Home Health Care Organizations Research Articles

Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient-nurse verbal communications in home healthcare settings?

Identifying health problems in audio-recorded patient-nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource-intensive human annotation. To generate synthetic patient-nurse communication and to automatically annotate for common health problems encountered in home healthcare settings using GPT-4. We also examined whether augmenting real-world patient-nurse communication with synthetic data can improve the performance of machine learning to identify health problems. Secondary data analysis of patient-nurse verbal communication data in home healthcare settings. The data were collected from one of the largest home healthcare organizations in the United States. We used 23 audio recordings of patient-nurse communications from 15 patients. The audio recordings were transcribed verbatim and manually annotated for health problems (e.g., circulation, skin, pain) indicated in the Omaha System Classification scheme. Synthetic data of patient-nurse communication were generated using the in-context learning prompting method, enhanced by chain-of-thought prompting to improve the automatic annotation performance. Machine learning classifiers were applied to three training datasets: real-world communication, synthetic communication, and real-world communication augmented by synthetic communication. Average F1 scores improved from 0.62 to 0.63 after training data were augmented with synthetic communication. The largest increase was observed using the XGBoost classifier where F1 scores improved from 0.61 to 0.64 (about 5% improvement). When trained solely on either real-world communication or synthetic communication, the classifiers showed comparable F1 scores of 0.62-0.61, respectively. Integrating synthetic data improves machine learning classifiers' ability to identify health problems in home healthcare, with performance comparable to training on real-world data alone, highlighting the potential of synthetic data in healthcare analytics. This study demonstrates the clinical relevance of leveraging synthetic patient-nurse communication data to enhance machine learning classifier performances to identify health problems in home healthcare settings, which will contribute to more accurate and efficient problem identification and detection of home healthcare patients with complex health conditions.

Infection prevention practice in home healthcare: a mixed-method study in two Swiss home healthcare organisations.

Infection prevention and control (IPC) research has long neglected the home healthcare sector with its unique challenges. This study aimed to gain an understanding of the barriers to the implementation of infection prevention practices relevant to this setting, the related attitudes, perceived relevance and priorities from the home healthcare worker perspective in Switzerland. The mixed-method study involved semi-structured interviews (n = 18) and an anonymous web-based survey (n = 144) among nursing assistants and nurses from two home healthcare organizations in northwest Switzerland. Questions in both sub-studies focused on perceived challenges to infection prevention practices, perceived relevance, and related attitudes and mitigation strategies. Using an exploratory-sequential design, survey questions were designed to quantify and complement the findings from the interview study. Healthcare workers in these two organisations felt adequately protected, trained and supported by their organisations regarding IPC (survey agreement rates > 90%). General challenges to IPC in the home environment most agreed on were lack of cleanliness, lack of space, and the priorities of the patient to be respected (survey agreement rates 85.4%, 77.1%, and 70.8%, respectively). Practices and perceived challenges in the case of colonisation with multi-drug resistant organisms (MDRO) and potentially infectious diarrheal or respiratory illnesses varied highly regarding information transfer, use of protective equipment, and use and disinfection practices of multi-use equipment. Challenges to hand hygiene, sharps safety, waste management and decontamination of equipment did not feature as a prominent concern. This study is the first to characterise the implementation of infection prevention practices and the related challenges in home healthcare in Switzerland. Home healthcare workers describe various challenges related to infection prevention practices as largely manageable in their work routine, and generally show satisfaction with the support provided by their organisations regarding IPC precautions. Key findings regarding challenges amenable to interventions include uncertainty and inconsistency regarding the management of MDRO colonisation and acute illnesses, and gaps in information transfer. Those challenges may benefit from both organisational interventions and further research into the level of precautions that are appropriate to the home healthcare setting.

Strategies and Interventions to Support Quality Outcomes in the Home Care Setting: A Longitudinal Multilevel Study.

