eHealth education should be integrated into vocational training and continuous professional development programmes. In this opinion article, we aim to support organisers of Continuing Professional Development (CPD) and teachers delivering medical vocational training by providing recommendations for eHealth education. First, we describe what is required to help primary care professionals and trainees learn about eHealth. Second, we elaborate on how eHealth education might be provided
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Background and Objective: To develop a health care value framework for physical therapy primary health care organizations including a definition. Method: A scoping review was performed. First, relevant studies were identified in 4 databases (n = 74). Independent reviewers selected eligible studies. Numerical and thematic analyses were performed to draft a preliminary framework including a definition. Next, the feasibility of the framework and definition was explored by physical therapy primary health care organization experts. Results: Numerical and thematic data on health care quality and context-specific performance resulted in a health care value framework for physical therapy primary health care organizations—including a definition of health care value, namely “to continuously attain physical therapy primary health care organization-centered outcomes in coherence with patient- and stakeholder-centered outcomes, leveraged by an organization’s capacity for change.” Conclusion: Prior literature mainly discussed health care quality and context-specific performance for primary health care organizations separately. The current study met the need for a value-based framework, feasible for physical therapy primary health care organizations, which are for a large part micro or small. It also solves the omissions of incoherent literature and existing frameworks on continuous health care quality and context-specific performance. Future research is recommended on longitudinal exploration of the HV (health care value) framework.
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Background: The substitution of healthcare is a way to control rising healthcare costs. The Primary Care Plus (PC+) intervention of the Dutch ‘Blue Care’ pioneer site aims to achieve this feat by facilitating consultations with medical specialists in the primary care setting. One of the specialties involved is dermatology. This study explores referral decisions following dermatology care in PC+ and the influence of predictive patient and consultation characteristics on this decision. Methods: This retrospective study used clinical data of patients who received dermatology care in PC+ between January 2015 and March 2017. The referral decision following PC+, (i.e., referral back to the general practitioner (GP) or referral to outpatient hospital care) was the primary outcome. Stepwise logistic regression modelling was used to describe variations in the referral decisions following PC+, with patient age and gender, number of PC+ consultations, patient diagnosis and treatment specialist as the predicting factors. Results: A total of 2952 patients visited PC+ for dermatology care. Of those patients with a registered referral, 80.2% (N = 2254) were referred back to the GP, and 19.8% (N = 558) were referred to outpatient hospital care. In the multivariable model, only the treating specialist and patient’s diagnosis independently influenced the referral decisions following PC+. Conclusion: The aim of PC+ is to reduce the number of referrals to outpatient hospital care. According to the results, the treating specialist and patient diagnosis influence referral decisions. Therefore, the results of this study can be used to discuss and improve specialist and patient profiles for PC+ to further optimise the effectiveness of the initiative.
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In most countries, maternal and newborn care is fragmented and focused on identification and treatment of pathology that affects only the minority of women and babies. Recently, a framework for quality maternal and newborn care was developed, which encourages a system-level shift to provide skilled care for all.This care includes preventive and supportive care that works to strengthen women’s capabilities and focuses on promotion of normal reproductive processes while ensuring access to emergency treatment when needed. Midwifery care is pivotal in this framework, which contains several elements that resonate with the main dimensions of primary care. Primary health care is the first level of contact with the health system where most of the population’s curative and preventive health needs can be fulfilled as close as possible to where people live and work. In this paper, we argue that midwifery as described in the framework requires the application of a primary care philosophy for all childbearing women and infants. Evaluation of the implementation of the framework should therefore include tools to monitor the performance of primary midwifery care.
