Effectiveness of home health care in reducing return to hospital: Evidence from a multi-hospital study in the US

Differentiating Between Home Care Types to Identify Older Adults at Risk of Adverse Health Outcomes in the Community

OBJECTIVES

Acute hospitalization, recurrent admissions, institutionalization, and death are important adverse health outcomes. Older adults receiving home care are especially at risk of these outcomes, yet it remains unclear if this risk differs between older adults receiving different types of home care and older adults not receiving home care.

DESIGN

Retrospective cohort study using national claims data from 2019.

SETTING AND PARTICIPANTS

Community-dwelling Dutch individuals aged ≥ 65 years (N = 3,174,953).

METHODS

Participants were categorized: no home care, household help, personal care, household help combined with personal care, or nursing home care at home. The primary outcomes were the number of people experiencing acute hospitalization, recurrent admissions, institutionalization, or death. Logistic regression models were applied.

RESULTS

In total, 2,758,093 adults were included in the no home care group, 131,260 in the household help group, 154,462 in the personal care group, 96,526 in the household help combined with personal care group, and 34,612 in the nursing home care at home group. The risk of adverse outcomes differed between home care groups, with all showing higher odds compared with the no home care group. Individuals receiving household help combined with personal care had the highest odds for acute hospitalization [odds ratio (OR), 2.60; 95% CI, 2.55-2.64] and recurrent admissions (OR, 2.60; 95% CI, 2.55-2.65), while those receiving nursing home care at home had the highest odds for death (OR, 7.59; 95% CI, 7.35-7.85) and institutionalization (OR, 63.22; 95% CI, 60.94-65.58).

CONCLUSIONS AND IMPLICATIONS

Differentiating between the type of home care older adults receive identifies subpopulations with different risks for adverse health outcomes compared with older adults not receiving home care. Older adults receiving personal care (nurse based) are at high risk for these outcomes and represent a substantial population with prevention potential. Future research should focus on developing effective interventions for this group.

Home care practice behavior and its influencing factors of primary care providers: a multicenter cross-sectional study in Sichuan Province, China

BACKGROUND

Primary care providers play an important role in home health care, and their practice behavior is significant for care quality and patient outcomes. This study aimed to assess the home care practice behavior of Chinese primary care providers and to explore the factors associated with the practice behavior.

METHODS

A multicenter cross-sectional design with a convenience sample was used to survey 863 registered primary care providers from 62 primary health care settings in Sichuan Province, China. Descriptive statistics, t-test or ANOVA for one-way analysis, and Pearson's correlation analyses were used to compare the differences and examine the relationships between participants' demographics and experience of home care services and practice behavior. Multiple linear regression models were performed to identify salient variables associated with the practice behavior from among demographic and home care experience.

RESULTS

The score of home care practice behavior questionnaire was 97.25 ± 21.05. The average scores for the dimensions of home visit preparation, assessment, medical care behavior and safety practice were 3.70 ± 0.95, 3.76 ± 1.02, 3.66 ± 1.03, and 3.20 ± 0.46, respectively. Home care practice behavior was associated with working years, working experience in general hospitals, work area, home care experience such as client types of home care, service frequency and willingness, explaining 21.5% of the total variance.

CONCLUSION

Chinese primary care providers had a medium to high level of home care practice behavior but poor implementation of safety practice. The results may provide clues to increased focus and implementation of safety practice, as well as providing targeted measures based on influencing factors.

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.

Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review

OBJECTIVES

To determine the scope of the application of natural language processing to free-text clinical notes in post-acute care and provide a foundation for future natural language processing-based research in these settings.

DESIGN

Scoping review; reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

SETTING AND PARTICIPANTS

Post-acute care (ie, home health care, long-term care, skilled nursing facilities, and inpatient rehabilitation facilities).

METHODS

PubMed, Cumulative Index of Nursing and Allied Health Literature, and Embase were searched in February 2023. Eligible studies had quantitative designs that used natural language processing applied to clinical documentation in post-acute care settings. The quality of each study was appraised.

RESULTS

Twenty-one studies were included. Almost all studies were conducted in home health care settings. Most studies extracted data from electronic health records to examine the risk for negative outcomes, including acute care utilization, medication errors, and suicide mortality. About half of the studies did not report age, sex, race, or ethnicity data or use standardized terminologies. Only 8 studies included variables from socio-behavioral domains. Most studies fulfilled all quality appraisal indicators.

CONCLUSIONS AND IMPLICATIONS

The application of natural language processing is nascent in post-acute care settings. Future research should apply natural language processing using standardized terminologies to leverage free-text clinical notes in post-acute care to promote timely, comprehensive, and equitable care. Natural language processing could be integrated with predictive models to help identify patients who are at risk of negative outcomes. Future research should incorporate socio-behavioral determinants and diverse samples to improve health equity in informatics tools.