The relationship between the practice environment, empowerment, and outcomes such as quality of care, job satisfaction, and intent to stay has been extensively studied in healthcare settings, including hospitals and long-term care facilities. Research consistently demonstrates that a positive practice environment, characterized by supportive leadership, adequate resources, and opportunities for professional growth, are associated with better quality of care, increased job satisfaction, and higher intent to stay among healthcare professionals. Limited knowledge exists regarding the specific relationship between the practice environment, empowerment, and these outcomes within home care organizations. This study assesses the impact of strategies on nurse practice environment, social capital, decision latitude, workload, care quality, job satisfaction, and retention in a Belgian home healthcare organization. A longitudinal survey was conducted in a home healthcare organization, with data collected at 3 time points: baseline (T1) (2015), T2 (2018), and T3 (2021). In T3, respondents reported significantly higher scores for departmental and general management compared with T1. The interventions led to significant improvements in social capital and decision latitude. Self-reported quality of care at the department level showed a significant increase, whereas no significant change was observed for quality of care during the last round. The implementation of strategies and interventions as part of a broader healthcare transformation process had a positive impact. Improvements were observed in nurse-reported quality of care, job satisfaction, and intent to stay in nursing. These findings emphasize the effectiveness of the implemented measures in enhancing nursing practice and creating a positive work environment. Continuous efforts to implement and evaluate such strategies are essential for enhancing the satisfaction and retention of nursing teams within healthcare organizations.

A multiobjective approach for weekly Green Home Health Care routing and scheduling problem with care continuity and synchronized services

Home Health Care (HHC) services are essential for delivering healthcare programs to patients in their homes, with the goal of reducing hospitalization rates and improving patients’ quality of life. However, HHC organizations face significant challenges in scheduling and routing caregivers for home care visits due to complex criteria and constraints. This paper addresses these challenges by considering both caregiver assignments and transportation logistics. The objective is to minimize the total travel distance and CO2 emissions while ensuring a balanced workload for caregivers, meeting patients’ preferences, synchronization, precedence, and availability constraints. To tackle this problem, we propose a multiperiodic Green Home Health Care (GHHC) framework. In the first stage, we utilize multiobjective programming and the NSGA-II algorithm to generate Pareto front solutions that consider travel distance and CO2 emissions. In the second stage, a Mixed-Integer Linear Programming (MILP) model is proposed to balance caregivers’ workload by assigning them to the patient routes generated in the first stage. The results highlight the trade-off between shorter routes and lower emissions. Furthermore, we examine the impact of prioritizing continuity of care and patient satisfaction. This research provides valuable insights into addressing the scheduling and routing challenges in HHC services, contributing to a more efficient and environmentally friendly healthcare delivery.

The Paradox of Choice in Palliative Care Decision-Making in Managed Long-Term Care: A Qualitative Study

Palliative care offers undeniable advantages to elderly patients with multiple chronic illnesses in managed long-term care. However, only approximately 14% of those who require palliative care actually receive it. To investigate factors influencing decision-making regarding palliative care acceptance, and healthcare providers’ communication strategies, which patients or family caregivers perceive during managed long-term care. Qualitative thematic content analysis study. Two data sources from home and community-based health care organization in a metropolitical city in the Northeastern United States were used: (a) retrospectively collected 79 phone call audio recordings between patients and/or family caregivers with healthcare providers when initiate palliative care option, and (b) prospectively collected 10 exploratory qualitative interviews with patients and/or family caregivers for this study purpose. From a total of 89 conversations, 7 themes emerged during palliative care decision-making: (a) capability for self-management; (b) symptom severity; (c) perceptions of chronic disease; (d) satisfaction with current health services; (e) code status; (f) caregiver burden and (g) other reasons, including financial considerations and service affiliations. In addition, from 10 qualitative interviews, 4 key themes in healthcare providers’ communication that optimize palliative care conversations were indicated: (i) trust and relationship dynamics; (ii) positive reinforcement and personal connection; (iii) conversation setting and initiator; and (iv) collaborative approach to care coordination. Enhancing decision-making around palliative care and improving acceptance of palliative care services may be improved through the integration of personalized care plans, empathetic communication, use of symptom-inclusive assessments for timely care, and proactively addressing caregiver burden.

