Home Healthcare System Research Articles

Balancing Staff Finishing Times vs. Minimizing Total Travel Distance in Home Healthcare Scheduling

Cost reduction and staff retention are important optimization objectives in home healthcare (HHC) systems. Home healthcare operators need to balance their objectives by optimizing resource use, service delivery and profits. Minimizing total travel distances to control costs is a common routing problem objective while minimizing total finishing time differences is a scheduling objective whose purpose is to enhance staff satisfaction. To optimize routing and scheduling, we propose mixed integer linear programming with a bi-objective function, which is a subset of the vehicle routing problem with time windows (VRPTWs). VRPTWs is a known NP-hard problem, and optimal solutions are very hard to obtain in practice. Metaheuristics offer an alternative solution to this type of problem. Our metaheuristic uses the simulated annealing algorithm and weighted sum approach to convert the problems to single-objective problems and is equipped with operators including swapping, moving, path exchange and ruin and recreate. The results show, firstly, that the algorithm can effectively find the Pareto front, and secondly, that minimizing total finishing time differences to balance the number of jobs per caretaker is an efficient way to tackle HHC scheduling. A statistical test shows that the algorithm can obtain the Pareto front with a lower number of weighted sum problems.

Using Bibliometric Analysis to Map the Impact of a Simulation Program's Published Scholarly Works.

Bibliometrics quantitatively evaluates the targeted literature sources and can help define research and scholarly publications' impact and demonstrate connections for authors, departments, or universities. This article presents a methodology for simulation programs to evaluate their influence in terms of both impact and scope of their published simulation-based healthcare scholarly output. Using the authors' home university and healthcare system as an example, the article outlines a methodology to map research and scholarly works networks within the systems, identify and map connections outside the system, and quantifiably score the overall impact of the simulation program's scholarly output using a common scoring metric, the h-index. This generates an objective measure of impact, rather than a subjective opinion of an organization's research and scholarly impact. The combination of an institutional h-index with mapping of simulation-based healthcare scholarly output provides a full, objective description of the institution's output and provides a benchmark for other simulation programs for comparison.

Teamwork and Nurse Care Coordination in Home Healthcare.

Home healthcare agencies provide interdisciplinary care to millions of individuals annually. Care is typically led by registered nurses who often determine additional disciplines need to be included in the plan of care. We found that, although persons living with dementia represent about 30% of the home healthcare population, data from our home healthcare system showed that over a 1-year period with 36,443 home care episodes, only 29.6% had one or more social worker visits. Recognizing Alzheimer's disease-related dementia as a terminal condition and shifting toward a palliative care approach can be a challenge in home healthcare where care is focused on restorative care or rehabilitative goals with a primary focus on improvement in condition. The goal of this article is to present insights into nurse-led care coordination and teamwork and provide implications for practice.

Impact of the Home-Based Medical Integrated Program on Health Outcomes and Medical Resource Utilization in Home Healthcare Patients in Taiwan.

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.

Home medical care and Home health care system and roles of the public health care in Korea

In the face of rapid aging in Korea, the demand for appropriate medical services for the elderly at home is increasing. This study investigates the current status of home medical care and Home health care in Korea based on the concept of Home-based primary care, and proposes strategies to implement home-care in public health centers and public hospitals that play a major role in the field of public health care.First of all, by presenting a conceptual framework for the current status of Korea’s home medical care and Home health care provision system, and described according to three financial resources: National Health Insurance(NHI), Long-Term Care Insurance(LTCI), and public health care. At the current level, the home health care systems are fragmented and they should be redesigned to improve the home care services.In order to implement home care in public health care institutions, a model centered on public health centers and public hospitals is proposed. Public health centers have various advantages, responsibility positions, and access to information, but they have working conditions and difficulties in providing incentives, and medical and nursing limitations. Public hospitals can provide a variety of services, but community access and insufficient knowledge are pointed out as disadvantages. Therefore, it is important to establish a cooperative system between the two institutions.Finally, we proposes the division and cooperation between public health centers and private medical institutions according to the level of service. Private medical institutions could be in charge of active treatment, medical services and skilled nursing cares. public health centers could perform monitoring and follow-up the patients. it is necessary to establish a coordinating system to cooperate the two parts of institutions.

