Reducing Readmissions among Heart Failure Patients Discharged to Home Health Care: Effectiveness of Early and Intensive Nursing Services and Early Physician Follow-Up

Improving TRansitions ANd outcomeS for heart FailurE patients in home health CaRe (I-TRANSFER-HF): a type 1 hybrid effectiveness-implementation trial: study protocol

BACKGROUND

Some of the most promising strategies to reduce hospital readmissions in heart failure (HF) is through the timely receipt of home health care (HHC), delivered by Medicare-certified home health agencies (HHAs), and outpatient medical follow-up after hospital discharge. Yet national data show that only 12% of Medicare beneficiaries receive these evidence-based practices, representing an implementation gap. To advance the science and improve outcomes in HF, we will test the effectiveness and implementation of an intervention called Improving TRansitions ANd OutcomeS for Heart FailurE Patients in Home Health CaRe (I-TRANSFER-HF), comprised of early and intensive HHC nurse visits combined with an early outpatient medical visit post-discharge, among HF patients receiving HHC.

METHODS

This study will use a Hybrid Type 1, stepped wedge randomized trial design, to test the effectiveness and implementation of I-TRANSFER-HF in partnership with four geographically diverse dyads of hospitals and HHAs ("hospital-HHA" dyads) across the US. Aim 1 will test the effectiveness of I-TRANSFER-HF to reduce 30-day readmissions (primary outcome) and ED visits (secondary outcome), and increase days at home (secondary outcome) among HF patients who receive timely follow-up compared to usual care. Hospital-HHA dyads will be randomized to cross over from a baseline period of no intervention to the intervention in a randomized sequential order. Medicare claims data from each dyad and from comparison dyads selected within the national dataset will be used to ascertain outcomes. Hypotheses will be tested with generalized mixed models. Aim 2 will assess the determinants of I-TRANSFER-HF's implementation using a mixed-methods approach and is guided by the Consolidated Framework for Implementation Research 2.0 (CFIR 2.0). Qualitative interviews will be conducted with key stakeholders across the hospital-HHA dyads to assess acceptability, barriers, and facilitators of implementation; feasibility and process measures will be assessed with Medicare claims data.

DISCUSSION

As the first pragmatic trial of promoting timely HHC and outpatient follow-up in HF, this study has the potential to dramatically improve care and outcomes for HF patients and produce novel insights for the implementation of HHC nationally.

TRIAL REGISTRATION

This trial has been registered on ClinicalTrials.Gov (#NCT06118983). Registered on 10/31/2023, https://clinicaltrials.gov/study/NCT06118983?id=NCT06118983&rank=1 .

Perioperative Primary Care Utilization and Postoperative Readmission, Emergency Department Use, and Mortality in Older Surgical Patients

BACKGROUND

Postdischarge primary care follow-up is associated with lower readmission rates after medical hospitalizations. However, the effect of primary care utilization on readmission has not been studied in surgical patients.

METHODS

Retrospective cohort study of Medicare beneficiaries aged 65 and older undergoing major inpatient diagnostic or therapeutic procedures (n = 3,552,906) from 2017 through 2018, examining the association between postdischarge primary care visits within 14 days of discharge (primary exposure), and Annual Wellness Visits in the year prior (secondary exposure), with 30-day unplanned readmission (primary outcome), emergency department visits, and mortality (secondary outcomes).

RESULTS

Overall, 9.5% (n = 336,837) had postdischarge visits within 14 days, 2.9% (n = 104,571) had Annual Wellness Visits in the year preceding the procedure, 9.5% (n = 336,401) were readmitted, 9% (n = 319,054) had emergency department visits, and 0.6% (n = 22,103) of the cohort died within 30 days. Our fully adjusted propensity-matched proportional hazards Cox regression analysis showed that postdischarge visits were associated with a 5% lower risk of readmission (hazard ratio [HR], 0.95, 95% confidence interval [CI], 0.93-0.97), 43% higher risk of emergency department use (HR, 1.43, 95% CI, 1.40-1.46) and no difference in mortality risk (HR, 0.98, 95% CI, 0.90-1.06), compared with not having a visit within 14 days of discharge. In a separate set of regression models, Annual Wellness Visits were associated with a 9% lower risk of readmission (HR, 0.91, 95% CI, 0.88-0.95), 45% higher risk of emergency department utilization (HR, 1.45, 95% CI, 1.40-1.49) and an 18% lower mortality risk (HR, 0.82, 95% CI, 0.75-0.89) compared with no Annual Wellness Visit in the year before the procedure.

CONCLUSIONS

Both postdischarge visits and the Medicare Annual Wellness Visit appear to be extremely underutilized among the older surgical population. In those patients who do utilize primary care, compared with propensity-matched patients who do not, our study suggests primary care use is associated with modestly lower readmission rates. Prospective studies are needed to determine whether targeted primary care involvement can reduce readmission.

Home Health Care Use and Outcomes After Coronary Artery Bypass Grafting Among Medicare Beneficiaries

BACKGROUND

Home health care (HHC) has been increasingly used to improve care transitions and avoid poor outcomes, but there is limited data on its use and efficacy following coronary artery bypass grafting. The purpose of this study was to describe HHC use and its association with outcomes among Medicare beneficiaries undergoing coronary artery bypass grafting.

METHODS

Retrospective analysis of 100% of Medicare fee-for-service files identified 77 331 beneficiaries undergoing coronary artery bypass grafting and discharged to home between July 2016 and December 2018. The primary exposure of HHC use was defined as the presence of paid HHC claims within 30 days of discharge. Hierarchical logistic regression identified predictors of HHC use and the percentage of variation in HHC use attributed to the hospital. Propensity-matched logistic regression compared mortality, readmissions, emergency department visits, and cardiac rehabilitation enrollment at 30 and 90 days after discharge between HHC users and nonusers.

RESULTS

A total of 26 751 (34.6%) of beneficiaries used HHC within 30 days of discharge, which was more common among beneficiaries who were older (72.9 versus 72.5 years), male (79.4% versus 77.4%), White (90.2% versus 89.2%), and not Medicare-Medicaid dual eligible (6.7% versus 8.8%). The median hospital-level rate of HHC use was 31.0% (interquartile range, 13.7%-54.5%) and ranged from 0% to 94.2%. Nearly 30% of the interhospital variation in HHC use was attributed to the discharging hospital (intraclass correlation coefficient, 0.296 [95% CI, 0.275-0.318]). Compared with non-HHC users, those using HHC were less likely to have a readmission or emergency department visit, were more likely to enroll in cardiac rehabilitation, and had modestly higher mortality within 30 or 90 days of discharge.

CONCLUSIONS

A third of Medicare beneficiaries undergoing coronary artery bypass grafting used HHC within 30 days of discharge, with wide interhospital variation in use and mixed associations with clinical outcomes and health care utilization.

2024 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

Racial and Ethnic Disparities in Home Health Referral Among Adult Medicare Patients

BACKGROUND

Home health care (HHC) services following hospital discharge provide essential continuity of care to mitigate risks of posthospitalization adverse outcomes and readmissions, yet patients from racial and ethnic minority groups are less likely to receive HHC visits.

OBJECTIVE

To examine how the association of nurse assessments of patients' readiness for discharge with referral to HHC services at the time of hospital discharge differs by race and ethnic minority group.

RESEARCH DESIGN

Secondary data analysis from a multisite study of the implementation of discharge readiness assessments in 31 US hospitals (READI Randomized Clinical Trial: 09/15/2014-03/31/2017), using linear and logistic models adjusted for patient demographic/clinical characteristics and hospital fixed effects.

SUBJECTS

All Medicare patients in the study's intervention arm (n=14,684).

MEASURES

Patient's race/ethnicity and discharge disposition code for referral to HHC (vs. home) from electronic health records. Patient's Readiness for Hospital Discharge Scale (RHDS) score (0-10 scale) assessed by the discharging nurse on the day of discharge.

RESULTS

Adjusted RHDS scores were similar for non-Hispanic White (8.21; 95% CI: 8.18-8.24), non-Hispanic Black (8.20; 95% CI: 8.12-8.28), Hispanic (7.92; 95% CI: 7.81-8.02), and other race/ethnicity patients (8.09; 95% CI: 8.01-8.17). Non-Hispanic Black patients with low RHDS scores (6 or less) were less likely than non-Hispanic White patients to be discharged with an HHC referral (Black: 26.8%, 95% CI: 23.3-30.3; White: 32.6%, 95% CI: 31.1-34.1).

CONCLUSIONS

Despite similar RHDS scores, Black patients were less likely to be discharged with HHC. A better understanding of root causes is needed to address systemic structural injustice in health care settings.

Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model

OBJECTIVES

Little is known about proactive risk assessment concerning emergency department (ED) visits and hospitalizations in patients with heart failure (HF) who receive home healthcare (HHC) services. This study developed a time series risk model for predicting ED visits and hospitalizations in patients with HF using longitudinal electronic health record data. We also explored which data sources yield the best-performing models over various time windows.