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Background: In recent years, the effectiveness and cost-effectiveness of digital health services for people with musculoskeletal conditions have increasingly been studied and show potential. Despite the potential of digital health services, their use in primary care is lagging. A thorough implementation is needed, including the development of implementation strategies that potentially improve the use of digital health services in primary care. The first step in designing implementation strategies that fit the local context is to gain insight into determinants that influence implementation for patients and health care professionals. Until now, no systematic overview has existed of barriers and facilitators influencing the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Objective: This systematic literature review aims to identify barriers and facilitators to the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Methods: PubMed, Embase, and CINAHL were searched for eligible qualitative and mixed methods studies up to March 2024. Methodological quality of the qualitative component of the included studies was assessed with the Mixed Methods Appraisal Tool. A framework synthesis of barriers and facilitators to implementation was conducted using the Consolidated Framework for Implementation Research (CFIR). All identified CFIR constructs were given a reliability rating (high, medium, or low) to assess the consistency of reporting across each construct. Results: Overall, 35 studies were included in the qualitative synthesis. Methodological quality was high in 34 studies and medium in 1 study. Barriers (–) of and facilitators (+) to implementation were identified in all 5 CFIR domains: “digital health characteristics” (ie, commercial neutral [+], privacy and safety [–], specificity [+], and good usability [+]), “outer setting” (ie, acceptance by stakeholders [+], lack of health care guidelines [–], and external financial incentives [–]), “inner setting” (ie, change of treatment routines [+ and –], information incongruence (–), and support from colleagues [+]), “characteristics of the healthcare professionals” (ie, health care professionals’ acceptance [+ and –] and job satisfaction [+ and –]), and the “implementation process” (involvement [+] and justification and delegation [–]). All identified constructs and subconstructs of the CFIR had a high reliability rating. Some identified determinants that influence implementation may be facilitators in certain cases, whereas in others, they may be barriers. Conclusions: Barriers and facilitators were identified across all 5 CFIR domains, suggesting that the implementation process can be complex and requires implementation strategies across all CFIR domains. Stakeholders, including digital health intervention developers, health care professionals, health care organizations, health policy makers, health care funders, and researchers, can consider the identified barriers and facilitators to design tailored implementation strategies after prioritization has been carried out in their local context
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Due to the ageing population, the prevalence of musculoskeletal disorders will continue to rise, as well as healthcare expenditure. To overcome these increasing expenditures, integration of orthopaedic care should be stimulated. The Primary Care Plus (PC+) intervention aimed to achieve this by facilitating collaboration between primary care and the hospital, in which specialised medical care is shifted to a primary care setting. The present study aims to evaluate the referral decision following orthopaedic care in PC+ and in particular to evaluate the influence of diagnostic tests on this decision. Therefore, retrospective monitoring data of patients visiting PC+ for orthopaedic care was used. Data was divided into two periods; P1 and P2. During P2, specialists in PC+ were able to request additional diagnostic tests (such as ultrasounds and MRIs). A total of 2,438 patients visiting PC+ for orthopaedic care were included in the analysis. The primary outcome was the referral decision following PC+ (back to the general practitioner (GP) or referral to outpatient hospital care). Independent variables were consultation- and patient-related predictors. To describe variations in the referral decision, logistic regression modelling was used. Results show that during P2, significantly more patients were referred back to their GP. Moreover, the multivariable analysis show a significant effect of patient age on the referral decision (OR 0.86, 95% CI = 0.81– 0.91) and a significant interaction was found between the treating specialist and the period (p = 0.015) and between patient’s diagnosis and the period (p < 0.001). Despite the significant impact of the possibility of requesting additional diagnostic tests in PC+, it is important to discuss the extent to which the availability of diagnostic tests fits within the vision of PC+. In addition, selecting appropriate profiles for specialists and patients for PC+ are necessary to further optimise the effectiveness and cost of care.
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Introduction: Primary care has a central role in integrating care within a health system. However, conceptual ambiguity regarding integrated care hampers a systematic understanding. This paper proposes a conceptual framework that combines the concepts of primary care and integrated care, in order to understand the complexity of integrated care. Methods: The search method involved a combination of electronic database searches, hand searches of reference lists (snowball method) and contacting researchers in the field. The process of synthesizing the literature was iterative, to relate the concepts of primary care and integrated care. First, we identified the general principles of primary care and integrated care. Second, we connected the dimensions of integrated care and the principles of primary care. Finally, to improve content validity we held several meetings with researchers in the field to develop and refine our conceptual framework. Results: The conceptual framework combines the functions of primary care with the dimensions of integrated care. Person-focused and population-based care serve as guiding principles for achieving integration across the care continuum. Integration plays complementary roles on the micro (clinical integration), meso (professional and organisational integration) and macro (system integration) level. Functional and normative integration ensure connectivity between the levels. Discussion: The presented conceptual framework is a first step to achieve a better understanding of the inter-relationships among the dimensions of integrated care from a primary care perspective.