Vehicle Routing Problem with Time Windows to Minimize Total Completion Time in Home Healthcare Systems

We propose a vehicle routing problem with time windows (VRPTW) with compatibility-matching constraints and total completion time as the objective function, with applications in home healthcare routing and scheduling. Mixed integer linear programming is provided with total completion time minimization as the objective function. The solution approach has two objectives, total completion time (primary objective) and total distance (secondary objective). A heuristic is proposed comprising three phases: initializing to find an initial feasible routing (inserting the procedure with a modified K-means algorithm), swapping and moving the procedure to find a local optimal routing, and shooting the procedure to move away from the local optimum. Proof of feasibility for the inserting procedure is provided to prevent unnecessary insertions. Phases 2 and 3 will be repeated as needed to ensure solution quality. Solving our model with the proposed heuristic algorithm increases the total distance by 90.00% but reduces the total completion time by 25.86%. To test our model and heuristic, we examined a system with 400 home-healthcare cases in Chiang Mai. The heuristic quickly solved the problem. When total completion time is minimized, some caretakers serve up to twice as many patients as their coworkers; when total distance is minimized, workload discrepancies can increase up to seven-fold.

Home health care facility location problem under demand uncertainty

The demand for home health care services is rapidly increasing due to the growing number of older people. The uncertainty surrounding this demand affects the network design processes and the performance of the home health care system in the long term. This study aims to address the issue of demand uncertainty in a home health care location problem. While decisions regarding the location of home health care facilities must be made immediately, the determination of distribution can be postponed until actual demand is observed. In such situations, minimax/maximin robust optimization methods are commonly employed to address uncertainty and facilitate informed decision-making, even in cases where there is limited information about future demand. However, these methods are often too conservative and may lead to suboptimal solutions. To tackle this issue, we propose a regret minimization method, which is reformulated as a robust model to overcome its intractability. Additionally, we propose a column-and-constraint generation algorithm to solve the robust optimization and regret minimization models. Finally, we conduct a comprehensive set of numerical experiments to compare the performance of the models in terms of solution quality and computational time. The results demonstrate that the regret minimization model enhances solution quality and consumes less computational time when reformulated.

Spider-inspired tunable mechanosensor for biomedical applications

The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal. However, biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment, allowing for a broad and enhanced detection. Here, we developed a Tunable, Ultrasensitive, Nature-inspired, Epidermal Sensor (TUNES) that the strain sensitivity was dramatically increased (GF ~30k) and the pressure sensitivity could be tuned (10–254 kPa−1) by preset membrane tension. The sensor adjusts the sensitivity to the pressure regime by preset tension, so it can measure a wide range (0.05 Pa–25 kPa) with the best performance: from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration. We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure (r = 0.96) and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning (accuracy 95%).

Home healthcare staff dimensioning problem for temporary caregivers: A matheuristic solution approach

Staff dimensioning, defined as determining the required numbers of caregivers with different types of skills, is a key decision for home healthcare systems. Home healthcare providers often use a combination of permanent and temporary (casual) caregivers. Determining the required number of temporary caregivers with different skill sets considering uncertainty and routing cost is the main objective of this study. To this end, we propose a two-stage stochastic programming model for the staff dimensioning problem for temporary caregivers, taking into account uncertainties in the required class of service, the required number of visits, and the required service time for each patient. Staff dimensioning decisions are defined in the first stage, and assignment with routing are positioned in the second stage of the model. To solve the problem, a two-phase matheuristic algorithm is developed where an initial solution is generated in the first phase by using an intermediate mathematical model and solving a series of Traveling Salesman Problems (TSPs), then a fix-and-optimize strategy is developed in the second phase to improve the obtained solution. The efficiency of the proposed matheuristic algorithm is examined by various test problems. The results highlight that the proposed model and solution method can be used by HHC providers to effectively utilize the option of recruitment of temporary caregivers in their resource planning considering inevitable uncertain parameters.

