Home Healthcare Program Among Adults Aged 50 and Older: A RE-AIM Framework Evaluation Using 3-Year Real-World Data.

BackgroundThe need for home healthcare programs is an increasingly becoming important common component of healthcare worldwide, as an alternative to hospitalization, owing to the growing elderly population, chronic and acute diseases that need continuous monitoring and care. The overall aim of this study was to describe and assess the quality of life (QOL) and associated determinants among patients enrolled in the Home Health Care (HHC) program affiliated with the Ministry of National Guard Health Affairs in Riyadh, Saudi Arabia.MethodsThis cross-sectional study was conducted among patients enrolled at the HHC program. The World Health Organization QOL questionnaire (WHOQOL-BREF) was used to collect data about the different domains of patients’ QOL. Logistic regression models were fitted to determine factors associated with QOL low score.ResultsThe study included 253 patients. Mean age was 67.05 (± 20.0). The overall QOL for HHC patients was significantly affected by both socio-demographic and morbid characteristics. In the final Multivariate logistic regression models, marital status, and having psychological problems, stroke and number illness were independently associated with the overall QOL of HHC patients (p = .022, p = .002, p = .031, .057 respectively). The physical health domain score was significantly associated with education level, having psychological problems and stroke (p = .028, p = .002, p = .007 retrospectively) whereas the psychological domain score was significantly associated with age (p = < 0.001) and three types of chronic diseases: pulmonary (p = .002), psychological problems (p = < 0.001). The social domain score was significantly associated only with the marital status (p = .026). The environmental domain was significantly associated with the education level and having stroke (p = .017 vs .027).ConclusionsThe overall QOL and its domains are significantly associated with several different factors. Many of these factors can be monitored and enhanced by improving quality of HHC services, thus improving the QOL of patients.

The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool. We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note-derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians. Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing-driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions. This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF. This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospitalizations.

背景與目的 台灣地區每年因為颱風（熱帶氣旋）造成的災害事件約三到四次，每次造成傷亡的人數大約由數十人到數百人不等，而急診是颱風期間病患就醫的唯一或主要的場所，因此急診於颱風前後的服務能量是否充足，在災害準備、應變與恢復期都扮演相當重要的醫療衛生角色，同時也是醫院訂定緊急應變計畫很重要的一部份。根據過去國外的文獻指出，颱風期間，急診的服務量會在颱風登陸當日顯著減少，但是於颱風過後，則會大量地增加，而其中又以外傷病患為主。本研究企圖探討台灣地區急診醫療服務在颱風期間及其後的變化，以進一步瞭解不同颱風的特性，在不同醫院層級對於急診服務量與及急診疾病型態的影響，以利日後醫院及衛生機關在進行災難應變規劃與準備時，可能所需人力及物資需求的參考。 研究方法 本研究主要以台灣東部地區（宜蘭縣、花蓮縣、台東縣）做為研究區域，針對西元2000年到2008年間，該地區颱風季節（6月到11月）急診服務量進行回溯性研究：資料蒐集來源為全民健保研究資料庫的每日急診申報資料，包含門診處方集治療明細檔（CD）及住院醫療費用清單明細檔（DD），以及醫療機構基本資料檔（HOSB）等，颱風的相關數據則來自中央氣象局的颱風資料庫。本研究利用多元迴歸的統計方法，分析急診服務量與急診疾病型態在颱風期間的變化，與颱風特徵（每日累積雨量、是否為登陸地區、颱風強度、陸上警報發佈警報天數、颱風近中心最大風速、近中心最低氣壓、七級風暴風半徑）及醫院規模的關係，颱風期間設定為颱風登陸前兩日到颱風登陸後五日共八天。 研究結果 每日急診就診人數在強烈颱風登陸當天會增加，在登陸地區影響可達兩天，以一家年每日平均來診人數達100人的醫院為例，於登陸當天每日急診就診人數較一般非颱風日（無颱風且日累積雨量小於50毫米）增加18.1人（p<0.001)，於登陸後第一日可增加24.9人（p<0.001）；而於未登陸但日累積雨量大於50毫米的僅在登陸當天一天，以一家年平均每日就診人數達100人的醫院為例，於登陸當天每日急診就診人數較一般非颱風日（無颱風且日累積雨量小於50毫米）增加6.3人（p<0.001)。然而創傷與非創傷的就診比例僅在強烈颱風登陸地區，於登陸當天有明顯增加，創傷就診比例以一家年每日平均來診人數達100人的醫院為例，約增加4.5%（p<0.001），其餘颱風影響日次，則無顯著差異。在創傷疾病型態中，因撕裂傷就診的病患比例，明顯在強烈颱風登陸當日上升4.1%（p<0.001），而於強烈颱風登陸後第1日，在未登陸但日累積雨量大於50毫米的地區，撕裂傷病患就醫比例增加6.9%（p=0.02）。 而在輕度颱風登陸當天，每日急診就診人數與非颱風日無顯著差異，在登陸後第一日則顯著減少；在中度颱風登陸前一日每日急診就診人數減少，在登陸後第一日於未登陸但有大雨（日雨量>50公釐）的地區，也是顯著減少，然而在登陸當天，在登陸地區每日急診就診人數則略微上升，以一家年每日平均來診人數達100人的醫院為例，約增加7.2人（p=0.002）。 結論 醫院急診部門應根據醫院的規模，在強烈颱風登陸時，增加急診的人力以因應急診就診人數的增加，在登陸地區更應維持人力支援直到颱風登陸後第一天。至於人力需求的種類，在強烈颱風登陸地區，於登陸當天應增加急診外科方面的人力，以應付較多的創傷病患。