MATERIALS AND METHODS

We used data collected from 9362 patients from a large HHC agency. We iteratively developed risk models using both structured (eg, standard assessment tools, vital signs, visit characteristics) and unstructured data (eg, clinical notes). Seven specific sets of variables included: (1) the Outcome and Assessment Information Set, (2) vital signs, (3) visit characteristics, (4) rule-based natural language processing-derived variables, (5) term frequency-inverse document frequency variables, (6) Bio-Clinical Bidirectional Encoder Representations from Transformers variables, and (7) topic modeling. Risk models were developed for 18 time windows (1-15, 30, 45, and 60 days) before an ED visit or hospitalization. Risk prediction performances were compared using recall, precision, accuracy, F1, and area under the receiver operating curve (AUC).

RESULTS

The best-performing model was built using a combination of all 7 sets of variables and the time window of 4 days before an ED visit or hospitalization (AUC = 0.89 and F1 = 0.69).

DISCUSSION AND CONCLUSION

This prediction model suggests that HHC clinicians can identify patients with HF at risk for visiting the ED or hospitalization within 4 days before the event, allowing for earlier targeted interventions.

2023 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease, including prevalence and incidence, mortality and morbidity, use and costs of care, and the overall impact on family caregivers, the dementia workforce and society. The Special Report examines the patient journey from awareness of cognitive changes to potential treatment with drugs that change the underlying biology of Alzheimer's. An estimated 6.7 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060 barring the development of medical breakthroughs to prevent, slow or cure AD. Official death certificates recorded 121,499 deaths from AD in 2019, and Alzheimer's disease was officially listed as the sixth-leading cause of death in the United States. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2019, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 145%. This trajectory of deaths from AD was likely exacerbated by the COVID-19 pandemic in 2020 and 2021. More than 11 million family members and other unpaid caregivers provided an estimated 18 billion hours of care to people with Alzheimer's or other dementias in 2022. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $339.5 billion in 2022. Its costs, however, extend to family caregivers' increased risk for emotional distress and negative mental and physical health outcomes - costs that have been aggravated by COVID-19. Members of the paid health care workforce are involved in diagnosing, treating and caring for people with dementia. In recent years, however, a shortage of such workers has developed in the United States. This shortage - brought about, in part, by COVID-19 - has occurred at a time when more members of the dementia care workforce are needed. Therefore, programs will be needed to attract workers and better train health care teams. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2023 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $345 billion. The Special Report examines whether there will be sufficient numbers of physician specialists to provide Alzheimer's care and treatment now that two drugs are available that change the underlying biology of Alzheimer's disease.

The effect of performance pay incentives on market frictions: evidence from medicare

Medicare has increased the use of performance pay incentives for hospitals, with the goal of increasing care coordination across providers, reducing market frictions, and ultimately to improve quality of care. This paper provides new empirical evidence by using novel operations and claims data from a large, independent home health care firm with the Hospital Readmissions Reduction Program (HRRP) penalty on hospitals providing identifying variation. We find that the penalty incentive to reduce re-hospitalizations passed through from hospitals to the firm for at least some types of patients, since it provided more care inputs for heart disease patients discharged from hospitals at greater penalty risk and that contributed more patients to the firm. This evidence suggests that HRRP helped increase coordination between hospitals and home health firms without formal integration. Greater home health effort does not appear to have led to lower patient readmissions.

Self-reported gaps in care coordination and preventable adverse outcomes among older adults receiving home health care

BACKGROUND

Older adults see multiple outpatient providers and increasingly use home health care (HHC) services. Previous studies attempting to draw inferences about the association between HHC use and patient outcomes have been mixed. Whether HHC is associated with care coordination and how both influence outcomes are unknown. In addition, prior studies have not taken the patient perspective into account. We examined the association between receiving HHC and self-reported gaps in care coordination and separately, preventable adverse outcomes.

METHODS

The analysis for this cross-sectional study was conducted between October 2021 and June 2022, using data on 4296 Medicare beneficiaries from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who completed a survey on care coordination from 2017 to 2018. The associations between the receipt of HHC and two outcomes (a gap in care coordination, and separately, a preventable adverse event) were examined with Poisson models with robust standard errors. Potential confounders were accounted for through propensity score-based inverse probability weighting.

RESULTS

Among 4296 participants, 430 (10%) received HHC and they were older and had more comorbidities and ambulatory visits than those without HHC. HHC was not associated with differences in self-reported gaps in care coordination (33.3% HHC vs. 32.5% no-HHC, p = 0.70). HHC recipients reported more preventable drug-drug interactions (9.1% vs. 4.0%, p < 0.001) but not more preventable ED visits or hospital admissions. In IPW-adjusted models, HHC was not associated with gaps in care coordination (p = 0.60) but was associated with double the risk of a preventable adverse outcome (aRR 2.06; CI: 1.37, 3.10, p < 0.001).

CONCLUSIONS

HHC recipients were significantly more likely (than those without HHC) to report a potentially preventable adverse event (particularly a drug-drug interaction), suggesting an opportunity to improve patient safety by leveraging the observations of older adults receiving HHC.

Body Weight Measurement for Adjusting Diuretics Is Not Associated With Hospitalization and Mortality of Heart Failure Patients Under Home Medical Care

INTRODUCTION

The post-discharge readmission rate for heart failure (HF) is high. Although some previous studies have shown the efficacy of clinic-based patient education of regular weighing in preventing readmission; however, none of these studies were conducted in home care settings.

METHODS

This retrospective observational study aimed to assess whether using body weight as an indicator for treating HF with diuretics reduced hospitalization and mortality in home medical care settings. We included 70 patients diagnosed with HF who were treated with diuretics in home medical care. Seventeen patients were in the body weight measurement group, and 53 were in the control group. The primary outcome was the time of the first hospitalization or death due to any cause. The secondary outcome was the time to first hospitalization or death due to HF.

RESULTS

The crude hazard ratio (HR) for the primary outcome was 0.59 [95% confidence interval (CI), 0.33-1.1]. The crude HR for the secondary outcome was 0.95 (95% CI, 0.46-1.95). After adjusting for confounding factors, the results were found to be consistent.

CONCLUSION

Body weight measurement for treating HF was not associated with reduced hospitalization and mortality in medical care settings. Hence, physicians need other appropriate indicators.

Risk of Rehospitalization or Emergency Department Visit is Significantly Higher for Patients who Receive Their First Home Health Care Nursing Visit Later than 2 Days After Hospital Discharge

OBJECTIVES

This study explored the association between the timing of the first home health care nursing visits (start-of-care visit) and 30-day rehospitalization or emergency department (ED) visits among patients discharged from hospitals.

DESIGN

Our cross-sectional study used data from 1 large, urban home health care agency in the northeastern United States.

SETTING/PARTICIPANTS

We analyzed data for 49,141 home health care episodes pertaining to 45,390 unique patients who were admitted to the agency following hospital discharge during 2019.

METHODS

We conducted multivariate logistic regression analyses to examine the association between start-of-care delays and 30-day hospitalizations and ED visits, adjusting for patients' age, race/ethnicity, gender, insurance type, and clinical and functional status. We defined delays in start-of-care as a first nursing home health care visit that occurred more than 2 full days after the hospital discharge date.

RESULTS

During the study period, we identified 16,251 start-of-care delays (34% of home health care episodes), with 14% of episodes resulting in 30-day rehospitalization and ED visits. Delayed episodes had 12% higher odds of rehospitalization or ED visit (OR 1.12; 95% CI: 1.06-1.18) compared with episodes with timely care.

CONCLUSIONS AND IMPLICATIONS

The findings suggest that timely start-of-care home health care nursing visit is associated with reduced rehospitalization and ED use among patients discharged from hospitals. With more than 6 million patients who receive home health care services across the United States, there are significant opportunities to improve timely care delivery to patients and improve clinical outcomes.

Addressing the Gap in Data Communication from Home Health Care to Primary Care during Care Transitions: Completeness of an Interoperability Data Standard

In a future where home health care is no longer an information silo, patient information will be communicated along transitions in care to improve care. Evidence-based practice in the United States supports home health care patients to see their primary care team within the first two weeks of hospital discharge to reduce rehospitalization risk. We sought to identify a parsimonious set of home health care data to be communicated to primary care for the post-hospitalization visit. Anticipating electronic dataset communication, we investigated the completeness of the international reference terminology, Logical Observation Identifiers Names and Codes (LOINC), for coverage of the data to be communicated. We conducted deductive qualitative analysis in three steps: (1) identify home health care data available for the visit by mapping home health care to the information needed for the visit; (2) reduce the resulting home health care data set to a parsimonious set clinicians wanted for the post-hospitalization visit by eliciting primary care clinician input; and (3) map the parsimonious dataset to LOINC and assess LOINC completeness. Our study reduced the number of standardized home health care assessment questions by 40% to a parsimonious set of 33 concepts that primary care team physicians wanted for the post-hospitalization visit. Findings indicate all home health care concepts in the parsimonious dataset mapped to the information needed for the post-hospitalization visit, and 84% of the home health care concepts mapped to a LOINC term. The results indicate data flow of parsimonious home health care dataset to primary care for the post-hospitalization visit is possible using existing LOINC codes, and would require adding some codes to LOINC for communication of a complete parsimonious data set.