A sustainable and efficient home health care network design model under uncertainty

To cater to the increasing demands, particularly during diseases such as Covid-19, the design and planning of home health care systems is of significant importance. The current study proposes a multi-objective mixed-integer linear model for a home health care network in two stages; the first is the opening of efficient health centres, and the second is the routing and scheduling considering corporate social responsibility and efficiency. There are multiple objectives that we consider, including minimization of total costs and inefficiency considerations, and maximization of social aspects. A novel aspect of this study is the consideration of social responsibility, which includes employment opportunities and regional economic development, and efficiency in terms of time, energy, and mismanagement of budgets. To measure efficiency, an augmented version of the data envelopment analysis approach is incorporated into the proposed optimization model. Additionally, the TH approach is developed as an interactive fuzzy method to deal with the proposed multi-objective model. Within the HHC problem, costs, social factors, and service time are inherently uncertain, and hence, to solve this problem, a robust-fuzzy approach is proposed. The ensuing model is applied to a real case study of Kermanshah in Iran. Moreover, several problem instances motivated by real cases are generated with different characteristics to measure the performance of the proposed model and approach. The results show that decision-makers’ preferences play a key role in human resource planning and regional development. Furthermore, the results confirm the efficiency of the proposed approach in different instances within reasonable time frames.

The experiences of home care team members regarding the needs of family caregivers of heart failure patients in home health care services in Iran: A qualitative study.

Home healthcare guidelines emphasize the engagement of family caregivers of heart failure (HF) patients in patient care at home. Thus, this study was conducted with the aim to explore the deep experiences of home care team members regarding the needs of family caregivers of HF patients in home healthcare services in Iran. The present qualitative study was performed with a conventional content analysis approach. Data were collected through in-depth, semi-structured interviews with 23 participants who were recruited through purposive sampling. The Data were analyzed using the Graneheim and Lundman method for conventional content analysis in MAXQDA Software. The participants included 14 women and 9 men with the mean age of 46.21 ± 11.44 years. After analyzing the interviews, 3 main categories and 15 subcategories were extracted. The main categories were "family caregiver's unmet needs" (with 5 subcategories), "Empowering Informal Caregivers" (with 3 subcategories), and "access to a standard home healthcare system" (with 7 subcategories). Deep understanding of the needs of family caregivers of HF patients in home health care services increases the quality of services, the quality of life (QOL) of the family, and prevents patients' hospital readmissions. Moreover, it will contribute to our next project of the home healthcare guideline for HF patients in the health care system of Iran. Identifying the training needs of caregivers within the home health care services has an important role in the designing of education strategies in policy making programs at the level of the Ministry of Health or planning at lower levels of the health network.

Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System

This work involves a heuristic for solving vehicle routing problems with time windows (VRPTW) with general compatibility-matching between customer/patient and server/caretaker constraints to capture the nature of systems such as caretakers’ home visiting systems or home healthcare (HHC) systems. Since any variation of VRPTW is more complicated than regular VRP, a specific, custom-made heuristic is needed to solve the problem. The heuristic proposed in this work is an efficient hybrid of a novice Local Search (LS), Ruin and Recreate procedure (R&amp;R) and Particle Swarm Optimization (PSO). The proposed LS acts as the initial solution finder as well as the engine for finding a feasible/local optimum. While PSO helps in moving from current best solution to the next best solution, the R&amp;R part allows the solution to be over-optimized and LS moves the solution back on the feasible side. To test our heuristic, we solved 56 benchmark instances of 25, 50, and 100 customers and found that our heuristics can find 52, 21, and 18 optimal cases, respectively. To further investigate the proficiency of our heuristic, we modified the benchmark instances to include compatibility constraints. The results show that our heuristic can reach the optimal solutions in 5 out of 56 instances.

The Risk and The Prevalence of Malnutrition in Elderly Home-care Patients

Objective: The elderly are more susceptible to undernourishment, and those receiving home-care services have a higher prevalence of malnutrition. The study aimed to determine the prevalence of the community-dwelling elderly with malnutrition and those at risk of malnutrition enrolled in the home healthcare system. Method: A cross-sectional, descriptive study was conducted using the Mini-Nutritional Assessment short-form among community-dwelling elderly home-care patients living in Adana, Turkey. Individuals the age of 65 and over and receiving home-care services were included. Patients were interviewed once at his or her residence individually, and on-site MNA questionnaires were completed. Results: Among the 321 patients included in the analysis, 126 were malnourished (39.25%), and 132 were at risk of malnutrition (41.12%). The mean MNA-SF was 8.28±3.36. There was a strong association between malnutrition and literacy, with a third of the study group found to be illiterate (n=108, 33.64%, p=0.001). Conclusion: The study showed that the majority of the patients were malnourished or at risk of malnutrition. Implementation of nutritional screening and interventions focusing on malnutrition might be required in home-care services.

