Search

biBackground:/i/bIntegrating palliative care services in the home health care (HHC) setting is an important strategy to provide care for seriously ill adults and improve symptom burden, quality of life, and caregiver burden. Routine palliative care in HHC is only possible if clinicians who provide this care are prepared and patients and caregivers are well equipped with the knowledge to receive this care. A key first step in integrating palliative care services within HHC is to measure preparedness of clinicians and readiness of patients and caregivers to receive it.biObjective:/i/bThe objective of this systematic review was to review existing literature related to the measurement of palliative care-related knowledge, attitudes, and confidence among HHC clinicians, patients, and caregivers.biMethods:/i/bWe searched PubMed, CINAHL, Web of Science, and Cochrane for relevant articles between 2000 and 2021. Articles were included in the final analysis if they (1) reported specifically on palliative care knowledge, attitudes, or confidence, (2) presented measurement tools, instruments, scales, or questionnaires, (3) were conducted in the HHC setting, (4) and included HHC clinicians, patients, or caregivers.biResults:/i/bSeventeen articles were included. While knowledge, attitudes, and confidence have been studied in HHC clinicians, patients, and caregivers, results varied significantly across countries and health care systems. No study captured knowledge, attitudes, and confidence of the full HHC workforce; notably, home health aides were not included in the studies.biConclusion:/i/bExisting instruments did not comprehensively contain elements of the eight domains of palliative care outlined by the National Consensus Project (NCP) for Quality Palliative Care. A comprehensive psychometrically tested instrument to measure palliative care-related knowledge, attitudes, and confidence in the HHC setting is needed.

AIMS: To identify clusters of risk factors in home health care and determine if the clusters are associated with hospitalizations or emergency department visits. DESIGN: A retrospective cohort study. METHODS: This study included 61,454 patients pertaining to 79,079 episodes receiving home health care between 2015 and 2017 from one of the largest home health care organizations in the United States. Potential risk factors were extracted from structured data and unstructured clinical notes analysed by natural language processing. A K-means cluster analysis was conducted. Kaplan–Meier analysis was conducted to identify the association between clusters and hospitalizations or emergency department visits during home health care. RESULTS: A total of 11.6% of home health episodes resulted in hospitalizations or emergency department visits. Risk factors formed three clusters. Cluster 1 is characterized by a combination of risk factors related to “impaired physical comfort with pain,” defined as situations where patients may experience increased pain. Cluster 2 is characterized by “high comorbidity burden” defined as multiple comorbidities or other risks for hospitalization (e.g., prior falls). Cluster 3 is characterized by “impaired cognitive/psychological and skin integrity” including dementia or skin ulcer. Compared to Cluster 1, the risk of hospitalizations or emergency department visits increased by 1.95 times for Cluster 2 and by 2.12 times for Cluster 3 (all p < .001). CONCLUSION: Risk factors were clustered into three types describing distinct characteristics for hospitalizations or emergency department visits. Different combinations of risk factors affected the likelihood of these negative outcomes. IMPACT: Cluster-based risk prediction models could be integrated into early warning systems to identify patients at risk for hospitalizations or emergency department visits leading to more timely, patient-centred care, ultimately preventing these events. PATIENT OR PUBLIC CONTRIBUTION: There was no involvement of patients in developing the research question, determining the outcome measures, or implementing the study.

Home health aides provide care to homebound older adults and those with chronic conditions. Aides were less likely to receive COVID-19 vaccines when they became available. We examined aides’ perspectives towards COVID-19 vaccination. Qualitative interviews were conducted with 56 home health aides at a large not-for-profit home care agency in New York City. Results suggested that aides’ vaccination decisions were shaped by (1) information sources, beliefs, their health, and experiences providing care during COVID-19; (2) perceived susceptibility and severity of COVID-19; (3) perceived benefits of vaccination including protection from COVID-19, respect from colleagues and patients, and fulfillment of work-related requirements; (4) perceived barriers to vaccination including concerns about safety, efficacy, and side effects; and (5) cues to action including access to vaccination sites/appointments, vaccination mandates, question and answer sessions from trusted sources, and testimonials. Providing tailored information with support to address vaccination barriers could lead to improved vaccine uptake.

Patients with heart failure (HF) who actively engage in their own self-management have better outcomes. Extracting data through natural language processing (NLP) holds great promise for identifying patients with or at risk of poor self-management.To identify home health care (HHC) patients with HF who have poor self-management using NLP of narrative notes, and to examine patient factors associated with poor self-management.An NLP algorithm was applied to extract poor self-management documentation using 353,718 HHC narrative notes of 9,710 patients with HF. Sociodemographic and structured clinical data were incorporated into multivariate logistic regression models to identify factors associated with poor self-management.There were 758 (7.8%) patients in this sample identified as having notes with language describing poor HF self-management. Younger age (OR 0.982, 95% CI 0.976-0.987, p .001), longer length of stay in HHC (OR 1.036, 95% CI 1.029- 1.043, p .001), diagnosis of diabetes (OR 1.47, 95% CI 1.3-1.67, p .001) and depression (OR 1.36, 95% CI 1.09-1.68, p .01), impaired decision-making (OR 1.64, 95% CI 1.37-1.95, p .001), smoking (OR 1.7, 95% CI 1.4-2.04, p .001), and shortness of breath with exertion (OR 1.25, 95% CI 1.1-1.42, p .01) were associated with poor self-management.Patients with HF who have poor self-management can be identified from the narrative notes in HHC using novel NLP methods. Meaningful information about the self-management of patients with HF can support HHC clinicians in developing individualized care plans to improve self-management and clinical outcomes.