Improving transitions and outcomes of sepsis survivors (I-TRANSFER): a type 1 hybrid protocol

BACKGROUND

This protocol is based on home health care (HHC) best practice evidence showing the value of coupling timely post-acute care visits by registered nurses and early outpatient provider follow-up for sepsis survivors. We found that 30-day rehospitalization rates were 7 percentage points lower (a 41% relative reduction) when sepsis survivors received a HHC nursing visit within 2 days of hospital discharge, at least 1 more nursing visit the first week, and an outpatient provider follow-up visit within 7 days compared to those without timely follow-up. However, nationwide, only 28% of sepsis survivors who transitioned to HHC received this timely visit protocol. The opportunity exists for many more sepsis survivors to benefit from timely home care and outpatient services. This protocol aims to achieve this goal.  METHODS: Guided by the Consolidated Framework for Implementation Research, this Type 1 hybrid pragmatic study will test the effectiveness of the Improving Transitions and Outcomes of Sepsis Survivors (I-TRANSFER) intervention compared to usual care on 30-day rehospitalization and emergency department use among sepsis survivors receiving HHC. The study design includes a baseline period with no intervention, a six-month start-up period followed by a one-year intervention period in partnership with five dyads of acute and HHC sites. In addition to the usual care/control periods from the dyad sites, additional survivors from national data will serve as control observations for comparison, weighted to produce covariate balance. The hypotheses will be tested using generalized mixed models with covariates guided by the Andersen Behavioral Model of Health Services. We will produce insights and generalizable knowledge regarding the context, processes, strategies, and determinants of I-TRANSFER implementation.

DISCUSSION

As the largest HHC study of its kind and the first to transform this novel evidence through implementation science, this study has the potential to produce new knowledge about the impact of timely attention in HHC to alleviate symptoms and support sepsis survivor's recovery at home. If effective, the impact of this intervention could be widespread, improving the quality of life and health outcomes for a growing, vulnerable population of sepsis survivors. A national advisory group will assist with widespread results dissemination.

2022 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including incidence and prevalence, mortality and morbidity, use and costs of care, and the overall impact on family caregivers, the dementia workforce and society. The Special Report discusses consumers' and primary care physicians' perspectives on awareness, diagnosis and treatment of mild cognitive impairment (MCI), including MCI due to Alzheimer's disease. An estimated 6.5 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060 barring the development of medical breakthroughs to prevent, slow or cure AD. Official death certificates recorded 121,499 deaths from AD in 2019, the latest year for which data are available. Alzheimer's disease was officially listed as the sixth-leading cause of death in the United States in 2019 and the seventh-leading cause of death in 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2019, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 145%. More than 11 million family members and other unpaid caregivers provided an estimated 16 billion hours of care to people with Alzheimer's or other dementias in 2021. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $271.6 billion in 2021. Its costs, however, extend to family caregivers' increased risk for emotional distress and negative mental and physical health outcomes - costs that have been aggravated by COVID-19. Members of the dementia care workforce have also been affected by COVID-19. As essential care workers, some have opted to change jobs to protect their own health and the health of their families. However, this occurs at a time when more members of the dementia care workforce are needed. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2022 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $321 billion. A recent survey commissioned by the Alzheimer's Association revealed several barriers to consumers' understanding of MCI. The survey showed low awareness of MCI among Americans, a reluctance among Americans to see their doctor after noticing MCI symptoms, and persistent challenges for primary care physicians in diagnosing MCI. Survey results indicate the need to improve MCI awareness and diagnosis, especially in underserved communities, and to encourage greater participation in MCI-related clinical trials.

Transitions of Care: Completeness of the Interoperability Data Standard for Communication from Home Health Care to Primary Care

Data sharing is necessary to address communication deficits along the transitions of care among community settings. Evidence-based practice supports home healthcare (HHC) patients to see their primary care team within the first two weeks of hospital discharge to reduce rehospitalization risk. A small subset of patient data collected at HHC admission is mandated to be transmitted to primary care, predominantly by fax. Using qualitative analysis, we assessed completeness of the United States Core Data for Interoperability (USCDI) interoperability standard, as compared to the patient data collected by the primary care team (topics) and HHC (classes) during the initial visit; and offer interoperability recommendations. Findings indicate the USCDI does not cover 74% of the 19 faxed HHC classes that mapped to the primary care topics, and 95% of the 38 not-faxed HHC classes. We offer USCDI recommendations to address these interoperability gaps.

Rural and urban disparities in quality of home health care: A longitudinal cohort study (2014-2018)

PURPOSE

Home health care is one of the fastest growing health care sectors in the United States. However, little is known of differences in trends in quality performance between rural and urban home health agencies over time. This study aimed to examine disparities in quality performance between rural and urban home health agencies between 2014 and 2018.

METHODS

This is a cohort study using 2014-2018 national Home Health Compare data and Providers of Service Profile data, including 7,908 home health agencies, of which 1,537 were rural agencies. Quality performance measures included timely initiation of care, hospitalization, and emergency department (ED) visits. Two-level hierarchical regression models were used to identify rural-urban differences in these quality indicators over time when controlling organizational characteristics.

FINDINGS

Rural agencies were less likely to be for-profit and accredited, and more likely to be hospital-based, serve both Medicare and Medicaid beneficiaries, and have hospice programs. Rural agencies consistently outperformed on timely initiation of care over time, and urban agencies consistently outperformed on hospitalization and ED visits over time. These gaps between rural and urban agencies were steady over time except the gap in hospitalization, which slightly narrowed over time (Coef. = 0.11, P = .001 for urban and year interaction term).

CONCLUSIONS

Significant differences exist in quality of care between rural and urban home health agencies and such differences have not been significantly narrowed over time. To reduce rural-urban disparities, policy makers should take into account unique challenges faced by urban and rural agencies when making policy decisions.

Exploring Reasons for Delayed Start-of-Care Nursing Visits in Home Health Care: Algorithm Development and Data Science Study

BACKGROUND

Delayed start-of-care nursing visits in home health care (HHC) can result in negative outcomes, such as hospitalization. No previous studies have investigated why start-of-care HHC nursing visits are delayed, in part because most reasons for delayed visits are documented in free-text HHC nursing notes.

OBJECTIVE

The aims of this study were to (1) develop and test a natural language processing (NLP) algorithm that automatically identifies reasons for delayed visits in HHC free-text clinical notes and (2) describe reasons for delayed visits in a large patient sample.

METHODS

This study was conducted at the Visiting Nurse Service of New York (VNSNY). We examined data available at the VNSNY on all new episodes of care started in 2019 (N=48,497). An NLP algorithm was developed and tested to automatically identify and classify reasons for delayed visits.

RESULTS

The performance of the NLP algorithm was 0.8, 0.75, and 0.77 for precision, recall, and F-score, respectively. A total of one-third of HHC episodes (n=16,244) had delayed start-of-care HHC nursing visits. The most prevalent identified category of reasons for delayed start-of-care nursing visits was no answer at the door or phone (3728/8051, 46.3%), followed by patient/family request to postpone or refuse some HHC services (n=2858, 35.5%), and administrative or scheduling issues (n=1465, 18.2%). In 40% (n=16,244) of HHC episodes, 2 or more reasons were documented.

CONCLUSIONS

To avoid critical delays in start-of-care nursing visits, HHC organizations might examine and improve ways to effectively address the reasons for delayed visits, using effective interventions, such as educating patients or caregivers on the importance of a timely nursing visit and improving patients' intake procedures.

Evaluation of the Effect of Intensive Nursing Intervention Based on Process Analysis

In order to achieve significant improvements in the evaluation of key indicators such as speed, quality, cost, and service, this paper fundamentally rethinks and completely redesigns the business process, and recreates a new business process. This study combines the particularity of AMI with emergency nursing to construct an in-hospital AMI emergency nursing process to further standardize the AMI rescue work. The implementation of the process helps to clarify the responsibilities and requirements of nurses in the AMI emergency process, reduce the delay time of AMI emergency, and improve the efficiency and effectiveness of emergency. In addition, after refactoring the business process, this paper builds an intelligent digital critical illness monitoring system. This system combines the original work flow of the ICU medical staff, optimizes the work flow of the medical staff through computer technology and information technology, and designs and completes the digital intensive nursing system software to run and use in the hospital and obtain significant results.

Investigating the demands for mobile internet-based home nursing services for the elderly

The great value of home nursing services in the treatment of ailments in elderly patients has attracted increasing attention. This study describes a new mobile internet-based home nursing service system and investigates the reasons for its use among elderly patients. 520 cases of mobile internet-based home nursing services were investigated. The proportion of major reasons to use mobile internet-based home nursing services among the elderly was analyzed and the satisfaction rate was investigated. The constituent ratios of nursing care for pressure ulcers, peripherally inserted central catheter (PICC), subcutaneous injection, general stoma care, psychological care, and intramuscular injection were 61.35%, 28.85%, 6.15%, 1.92%, 1.35%, and 0.38%, respectively. The satisfaction rate with mobile internet-based home nursing services among elderly patients was 100%. Considering the demand for home nursing services for elderly patients, this is the first time that a new mobile internet-based home nursing service has been applied to provide home nursing services to elderly patients and meet their home nursing service needs. Treatment for pressure ulcers, PICC, subcutaneous injection, general stoma care, psychological care, and intramuscular injection were found to be the main reasons to use mobile internet-based home nursing services among the elderly. The new mobile internet-based home nursing service system provides convenient home nursing services to elderly patients and ensures that they get equal rights in home nursing. The results provide basis for healthcare policy makers to formulate new home nursing policies for elderly patients.