Health economic evaluation of a nurse-assisted online eye screening in home healthcare to reduce avoidable vision impairment (iScreen): study protocol for a cluster randomized controlled trial

BackgroundAmong older people undiagnosed and untreated vision impairment and blindness are common. The leading causes are uncorrected refractive errors and cataracts. Vision problems are associated with a lower quality of life, several health problems, and a higher chance of falling accidents and fractures. To eliminate avoidable vision impairment and blindness, targeted eye screening programs are recommended. Older patients, receiving home healthcare, have not yet been considered as a population at risk who could benefit from eye screening.MethodsA cluster-randomized controlled trial will be conducted to investigate the cost-effectiveness and cost-utility of online nurse-assisted eye screening in home healthcare, compared to care as usual, in reducing avoidable vision impairment. A healthcare and societal perspective will be used. The study will be performed in collaboration with several home healthcare organizations in the Netherlands. The online eye screening consists of near and distance visual acuity, followed by an Amsler grading test. Measurements in both groups will take place at baseline and after 6 and 12 months of follow-up. A total of 240 participants will be recruited. Older men and women (65 +), who receive home-based nursing and are cognitively able to participate, will be included. The primary outcome will be the change of two lines or more on the Colenbrander-1 M visual acuity chart between baseline and 12-month follow-up.DiscussionAn eye screening for populations at risk contributes to the detection of undiagnosed and untreated vision impairment. This may reduce the health-related consequences of vision loss and the high economic burden associated with vision impairment.Trial registrationClinicalTrials.gov NCT06058637. Registered on 27 September 2023.

PATIENT-CLINICIAN RELATIONSHIPS IN HOME HEALTH CARE

Abstract Patient-clinician relationships are fundamental attributes of high-quality home health care (HHC); yet little is known about patient-clinician relationships in HHC (where 5 million Medicare beneficiaries receive care annually). The objective of the study was to describe perspectives of HHC patients and HHC clinicians about patient-clinician relationships in HHC. We conducted a secondary qualitative analysis of semi-structured interviews (n=34) from a completed qualitative study investigating perspectives of older adult HHC patients (or caregivers as proxy) and their HHC clinicians (17 pairs) on discharge preparedness in a large HHC organization in North-Carolina. A conceptual model of patient-clinician relationships guided content analysis of the interview data. HHC patients identified as White (65%) and black (35%). Most HHC patients reported female sex (53%) and average age was 83 years (range= 69-93). Clinicians were registered nurses and physical therapists. Across the patient-clinician pairs, HHC patients valued relationships with clinicians with shared commonalities and those who provided reciprocal informational exchange and respected their autonomy. HHC clinicians valued relationships in which they felt helpful and respected as a healthcare professional. Relational conflicts arose when there was discordance in expectations of care (e.g., type of HHC services provided). Conflicts also arose when organizational constraints, such as disruptive scheduling, limited HHC visit time, and when limited continuity of care prevented the formation of patient-clinician relationships. Relational conflicts and organizational constraints influence patient-clinician relationships in HHC. Multi-level interventions (targeting modifiable factors at the patient, clinician, and organizational levels) are needed to improve the patient-clinician relationships and the quality of HHC.

Home Healthcare Patients With Distinct Psychological, Cognitive, and Behavioral Symptom Profiles and At-Risk Subgroup for Hospitalization and Emergency Department Visits Using Latent Class Analysis.

One-third of home healthcare patients are hospitalized or visit emergency departments during a 60-day episode of care. Among all risk factors, psychological, cognitive, and behavioral symptoms often remain underdiagnosed or undertreated in older adults. Little is known on subgroups of older adults receiving home healthcare services with similar psychological, cognitive, and behavioral symptom profiles and an at-risk subgroup for future hospitalization and emergency department visits. Our cross-sectional study used data from a large, urban home healthcare organization (n = 87,943). Latent class analysis was conducted to identify meaningful subgroups of older adults based on their distinct psychological, cognitive, and behavioral symptom profiles. Adjusted multiple logistic regression was used to understand the association between the latent subgroup and future hospitalization and emergency department visits. Descriptive and inferential statistics were conducted to describe the individual characteristics and to test for significant differences. The three-class model consisted of Class 1: "Moderate psychological symptoms without behavioral issues," Class 2: "Severe psychological symptoms with behavioral issues," and Class 3: "Mild psychological symptoms without behavioral issues." Compared to Class 3, Class 1 patients had 1.14 higher odds and Class 2 patients had 1.26 higher odds of being hospitalized or visiting emergency departments. Significant differences were found in individual characteristics such as age, gender, race/ethnicity, and insurance. Home healthcare clinicians should consider the different latent subgroups of older adults based on their psychological, cognitive, and behavioral symptoms. In addition, they should provide timely assessment and intervention especially to those at-risk for hospitalization and emergency department visits.

Uncovering hidden trends: identifying time trajectories in risk factors documented in clinical notes and predicting hospitalizations and emergency department visits during home health care.