Medicare's home health care program, consisting primarily of home visits by nurses and health aides, was conceived as a means to facilitate hospital discharge. Because home health care is now one of the fastest-growing categories of Medicare expenditures, we analyzed Medicare claims data to determine current patterns of use. We used 1993 data from Medicare's National Claims History File to examine the temporal relation between home visits and hospital discharge, as well as the number of months Medicare enrollees received home health care. To determine whether home visits replaced hospital services, we calculated population-based utilization rates, adjusted for age and sex, for enrollees living in the 310 U.S. metropolitan statistical areas and determined whether the areas with higher rates of home health care also had lower admission rates or shorter lengths of stay. Finally, we compared the geographic variation in use of home health care with that of other Medicare services. Roughly 3 million Medicare enrollees received over 160 million home health care visits in 1993. Seventy-eight percent of the visits either occurred more than a month after hospital discharge (35 percent) or were not associated with any inpatient care during the previous six months (43%). Home health care often represented a long-term intervention: 61 percent of the visits were to enrollees who received home health care for six months or more. We could find no evidence that home health care was substituted for hospital care; the metropolitan statistical areas with higher rates of home health care did not have fewer hospital admissions or shorter lengths of stay. There was more geographic variation in the use of home health care than in the use of other major categories of Medicare services (e.g., hospital admissions and physicians' services). Five states (all in the South) had more than 9000 visits per 1000 enrollees, and 14 states had fewer than 3000 visits per 1000 enrollees. Home health care visits are used primarily to provide long-term care. There is no evidence that services provided at home replace hospital services, and the dramatic geographic variation in home visits suggests a lack of consensus about their appropriate use.