Assessing the influence of patient language preference on 30 day hospital readmission risk from home health care: A retrospective analysis

BACKGROUND

In home health care, language barriers are understudied. Language barriers between patients and providers are known to affect a variety of patient outcomes. How a patient's language preference influences hospital readmission risk from home health care has yet to be determined.

OBJECTIVE

To determine if home care patients' language preference is associated with their risk for hospital readmission from home health care within 30 days of hospital discharge.

DESIGN

Retrospective cross-sectional study of hospital readmissions from an urban home health care agency's administrative records and the national electronic home health care record for the United States, captured between 2010 and 2015.

SETTING

New York City, New York, USA.

PARTICIPANTS

The dataset comprised 90,221 post-hospitalization patients and 6.5 million home health care visits.

METHODS

First, a Chi-square test was used to determine if there were significant differences in crude readmission rates based on language group. Inverse probability of treatment weighting was used to adjust for significant differences in known hospital readmission risk factors between to examine all-cause hospital readmission during a home health care stay. The final matched sample included 87,561 patients with a language preference of English, Spanish, Russian, Chinese, or Korean. English-speaking patients were considered the comparison group to the non-English speaking patients. A Marginal Structural Model was applied to estimate the impact of non-English language preference against English language preference on rehospitalization. The results of the marginal structural model were expressed as an odds ratio of likelihood of readmission to the hospital from home health care.

RESULTS

Home health patients with a non-English language preference had a higher hospital readmission risk than English-speaking patients. Crude readmission rate for the limited English proficiency patients was 20.4% (95% CI, 19.9-21.0%) overall compared to 18.5% (95% CI, 18.7-19.2%) for English speakers (p < 0.001). Being a non-English-speaking patient was associated with an odds ratio of 1.011 (95% CI, 1.004-1.018) in increased hospital readmission rates from home health care (p = 0.001). There were also statistically significant differences in readmission rate by language group (p < 0.001), with Korean speakers having the lowest rate and Spanish speakers having the highest, when compared to English speakers.

CONCLUSIONS

People with a non-English language preference have a higher readmission rate from home health care. Hospital and home healthcare agencies may need specialized care coordination services to reduce readmission risk for these patients. Tweetable abstract: A new US-based study finds that home care patients with language barriers are at higher risk for hospital readmission.

Home health care after discharge is associated with lower readmission rates for patients with acute myocardial infarction

OBJECTIVE

We studied the utilization of home health care (HHC) among acute myocardial infarction (AMI) patients, impact of HHC on and predictors of 30-day readmission.

METHODS

We queried the National Readmission Database (NRD) from 2012 to 2014identify patients with AMI discharged home with (HHC+) and without HHC (HHC-). Linkage provided in the data identified patients who had 30-day readmission, our primary end-point. The probability for each patient to receive HHC was calculated by a multivariable logistic regression. Average treatment of treated weights were derived from propensity scores. Weight-adjusted logistic regression was used to determine impact of HHC on readmission.

RESULTS

A total of 406 237 patients with AMI were discharged home. Patients in the HHC+ cohort (38 215 patients, 9.4%) were older (mean age 77 vs. 60 years P < 0.001), more likely women (53 vs. 26%, P < 0.001), have heart failure (5 vs. 0.5%, P < 0.001), chronic kidney disease (26 vs. 6%, P < 0.001) and diabetes (35 vs. 26%, P < 0.001). Patients readmitted within 30-days were older with higher rates of diabetes (RR = 1.4, 95% CI: 1.37-1.48) and heart failure (RR = 5.8, 95% CI: 5.5-6.2). Unadjusted 30-day readmission rates were 21 and 8% for HHC+ and HHC- patients, respectively. After adjustment, readmission was lower with HHC (21 vs. 24%, RR = 0.89, 95% CI: 0.82-0.96; P < 0.001).

CONCLUSION

In the United States, AMI patients receiving HHC are older and have more comorbidities; however, HHC was associated with a lower 30-day readmission rate.

Timing of Home Health Care Initiation and 30-Day Rehospitalizations among Medicare Beneficiaries with Diabetes by Race and Ethnicity

Older adults with diabetes are at elevated risk of complications following hospitalization. Home health care services mitigate the risk of adverse events and facilitate a safe transition home. In the United States, when home health care services are prescribed, federal guidelines require they begin within two days of hospital discharge. This study examined the association between timing of home health care initiation and 30-day rehospitalization outcomes in a cohort of 786,734 Medicare beneficiaries following a diabetes-related index hospitalization admission during 2015. Of these patients, 26.6% were discharged to home health care. To evaluate the association between timing of home health care initiation and 30-day rehospitalizations, multivariate logistic regression models including patient demographics, clinical and geographic variables, and neighborhood socioeconomic variables were used. Inverse probability-weighted propensity scores were incorporated into the analysis to account for potential confounding between the timing of home health care initiation and the outcome in the cohort. Compared to the patients who received home health care within the recommended first two days, the patients who received delayed services (3-7 days after discharge) had higher odds of rehospitalization (OR, 1.28; 95% CI, 1.25-1.32). Among the patients who received late services (8-14 days after discharge), the odds of rehospitalization were four times greater than among the patients receiving services within two days (OR, 4.12; 95% CI, 3.97-4.28). Timely initiation of home health care following diabetes-related hospitalizations is one strategy to improve outcomes.

Factors Associated with Timing of the Start-of-Care Nursing Visits in Home Health Care

OBJECTIVES

Home health care patients have critical needs requiring timely care following hospital discharge. Although Medicare requires timely start-of-care nursing visits, a significant portion of home health care patients wait longer than 2 days for the first visit. No previous studies investigated the pattern of start-of-care visits or factors associated with their timing. This study's purpose was to examine variation in timing of start-of-care visits and characterize patients with visits later than 2 days postdischarge.

DESIGN

Retrospective cohort study.

SETTING/PARTICIPANTS

Patients admitted to a large, Northeastern US, urban home health care organization during 2019. The study included 48,497 home care episodes for 45,390 individual patients.

MEASUREMENT

We calculated time to start of care from hospital discharge for 2 patient groups: those seen within 2 days vs those seen >2 days postdischarge. We examined patient factors, hospital discharge factors, and timing of start of care using multivariate logistic regression.

RESULTS

Of 48,497 episodes, 16,251 (33.5%) had a start-of-care nursing visit >2 days after discharge. Increased odds of this time frame were associated with being black or Hispanic and having solely Medicaid insurance. Odds were highest for patients discharged on Fridays, Saturdays, and Mondays. Factors associated with visits within 2 days included surgical wound presence, urinary catheter, pain, 5 or more medications, and intravenous or infusion therapies at home.

CONCLUSIONS AND IMPLICATIONS

Findings provide the first publication of clinical and demographic characteristics associated with home health care start-of-care timing and its variation. Further examination is needed, and adjustments to staff scheduling and improved information transfer are 2 suggested interventions to decrease variation.

Racial Disparities in Post-Acute Home Health Care Referral and Utilization among Older Adults with Diabetes

Racial and ethnic disparities exist in diabetes prevalence, health services utilization, and outcomes including disabling and life-threatening complications among patients with diabetes. Home health care may especially benefit older adults with diabetes through individualized education, advocacy, care coordination, and psychosocial support for patients and their caregivers. The purpose of this study was to examine the association between race/ethnicity and hospital discharge to home health care and subsequent utilization of home health care among a cohort of adults (age 50 and older) who experienced a diabetes-related hospitalization. The study was limited to patients who were continuously enrolled in Medicare for at least 12 months and in the United States. The cohort (n = 786,758) was followed for 14 days after their diabetes-related index hospitalization, using linked Medicare administrative, claims, and assessment data (2014–2016). Multivariate logistic regression models included patient demographics, comorbidities, hospital length of stay, geographic region, neighborhood deprivation, and rural/urban setting. In fully adjusted models, hospital discharge to home health care was significantly less likely among Hispanic (OR 0.8, 95% CI 0.8–0.8) and American Indian (OR 0.8, CI 0.8–0.8) patients compared to White patients. Among those discharged to home health care, all non-white racial/ethnic minority patients were less likely to receive services within 14-days. Future efforts to reduce racial/ethnic disparities in post-acute care outcomes among patients with a diabetes-related hospitalization should include policies and practice guidelines that address structural racism and systemic barriers to accessing home health care services.