BACKGROUND: About one in five patients receiving home health care (HHC) services are hospitalized or visit an emergency department (ED) during a home care episode. Early identification of patients at risk can prevent these negative outcomes. However, risk indicators, including language in clinical notes that indicate a concern about a patient, are often hidden in narrative documentation throughout their HHC episode. OBJECTIVE: To develop an automated natural language processing (NLP) algorithm to identify concerning language indicative of HHC patient risk of hospitalizations or ED visits. METHODS: This study used the Omaha System—a standardized nursing terminology that describes problems/signs/symptoms that can occur in the community setting. First, five HHC experts iteratively reviewed the Omaha System and identified concerning concepts indicative of HHC patient risk of hospitalizations or ED visits. Next, we developed and tested an NLP algorithm to identify these concerning concepts in HHC clinical notes automatically. The resulting NLP algorithm was applied on a large subset of narrative notes (2.3 million notes) documented for 66,317 unique patients (n = 87,966 HHC episodes) admitted to one large HHC agency in the Northeast United States between 2015 and 2017. RESULTS: A total of 160 Omaha System signs/symptoms were identified as concerning concepts for hospitalizations or ED visits in HHC. These signs/symptoms belong to 31 of the 42 available Omaha System problems. Overall, the NLP algorithm showed good performance in identifying concerning concepts in clinical notes. More than 18% of clinical notes were detected as having at least one concerning concept, and more than 90% of HHC episodes included at least one Omaha System problem. The most frequently documented concerning concepts were pain, followed by issues related to neuro-musculoskeletal function, circulation, mental health, and communicable/infectious conditions. CONCLUSION: Our findings suggest that concerning problems or symptoms that could increase the risk of hospitalization or ED visit were frequently documented in narrative clinical notes. NLP can automatically extract information from narrative clinical notes to improve our understanding of care needs in HHC. Next steps are to evaluate which concerning concepts identified in clinical notes predict hospitalization or ED visit.

Background: Urinary incontinence is prevalent among patients receiving home hospice and presents multiple care management challenges for nurses and family caregivers. Aim: This study sought to understand how urinary incontinence influences the psychosocial care of patients receiving home hospice and the strategies that nurses employ to maximize patient and family comfort. Design: Qualitative descriptive study using semi-structured interviews. Setting/participants: Nurses employed at a large not-for-profit hospice agency in New York City. Results: Analyses of 32 interviews revealed three primary themes. First, nurses considered urinary incontinence to be associated with multiple psychosocial issues including embarrassment for patients and caregiver burden. Second, nurses described urinary incontinence as a threat to patient dignity and took steps to preserve their continence function. Third, nurses assisted patients and their families to cope with urinary incontinence through normalization, reframing incontinence as part of the disease process, mobilizing caregiving assistance, and encouraging use of continence supplies such as diapers and liners. Conclusion: Urinary incontinence influences the psychosocial care of patients receiving home hospice and nurses employ strategies to maximize patient and family comfort. Additional research is needed to examine the psychosocial benefits of facilitated discussions with patients and family members about incontinence, provision of caregiving support, and distribution of comprehensive incontinence supplies to patients with fewer resources.

Context To date, no studies have characterized the impacts of urinary incontinence (UI) at the end of life in the home hospice (HH) setting. UI is highly prevalent at the end of life and adversely affects quality of life. Objectives To characterize HH nurses’ perspectives on UI in HH patients. Methods We conducted a qualitative descriptive study of interviews between HH nurses and the study investigator. Thirty-two interviews with HH nurses were transcribed and analyzed. Nurses were mostly female, college-educated, and had several years of experience in HH nursing. Results We identified findings in four major themes: 1) HH nurses' definition and identification of UI, 2) the absence of formal guidelines for diagnosing UI in HH patients, 3) UI's adverse effect on HH patients and their families, and 4) the lack of standardized guidelines for the management of UI in the HH setting. We found that there was a general lack of clarity on the subtypes of UI and no standardized guidelines for management of UI in the HH setting. Nurses reported that UI was bothersome to HH patients and their caregivers, citing patient discomfort, loss of dignity, and additional labor burden as reasons for this. Management strategies for UI lacked standardization. Conclusion UI is a prevalent and debilitating condition in HH patients. There is a need for studies to further characterize the impacts of UI on HH patients and their caregivers. Formal training on UI subtypes and management is needed to facilitate proper documentation, research, and improve patient outcomes.

Background Infection Prevention and Control (IPC) practices have been established in home health care. Adherence to IPC practices has been suboptimal with limited available evidence. The study aim was to examine the impact of individual, home environment, and organizational factors on IPC practices using human factors model. Methods Three hundred and fifty-three nurses were surveyed across two large home care agencies to examine the relationship between IPC adherence and individual, home environment, and organizational factors. Results Nurses reported multiple barriers to IPC practices in patients’ homes (mean = 4.34, standard deviation = 2.53). Frequent barriers included clutter (reported by 74.5% of nurses) and a dirty environment (70.3%). Nurses also reported limited availability of some IPC supplies (mean = 7.76, standard deviation = 2.44), including personal protective equipment. Home environment factors were significant barriers, and availability of IPC supplies were significant enablers of IPC adherence. Agency-provided training and decision-making resources were not significant factors for IPC adherence in the presence of home environment barriers and IPC supplies. Conclusions This study findings suggest that IPC adherence strategies point to addressing barriers in the home environment and increasing availability of IPC supplies. The relationship between the patient's home environment, organizational factors, and IPC practices among home health care nurses warrants further study.