This study aimed to identify temporal risk factor patterns documented in home health care (HHC) clinical notes and examine their association with hospitalizations or emergency department (ED) visits. Data for 73350 episodes of care from one large HHC organization were analyzed using dynamic time warping and hierarchical clustering analysis to identify the temporal patterns of risk factors documented in clinical notes. The Omaha System nursing terminology represented risk factors. First, clinical characteristics were compared between clusters. Next, multivariate logistic regression was used to examine the association between clusters and risk for hospitalizations or ED visits. Omaha System domains corresponding to risk factors were analyzed and described in each cluster. Six temporal clusters emerged, showing different patterns in how risk factors were documented over time. Patients with a steep increase in documented risk factors over time had a 3 times higher likelihood of hospitalization or ED visit than patients with no documented risk factors. Most risk factors belonged to the physiological domain, and only a few were in the environmental domain. An analysis of risk factor trajectories reflects a patient's evolving health status during a HHC episode. Using standardized nursing terminology, this study provided new insights into the complex temporal dynamics of HHC, which may lead to improved patient outcomes through better treatment and management plans. Incorporating temporal patterns in documented risk factors and their clusters into early warning systems may activate interventions to prevent hospitalizations or ED visits in HHC.

Home Health Care Clinicians' Use of Judgment Language for Black and Hispanic Patients: Natural Language Processing Study.

A clinician's biased behavior toward patients can affect the quality of care. Recent literature reviews report on widespread implicit biases among clinicians. Although emerging studies in hospital settings show racial biases in the language used in clinical documentation within electronic health records, no studies have yet investigated the extent of judgment language in home health care. We aimed to examine racial differences in judgment language use and the relationship between judgment language use and the amount of time clinicians spent on home visits as a reflection of care quality in home health care. This study is a retrospective observational cohort study. Study data were extracted from a large urban home health care organization in the Northeastern United States. Study data set included patients (N=45,384) who received home health care services between January 1 and December 31, 2019. The study applied a natural language processing algorithm to automatically detect the language of judgment in clinical notes. The use of judgment language was observed in 38% (n=17,141) of the patients. The highest use of judgment language was found in Hispanic (7,167/66,282, 10.8% of all clinical notes), followed by Black (7,010/65,628, 10.7%), White (10,206/107,626, 9.5%), and Asian (1,756/22,548, 7.8%) patients. Black and Hispanic patients were 14% more likely to have notes with judgment language than White patients. The length of a home health care visit was reduced by 21 minutes when judgment language was used. Racial differences were identified in judgment language use. When judgment language is used, clinicians spend less time at patients' homes. Because the language clinicians use in documentation is associated with the time spent providing care, further research is needed to study the impact of using judgment language on quality of home health care. Policy, education, and clinical practice improvements are needed to address the biases behind judgment language.

UNMET TRANSITIONAL CARE NEEDS OF OLDER ADULTS DISCHARGED FROM HOME HEALTH CARE: A QUALITATIVE NEEDS ASSESSMENT

Abstract Transitional care is widely recognized as a set of time-limited services to support older adults during transfers between settings and providers of care; however, little is known about services that prepare older adults and their caregivers for transitions from Home Health Care (HHC) to independent self-care at home. The objective of this study was to describe HHC patients and clinician perceptions of unmet needs after HHC discharge and recommendations to address them in future research. A multiple case-study design was used in a single large HHC organization in North Carolina. Data were collected using chart reviews of HHC records and semi-structured interviews with paired patients (or caregivers as proxy) and HHC clinicians (Nf17 pairs). A transitional care intervention model was used as a conceptual framework to guide framework analysis of interview transcripts. Most patients were White (65%) and female (53%) with mean age of 83 years. Clinicians were Registered nurses and Physical therapists. Across cases, 17 patient and clinicians pairs described three unmet needs: (1)skills for symptom management; (2)community-based support for transportation, food, social engagement, and health services; (3)in-home support to assist with safety, and activities of daily living. HHC patients recommended new services while clinicians emphasized the need for resources to improve their capacity to prepare patients for discharge. These findings will inform an innovative adaptation of transitional care and other supports to prepare older adults and caregivers for transitions from HHC to independent self-care at home. Future research should explore adding transitional care services to address these needs.

The identification of clusters of risk factors and their association with hospitalizations or emergency department visits in home health care.