Planning the Episode: Home Care Admission Nurse Decision-Making Regarding the Patient Visit Pattern

During home health care (HHC) admissions, nurses provide input into decisions regarding the skilled nursing visit frequency and episode duration. This important clinical decision can impact patient outcomes including hospitalization. Episode duration has recently gained greater importance due to the Centers for Medicare and Medicaid Services (CMS) decrease in reimbursable episode length from 60 to 30 days. We examined admissions nurses’ visit pattern decision-making and whether it is influenced by documentation available before and during the first home visit, agency standards, other disciplines being scheduled, and electronic health record (EHR) use. This observational mixed-methods study included admission document analysis, structured interviews, and a think-aloud protocol with 18 nurses from 3 diverse HHC agencies (6 at each) admitting 2 patients each (36 patients). Findings show that prior to entering the home, nurses had an information deficit; they either did not predict the patient’s visit frequency and episode duration or stated them based on experience with similar patients. Following patient interaction in the home, nurses were able to make this decision. Completion of documentation using the EHR did not appear to influence visit pattern decisions. Patient condition and insurance restrictions were influential on both frequency and duration. Given the information deficit at admission, and the delay in visit pattern decision making, we offer health information technology recommendations on electronic communication of structured information, and EHR documentation and decision support.

Improving Patient Prioritization During Hospital-Homecare Transition: Protocol for a Mixed Methods Study of a Clinical Decision Support Tool Implementation

Background

Homecare settings across the United States provide care to more than 5 million patients every year. About one in five homecare patients are rehospitalized during the homecare episode, with up to two-thirds of these rehospitalizations occurring within the first 2 weeks of services. Timely allocation of homecare services might prevent a significant portion of these rehospitalizations. The first homecare nursing visit is one of the most critical steps of the homecare episode. This visit includes an assessment of the patient’s capacity for self-care, medication reconciliation, an examination of the home environment, and a discussion regarding whether a caregiver is present. Hence, appropriate timing of the first visit is crucial, especially for patients with urgent health care needs. However, nurses often have limited and inaccurate information about incoming patients, and patient priority decisions vary significantly between nurses. We developed an innovative decision support tool called Priority for the First Nursing Visit Tool (PREVENT) to assist nurses in prioritizing patients in need of immediate first homecare nursing visits.

Objective

This study aims to evaluate the effectiveness of the PREVENT tool on process and patient outcomes and to examine the reach, adoption, and implementation of PREVENT.

Methods

Employing a pre-post design, survival analysis, and logistic regression with propensity score matching analysis, we will test the following hypotheses: compared with not using the tool in the preintervention phase, when homecare clinicians use the PREVENT tool, high-risk patients in the intervention phase will (1) receive more timely first homecare visits and (2) have decreased incidence of rehospitalization and have decreased emergency department use within 60 days. Reach, adoption, and implementation will be assessed using mixed methods including homecare admission staff interviews, think-aloud observations, and analysis of staffing and other relevant data.

Results

The study research protocol was approved by the institutional review board in October 2019. PREVENT is currently being integrated into the electronic health records at the participating study sites. Data collection is planned to start in early 2021.

Conclusions

Mixed methods will enable us to gain an in-depth understanding of the complex socio-technological aspects of the hospital to homecare transition. The results have the potential to (1) influence the standardization and individualization of nurse decision making through the use of cutting-edge technology and (2) improve patient outcomes in the understudied homecare setting.

Trial Registration

ClinicalTrials.gov NCT04136951; https://clinicaltrials.gov/ct2/show/NCT04136951

International Registered Report Identifier (IRRID)

PRR1-10.2196/20184

Gender differences in the impact of frailty on 90-day hospital readmission in heart failure patients: a retrospective cohort study

AIMS

Frequent hospital readmissions after heart failure (HF) are common, however, there is limited data on the association between frailty status and hospital readmission in HF patients. This study aimed to examine the 90-day hospital readmission rates and gender differences in the impact of frailty on 90-day hospital readmission in HF patients.

METHODS AND RESULTS

We retrospectively analysed hospital discharge records of 279 patients (men = 169, women = 110) who were diagnosed with HF between January 2017 and December 2018. Frailty was assessed using the Korean version of the FRAIL scale. A logistic regression analysis was conducted to explore the factors predicting 90-day hospital readmission by gender. The prevalence of frailty and 90-day hospital readmissions were ∼54.4% and 22.7% in women, compared with 45.6% and 27.8% in men, respectively. Frail patients with HF have an increased risk of 90-day hospital readmission in both males and females. Particularly, women with frailty had a higher risk of 90-day hospital readmission [adjusted odds ratio (OR) 6.72, 95% confidence interval (CI) 1.41-32.09] than men with frailty (adjusted OR 4.40, 95% CI 1.73-11.17).

CONCLUSION

Our findings highlight that readmission within 90 days of hospitalization for HF can be predicted by patients' frailty. More importantly, we found that women with frailty have a greater risk of readmission than men with frailty. Screening for frailty should therefore be integrated into the assessment of HF patients. Tailored interventions for preventing adverse outcomes should consider gender-associated factors in HF patients with frailty.

Incomplete Home Health Care Referral After Hospitalization Among Medicare Beneficiaries

OBJECTIVES

Patients who are referred to home health care after an acute care hospitalization may not receive home health care, resulting in incomplete home health referrals. This study examines the prevalence of incomplete referrals to home health, defined as not receiving home health care within 7 days after an initial hospital discharge, and investigates the relationship between home health referral completion and patient outcomes.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Medicare beneficiaries who are discharged from short-term acute care hospitals between October 2015 and December 2016 with a discharge status code on the hospital claim indicating home health care.

METHODS

Patient characteristics and outcomes were compared between Medicare beneficiaries with complete and incomplete home health referrals after hospital discharge. The outcomes included mortality, readmission rate, and total spending over a 1-year episode following hospitalization. These outcomes were risk-adjusted using patient demographic, socioeconomic, clinical characteristic, hospital characteristic, and state fixed effects.

RESULTS

Approximately 29% of the 724,700 hospitalizations in the analytic dataset had incomplete home health referrals after discharge. The rate of incomplete home health referrals varied among clinical conditions, ranging from 17% among joint/musculoskeletal patients and 38% among digestive/endocrine patients. Risk-adjusted 1-year mortality and readmission rates were 1.4 and 2.4 percentage points lower and total spending was $1053 higher among patients with complete home health referrals as compared with those with incomplete home health referrals after hospital discharge.

CONCLUSIONS AND IMPLICATIONS

The analysis revealed that almost 1 in 3 patients discharged from a hospital with a discharge status of home health does not receive home health care. In addition, complete home health referrals are associated with lower mortality and readmission rates and higher spending. As home health care utilization increases, policymakers should pay attention to the tradeoff between quality and cost when implementing alternative policies and payment models.

Receipt of Timely Primary Care Services Following Post-Acute Skilled Nursing Facility Care

OBJECTIVES

Our study examined the proportion of skilled nursing facility (SNF) post-acute care residents who did not receive timely primary care provider (PCP) services following discharge, factors associated with lack of timely PCP services, and factors associated with perfect 30-day home time among those who did not receive timely PCP services.

DESIGN

Longitudinal cohort study; data sources included Medicare claims and other administrative databases.

SETTING AND PARTICIPANTS

25,357 fee-for-service New York State Medicare beneficiaries aged 65 years and older admitted to SNFs for post-acute care in 2014 and then discharged to the community.

METHODS

Our outcomes were a timely PCP visit (within 7 days of SNF discharge) and perfect 30-day home time, and we examined their association with patient, SNF, and county factors.

RESULTS

Among SNF discharges, 60.6% had a timely PCP visit. In multivariate regression analyses, female sex, nonwhite race, Medicare only status, less functional impairment and medical comorbidity, a surgical hospitalization, fewer hospital days, more SNF days, absence of home health services, for-profit SNF status, higher SNF star rating, lower ratio of registered nurse/total nursing hours, and rural counties were associated with lower odds of a timely PCP visit following SNF discharge. Among those without a timely PCP visit, female sex, less cognitive and functional impairment, less medical comorbidity, a surgical hospitalization, fewer hospital days, receipt of home health services, and higher SNF star rating were associated with increased odds of perfect 30-day home time following SNF discharge.

CONCLUSIONS AND IMPLICATIONS

That 4 in 10 post-acute care SNF patients did not have a timely PCP visit post-SNF discharge, with racial minority and rural county status associated with decreased odds of a timely PCP visit, is concerning. Examination of whether the timing and type of outpatient visit may have varying effects on different post-acute care subpopulations would build on this work.

Patient stratification for risk of readmission due to heart failure by using nationwide administrative data

BACKGROUND

Identifying patients with heart failure (HF) who are most at risk of readmission permits targeting adapted interventions. The use of administrative data enables regulators to support the implementation of such interventions.

METHODS AND RESULTS

In a French nationwide cohort of patients aged 65 years or older, surviving an index hospitalization for HF in 2015 (N = 70,657), we studied HF readmission predictors available in administrative data, distinguishing HF severity from overall morbidity and taking into account the competing mortality risk, over a 1-year follow-up period. We also computed cumulative incidences and daily rates of HF readmission for patient groups defined according to HF severity and overall morbidity. Of the patients, 31.8% (n = 22,475) were readmitted at least once for HF, and 17.6% (n = 12,416) died without any readmission for HF. HF severity and overall morbidity were the strongest readmission predictors were the strongest readmission predictors (subdistribution hazard ratios 2.66 [95% CI: 2.52-2.81] and 1.37 [1.30-1.45], respectively, when comparing extreme categories). Overall morbidity and age were more strongly associated with the rate of death without HF readmission (cause-specific hazard ratios). The difference in observed HF readmission between patient risk groups was approximately 40% (21.9%, n = 2144/9,786 vs 60.4%, n = 618/1023).