Information does not yet exist on the characteristics and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19) who are discharged to the home setting. Using rich data from home health care (HHC), the authors describe characteristics of COVID-19 survivors upon admission to HHC, the home visits they received, and the extent of recovery among those discharged from HHC. They also profile the risk factors associated with rehospitalization and death., Background: Little is known about recovery from coronavirus disease 2019 (COVID-19) after hospital discharge. Objective: To describe the home health recovery of patients with COVID-19 and risk factors associated with rehospitalization or death. Design: Retrospective observational cohort. Setting: New York City. Participants: 1409 patients with COVID-19 admitted to home health care (HHC) between 1 April and 15 June 2020 after hospitalization. Measurements: Covariates and outcomes were obtained from the mandated OASIS (Outcome and Assessment Information Set). Cox proportional hazard models were used to estimate the hazard ratio (HR) of risk factors associated with rehospitalization or death. Results: After an average of 32 days in HHC, 94% of patients were discharged and most achieved statistically significant improvements in symptoms and function. Activity-of-daily-living dependencies decreased from an average of 6 (95% CI, 5.9 to 6.1) to 1.2 (CI, 1.1 to 1.3). Risk for rehospitalization or death was higher for male patients (HR, 1.45 [CI, 1.04 to 2.03]); White patients (HR, 1.74 [CI, 1.22 to 2.47]); and patients with heart failure (HR, 2.12 [CI, 1.41 to 3.19]), diabetes with complications (HR, 1.71 [CI, 1.17 to 2.52]), 2 or more emergency department visits in the past 6 months (HR, 1.78 [CI, 1.21 to 2.62]), pain daily or all the time (HR, 1.46 [CI, 1.05 to 2.05]), cognitive impairment (HR, 1.49 [CI, 1.04 to 2.13]), or functional dependencies (HR, 1.09 [CI, 1.00 to 1.20]). Eleven patients (1%) died, 137 (10%) were rehospitalized, and 23 (2%) remain on service. Limitations: Care was provided by 1 home health agency. Information on rehospitalization and death after HHC discharge is not available. Conclusion: Symptom burden and functional dependence were common at the time of HHC admission but improved for most patients. Comorbid conditions of heart failure and diabetes, as well as characteristics present at admission, identified patients at greatest risk for an adverse event. Primary Funding Source: No direct funding.

There has been limited research into the individual, social, and environmental factors for infection risk among patients in the home healthcare (HHC) setting, where the infection is a leading cause of hospitalisation. The aims of this study were to (1) explore nurse perceptions of individual, social, and environmental factors for infection risk among HHC patients; and (2) identify the frequency of environmental barriers to infection prevention and control in HHC. Data were collected in 2017-2018 and included qualitative interviews with HHC nurses (n = 50) and structured observations of nurse visits to patients' homes (n = 400). Thematic analyses of interviews with nurses suggested they perceived infection risk among patients as being influenced by knowledge of and attitudes towards infection prevention and engagement in hygiene practices, receipt of support from informal caregivers and nurse interventions aimed at cultivating infection control knowledge and practices, and the home environment. Statistical analyses of observation checklists revealed nurses encountered an average of 1.7 environmental barriers upon each home visit. Frequent environmental barriers observed during visits to HHC patients included clutter (39.5%), poor lighting (38.8%), dirtiness (28.5%), and pets (17.2%). Additional research is needed to clarify inter-relationships among these factors and identify strategies for addressing each as part of a comprehensive infection control program in HHC.

Objective The study sought to outline how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses, and to inform how the output of the model could be integrated into a clinical workflow. Materials and Methods This was a qualitative study using semi-structured interviews with 50 home care nurses. Interviews explored nurses’ perceptions of clinical risk prediction models, their experiences using them in practice, and what elements are important for the implementation of a clinical risk prediction model focusing on infection. Interviews were audio-taped and transcribed, with data evaluated using thematic analysis. Results Two themes were derived from the data: (1) informing nursing practice, which outlined how a clinical risk prediction model could inform nurse clinical judgment and be used to modify their care plan interventions, and (2) operationalizing the score, which summarized how the clinical risk prediction model could be incorporated in home care settings. Discussion The findings indicate that home care nurses would find a clinical risk prediction model for infection useful, as long as it provided both context around the reasons why a patient was deemed to be at high risk and provided some guidance for action. Conclusions It is important to evaluate the potential feasibility and acceptability of a clinical risk prediction model, to inform the intervention design and implementation strategy. The results of this study can provide guidance for the development of the clinical risk prediction tool as an intervention for integration in home care settings.

Objective To assess the overlap of information between electronic health record (EHR) and patient–nurse verbal communication in home healthcare (HHC). Methods Patient–nurse verbal communications during home visits were recorded between February 16, 2021 and September 2, 2021 with patients being served in an organization located in the Northeast United States. Twenty-two audio recordings for 15 patients were transcribed. To compare overlap of information, manual annotations of problems and interventions were made on transcriptions as well as information from EHR including structured data and clinical notes corresponding to HHC visits. Results About 30% (1534/5118) of utterances (ie, spoken language preceding/following silence or a change of speaker) were identified as including problems or interventions. A total of 216 problems and 492 interventions were identified through verbal communication among all the patients in the study. Approximately 50.5% of the problems and 20.8% of the interventions discussed during the verbal communication were not documented in the EHR. Preliminary results showed that statistical differences between racial groups were observed in a comparison of problems and interventions. Discussion This study was the first to investigate the extent that problems and interventions were mentioned in patient–nurse verbal communication during HHC visits and whether this information was documented in EHR. Our analysis identified gaps in information overlap and possible racial disparities. Conclusion Our results highlight the value of analyzing communications between HHC patients and nurses. Future studies should explore ways to capture information in verbal communication using automated speech recognition.