To identify clusters of risk factors in home health care and determine if the clusters are associated with hospitalizations or emergency department visits. A retrospective cohort study. 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. 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). 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. 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. There was no involvement of patients in developing the research question, determining the outcome measures, or implementing the study.

Create and Sustain a Culture of Curiosity: A Case Study of a Home Healthcare Organization in Toronto.

Increased integration in the healthcare sector requires traditionally non-research-based organizations to contribute to evidence-based decision making as equal partners. This requires a culture and infrastructure that support structured inquiry to improve best practice, quality and safety. We present the roadmap used by one home healthcare organization to create an embedded research unit to drive this transformation. The use of a relevant model and a framework provided structure to guide and sustain the process. We expect that the core strategies and combination of frameworks should be transferrable to others wishing to contribute meaningfully to evidence-based health system transformation.

Contextual Forces Shaping Home-Based Health Care Services Between 2010 and 2020: Insights From the Social-Ecological Model and Organizational Theory.

Demands for home-based care have surged alongside population aging, preferences for aging in place, policy-driven reforms incentivizing lower hospital utilization, and public concerns around COVID-19 transmissions in institutional care settings. However, at both macro and micro levels, sociopolitical and infrastructural contexts are not aligned with the operational needs of home healthcare organizations, presenting obstacles to home healthcare equity.We integrate the social-ecological model and organizational theory to highlight contextual forces shaping the delivery of home-based care services between 2010 and 2020. Placing home-based healthcare organizations at the center of observation, we discuss patterns and trends of service delivery as systematic organizational behaviors reflecting the organizations’ adaptations and responses to their surrounding forces. In this light, we consider the implications of provision and access to home care services for health equity, discuss topics that are understudied, and provide recommendations for home-based healthcare organizations to advance home healthcare equity. The paper represents a synthesis of recent literature and our research and industry experiences.

Regional Impact of COVID-19 on Acute Case Management Practice.

Nadine M. Carter, MBA, BSN, RN, CDMS, CCM, has acquired cumulative health care experience in the areas of case management, utilization management, transitional management, nursing leadership, and personnel performance. Nadine has 30 years of case management experience. Nadine's passion is evident in her work with the Case Management Societ of America (CMSA), where she has served as president and board member to CMSA NJ, various national committees, and currently serves on the CMSA Board in Georgia and is the Secretary of the CMSA and a member of the Editorial Review Board for the Professional Case Management Journal. Marianne DiMola has more than 25 years of experience in health care human resources management and career development. Her experience includes branch directorships with two of the country's leading home health care organizations, Bayada Nurses and Nursefinders. She is a founding member of CMSA's TriChapter New York Conferences and served as the Executive Director of the New York City Chapter of CMSA for 20 years. Ms. DiMola is active with CMSA on national committees. Ms. DiMola is currently President and founder of Global Care Management, specialist in care management staffing and consulting. In addition, Marianne is one of the founders of Pathway Medical Staffing, a nationally recognized leader providing case management recruitment and retention advisory services, HEDIS staffing, and project management. Address correspondence to Nadine M. Carter, MBA, BSN, RN, CDMS, CCM, 3345 Hunting Creek Pass, Douglasville, GA 30135 ([email protected]; [email protected]) Disclaimer: The information contained in this department is for educational purposes only. It is not legal advice, which can only be given by an attorney admitted to practice in the jurisdiction/state(s) in which you practice. Do you have a question or issue you would like to be addressed here? Questions are always welcome. We encourage ALL readers to submit questions and/or manuscripts, as well as topics you would like to see addressed in this department. Questions and other inquiries are accepted by email at: [email protected]. If you have an idea you would like to discuss, send your contact information by email and you will be contacted via your preferred method. The authors report no conflicts of interest.

Clinical notes: An untapped opportunity for improving risk prediction for hospitalization and emergency department visit during home health care.

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. 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. 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. 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.