CONCLUSIONS

Segmentation of HF patients into readmission risk groups is possible by using administrative data, and it enables the targeting of preventive interventions.

Patient Factors Linked with Return Acute Healthcare Use in Older Adults by Discharge Disposition

OBJECTIVES

Compare patient characteristics by hospital discharge disposition (home without services, home with home healthcare (HHC) services, or post-acute care (PAC) facilities). Examine timing and rates of 30-day healthcare utilization (rehospitalization, emergency department (ED) visit, or observation (OBS) visit) and patient characteristics associated with rehospitalization by discharge location.

DESIGN

Retrospective analysis of hospital administrative and clinical data.

SETTING AND PARTICIPANTS

A total of 3,294 older adult inpatients discharged home with or without HHC services or to a PAC facility.

MEASUREMENTS

Patient-level sociodemographic and clinical characteristics. Number of and time to occurrences of rehospitalization or ED/OBS visit within 30 days of hospital discharge.

RESULTS

Most rehospitalizations and ED/OBS visits occurred within 14 days from hospital discharge. Patients who returned within 24 hours came mostly from inpatient rehabilitation facilities (IRFs). More intense levels of PAC services were linked with higher rehospitalization risk. However, specific predictors differed by discharge location. Being unemployed, being single, and having more comorbidities were most associated with rehospitalization in those who went home with or without services, whereas patients rehospitalized from IRFs were younger, with less chronic illness burden, but greater and recent functional decline. Those discharged with HHC services had more return ED/OBS visits.

CONCLUSIONS

Although sicker patients were referred for more intense levels of PAC services, patients with greater chronic illness burden were still most often rehospitalized. In addition to unique patient differences, rehospitalizations from IRF within 24 hours suggest systems factors are contributory. Most return acute healthcare utilization occurred within 14 days; therefore, interventions should focus on smoothing transitions to all discharge locations. Because predictors of rehospitalization risk differed by discharge disposition, future research is necessary to study approaches aimed at matching patients' care needs with the most suitable PAC services at the right time. J Am Geriatr Soc 68:2279-2287, 2020.

Home care nurses' identification of patients at risk of infection and their risk mitigation strategies: A qualitative interview study

BACKGROUND

There is an increase in the number of individuals who receive care at home. A significant proportion of these patients acquire infections during their care episode. Whilst there has been significant focus on strategies for infection prevention and control in acute care environments, there is a lack of research into infection prevention in a home care setting.

OBJECTIVES

To understand (1) if and how home care nurses identify patients at high risk of infection and (2) the strategies they use to mitigate that risk.

DESIGN

A qualitative descriptive study, using semi-structured interviews.

SETTING

A large not for profit home care agency located in the New York region of the United States.

PARTICIPANTS

Fifty nurses with a range of experience in home care nursing.

METHODS

Purposive and snowball sampling was used to recruit nurses from across the home care agency with varied years of work experience. Interviews were audio recorded and transcribed. The interviews explored how home care nurses evaluate their patients' risk of developing an infection and if/how they modify the plan of care based on that risk. Data were analysed using thematic analysis.

RESULTS

Three themes were derived from the data; assessing a patient's risk of infection, the risk assessment process, and strategies for mitigating infection risk. Factors identified by nurses as putting a patient at higher risk of infection included being older, having diabetes, inadequate nutrition; along with inadequate clinical information available at start of care. The patient's knowledge and understanding of infection prevention, and the availability and knowledge of caregivers were also important, as was the cleanliness of the home environment. Given the context of home care, where nurses have little control over the environment and care processes in-between visits, the main strategy for infection prevention was patient and caregiver education. Nurses also discussed the importance of their own infection prevention behaviours, and the ability to adjust a patient's plan of care according to their infection risk.

CONCLUSIONS

The study highlights the complexity of the risk assessment process in relation to infection. Existing guidelines for infection prevention and control do not adequately cover the home care environment and more research needs to determine which interventions (such as patient/caregiver education) would be most effective to prevent infections in the home care setting.

Composite Outcomes of Mortality and Readmission in Patients with Heart Failure: Retrospective Review of Administrative Datasets

Background

Controlling the quality of care through readmissions and mortality for patients with heart failure (HF) is a national priority for healthcare regulators in developed countries. In this longitudinal cohort study, using administrative data such as hospital discharge forms (HDFs), emergency departments (EDs) accesses, and vital statistics, we test new covariates for predicting mortality and readmissions of patients hospitalized for HF and discuss the use of combined outcome as an alternative.

Methods

Logistic models, with a stepwise selection method, were estimated on 70% of the sample and validated on the remaining 30% to evaluate 30-day mortality, 30-day readmissions, and the combined outcome. We followed an extraction method for any-cause mortality and unplanned readmission within 30 days after incident HF hospitalization. Data on patient admission and previous history were extracted by HDFs and ED dataset.

Results

Our principal findings demonstrate that the model’s discriminant ability is consistent with literature both for mortality (AUC=0.738, CI (0.729–0.748)) and readmissions (AUC=0.578, CI (0.562–0.594)). Additionally, the discriminant ability of the composite outcome model is satisfactory (AUC=0.675, CI (0.666–0.684)).

Conclusion

Hospitalization characteristics and patient history introduced in the logistic models do not improve their discriminant ability. The composite outcome prediction is led more by mortality than readmission, without improvements for the comprehension of the readmission phenomenon.

The Demographics and Economics of Direct Care Staff Highlight Their Vulnerabilities Amidst the COVID-19 Pandemic

An estimated 3.5 million direct care staff working in facilities and people's homes play a critical role during the COVID-19 pandemic. They allow vulnerable care recipients to stay at home and they provide necessary help in facilities. Direct care staff, on average, have decades of experience, often have certifications and licenses, and many have at least some college education to help them perform the myriad of responsibilities to properly care for care recipients. Yet, they are at heightened health and financial risks. They often receive low wages, limited benefits, and have few financial resources to fall back on when they get sick themselves and can no longer work. Furthermore, most direct care staff are parents with children in the house and almost one-fourth are single parents. If they fall ill, both they and their families are put into physical and financial risk.

Understanding the Workflow of Home Health Care for Patients with Heart Failure: Challenges and Opportunities

BACKGROUND

Readmission rates are high among heart failure (HF) patients who require home health care (HHC) after hospitalization. Although HF patients who require HHC are often sicker than those who do not, HHC delivery itself may also be suboptimal.

OBJECTIVE

We aimed to describe the workflow of HHC among adults discharged home after a HF hospitalization, including the roles of various stakeholders, and to determine where along these workflow challenges and opportunities for improvement exist.

DESIGN AND PARTICIPANTS

In this qualitative study, we used purposeful sampling to approach and recruit a variety of key stakeholders including home health aides, nurses, HF patients, family caregivers, physicians, social workers, home care agency leaders, and policy experts. The study took place in New York, NY, from March to October 2018.

APPROACH

Using a semi-structured topic guide, we elicited participants' experiences with HHC in HF through a combination of one-on-one interviews and focus groups. Data were recorded, transcribed, and analyzed thematically. We also asked selected participants to depict in a drawing their understanding of HHC workflow after hospitalization for HF patients. We synthesized the drawings into a final image.

KEY RESULTS

Study participants (N = 80) described HHC for HF patients occurring in 6 steps, with home health aides playing a main role: (1) transitioning from hospital to home; (2) recognizing clinical changes; (3) making decisions; (4) managing symptoms; (5) asking for help; and (6) calling 911. Participants identified challenges and opportunities for improvement for each step.

CONCLUSIONS

Our findings suggest that HHC for HF patients occurs in discrete steps, each with different challenges. Rather than a one-size-fits-all approach, various interventions may be required to optimize HHC delivery for HF patients in the post-discharge period.

Functional outcome in home health: Do racial and ethnic minority patients with dementia fare worse?

Objectives

Evaluate the independent and interactive effects of dementia and racial/ethnic minority status on functional outcomes during a home health (HH) admission among Medicare beneficiaries.

Methods

Secondary analysis of data from the Outcome and Assessment Information Set [OASIS] and billing records in a non-profit HH agency in New York. Participants were adults ≥ 65 years old who received HH in CY 2017 with OASIS records at HH admission and HH discharge. Dementia was identified by diagnosis (ICD-10 codes) and cognitive impairment (OASIS: M1700, M1710, M1740). We used OASIS records to assess race/ethnicity (M0140) and functional status (M1800-M1870 on activities of daily living [ADL]). Functional outcome was measured as change in the composite ADL score from HH admission to HH discharge, where a negative score means improvement and a positive score means decline.