Infection prevention is a high priority for home healthcare (HHC) but tools are lacking to identify patients at highest risk for developing infections. The purpose of this study was to develop and test a predictive risk model to identify HHC patients at risk of an infection-related hospitalization or emergency department visit. A non-experimental study using secondary data was conducted. The Outcome and Assessment Information Set linked with relevant clinical data from 112,788 HHC admissions in 2014 were used for model development (70% of data) and testing (30%). A total of 1,908 patients (1.69%) were hospitalized or received emergency care associated with infection. Stepwise logistic regression models discriminated between individuals with and without infections. Our final model, when classified by highest risk of infection, identified a high portion of those who were hospitalized or received emergent care for an infection while also correctly categorizing 90.5% of patients without infection. The risk model can be used by clinicians to inform care planning. This is the first study to develop a tool for predicting infection risk that can be used to inform how to direct additional infection control intervention resources on high-risk patients, potentially reducing infection related hospitalizations, emergency department visits, and costs.

BACKGROUND Patients’ spontaneous speech can act as a biomarker for identifying pathological entities, such as mental illness. Despite this potential, audio recording patients’ spontaneous speech is not part of clinical workflows, and health care organizations often do not have dedicated policies regarding the audio recording of clinical encounters. No previous studies have investigated the best practical approach for integrating audio recording of patient-clinician encounters into clinical workflows, particularly in the home health care (HHC) setting. OBJECTIVE This study aimed to evaluate the functionality and usability of several audio-recording devices for the audio recording of patient-nurse verbal communications in the HHC settings and elicit HHC stakeholder (patients and nurses) perspectives about the facilitators of and barriers to integrating audio recordings into clinical workflows. METHODS This study was conducted at a large urban HHC agency located in New York, United States. We evaluated the usability and functionality of 7 audio-recording devices in a laboratory (controlled) setting. A total of 3 devices—Saramonic Blink500, Sony ICD-TX6, and Black Vox 365—were further evaluated in a clinical setting (patients’ homes) by HHC nurses who completed the System Usability Scale questionnaire and participated in a short, structured interview to elicit feedback about each device. We also evaluated the accuracy of the automatic transcription of audio-recorded encounters for the 3 devices using the Amazon Web Service Transcribe. Word error rate was used to measure the accuracy of automated speech transcription. To understand the facilitators of and barriers to integrating audio recording of encounters into clinical workflows, we conducted semistructured interviews with 3 HHC nurses and 10 HHC patients. Thematic analysis was used to analyze the transcribed interviews. RESULTS Saramonic Blink500 received the best overall evaluation score. The System Usability Scale score and word error rate for Saramonic Blink500 were 65% and 26%, respectively, and nurses found it easier to approach patients using this device than with the other 2 devices. Overall, patients found the process of audio recording to be satisfactory and convenient, with minimal impact on their communication with nurses. Although, in general, nurses also found the process easy to learn and satisfactory, they suggested that the audio recording of HHC encounters can affect their communication patterns. In addition, nurses were not aware of the potential to use audio-recorded encounters to improve health care services. Nurses also indicated that they would need to involve their managers to determine how audio recordings could be integrated into their clinical workflows and for any ongoing use of audio recordings during patient care management. CONCLUSIONS This study established the feasibility of audio recording HHC patient-nurse encounters. Training HHC nurses about the importance of the audio-recording process and the support of clinical managers are essential factors for successful implementation.

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

BACKGROUND/OBJECTIVE: Between 10 and 25% patients are hospitalized or visit emergency department (ED) during home healthcare (HHC). Given that up to 40% of these negative clinical outcomes are preventable, early and accurate prediction of hospitalization risk can be one strategy to prevent them. In recent years, machine learning-based predictive modeling has become widely used for building risk models. This study aimed to compare the predictive performance of four risk models built with various data sources for hospitalization and ED visits in HHC. METHODS: Four risk models were built using different variables from two data sources: structured data (i.e., Outcome and Assessment Information Set (OASIS) and other assessment items from the electronic health record (EHR)) and unstructured narrative-free text clinical notes for patients who received HHC services from the largest non-profit HHC organization in New York between 2015 and 2017. Then, five machine learning algorithms (logistic regression, Random Forest, Bayesian network, support vector machine (SVM), and Naïve Bayes) were used on each risk model. Risk model performance was evaluated using the F-score and Precision-Recall Curve (PRC) area metrics. RESULTS: During the study period, 8373/86,823 (9.6%) HHC episodes resulted in hospitalization or ED visits. Among five machine learning algorithms on each model, the SVM showed the highest F-score (0.82), while the Random Forest showed the highest PRC area (0.864). Adding information extracted from clinical notes significantly improved the risk prediction ability by up to 16.6% in F-score and 17.8% in PRC. CONCLUSION: All models showed relatively good hospitalization or ED visit risk predictive performance in HHC. Information from clinical notes integrated with the structured data improved the ability to identify patients at risk for these emergent care events.

Background Home health care (HHC) is a leading form of home and community-based services for persons with dementia (PWD). Nurses are the primary providers of HHC; however, little is known of nursing care delivery and quality. Objective The objective of this study was to examine the association between continuity of nursing care in HHC and rehospitalization among PWD. Research design This is a retrospective cohort study using multiple years (2010-2015) of HHC assessment, administrative, and human resources data from a large urban not-for-profit home health agency. Subjects This study included 23,886 PWD receiving HHC following a hospitalization. Measures Continuity of nursing care was calculated using the Bice and Boxerman method, which considered the number of total visits, nurses, and visits from each nurse during an HHC episode. The outcome was all-cause rehospitalization during HHC. Risk-adjusted logistic regression was used for analysis. Results Approximately 24% of PWD were rehospitalized. The mean continuity of nursing care score was 0.56 (SD=0.33). Eight percent of PWD received each nursing visit from a different nurse (no continuity), and 26% received all visits from one nurse during an HHC episode (full continuity). Compared with those receiving high continuity of nursing care (third tertile), PWD receiving low (first tertile) or moderate (second tertile) continuity of nursing care had an adjusted odds ratio of 1.33 (95% confidence interval: 1.25-1.46) and 1.30 (95% confidence interval: 1.22-1.43), respectively, for being rehospitalized. Conclusions Wide variations exist in continuity of nursing care to PWD. Consistency in nurse staff when providing HHC visits to PWD is critical for preventing rehospitalizations.