Seroprevalence of SARS-CoV-2 antibodies, associated factors, experiences and attitudes of nursing home and home healthcare employees in Switzerland

BackgroundMany studies in hospital settings exist and have shown healthcare employees to be particularly exposed to SARS-CoV-2. While research focused on hospital staff, little evidence exists for employees in nursing homes and home care. The aims of this study were to assess the seroprevalence in nursing homes and home care employees in the Canton of Zurich, compare it to the general population, assess factors associated with seropositivity and explore the perspective of the employees regarding how the pandemic changed their daily work.MethodsThis cross-sectional study is part of the national Corona Immunitas research program of coordinated, seroprevalence studies in Switzerland. Six nursing homes and six home healthcare organizations providing at home care services in Zurich were selected and 296 and 131 employees were recruited, respectively. Assessments included standardized questionnaires, blood sampling for antibodies, and additional work-specific questions. All participants were recruited between 21st September and 23rd October 2020, before the second wave of the pandemic hit Switzerland, and were possibly exposed to SARS-CoV-2 at their work during the first wave in spring 2020.ResultsSeroprevalence of SARS-CoV-2 was 14.9% (95% CI 11.1%-19.6%; range 3.8% to 24.4%) for nursing home employees and 3.8% (95% CI 1.4–9.1%; range 0% to 10%) for home healthcare employees, compared to the general population of Zurich at 3.5% in September 2020 for those aged 20–64. Nurses were 2.6 times more likely to have SARS-CoV-2 antibodies than those employees who were not nurses (95% CI 1.1–6.2). The employees (nursing homes vs. home healthcare) perceived the implementation of general safety measures (44.9% vs. 57.3%) and wearing masks during work (36.8% vs. 43.5%), especially due to the limited communication with residents/clients, as the most crucial changes.ConclusionsNursing home employees who worked through SARS-CoV-2 outbreaks at their work were substantially more affected by SARS-CoV-2 infection compared to the general population and to home healthcare employees who similarly worked through outbreaks in their communities. Employees reported that important resources to cope with the burdensome changes they perceived in their daily work were personal resources and team support.Trial registrationCurrent Controlled Trials ISRCTN18181860 dated 09/07/2020.Retrospectively registered.

In the Eye of the Storm: A Quantitative and Qualitative Account of the Impact of the COVID-19 Pandemic on Dutch Home Healthcare

The COVID-19 pandemic has severely affected healthcare delivery across the world. However, little is known about COVID-19’s impact on home healthcare (HHC) services. Our study aimed to: (1) describe the changes in volume and intensity of HHC services and the crisis management policies implemented; (2) understand the responses and the experiences of HHC staff and clients. We conducted an explanatory sequential mixed methods study. First, retrospective client data (N = 43,495) from four Dutch HHC organizations was analyzed. Second, four focus group interviews were conducted for the strategic, tactical, operational, and client levels of the four HHC organizations. Our results showed that both the supply of and demand for Dutch HHC decreased considerably, especially during the first wave (March–June 2020). This was due to factors such as fear of infection, anticipation of a high demand for COVID-19-related care from the hospital sector, and lack of personal protective equipment. The top-down management style initially applied made way for a more bottom-up approach in the second wave (July 2020–January 2021). Experiences vary between levels and waves. HHC organizations need more responsive protocols to prevent such radical scaling-back of HHC in future crises, and interventions to help HHC professionals cope with crisis situations.

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

BackgroundDelayed 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.ObjectiveThe 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.MethodsThis 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.ResultsThe 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.ConclusionsTo 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.

Frontline provider perceptions of implementing home-based palliative care covered by an insurer.

To examine frontline providers' experiences implementing home-based palliative care (HBPC) covered by a private health insurer in partnership with community-based hospice, home health, and Accountable Care Organizations. Primary data collection at three community-based hospice and home health organizations in Northern and Southern California at the outset of the new private payer-contracted HBPC. Qualitative focus groups with frontline HBPC providers. Focus groups were guided by a nine-item, semi-structured research protocol, audio-recorded, transcribed verbatim, and analyzed by two independent coders using a grounded theory approach. Participants (n= 24) were mostly White (79.2%) female (91.7%) aged 39 years or less (62.5%), and from diverse disciplines. Three major themes were identified: (1) patient referrals, (2) organizational factors, and (3) HBPC reimbursement. Findings highlight barriers and facilitators to implementing HBPC covered by an insurer including the organization's community reputation, the dynamic/"teaminess" of the HBPC team, having a site champion/"quarterback," and issues from a siloed medical system. Participants also discussed challenges with patient referrals, specifically, lack of palliative care knowledge (both providers and patients/families) and poor communication with patients referred to HBPC. This study found that despite a favorable perception of payer-contracted HBPC by frontline providers, barriers and facilitators persist, with patient accrual/referral paramount.