The aim of this study was to evaluate the impact of home health care (HHC) for disabled patients.We conducted a nationwide population-based retrospective cohort study. A total of 5838 disabled patients with HHC were identified to match by propensity score with 15,829 disabled patients without HHC receiving tube or catheter care (tracheostomy tube, nasogastric tube, urinary catheter, cystostomy tube, nephrostomy tube) or stage 3 or 4 pressure sore care from the Taiwanese National Health Insurance Research Database between 2005 and 2009. After 1:1 matching, 2901 subjects in the HHC group and 2901 subjects in the non-HHC group were selected and analyzed. Generalized estimating equations (GEEs) were used to compare the risk of health outcomes (rate of hospitalization and emergency services use) and the healthcare expenditure between the 2 groups.Compared to those in the non-HHC group, the patients in the HHC group had significantly higher risk for hospitalization (odds ratio [OR] = 18.43, 95% confidence interval [CI]: 15.62–21.75, P < .001) and emergency services use (OR = 3.72, 95% CI: 3.32–4.17, P < .001) 1 year before the index date. However, 1 year after the index date, the risk for hospitalization (OR = 1.6, 95% CI: 1.41–1.83, P < .001) and emergency services use (OR = 1.16, 95% CI: 1.04–1.30, P < .05) attenuated significantly. Regarding the comparison of total healthcare expenditure 1 year before and after the index date, our study showed an insignificant decrease of US$1.5 per person per day and a significant increase of US$5.2 per person per day (P < .001) in the HHC and non-HHC groups, respectively.The HHC for disabled patients has a potential role to reduce hospitalization and emergency services use. Besides, the improvement of healthcare quality through HHC was not accompanied by increased healthcare expenditure. The clinical impact of HHC emphasizes the importance for public health officials to promote HHC model to meet the needs of disabled patients.

A method for analyzing the financial impact of new home health-care (HHC) programs on the hospital is presented. Clinical service objectives and long-term goals for new programs must match patient needs with institutional opportunities and constraints. Planning and evaluating new HHC programs require an accurate analysis of the financial impact of the proposed program on the hospital. A method for financial program analysis is presented through three different hypothetical scenarios based on realistic situations of hospitals considering HHC alternatives. Marginal analysis is presented as a microeconomic tool, and the calculation of marginal cost from a linear total cost function is described. Pro forma spread sheets of revenue and expense are used to assess three different HHC program alternatives--an independent HHC agency, a hospital-based agency, and a joint venture between a vendor and a hospital. Net present-value calculations are explained and applied to one case. It is important to use realistic assumptions in estimating the financial performance of HHC programs.

In order to (1) present the structure of Taiwan's National Health Insurance (NHI) research databases, along with the comparison with automated databases in other countries, (2) estimate the strengths and weaknesses of the NHI research databases, and (3) systematically review pharmacoepidemiology studies using the NHI research databases, we compared the characteristics of existing automated databases to reveal the strengths and weaknesses of the NHI research databases. In addition, the Medline was used as a tool to search pharmacoepidemiology studies using Taiwan's NHI research databases since 1997. The automated NHI research databases are very comparable with large research databases of other countries (US, Canada and UK). As a result, they serve as major resources for up to 11 pharmacoepidemiology studies published since 2002. However, these studies usually focused on the analysis of drug utilization pattern and drug utilization volume. As a result, there is still a huge lack of identification of potential drug safety issues using the NHI research databases. The construction of NHI research databases absolutely provides abundant research resources for scholars not only in medical fields but also in public health-related disciplines. Many studies using the NHI research databases have been published in international journals. Yet, researchers in Taiwan could make even greater progress toward thorough pharmacoepidemiology studies using the NHI research databases.

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

Social Risk Factors are Associated with Risk for Hospitalization in Home Health Care: A Natural Language Processing Study

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.