Background Despite improvements in hypertension treatment in the United States, Black and Hispanic individuals experience poor blood pressure control and have worse hypertension-related outcomes compared to Whites. Objective The aim of the study was to determine the effect on hospitalization of supplementing usual home care (UHC) with two hypertension-focused transitional care interventions-one deploying nurse practitioners (NPs) and the other NPs plus health coaches. Methods We examined post hoc the effect of two hypertension-focused NP interventions on hospitalizations in the Community Transitions Intervention trial-a three-arm, randomized controlled trial comparing the effectiveness of (a) UHC with (b) UHC plus a 30-day NP transitional care intervention or (c) UHC plus NP plus 60-day health coach intervention. Results The study comprised 495 participants: mean age = 66 years; 57% female; 70% Black, non-Hispanic; 30% Hispanic. At the 3- and 12-month follow-up, all three groups showed a significant decrease in the average number of hospitalizations compared to baseline. The interventions were not significantly different from UHC. Conclusion The results of this post hoc analysis show that, during the study period, decreases in hospitalizations in the intervention groups were comparable to those in UHC, and deploying NPs provided no detectable value added. Future research should focus on testing ways to optimize UHC services.

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.

According to the U.S. census Bureau, close to 20% of the U.S. population speaks a language other than English at home. Home health care (HHC) patients who speak English less than very well or have limited English proficiency (LEP) are at an increased risk for medication mismanagement and serious health consequences. The purpose of this study was to examine if there were differences in medication management between English-speaking patients and patients with LEP receiving HHC services. Data for this cross-sectional observation study were collected from 2010 to 2014. Medication management was measured by two items in the Centers for Medicare and Medicaid Services–mandated Outcomes Assessment Information Set (OASIS). All patients in the database who were taking medications and had a valid admission and discharge assessment from HHC were included in the analysis. Inverse probability of treatment weighting (IPTW) with a marginal structural model was used to address potential imbalances in observed patient characteristics when estimating the effect of having LEP or being an English-speaking HHC patient on changes in medication management over the course of a HHC episode. Estimates from marginal structural model with inverse probability weighting indicate that being LEP was associated with less improvement in medication management and increased likelihood of getting worse over the course of a HHC episode. This study is one of the first to demonstrate that patients with LEP experience disparities in medication management when compared to English-speaking patients in HHC.

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.

Healthcare-associated infections are a significant reason for readmission to hospital post-discharge to the community. In this paper, the authors describe some of the key findings from a programme of work conducted in a home care agency (community care organisation) in the US. A survey was conducted to explore home care nurses' knowledge, attitudes and beliefs around infection control (n=415); 400 nurse-patient visits were observed, and 50 nurses were interviewed about their infection control practices. Nurses reported high compliance with infection control practices. However, the overall average adherence rate to observed hand hygiene practices was 45.6%. Interview data provided valuable insights into specific challenges faced by nurses in a home care setting. This study provides insights that can be used to enhance infection control practice in community care in the UK.

Introduction: Mental health issues are on an exponential rise in Kashmir due to varied reasons including political instability, eco fragility, the growing lag in the provision of education and employment, and several other reasons. Impediments such as the overwhelming stigma and the cultural sensitivity associated with mental health issues both sustain and perpetuate mental ill health and also prevent any treatment and rehabilitation. This article describes the protocol of a research project, funded by the Indian Council of Medical Research, which aims to address this issue. Aim: To screen the population for mental health issues and to provide community-based intervention for the identified cases also to train community health workers for sustainable mental health support. Methods: We will conduct a household survey using the Hopkins Symptom Checklist (HSCL-25) for the identification of the clients. A multi-stage random sampling shall be used to select the villages and the households from the marginalized communities. A sample of 500 respondents shall be screened using HSCL-25. Those who screen positive for mental health issues will be offered cognitive behavioral therapy (CBT) by a qualified clinical psychologist. The research will be able to address the diagnosis of depression and anxiety-related cases and the subsequent intervention. Additionally, we will utilize the facilitator’s manual for Mental Health Training Program for Community Health Workers to build sustainable mental health services in community settings. Discussion: The study shall present a roadmap focusing on the indispensability of a comprehensive community-based intervention on mental health utilizing a non-pharmacological method. Assessing and analyzing the dynamics of mental health illness first hand, the study shall move ahead to offer a culturally tailored counseling program at the community level. The study also aims to highlight the role of the indigenous human resource (community health workers) and how its participation leads to a more scientific and sustainable intervention for more effective results, with an increased level of awareness and sensitization in a conventional society like Kashmir.