Results

The sample included 4,783 patients, among whom 93.9% improved in ADLs at HH discharge. In multivariable linear regression that adjusted for HH service use and covariates (R² = 0.23), being African American (β = 0.21, 95% confidence interval [CI]: 0.06, 0.35, p = 0.005) and having dementia (β = 0.51, 95% CI: 0.41, 0.62, p<0.001) were independently related to less ADL improvement at HH discharge, with significant interaction related to further decrease in ADL improvement. Relative to white patients without dementia, African American patients with dementia (β = 1.08, 95% CI: 0.81, 1.35, p<0.001), Hispanics with dementia (β = 0.92, 95% CI: 0.38, 1.47, p = 0.001) and Asian Americans with dementia (β = 1.47, 95% CI: 0.81, 2.13, p<0.001) showed the least ADL improvement at HH discharge.

Conclusion

Racial/ethnic minority status and dementia were associated with less ADL improvement in HH with independent and interactive effects. Policies should ensure that these patients have equitable access to appropriate, adequate community-based services to meet their needs in ADLs and disease management for improved outcomes.

Risk Factors for Long-term Mortality and Patterns of End-of-Life Care Among Medicare Sepsis Survivors Discharged to Home Health Care

IMPORTANCE

Despite a growing recognition of the increased mortality risk among sepsis survivors, little is known about the patterns of end-of-life care among this population.

OBJECTIVE

To describe patterns of end-of-life care among a national sample of sepsis survivors and identify factors associated with long-term mortality risk and hospice use.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study assessed sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care using national Medicare administrative, claims, and home health assessment data from 2013 to 2014. The initial and final primary analyses were conducted in July 2017 and from July to August 2019, respectively.

EXPOSURES

Sepsis hospital discharge and 1 or more home health assessments within 1 week.

MAIN OUTCOMES AND MEASURES

Outcomes were 1-year mortality among all sepsis survivors and hospitalization in the last 30 days of life, death in an acute care hospital, and hospice use among decedents. Multivariate logistic regression was used to identify factors associated with 1-year mortality and hospice use.

RESULTS

Among 87 581 sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care, 49 323 (56.3%) were aged 75 years or older, 69 499 (79.4%) were non-Hispanic white, and 48 472 (55.3%) were female. Among the total survivors, 24 423 (27.9%) people died within 1 year of discharge, with a median (interquartile range) survival time of 119 (51-220) days. Among these decedents, 16 684 (68.2%) were hospitalized in the last 30 days of life, 6560 (26.8%) died in an acute care hospital, and 12 573 (51.4%) were enrolled in hospice, with 5729 (45.6%) using hospice for 7 or fewer days. Several factors were associated with 1-year mortality, including a cancer diagnosis (odds ratio [OR], 3.66; 95% CI, 3.50-3.83; P < .001), multiple dependencies of activities of daily living or instrumental activities of daily living (OR, 2.80; 95% CI, 2.57-3.05; P < .001), and an overall poor health status (OR, 2.21; 95% CI, 2.01-2.44; P < .001) documented on home health assessment. Among the decedents, cancer was associated with hospice use (OR, 2.25; 95% CI, 2.11-2.41; P < .001), patients aged 85 years or older (OR, 1.49; 95% CI, 1.37-1.61; P < .001), and living in an assisted living setting (OR, 1.93; 95% CI, 1.69-2.19; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that death within 1 year after sepsis discharge may be common among Medicare beneficiaries discharged to home health care. Although 1 in 2 decedents used hospice, aggressive care near the end of life and late hospice referral were common. Readily identifiable risk factors suggest opportunities to target efforts to improve palliative and end-of-life care among high-risk sepsis survivors.

Thirty-day readmission risk after intracranial tumor resection surgeries in children

OBJECTIVE

The risk of readmission after brain tumor resection among pediatric patients has not been defined. The authors' objective was to evaluate the readmission rates and predictors of readmission after pediatric brain tumor resection.

METHODS

Nationwide Readmissions Database (NRD) data sets from 2010 to 2014 were searched for unplanned readmissions within 30 days of the discharge date after pediatric brain tumor resection. Patient demographic variables included sex, age, expected payment source (Medicaid or private insurance), and median annual household income. Readmission events for chemotherapy, radiation therapy, or further tumor resection were not included.

RESULTS

Of 282 patients (12.7%) readmitted within 30 days of the index event, the median time to readmission was 10 days (IQR 5-19 days). The most common reason for readmission was hydrocephalus, which accounted for 19% of readmission events. Other CNS-related complications (24%), surgical site infections or septicemia (14%), seizures (7%), and hematological disorders (7%) accounted for other major readmission events. The median charge for readmission events was $35,431, and the median length of readmission stay was 4 days. In multivariate regression, factors associated with a significant increase in readmission risk included Medicaid as the primary payor, discharge from the index event with home health services, and fluid and electrolyte disorders during the index event.

CONCLUSIONS

More than 10% of pediatric brain tumor patients have unplanned readmission events within 30 days of discharge after tumor resection. Medicaid patients and those with preoperative or early postoperative fluid and electrolyte disturbances may benefit from early or frequent outpatient visits after tumor resection.

Hospital Readmissions in Medicare Home Healthcare: What Are the Leading Risk Indicators?

A large sample of all 2011 home healthcare users in traditional Medicare was analyzed to identify the risk indicators at start-of-care that were associated with the highest probability of readmission (N = 597,493). Thirty-five patient characteristics found in Outcome and Assessment Information Set, claims history, or other administrative data were associated with a 30-day readmission risk 30% to 100% above the average in the sample. Most of these characteristics were associated with a 30-day readmission probability of approximately 1 in 5, and several were associated with a readmission probability approaching 1 in 10 during the first 7 days. A majority of the high-risk characteristics were uncommon, and they tended not to occur together, suggesting they can be useful flags for clinicians in prioritizing cases to reduce readmissions. Readmission risk grows most quickly early in the episode of care; typically one-third of the readmissions in the first 30 days occurred by the end of 7 days. High-risk markers at 7 and 30 days were substantially the same, illustrating the importance of the early days at home in influencing the 30-day outcome. A variety of domains and characteristics are represented among the highest-risk markers, suggesting challenges to home healthcare clinicians in maintaining the knowledge and skills needed to address readmission prevention. We suggest possible responses to this problem as strategies to consider, and also discuss implications for assessment practices in home healthcare.

Sepsis Survivors Transitioned to Home Health Care: Characteristics and Early Readmission Risk Factors

OBJECTIVE

To profile the characteristics of growing numbers of sepsis survivors receiving home healthcare (HHC) by type of sepsis before, during, and after a sepsis hospitalization and identify characteristics significantly associated with 7-day readmission.

DESIGN

Cross-sectional descriptive study. Data sources included the Outcome and Assessment Information Set (OASIS) and Medicare administrative and claims data.

SETTING AND PARTICIPANTS

National sample of Medicare beneficiaries hospitalized for sepsis who were discharged to HHC between July 1, 2013 and June 30, 2014 (N = 165,228).

METHODS

We used an indicator distinguishing among 3 types of sepsis: explicitly coded sepsis diagnosis without organ dysfunction; severe sepsis with organ dysfunction; and septic shock. We compared these subgroups' demographic, clinical and functional characteristics, comorbidities, risk factors for rehospitalization, characteristics of the index hospital stay, and predicted 7-day hospital readmission.

RESULTS

The majority (80.7%) had severe sepsis, 5.7% had septic shock, and 13.6% had sepsis without acute organ system dysfunction. The medical diagnoses recorded at HHC admission identified sepsis or blood infection only 7% of the time, potentially creating difficulty identifying the sepsis survivor in HHC. Among sepsis types, septic shock survivors had the greatest illness burden profile. This study describes 12 key variables, each of which individually raises the relative 7-day readmission risk by as much as 60%. Increased risk of 7-day rehospitalization was found among those with septic shock, 3 or more previous inpatient stays, index hospital length of stay of >8 days, dyspnea, >6 functional dependencies, and other risk factors.

CONCLUSIONS AND IMPLICATIONS

Implications for practice include using our findings to identify sepsis survivors who are at risk for early readmission. Assessment for these factors may profile the at-risk patient, thereby triggering the call for additional acute care intervention such as delayed discharge, or post-acute intervention such as early home visit and outpatient follow-up.

Risk of Hospitalization in Long-Term Care Residents Living with Heart Failure: a Retrospective Cohort Study

BACKGROUND

Older adults living with heart failure (HF) in long-term care (LTC) experience frequent hospitalization. Using routinely available clinical information, we examined resident-level factors that precipitate hospitalization within 90 days of admission to LTC.

METHODS

This was a retrospective cohort study of older adults diagnosed with HF, who were admitted to LTC in Ontario, Canada, between 2011 and 2013. Multivariate logistic regression models using generalized estimating equations were developed to determine predictors of hospitalization in residents with HF.

RESULTS

Entry to LTC from a hospital was the strongest predictor of future hospitalization (OR: 8.1, 95% CI: 7.1-9.3), followed by a score of three or greater on the Changes in Health, End-stage Signs and Symptoms scale, a measure of moderate to severe medical instability (O.R 4.2, 95% CI: 3.1-5.9). Other variables that increased the likelihood of hospitalization included being flagged as a high risk for falls, two or more physician visits, and increased monitoring for acute medical illness within 14 days of admission.

CONCLUSION

Our findings highlight that health instability and transitions from acute to LTC will increase the likelihood of transitioning back into the hospital setting. The identified predisposing factors suggest the need for targeted prevention strategies for those in high-risk groups.