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Background: The number of people with multiple chronic conditions demanding primary care services is increasing. To deal with the complex health care demands of these people, professionals from different disciplines collaborate. This study aims to explore influential factors regarding interprofessional collaboration related to care plan development in primary care. Methods: A qualitative study, including four semi-structured focus group interviews (n = 4). In total, a heterogeneous group of experts (n = 16) and health care professionals (n = 15) participated. Participants discussed viewpoints, barriers, and facilitators regarding interprofessional collaboration related to care plan development. The data were analysed by means of inductive content analysis. Results: The findings show a variety of factors influencing the interprofessional collaboration in developing a care plan. Factors can be divided into 5 key categories: (1) patient-related factors: active role, self-management, goals and wishes, membership of the team; (2) professional-related factors: individual competences, domain thinking, motivation; (3) interpersonal factors: language differences, knowing each other, trust and respect, and motivation; (4) organisational factors: structure, composition, time, shared vision, leadership and administrative support; and (5) external factors: education, culture, hierarchy, domain thinking, law and regulations, finance, technology and ICT. Conclusions: Improving interprofessional collaboration regarding care plan development calls for an integral approach including patient- and professional related factors, interpersonal, organisational, and external factors. Further, the leader of the team seems to play a key role in watching the patient perspective, organising and coordinating interprofessional collaborations, and guiding the team through developments. The results of this study can be used as input for developing tools and interventions targeted at executing and improving interprofessional collaboration related to care plan development.
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Purpose: The increasing number of cancer survivors has heightened demands on hospital-based follow-up care resources. To address this, involving general practitioners (GPs) in oncological follow-up is proposed. This study explores secondary care providers’ views on integrating GPs into follow-up care for curatively treated breast and colorectal cancer survivors. Methods: A qualitative exploratory study was conducted using semi-structured interviews with Dutch medical specialists and nurse practitioners. Interviews were recorded, transcribed verbatim, and analyzed using thematic analysis by two independent researchers. Results: Fifteen medical specialists and nine nurse practitioners participated. They identified barriers such as re-referral delays, inexperience to perform structured follow-up, and worries about the lack of oncological knowledge among GPs. Benefits included the GPs’ accessibility and their contextual knowledge. For future organization, they emphasized the need for hospital logistics changes, formal GP training, sufficient case-load, proper staffing, remuneration, and time allocation. They suggested that formal GP involvement should initially be implemented for frail older patients and for prevalent cancer types. Conclusions: The interviewed Dutch secondary care providers generally supported formal involvement of primary care in cancer follow-up. A well-organized shared-care model with defined roles and clear coordination, supported by individual patients, was considered essential. This approach requires logistics adaptation, resources, and training for GPs. Implications for cancer survivors: Integrating oncological follow-up into routine primary care through a shared-care model may lead to personalized, effective, and efficient care for survivors because of their long-term relationships with GPs.
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Rationale, aims and objective: Primary Care Plus (PC+) focuses on the substitution of hospital-based medical care to the primary care setting without moving hospital facilities. The aim of this study was to examine whether population health and experience of care in PC+ could be maintained. Therefore, health-related quality of life (HRQoL) and experienced quality of care from a patient perspective were compared between patients referred to PC+ and to hospital-based outpatient care (HBOC). Methods: This cohort study included patients from a Dutch region, visiting PC+ or HBOC between December 2014 and April 2018. With patient questionnaires (T0, T1 and T2), the HRQoL and experience of care were measured. One-to-two nearest neighbour calliper propensity score matching (PSM) was used to control for potential selection bias. Outcomes were compared using marginal linear models and Pearson chi-square tests. Results: One thousand one hundred thirteen PC+ patients were matched to 606 HBOC patients with well-balanced baseline characteristics (SMDs <0.1). Regarding HRQoL outcomes, no significant interaction terms between time and group were found (P > .05), indicating no difference in HRQoL development between the groups over time. Regarding experienced quality of care, no differences were found between PC+ and HBOC patients. Only travel time was significantly shorter in the HBOC group (P ≤ .001). Conclusion: Results show equal effects on HRQoL outcomes over time between the groups. Regarding experienced quality of care, only differences in travel time were found. Taken as a whole, population health and quality of care were maintained with PC+ and future research should focus more on cost-related outcomes.
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