Background: Bridging the alarming treatment gap for mental disorders in India requires a monumental effort from all stakeholders. Harnessing digital technology is one of the potential ways to leapfrog many known barriers for capacity building. Aim and Context: The ongoing Virtual Knowledge Network (VKN)–National Institute of Mental Health and Neurosciences (NIMHANS)–Extension of Community Health Outcomes (ECHO) (VKN–NIMHANS–ECHO: hub and spokes model) model for skilled capacity building is a collaborative effort between NIMHANS and the University of New Mexico Health Sciences Centre, USA. This article aims to summarize the methodology of two randomized controlled trials funded by the Indian Council of Medical Research (ICMR) designed to evaluate the effectiveness of the VKN–NIMHANS–ECHO model of training as compared to training as usual (TAU). Methods: Both RCTs were conducted in Karnataka, a southern Indian state in which the DMHP operates in all districts. We compared the impact of the following two models of capacity building for the DMHP workforce (a) the VKN–NIMHANS–ECHO model and (b) the traditional method. We use the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statement to describe the methods of these two trials. Trial 1 is to evaluate the “Effectiveness of addition of Virtual-NIMHANS–ECHO tele-mentoring model for skilled capacity building in providing quality care in alcohol use disorders by the existing staff of DMHP districts of Karnataka.” Hub for trial 1 was set up at NIMHANS and the spokes were psychiatrists and other mental health professionals headquartered in the district level office. Trial 2 assesses the implementation and evaluation of the NIMHANS–ECHO blended training program for the DMHP workforce in a rural south-Indian district of Karnataka state. The hub for trial 2 was set up in the district headquarter of Ramanagaram. Hub specialists are DMHP psychiatrists, whereas spokes are the non-doctor workforce (including auxiliary nurse midwives [ANMs] and accredited social health activists [ASHA] workers) medical officers of primary health centers. The location of the HubHub differs in these two studies. Both trials are funded by the ICMR, Government of India Discussion: Both these trials, though conceptually similar, have some operational differences which have been highlighted. If demonstrated to be effective, this model of telementoring can be generalized and widely merged into the Indian health care system, thus aiding in reducing the treatment gap for patients unable to access care.

Objective To describe nurse hand hygiene practices in the home health care (HHC) setting, nurse adherence to hand hygiene guidelines, and factors associated with hand hygiene opportunities during home care visits. Design Observational study of nurse hand hygiene practices. Setting and Participants: Licensed practical/vocational and registered nurses were observed in the homes of patients being served by a large nonprofit HHC agency. Methods Two researchers observed 400 home care visits conducted by 50 nurses. The World Health Organization's “5 Moments for Hand Hygiene” validated observation tool was used to record opportunities and actual practices of hand hygiene, with 3 additional opportunities specific to the HHC setting. Patient assessment data available in the agency electronic health record and a nurse demographic questionnaire were also collected to describe patients and nurse participants. Results A total of 2014 opportunities were observed. On arrival in the home was the most frequent opportunity (n = 384), the least frequent was after touching a patient's surroundings (n = 43). The average hand hygiene adherence rate was 45.6% after adjusting for clustering at the nurse level. Adherence was highest after contact with body fluid (65.1%) and lowest after touching a patient (29.5%). The number of hand hygiene opportunities was higher when patients being served were at increased risk of an infection-related emergency department visit or hospitalization and when the home environment was observed to be “dirty.” No nurse or patient demographic characteristics were associated with the rate of nurse hand hygiene adherence. Conclusions and Implications Hand hygiene adherence in HHC is suboptimal, with rates mirroring those reported in hospital and outpatient settings. The connection between poor hand hygiene and infection transmission has been well studied, and it has received widespread attention with the outbreak of SARS-CoV-2. Agencies can use results found in this study to better inform quality improvement initiatives.

Background: Urinary tract infection (UTI) is a complication often experienced during a home health care (HHC) episode, yet related hospitalization risk factors are unclear. Objectives: This study use multiple data sources to identify risk factors for UTI related hospitalization or emergency department (ED) visits among HHC patients.Method: We performed a multivariable logistic regression to identify risk factors for UTI-related hospitalization or ED visits using merged data from the Outcome and Assessment Information Set, electronic health record from a large HHC agency, and Center for Medicare and Medicaid claims. Results: Of 48,336 cases, 1,689 patients (3.5%) had a UTI-related hospitalization/ED visits. Being a female (OR = 1.31; 95% CI: 1.16–1.46), the presence of a urinary catheter (OR = 5.7; 95% CI: 4.54–7.14), treatment with general antibacterial and antiseptics (OR = 2.75; 95% CI: 1.02–7.38), dependency in instrumental activities of daily living (e.g., meal preparation [OR=1.72; 95% CI: 1.25-2.37]), and no available caregivers (OR = 1.79; 95% CI: 1.2–2.68) increased the odds of a UTI related event among HHC patients. Discussion/conclusion: We identified notable risk factors for UTI related hospitalization/ER visit, filling a knowledge gap on the currently understudied HHC population. Risk factors identified in this study can be used to proactively identify HHC patients at risk for UTI related hospitalization and target them for preventive interventions. Further research is needed in HHC to develop tailored interventions for at-risk patients.

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. CLINICALTRIAL ClinicalTrials.gov NCT04136951; https://clinicaltrials.gov/ct2/show/NCT04136951 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/20184

BackgroundThere 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.ObjectivesTo 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.DesignA qualitative descriptive study, using semi-structured interviews.SettingA large not for profit home care agency located in the New York region of the United States.ParticipantsFifty nurses with a range of experience in home care nursing.MethodsPurposive and snowball sampling was used to recruit nurses from across the home care agency with varied years of work experience. Interviews were audio recorded andtranscribed. 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.ResultsThree 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.ConclusionsThe 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.