The Inauguration of the Journal of Eastern Health Care: a Regional Forum to Share Public Health Science

We are delighted to launch the inaugural issue of our new online publication, Eastern Journal of Healthcare (EJHC). EJHC aims to empower local researchers from developing and emerging countries in Middle, Eastern, Southern and Southeast Asia and offer an avenue for publication of studies that both matter to their local contexts and inform international readers. EJHC will enable researchers from these countries to publish researches on priority topics for their home countries and healthcare systems, even though these researches may be perceived as of less interest or relevance to non-Eastern/developed countries.

Calcium-Modified Silk Patch as a Next-Generation Ultrasound Coupling Medium.

There is an increasing interest in developing next-generation wearable ultrasound patch systems because of their wide range of applications, such as home healthcare systems and continuous monitoring systems for physiological conditions. A wearable ultrasound patch system requires a stable interface to the skin, an ultrasound coupling medium, a flexible transducer array, and miniaturized operating circuitries. In this study, we proposed a patch composed of calcium (Ca)-modified silk, which serves as both a stable interface and a coupling medium for ultrasound transducer arrays. The Ca-modified silk patch provided not only a stable and conformal interface between the epidermal ultrasound transducer and human skin with high adhesion but also offered acoustic impedance close to that of human skin. The Ca-modified silk patch was flexible and stretchable (∼400% strain) and could be attached to various materials. In addition, because the acoustic impedance of the Ca-modified silk patch was 2.15 MRayl, which was similar to that of human skin (1.99 MRayl), the ultrasound transmission loss of the proposed patch was relatively low (∼0.002 dB). We also verified the use of the Ca-modified silk patch in various ultrasound applications, including ultrasound imaging, ultrasound heating, and transcranial ultrasound stimulation for neuromodulation. The comparable performance of the Ca-modified patch to that of a commercial ultrasound gel and its durability against various environmental conditions confirmed that the Ca-modified silk patch could be a promising candidate as a coupling medium for next-generation ultrasound patch systems.

Insights and decision support for home health care services in times of disasters

Home health care (HHC) services are of vital importance for the health care system of many countries. Further increases in their demand must be expected and with it grows the need to sustain these services in times of disasters. Existing risk assessment tools and guides support HHC service providers to secure their services. However, they do not provide insights on interdependencies of complex systems like HHC. Causal-Loop-Diagrams (CLDs) are generated to visualize the impacts of epidemics, blackouts, heatwaves, and floods on the HHC system. CLDs help to understand the system design as well as cascading effects. Additionally, they simplify the process of identifying points of action in order to mitigate the impacts of disasters. In a case study, the course of the COVID-19 pandemic and its effects on HHC in Austria in spring 2020 are shown. A decision support system (DSS) to support the daily scheduling of HHC nurses is presented and applied to numerically analyze the impacts of the COVID-19 pandemic, using real-world data from a HHC service provider in Vienna. The DSS is based on a Tabu Search metaheuristic that specifically aims to deal with the peculiarities of urban regions. Various transport modes are considered, including time-dependent public transport.

Translation, cross-cultural adaptation, and validation of the Danish version of the revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire: Version for older people with limited life expectancy.

Knowledge about patients' attitudes towards deprescribing is essential for optimizing medication use. The revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire is a 22-item self-report instrument capturing older patients' beliefs and attitudes towards deprescribing. To translate and cross-culturally adapt the rPATD questionnaire into Danish and subsequently validate it in a cohort of nursing home residents. The rPATD questionnaire was translated and cross-culturally adapted during five stages of forward and backward translation. The validation study included 162 Danish nursing home residents (median age 84 years; 67% women). Validity was assessed through exploratory factor analysis (structural validity) and hypothesis testing (construct validity), while reliability was assessed through internal consistency. Floor and ceiling effects were examined. The exploratory factor analysis revealed a 4-factor structure similar to the original rPATD questionnaire, with items loading into four factors related to level of involvement in medication use, perceived burden of taking medication, belief in appropriateness of using medication, and concerns about stopping medication. The questionnaire was adjusted to the Danish nursing home population and health care system by omission of two items, concerning medication expenses and inconvenience of taking medication, which resulted in a model with factor loadings ranging from 0.29 to 0.84 and only minor cross-loading. Construct validity correctly predicted 67% of the hypothesized correlations. Internal consistency of all factors was generally acceptable with Cronbach's α ranging from 0.67 to 0.78. No floor and ceiling effects were identified. Results suggest that the Danish modified model of the rPATD questionnaire generally has acceptable validity and reliability.

