group criteria. Online databases were searched in June 2020 to identify all published studies in this area. Data were extracted based on the CHARMS checklist, and studies were evaluated based on predictor variables, validation, performance in validation, risk of bias, and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) tool.

RESULTS

The final sample contained 28 articles with 35 models for evaluation. Models focused on surgical (22), medical (5), or both (8) populations. Eighteen models were internally validated, 10 were externally validated, and 7 models underwent both types. Model performance varied within and across populations. Most models used retrospective data, the median number of predictors was 8.5, and most models demonstrated risk of bias.

DISCUSSION AND CONCLUSION

Prediction modeling studies for postacute care destinations are becoming more prolific in the literature, but model development and validation strategies are inconsistent, and performance is variable. Most models are developed using regression, but machine learning methods are increasing in frequency. Future studies should ensure the rigorous variable selection and follow TRIPOD guidelines. Only 14% of the models have been tested or implemented beyond original studies, so translation into practice requires further investigation.

Sex differences in discharge destination following acute myocardial infarction

BACKGROUND

Despite advancements in treatment, acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality in the elderly population. Previous research has highlighted long-standing sex disparities in the care of these patients. However, differences in the patterns of discharge are not well described. One key parameter is the destination of discharge, and in particular - discharge to skilled nursing facilities (SNFs), a factor associated with worse prognosis and greater costs to the healthcare system. Our aim, therefore, was to observe destination differences after AMI on the basis of sex and other baseline characteristics.

MATERIALS AND METHODS

From a cohort of 143 180 claims, we carried out an observational analysis of 6123 Medicare beneficiaries discharged following AMI during the first quarter of 2016.

RESULTS

For patients who were referred from SNF, the rates of in-hospital death are higher, even after adjustment for baseline characteristics (odds ratio: 1.78, 95% confidence interval: 1.17-2.70). Of those discharged to SNF or home, 36.33% of the female patients were discharged to an SNF versus 25.12% (P<0.01) of the male patients. After adjusting for baseline characteristics, discharge to SNF remained significantly higher among female patients (odds ratio: 1.57, 95% confidence interval: 1.27-1.94).

CONCLUSION

Discharge to SNF following AMI is more frequent for female patients, even after adjustment for risk factors. Our findings highlight the need to better characterize this unique patient population and understand the cycle of care that they receive following AMI.

Perspectives of Post-Acute Transition of Care for Cardiac Surgery Patients

Post-acute care (PAC) facilities improve patient recovery, as measured by activities of daily living, rehabilitation, hospital readmission, and survival rates. Seamless transitions between discharge and PAC settings continue to be challenges that hamper patient outcomes, specifically problems with effective communication and coordination between hospitals and PAC facilities at patient discharge, patient adherence and access to cardiac rehabilitation (CR) services, caregiver burden, and the financial impact of care. The objective of this review is to examine existing models of cardiac transitional care, identify major challenges and social factors that affect PAC, and analyze the impact of current transitional care efforts and strategies implemented to improve health outcomes in this patient population. We intend to discuss successful methods to address the following aspects: hospital-PAC linkages, improved discharge planning, caregiver burden, and CR access and utilization through patient-centered programs. Regular home visits by healthcare providers result in decreased hospital readmission rates for patients utilizing home healthcare while improved hospital-PAC linkages reduced hospital readmissions by 25%. We conclude that widespread adoption of improvements in transitional care will play a key role in patient recovery and decrease hospital readmission, morbidity, and mortality.

Predictors of Hospital Discharge to an Extended Care Facility after Major General Thoracic Surgery

Failure to anticipate the need to discharge patients to rehabilitation centers and skilled nursing facilities results in expensive delays in the discharge of patients after surgery. Early identification of patients at high risk for discharge to these extended care facilities could mitigate these delays and expenditures. The purpose of this study was to identify preoperative patient factors associated with discharge to extended care facilities after major general thoracic surgery. Discharge records were identified for all patients undergoing major general thoracic surgery admitted to a university hospital between January 2006 and May 2009 who had a stay of longer than one day. The following risk factors were selected a priori based on clinical judgment: age, preoperative albumin, pre-operative Zubrod score, history of peripheral vascular disease, and use of home oxygen. Multiple logistic regression analysis was used to estimate the statistical significance and magnitude of risk associated with each predictor of patient discharge to extended care facilities. Of the 1646 patients identified, 68 (4.1%) were discharged to extended care facilities. Hospital length of stay was on average six days longer for patients discharged to these facilities than for patients discharged home ( P < 0.0001). Multivariate analysis demonstrated that advanced age, lower preoperative albumin, and increased preoperative Zubrod score were statistically significant predictors of discharge to extended care facilities. Age, preoperative nutritional status, and functional status are strong predictors of patient discharge to extended care facilities. Early identification of these patients may improve patient discharge planning and reduce hospital length of stay after major thoracic surgery.

Risk of not being discharged home after isolated coronary artery bypass graft operations

BACKGROUND

The age and risk profile of patients undergoing isolated coronary artery bypass grafting (CABG) is increasing, which will likely increase the proportion of CABG patients discharged to nursing homes, rehabilitation, or long-term care. Because discharge disposition can be important to a patient's treatment goals, developing and using predictive tools will improve informed treatment decision making. We examined the utility of The Society of Thoracic Surgeons (STS) risk of mortality score in predicting discharge disposition after CABG.

METHODS

From January 1, 2004 to October 31, 2011, 5,119 patients underwent isolated CABG at The Heart Hospital Baylor Plano or Baylor University Medical Center (Texas) and were discharged alive. The association between STS risk of mortality and discharge to nursing home, rehabilitation, or long-term care was assessed using multivariable logistic regression, adjusted for age, body surface area, marital status, site, and year of operation.

RESULTS

At discharge, 216 patients (4.21%) went to nursing homes, 153 (2.99%) to rehabilitation, and 115 (2.25%) to long-term care. The STS risk of mortality score was significantly positively associated with discharge status (p < 0.001). Patients with 1%, 2%, 3%, 4%, and 5% STS risk of mortality had 11.25%, 22.10%, 29.45%, 35.00%, and 38.50% probability, respectively, of not being discharged home. When the STS risk of mortality was 5%, the risk of not being discharged home was 47.9% for off-pump patients and 38.10% for on-pump patients.

CONCLUSIONS

STS risk score is strongly associated with CABG discharge status. Patients with a risk score exceeding 2 are at high risk (>22%) of not being discharged home. This risk should be discussed when treatment decisions are being made.

Institutionalization of older people: prediction and prevention

Expenditure on long-term care is likely to increase with the aging of the population and the increased need for institutionalization. Identifying risk factors for nursing home admission is of particular interest to develop predictive tools and intervention programs to reduce entry into nursing homes. Most of the patient-related risk factors leading to nursing home admission are based on an underlying decline in physical and/or cognitive functions. Interaction between caregiver and care recipient characteristics is also an important contributing factor. Structured preventive programs are more effective than individual counseling. Tailoring intervention programs to individual needs and preferences, continuous and comprehensive support of patients and their caregivers with access to a geriatrician is an important factor in the success of an intervention. Further research is still required to explore whether interventions at early stages of chronic diseases would delay physical and cognitive dysfunction and reduce the institutionalization of older people.