Hemophilia B requires replacement therapy with factor IX (FIX) coagulation products to treat and prevent bleeding episodes. A recently introduced extended half-life (EHL) recombinant FIX replacement product provided the opportunity to compare the amount of dispensed factor and expenditures for EHL treatment compared with a standard half-life (SHL) product.To determine factor international units (IUs) dispensed and expenditures associated with switching from nonacog alfa, the most commonly used SHL replacement product, to eftrenonacog alfa, an EHL FIX replacement product.Two U.S. claims databases were analyzed. A large national specialty pharmacy dispensation claims database was used to identify the number of IUs dispensed and monthly charges for all patients with hemophilia B from April 2015 to June 2016. Truven Health MarketScan Research Databases (January 2010-July 2016) were used to identify IUs and expenditures for patients with claims data for at least 3 months before and after switching from the SHL to the EHL product. Medians for IUs and expenditures are presented to accommodate for skewness of data distribution.The national specialty pharmacy database analysis included 296 patients with moderate or severe hemophilia B (233 on SHL; 94 on EHL). Median monthly factor dispensed was 11% lower (2,142 IU) in the EHL versus SHL cohort over the study period, while individual monthly reductions ranged from 32% to 47% (9,838 IU to 16,514 IU). Using the wholesale acquisition cost, the median per-patient monthly factor expenditures over the 15-month study period were 94% higher ($23,005) for the EHL than for the SHL product. Individual median monthly expenditure differences ranged from 15% ($6,562) to 49% ($19,624). In the Truven database, 14 patients switched from the SHL to the EHL product. The amount of factor dispensed was variable; in the 1-year period before and after the switch from the SHL to the EHL product, mean IUs dispensed decreased by 3,005 IU, while median IUs dispensed increased by 4,775 IU. Factor replacement expenditures were higher after switching from the SHL to the EHL product in each of the 3-month periods examined before versus after the switch.This analysis of real-world data showed that switching from the SHL to the EHL product was associated with higher expenditures. Increased expenditures noted in the first 3 months after switching may be related to initial stocking up of the EHL product, but expenditures were sustained throughout the 1-year period of data analysis. Further analysis of these findings with larger numbers of patients should be explored.This study was sponsored by Pfizer. Pfizer employees were involved in the study design; the collection, analysis, and interpretation of data; the review of the manuscript; and the decision to submit for publication. All authors are employees of Pfizer. No author received an honorarium or other form of payment related to the development of this manuscript. All authors participated in the study design, data interpretation, and manuscript review and revisions and granted approval for the submission of the manuscript. Alvir, McDonald, and Tortella also participated in data analysis. Data from this paper were presented in part at the European Association for Haemophilia and Allied Disorders Annual Meeting, February 1-3, 2017, Paris, France; at the International Society for Pharmacoeconomics and Outcomes Research Annual Meeting, May 20-24, 2017, Boston, MA; and at the International Society on Thrombosis and Haemostasis Congress, July 8-13, 2017, Berlin, Germany.

Interprofessional collaborative education and practice has become a cornerstone of optimal person-centered management in the current complex health care climate. This is especially important when working with older adults, many with multiple chronic conditions and challenging health care needs. This paper describes a feasibility study of the Geriatric Interdisciplinary Team Training 2.0 (GITT 2.0) program focused on providing interprofessional care to complex and frail older adults with multiple chronic conditions. A concurrent triangulation mixed-methods design facilitated program implementation and evaluation. Over three years (2013-2016), 65 graduate students from nursing, midwifery, social work, and pharmacy participated along with 25 preceptors. Participants were surveyed on their attitudes toward interprofessional collaboration pre and post-intervention and participated in focus groups. While attitudes toward interprofessional collaboration did not change quantitatively, focus groups revealed changes in language and enhanced perspectives of participants. Based on the evaluation data, the GITT 2.0 Toolkit was refined for use in interprofessional education and practice activities related to quality initiatives.

Markay Hopps,Laura Iadeluca,Margaret McDonald,Geoffrey T MakinsonPfizer Inc., New York, NY, USA Background: Family caregiving is an increasingly important component of care for patients and the elderly. Objective: The aim of this study is to characterize the burden of family caregiving among employed adults. Methods: Employed adults (≥18years) from the 2013 US National Health and Wellness Survey (NHWS) were classified as family caregivers if they reported currently caring for at least one adult relative. Chi-square tests and one-way analyses of variance assessed whether employed caregivers, weighted to the US population, differed from employed non-caregivers on behavioral characteristics, workplace productivity, and health care resource utilization. Results: Eight million workers were family caregivers in the United States, more often female than male (51% vs. 49%, P < 0.05), and 53% were between 40 and 64years of age. Eighteen percent of caregivers were Hispanic compared with 15% of non-caregivers (P < 0.05). Similar behavioral characteristics between caregivers and non-caregivers included daily alcohol consumption (6% vs. 5%) and lack of vigorous exercise (25% vs. 29%), but caregivers had a higher prevalence of smoking (26% vs. 19%, P < 0.05). Caregivers reported a higher mean percentage of work time missed (8% vs. 4%, P < 0.05) and greater productivity impairment (24% vs. 14%, P < 0.05). Some form of depression was reported by 53% of caregivers compared with 32% of non-caregivers (P < 0.05), and more caregivers had self-reported insomnia than non-caregivers (46% vs. 37%, P < 0.05). The number of self-reported diagnosed comorbidities was higher among caregivers compared with that of non-caregivers (5.0 vs. 3.1, P < 0.05), as was the mean number of outpatient visits in the previous 6months (4.1 vs. 2.7, P < 0.05). Conclusion: Family caregiving is associated with a multidimensional burden that impacts caregivers and has implications for employers and the health care system. Clinicians and employers need to recognize and understand this burden. Characterization of caregivers as reported in this study can inform development of targeted programs to help mitigate the burden. Keywords: caregiver burden, productivity, mental health, health care resource use, workforce, employed, family caregivers