Exploring the challenges and needs of home caregivers of hemodialysis patients in the Philippines: A mixed methods study.

Although the importance of home caregivers of chronic kidney disease patients has been increasingly recognized, their perceived caregiving difficulties and requisites remain underexplored. This study investigated the challenges and needs of home caregivers of hemodialysis patients in the Philippines. We utilized a mixed-method (QUAN + qual), explanatory sequential design. Data were collected from July 2017 to May 2018 from 46 home caregivers of hemodialysis patients. A three-part researcher-made survey were developed from literature search, personal values and cultural context, while some items were generated from a standardized tool that measures caregiver infrastructure and needs of those caring from frail US veterans. The tool developed gathered the participants' profile, caregiving characteristics, and related needs. The tool was validated and pretested for reliability. Fifteen participants were also interviewed to explore caregiving challenges and needs. Descriptive and χ2 statistics were used for quantitative outcomes, while thematic analysis was employed for qualitative data. Participants provided moderate assistance to patients, spending an average of 10.65 h/day and 5.08 days/week in caregiving. The most difficult caregiving circumstances were having costly expenses (78.26%); missing work (50.00%); and experiencing negative feelings (47.83%), stress (43.48%), and physical difficulties (34.78%). They also had the lowest confidence in deciding when to contact health providers (x̅ = 3.31, SD = 0.94) and finding patient care services (x̅ = 2.93, SD = 1.08). Qualitative findings further revealed caregiving needs and challenges in cost management, physical and psychological health, assumption of multiple roles, lifestyle adjustment, and reinforcement of carer knowledge, skills, and attitudes. Supportive strategies are needed to address the challenges encountered by home caregivers of hemodialysis patients. Findings can be utilized in developing appropriate interventions for home caregivers in low-resource settings where home caregiving and healthcare system issues, such as lack of access to resources and social support, are prevalent.

A Hybrid Approach for Home Health Care Routing and Scheduling Using an Agent-Based Model

Home health care systems, as a growing economic system in the field of health systems, face various problems and issues such as routing, scheduling and allocation. Given that a growing number of home health care workers in health care systems around the world tend to work for themselves instead of hospitals or other health care institutions. As a result, centralized and one-factor models are not responsible for solving these problems. Therefore, this paper focuses on situations by designing an agent-based planning system that is simulated in a decentralized environment and using the Fuzzy C-Means clustering algorithm and the repetitive suggestion mechanism (Vickery) as a negotiation protocol focuses on situations that a home health care agency needs to schedule a home visit among a group of independent physicians. The goal of the home health care agency is to minimize the overall cost of the service by covering all patients by qualified physicians. The results of the implementation of the proposed algorithm for real geographical data in the city of Tehran in GAMS show that this framework achieves high efficiency of optimal solutions.

Stochastic joint homecare service and capacity planning with nested decomposition approaches

In this paper, we study a joint service authorization and capacity planning problem for the home health care (HHC) system with demand uncertainty. We formulate the problem as a two-stage stochastic programming with recourse which maximizes the expected total revenue. The service authorization and capacity planning are the mixed binary-and-continuous first stage decisions, and the service hour (resource) allocation is modeled as the second-stage decision which adapts to the demand realizations. The resulting sample average approximation problem (of the stochastic program) could be a large scaled mixed integer linear program. To solve the model in a more scalable fashion, we propose a supergradient-based nested decomposition algorithm that exploits the nice decomposable structure of the problem to cope with the binary and continuous variables separately. The proposed nested decomposition scheme consists of two-layer of decomposition, where the outer decomposition solves for the authorization decision (binaries) with the supergradient cuts and each supergradient can be computed iteratively in the inner decomposition scheme. The proposed nested decomposition algorithm is feasibility-cut-free and is guaranteed to reach the exact optimality in finite steps. Furthermore, we extend our stochastic HHC planning model to a more general framework of Conditional Value-at-Risk (CV@R), and by model transformation with variable change we show that the CV@R model can actually be reformulated in a structure that the proposed nested decomposition scheme can be applied almost directly. Finally, a comprehensive computational study is performed which demonstrates the effectiveness of our model and the performance of the algorithm.