Home Health Care After Skilled Nursing Facility Discharge Following Heart Failure Hospitalization

BACKGROUND/OBJECTIVE

Heart failure (HF) readmission rates have plateaued despite scrutiny of hospital discharge practices. Many HF patients are discharged to skilled nursing facility (SNF) after hospitalization before returning home. Home healthcare (HHC) services received during the additional transition from SNF to home may affect readmission risk. Here, we examined whether receipt of HHC affects readmission risk during the transition from SNF to home following HF hospitalization.

DESIGN

Retrospective cohort study.

SETTING

Fee-for-service Medicare data, 2012 to 2015.

PARTICIPANTS

Beneficiaries, aged 65 years and older, hospitalized with HF who were subsequently discharged to SNF and then discharged home.

MEASUREMENTS

The primary outcome was unplanned readmission within 30 days of discharge to home from SNF. We compared time to readmission between those with and without HHC services using a Cox model.

RESULTS

Of 67 585 HF hospitalizations discharged to SNFs and subsequently discharged home, 13 257 (19.6%) were discharged with HHC, and 54 328 (80.4%) were discharged without HHC. Patients discharged home from SNFs with HHC had lower 30-day readmission rates than patients discharged without HHC (22.8% vs 24.5%; P < .0001) and a longer time to readmission. In an adjusted model, the hazard for readmission was 0.91 (0.86-0.95) with receipt of HHC.

CONCLUSIONS

Recipients of HHC were less likely to be readmitted within 30 days vs those discharged home without HHC. This is unexpected, as patients discharged with HHC likely have more functional impairments. Since patients requiring a SNF stay after hospital discharge may have additional needs, they may particularly benefit from restorative therapy through HHC; however, only approximately 20% received such services. J Am Geriatr Soc 68:96-102, 2019.

Technology Solutions to Support Care Continuity in Home Care: A Focus Group Study

BACKGROUND

Elevated hospital readmission rates from home care are an indicator of poor care quality, and rates are particularly high for patients with heart failure. Readmissions may be avoided by optimizing continuity of care.

PURPOSE

To explore perceptions among home care clinicians of the barriers they face and the information they need to improve care continuity for patients with heart failure.

METHODS

Focus groups were conducted with teams of home care clinicians at a large certified home healthcare agency in the Northeastern United states.

RESULTS

In total, there were 61 participants across 6 focus groups. Three overarching themes emerged: continuity of care and communication on care transitions, maintaining continuity of care during a home care episode (with subthemes tracking signs and symptoms and patient teaching), and health information technology (HIT) characteristics to support communication and care continuity.

CONCLUSIONS

Our study highlights areas of improvement for HIT solutions that could support care delivery for patients with heart failure in a home care setting.

IMPLICATIONS

Home care agencies planning to introduce technology can use these findings to assess if and how potential systems can support nurses to provide continuity of care across healthcare organizations and home care visits.

Health coaching to improve self-care of informal caregivers of adults with chronic heart failure - iCare4Me: Study protocol for a randomized controlled trial

BACKGROUND

Persons with chronic heart failure are living longer. These patients typically live in the community and are cared for at home by informal caregivers. These caregivers are an understudied and stressed group.

METHODS

We are conducting a two-arm, randomized controlled trial of 250 caregivers of persons with chronic heart failure to evaluate the efficacy of a health coaching intervention. A consecutive sample of participants is being enrolled from both clinic and hospital settings at a single institution affiliated with a large medical center in the northeastern US. Both the intervention and control groups receive tablets programmed to provide standardized health information. In addition, the intervention group receives 10 live coaching sessions delivered virtually by health coaches using the tablets. The intervention is evaluated at 6-months, with self-care as the primary outcome. Cost-effectiveness of the intervention is evaluated at 12-months. We are also enrolling heart failure patients (dyads) whenever possible to explore the effect of caregiver outcomes (self-care, stress, coping, health status) on heart failure patient outcomes (number of hospitalizations and days in the hospital) at 12-months.

DISCUSSION

We expect the proposed study to require 5 years for completion. If shown to be efficacious and cost-effective, our virtual health coaching intervention can easily be scaled to. support millions of caregivers worldwide.

Temporal Trends in Incidence, Sepsis-Related Mortality, and Hospital-Based Acute Care After Sepsis

OBJECTIVES

A growing number of patients survive sepsis hospitalizations each year and are at high risk for readmission. However, little is known about temporal trends in hospital-based acute care (emergency department treat-and-release visits and hospital readmission) after sepsis. Our primary objective was to measure temporal trends in sepsis survivorship and hospital-based acute care use in sepsis survivors. In addition, because readmissions after pneumonia are subject to penalty under the national readmission reduction program, we examined whether readmission rates declined after sepsis hospitalizations related to pneumonia.

DESIGN AND SETTING

Retrospective, observational cohort study conducted within an academic healthcare system from 2010 to 2015.

PATIENTS

We used three validated, claims-based approaches to identify 17,256 sepsis or severe sepsis hospitalizations to examine trends in hospital-based acute care after sepsis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

From 2010 to 2015, sepsis as a proportion of medical and surgical admissions increased from 3.9% to 9.4%, whereas in-hospital mortality rate for sepsis hospitalizations declined from 24.1% to 14.8%. As a result, the proportion of medical and surgical discharges at-risk for hospital readmission after sepsis increased from 2.7% to 7.8%. Over 6 years, 30-day hospital readmission rates declined modestly, from 26.4% in 2010 to 23.1% in 2015, driven largely by a decline in readmission rates among survivors of nonsevere sepsis, and nonpneumonia sepsis specifically, as the readmission rate of severe sepsis survivors was stable. The modest decline in 30-day readmission rates was offset by an increase in emergency department treat-and-release visits, from 2.8% in 2010 to a peak of 5.4% in 2014.

CONCLUSIONS

Owing to increasing incidence and declining mortality, the number of sepsis survivors at risk for hospital readmission rose significantly between 2010 and 2015. The 30-day hospital readmission rates for sepsis declined modestly but were offset by a rise in emergency department treat-and-release visits.

Does Early Follow-Up Improve the Outcomes of Sepsis Survivors Discharged to Home Health Care?

BACKGROUND

There is little evidence to guide the care of over a million sepsis survivors following hospital discharge despite high rates of hospital readmission.

OBJECTIVE

We examined whether early home health nursing (first visit within 2 days of hospital discharge and at least 1 additional visit in the first posthospital week) and early physician follow-up (an outpatient visit in the first posthospital week) reduce 30-day readmissions among Medicare sepsis survivors.

DESIGN

A pragmatic, comparative effectiveness analysis of Medicare data from 2013 to 2014 using nonlinear instrumental variable analysis.

SUBJECTS

Medicare beneficiaries in the 50 states and District of Columbia discharged alive after a sepsis hospitalization and received home health care.

MEASURES

The outcomes, protocol parameters, and control variables were from Medicare administrative and claim files and the home health Outcome and Assessment Information Set (OASIS). The primary outcome was 30-day all-cause hospital readmission.

RESULTS

Our sample consisted of 170,571 mostly non-Hispanic white (82.3%), female (57.5%), older adults (mean age, 76 y) with severe sepsis (86.9%) and a multitude of comorbid conditions and functional limitations. Among them, 44.7% received only the nursing protocol, 11.0% only the medical doctor protocol, 28.1% both protocols, and 16.2% neither. Although neither protocol by itself had a statistically significant effect on readmission, both together reduced the probability of 30-day all-cause readmission by 7 percentage points (P=0.006; 95% confidence interval=2, 12).

CONCLUSIONS

Our findings suggest that, together, early postdischarge care by home health and medical providers can reduce hospital readmissions for sepsis survivors.

Patients' ratings of the in-hospital discharge briefing and post-discharge primary care follow-up: The association with 30-day readmissions

OBJECTIVE

We examined whether patients' ratings of their in-hospital discharge briefing and their post-discharge Primary Care Physicians' (PCP) review of the discharge summary are associated with 30-day readmissions.

METHODS

A prospective study of 594 internal-medicine patients at a tertiary medical-center in Israel. The in-hospital baseline questionnaire included sociodemographic characteristics, physical, mental, and functional health status. Patients were surveyed by phone about the discharge and post-discharge processes. Clinical data and health-service use was retrieved from a central data-warehouse. Multivariate regressions modeled the relationship between in-hospital baseline characteristics, discharge briefing, PCP visit indicator, the PCP discharge summary review, and 30-day readmissions.

RESULTS

The extent of the PCPs' review of the hospital discharge summary at the post-discharge visit was rated higher than the in-hospital discharge briefing (3.46 vs. 3.17, p = 0.001) and was associated with lower odds of readmission (OR=0.35, 95% CI 0.26-0.45). The model that included this assessment performed better than the in-hospital baseline, the in-hospital discharge-briefing, and the PCP visit models (C-statistic = 0.87, compared with: 0.70, 0.81, 0.81, respectively).

CONCLUSIONS

Providing extensive post-discharge explanations by PCPs serves as a significant protective factor against readmissions.

PRACTICE IMPLICATIONS

PCPs should be encouraged to thoroughly review the discharge summary letter with the patient.