BACKGROUND Uncontrolled hypertension (HTN) is a leading modifiable stroke risk factor contributing to global stroke disparities. This study is unique in testing a transitional care model aimed at controlling HTN in black and Hispanic poststroke, home health patients, an understudied group. METHODS A 3-arm randomized controlled trial design compared (i) usual home care (UHC), with (ii) UHC plus a 30-day nurse practitioner transitional care program, or (iii) UHC plus nurse practitioner plus a 60-day health coach program. The trial enrolled 495 black and Hispanic, English- and Spanish- speaking adults with uncontrolled systolic blood pressure (SBP ≥ 140 mm Hg) who had experienced a first-time or recurrent stroke or transient ischemic attack. The primary outcome was change in SBP from baseline to 3 and 12 months. RESULTS Mean participant age was 67; 57.0% were female; 69.7% were black, non-Hispanic; and 30.3% were Hispanic. Three-month follow-up retention was 87%; 12-month retention was 81%. SBP declined 9–10 mm Hg from baseline to 12 months across all groups; the greatest decrease occurred between baseline and 3 months. The interventions demonstrated no relative advantage compared to UHC. CONCLUSION The significant across-the-board SBP decreases suggest that UHC nurse/patient/physician interactions were the central component of SBP reduction and that additional efforts to lower recurrent stroke risk should test incremental improvements in usual care, not resource-intensive transitional care interventions. They also suggest the potential value of pragmatic home care programs as part of a broader strategy to overcome HTN treatment barriers and improve secondary stroke prevention globally. CLINICAL TRIALS REGISTRATION Trial Number NCT01918891.

OBJECTIVES: To estimate the health care resource use (HCRU) and costs for patients diagnosed with acromegaly, following treatment with either pegvisomant, a growth hormone receptor antagonist (GHRA); or a somatostatin analogue (SSA). METHODS: De-identified data from Optum’s ClinformaticsTM Data Mart (CDM), a US claims database, were used to retrospectively identify patients with acromegaly from January 2011 - June 2018 who were treated with the GHRA or an SSA. Propensity score matching (PSM) was used to address the small sample size of acromegaly patients and to ensure a direct comparison between the two treatment groups. PSM was fitted using a logistic regression model that included age, gender, total cost and Charlson Comorbidity Index (CCMI) score at index¹. Follow up (FU), HCRU (including Emergency Room [ER] costs, outpatient and inpatient costs) were compared. Average differences in change from baseline costs between the GHRA and SSA from the matched groups are shown with p-values obtained from a t-test. All costs are average across visits. RESULTS: Following PSM 91 patients were treated with GHRA and 269 patients were treated with SSAs. Mean ER costs were higher in the SSA vs GHRA group ($63 vs -$19, p=0.5646). On average outpatient visits were higher in the SSA vs GHRA group (2.88 and 2.82 respectively, p=0.8583); associated costs were higher ($1181 and $789 respectively p=0.3832). Regarding office visits and associated costs, these were also higher in the SSA group (Visit: 0.77 vs 0.74 and Cost: $1 vs -$7). The number of inpatient visits was equal (average =0.03) for both groups, with slightly higher costs in the GHRA group ($131 vs $161, p=0.9644). The drug cost and overall total cost of SSAs vs GHRA were significantly different ($2630 vs $6933, p

A primary service provided by home care is medication management. Issues with medication management at home place older adults at high risk for hospital admission, readmission, and adverse events. This study sought to understand medication management challenges from the home care provider perspective. A qualitative secondary data analysis approach was used to analyze program evaluation interview data from an interprofessional educational intervention study designed to decrease medication complexity in older urban adults receiving home care. Directed and summative content analysis approaches were used to analyze data from 90 clinician and student participants. Medication safety issues along with provider–provider communication problems were central themes with medication complexity. Fragmented care coordination contributed to medication management complexity. Patient-, provider-, and system-level factors influencing medication complexity and management were identified as contributing to both communication and coordination challenges.

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

Objectives: Urinary tract infection (UTI) is common in home care but not easily captured with standard assessment. This study aimed to examine the value of nursing notes in detecting UTI signs and symptoms in home care. Design: The study developed a natural language processing (NLP) algorithm to automatically identify UTI-related information in nursing notes. Setting and Participants: Home care visit notes (n = 1,149,586) and care coordination notes (n = 1,461,171) for 89,459 patients treated in the largest nonprofit home care agency in the United States during 2014. Measures: We generated 6 categories of UTI-related information from literature and used the Unified Medical Language System (UMLS) to identify a preliminary list of terms. The NLP algorithm was tested on a gold standard set of 300 clinical notes annotated by clinical experts. We used structured Outcome and Assessment Information Set data to extract the frequency of UTI-related emergency department (ED) visits or hospitalizations and explored time-patterns in documentation of UTI-related information. Results: The NLP system achieved very good overall performance (F measure = 0.9, 95% CI: 0.87–0.93) based on the test results obtained by using the notes for patients admitted to the ED or hospital due to UTI. UTI-related information was significantly more prevalent (P < .01 for all the tests) in home care episodes with UTI-related ED admission or hospitalization vs the general patient population; 81% of home care episodes with UTI-related hospitalization or ED admission had at least 1 category of UTI-related information vs 21.6% among episodes without UTI-related hospitalization or ED admission. Frequency of UTI-related information documentation increased in advance of UTI-related hospitalization or ED admission, peaking within a few days before the event. Conclusions and Implications: Information in nursing notes is often overlooked by stakeholders and not integrated into predictive modeling for decision-making support, but our findings highlight their value in early risk identification and care guidance. Health care administrators should consider using NLP to extract clinical data from nursing notes to improve early detection and treatment, which may lead to quality improvement and cost reduction.