The home-based medical integrated program (HMIP) is a novel model for home healthcare (HHC) in Taiwan, initiated in 2016 to enhance care quality. However, the outcomes of this program on health outcomes and medical resource utilization in HHC patients remain unclear. Thus, we conducted this study to clarify it. The authors utilized the Taiwan National Health Insurance Research Database to identify HHC patients who received HMIP and those who did not between January 2015 and December 2017. A retrospective cohort study design was used. Convenience sampling was employed to select patients who met the inclusion criteria: being part of the HHC program and having complete data for analysis. A total of 4982 HHC patients in the HMIP group and 10,447 patients in the non-HMIP group were identified for this study. The mean age in the HMIP group and non-HMIP group was 77.6 years and 76.1 years, respectively. Compared with the non-HMIP group, the HMIP group had lower total medical costs for HHC, fewer outpatient department visits and lower medical costs, lower medical costs for emergency department visits, fewer hospitalizations, and a lower mortality rate (34.6% vs 41.2%, p<0.001). The HMIP is a promising model for improving care quality and reducing medical resource utilization in HHC patients. While this suggests that the non-HMIP model should be replaced, it's important to note that both non-HMIP and HMIP models currently coexist. The HMIP may serve as an important reference for other nations seeking to improve care quality and reduce medical resource utilization in their own HHC systems.

Does lack of a usual source of care or health insurance increase the likelihood of an emergency department visit? Results of a national population-based study

Background: Physical distancing during the COVID-19 pandemic has impacted the activities of daily living (ADLs) of families, such as physical and psychosocial aspects, self-efficacy, family social function, and overall quality of life. However, research investigating the effects of home health care in enhancing these aspects during the physical distancing period remains limited.Purpose: This study aimed to evaluate the effects of implementing home health care on physical and psychosocial aspects, self-efficacy, family social function, and quality of life of families in East Java Province, Indonesia.Methods: A quasi-experimental study was conducted among 768 healthy families that were purposively recruited from April to May 2020. The home health care program was implemented for one month to provide nursing care to the families. Data were collected using self-administered questionnaires, and SPSS software was employed for data analysis. Chi-square tests were applied for categorical variables, while paired t-tests were used for continuous variables.Results: Significant differences were observed in blood pressure, pulse, and temperature before and after the implementation of home health care during the physical distancing period (p&lt;0.05). There was an increase in body mass index (23.29(5.59) vs. 23.78(7.53); p=0.001). Notably, significant differences were also found in COVID-19 exposure risk factors, personal risk factors, sleep patterns, and physical activity before and after home health care (p&lt;0.05). Furthermore, improvements were noted in self-efficacy, family social function, and the quality of life of the families after one month of home health care (p&lt;0.05).Conclusion: Home health care during physical distancing positively affected the physical and psychosocial aspects, self-efficacy, family social function, and quality of life of the families. Thus, the guidance and support offered through home health care should be further developed to help families navigate the “new normal” era of COVID-19.

Previous studies have focused on identifying risk factors for older adults receiving home healthcare services without considering vital signs. This may provide important information on deteriorating health conditions that may lead to hospitalization and/or emergency department (ED) visits. Thus, it is important to understand the relationship between vital signs and hospitalization and/or ED visits and critical vital sign points for mitigating the higher risks of hospitalization and/or ED visits. This secondary data analysis uses cross-sectional data from a large, urban home healthcare organization (n = 61,615). A generalized additive model was used to understand the nonlinear relationship between each vital sign and hospitalization and/or ED visits through three unadjusted and adjusted models, and to identify a critical vital sign point related to a higher risk of hospitalization and/or ED visits. A significant nonlinear relationship (effective degree of freedom >2.0) was found between systolic, diastolic blood pressure, heart rate, hospitalization, and/or ED visits. The critical inflection point for systolic blood pressure was 120.36 (SE 3.625, p < .001), diastolic blood pressure was 72.00 (SE 3.108, p < .001), and heart rate was 83.24 (SE 1.994, p = .052). Among all vital signs, the risk of hospitalization and/or ED visits sharply increased when an older adult's heart rate surpassed 83.24 bpm. Our findings reveal that vital signs may serve as a critical indicator of a patient's clinical condition, especially related to hospitalization and/or ED visit. Clinicians need to be cognizant of these critical thresholds for each vital sign and monitor any deviations from baseline to preempt adverse outcomes.

Efficacy of home health care in patients with peripheral vascular disease