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.

Home Health Care Is Associated With an Increased Risk of Emergency Department Visit, Readmission, and Cost of Care Without Reducing Risk of Complication Following Total Hip Arthroplasty: A Propensity-Score Analysis

BACKGROUND

Home health services have long been implemented for patients to receive additional professional care and supervision following discharge from the hospital to theoretically reduce the risk of complications and health care utilizations. The aim of this investigation was to determine if patients assigned home health services exhibited lower rates of medical and surgical complications, health care utilizations, and costs of care following total hip arthroplasty.

METHODS

A large national database was retrospectively reviewed to identify all primary total hip arthroplasty patients from 2010 to 2019. Patients who received home health services were matched using a propensity score algorithm to a set of similar patients who were discharged home under self-care. We compared medical and surgical complication rates, emergency room visits, readmissions, and 90-day costs of care between the groups. Multivariate regression analyses were performed to determine the independent effect of home health services on all outcomes. There were 7,243 patients who received home health services and were matched to 72,430 patients who were discharged home under self-care.

RESULTS

Patients who received home health services had higher rates of emergency department visits at 30 days (Odds Ratio [OR] R statistical programming software v 3.6.1 [Lucent Technologies, New Providence, RJ] 1.1544; P = .002) as well as increased readmissions at 30 days (OR 1.137; P = .039); complication rates were similar between groups. Episode-of-care costs for home health patients were higher than those discharged under self-care ($14,236.97 versus $12,817.12; P < .001).

CONCLUSION

Patients assigned home health care services exhibited higher costs of care without decreased risk of complications and had increased risk of early returns to the emergency department and readmissions.

Machine learning applied to electronic health record data in home healthcare: A scoping review

OBJECTIVE

Despite recent calls for home healthcare (HHC) to integrate informatics, the application of machine learning in HHC is relatively unknown. Thus, this study aimed to synthesize and appraise the literature describing the application of machine learning to predict adverse outcomes (e.g., hospitalization, mortality) using electronic health record (EHR) data in the HHC setting. Our secondary aim was to evaluate the comprehensiveness of predictors used in the machine learning algorithms guided by the Biopsychosocial Model.

METHODS

During March 2022 we conducted a literature search in four databases: PubMed, Embase, CINAHL, and Scopus. Inclusion criteria were 1) describing services provided in the HHC setting, 2) applying machine learning algorithms to predict adverse outcomes, defined as outcomes related to patient deterioration, 3) using EHR data and 4) focusing on the adult population. Predictors were mapped to the Biopsychosocial Model. A risk of bias analysis was conducted using the Prediction Model Risk Of Bias Assessment Tool.

RESULTS

The final sample included 20 studies. Eighteen studies used predictors from standardized assessments integrated in the EHR. The most common outcome of interest was hospitalization (55%), followed by mortality (25%). Psychological predictors were frequently excluded (35%). Tree based algorithms were most frequently applied (75%). Most studies demonstrated high or unclear risk of bias (75%).

CONCLUSION

Future studies in HHC should consider incorporating machine learning algorithms into clinical decision support systems to identify patients at risk. Based on the Biopsychosocial model, psychological and interpersonal characteristics should be used along with biological characteristics to enhance risk prediction. To facilitate the widespread adoption of machine learning, stakeholders should encourage standardization in the HHC setting.

Discharge destination and readmissions among patients with head and neck cancer

Objective

Lowering hospital readmission rates is a national goal, and presents an opportunity to lower health care costs, improve quality, and increase patient satisfaction. We aim to assess whether discharge disposition is associated with readmission.

Methods

A retrospective cohort study using logistic regression to quantify risk factors of hospital readmission in patients with confirmed head and neck cancer (HNC) who underwent surgery from 2010 to 2018 contained in the Pennsylvania Health Care Cost Containment Council database, which includes patients treated in Pennsylvania hospitals.

Results

The readmission rate in this study was 18.1%. Cancers of the hypopharynx had the highest rates of readmission (29.2%). Male sex (odds ratio [OR]: 0.87, 95% CI: 0.75-1.00), emergent admission (vs. elective admission: OR = 1.33, 95% CI: 1.02-1.74), discharge to home health (vs. home: OR = 1.85, 95% CI: 1.59-2.16), discharge to skilled nursing facility (SNF) (vs. home: OR = 2.21, 95% CI: 1.80-2.72), and having 4+ comorbidities (vs. 0-1: OR = 1.39, 95% CI: 1.09-1.76) were significant risk factors for hospital readmission.

Conclusion

It is necessary to consider the readmission risk associated with HNC patients. Reasons for readmission are multifactorial and can be related to demographics, hospital course, comorbidities, or discharge disposition-this requires further assessment. There is importance in increasing HNC awareness and staff education about the unique needs of this population.

Level of Evidence

4.