Background: The COVID-19 pandemic taught us how to rethink care delivery. It catalyzed creative solutions to amplify the potential of personnel and facilities. This paper presents and evaluates a promptly introduced triaging solution that evolved into a tool to tackle the ever-growing waiting lists at an academic ophthalmology department, the TeleTriageTeam (TTT). A team of undergraduate optometry students, tutor optometrists, and ophthalmologists collaborate to maintain continuity of eye care. In this ongoing project, we combine innovative interprofessional task allocation, teaching, and remote care delivery. Objective: In this paper, we described a novel approach, the TTT; reported its clinical effectiveness and impact on waiting lists; and discussed its transformation to a sustainable method for delivering remote eye care. Methods: Real-world clinical data of all patients assessed by the TTT between April 16, 2020, and December 31, 2021, are covered in this paper. Business data on waiting lists and patient portal access were collected from the capacity management team and IT department of our hospital. Interim analyses were performed at different time points during the project, and this study presents a synthesis of these analyses. Results: A total of 3658 cases were assessed by the TTT. For approximately half (1789/3658, 48.91%) of the assessed cases, an alternative to a conventional face-to-face consultation was found. The waiting lists that had built up during the first months of the pandemic diminished and have been stable since the end of 2020, even during periods of imposed lockdown restrictions and reduced capacity. Patient portal access decreased with age, and patients who were invited to perform a remote, web-based eye test at home were on average younger than patients who were not invited. Conclusions: Our promptly introduced approach to remotely review cases and prioritize urgency has been successful in maintaining continuity of care and education throughout the pandemic and has evolved into a telemedicine service that is of great interest for future purposes, especially in the routine follow-up of patients with chronic diseases. TTT appears to be a potentially preferred practice in other clinics and medical specialties. The paradox is that judicious clinical decision-making based on remotely collected data is possible, only if we as caregivers are willing to change our routines and cognitions regarding face-to-face care delivery.
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Background: Follow‑up of curatively treated primary breast cancer patients consists of surveillance and aftercare and is currently mostly the same for all patients. A more personalized approach, based on patients’ individual risk of recurrence and personal needs and preferences, may reduce patient burden and reduce (healthcare) costs. The NABOR study will examine the (cost‑)effectiveness of personalized surveillance (PSP) and personalized aftercare plans (PAP) on patient‑reported cancer worry, self‑rated and overall quality of life and (cost‑)effectiveness. Methods: A prospective multicenter multiple interrupted time series (MITs) design is being used. In this design, 10 participating hospitals will be observed for a period of eighteen months, while they ‑stepwise‑ will transit from care as usual to PSPs and PAPs. The PSP contains decisions on the surveillance trajectory based on individual risks and needs, assessed with the ‘Breast Cancer Surveillance Decision Aid’ including the INFLUENCE prediction tool. The PAP contains decisions on the aftercare trajectory based on individual needs and preferences and available care resources, which decision‑making is supported by a patient decision aid. Patients are non‑metastasized female primary breast cancer patients (N= 1040) who are curatively treated and start follow‑up care. Patient reported outcomes will be measured at five points in time during two years of follow‑up care (starting about one year after treatment and every six months thereafter). In addition, data on diagnostics and hospital visits from patients’ Electronical Health Records (EHR) will be gathered. Primary outcomes are patient‑reported cancer worry (Cancer Worry Scale) and over‑all quality of life (as assessed with EQ‑VAS score). Secondary outcomes include health care costs and resource use, health‑related quality of life (as measured with EQ5D‑5L/SF‑12/EORTC‑QLQ‑C30), risk perception, shared decision‑making, patient satisfaction, societal participation, and cost‑effectiveness. Next, the uptake and appreciation of personalized plans and patients’ experiences of their decision‑making process will be evaluated. Discussion: This study will contribute to insight in the (cost‑)effectiveness of personalized follow‑up care and contributes to development of uniform evidence‑based guidelines, stimulating sustainable implementation of personalized surveillance and aftercare plans. Trial registration: Study sponsor: ZonMw. Retrospectively registered at ClinicalTrials.gov (2023), ID: NCT05975437.
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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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Alcohol use disorder (AUD) is a major problem. In the USA alone there are 15 million people with an AUD and more than 950,000 Dutch people drink excessively. Worldwide, 3-8% of all deaths and 5% of all illnesses and injuries are attributable to AUD. Care faces challenges. For example, more than half of AUD patients relapse within a year of treatment. A solution for this is the use of Cue-Exposure-Therapy (CET). Clients are exposed to triggers through objects, people and environments that arouse craving. Virtual Reality (VRET) is used to experience these triggers in a realistic, safe, and personalized way. In this way, coping skills are trained to counteract alcohol cravings. The effectiveness of VRET has been (clinically) proven. However, the advent of AR technologies raises the question of exploring possibilities of Augmented-Reality-Exposure-Therapy (ARET). ARET enjoys the same benefits as VRET (such as a realistic safe experience). But because AR integrates virtual components into the real environment, with the body visible, it presumably evokes a different type of experience. This may increase the ecological validity of CET in treatment. In addition, ARET is cheaper to develop (fewer virtual elements) and clients/clinics have easier access to AR (via smartphone/tablet). In addition, new AR glasses are being developed, which solve disadvantages such as a smartphone screen that is too small. Despite the demand from practitioners, ARET has never been developed and researched around addiction. In this project, the first ARET prototype is developed around AUD in the treatment of alcohol addiction. The prototype is being developed based on Volumetric-Captured-Digital-Humans and made accessible for AR glasses, tablets and smartphones. The prototype will be based on RECOVRY, a VRET around AUD developed by the consortium. A prototype test among (ex)AUD clients will provide insight into needs and points for improvement from patient and care provider and into the effect of ARET compared to VRET.
In this project, we explore how healthcare providers and the creative industry can collaborate to develop effective digital mental health interventions, particularly for survivors of sexual assault. Sexual assault victims face significant barriers to seeking professional help, including shame, self-blame, and fear of judgment. With over 100,000 cases reported annually in the Netherlands the need for accessible, stigma-free support is urgent. Digital interventions, such as chatbots, offer a promising solution by providing a safe, confidential, and cost-effective space for victims to share their experiences before seeking professional care. However, existing commercial AI chatbots remain unsuitable for complex mental health support. While widely used for general health inquiries and basic therapy, they lack the human qualities essential for empathetic conversations. Additionally, training AI for this sensitive context is challenging due to limited caregiver-patient conversation data. A key concern raised by professionals worldwide is the risk of AI-driven chatbots being misused as therapy substitutes. Without proper safeguards, they may offer inappropriate responses, potentially harming users. This highlights the urgent need for strict design guidelines, robust safety measures, and comprehensive oversight in AI-based mental health solutions. To address these challenges, this project brings together experts from healthcare and design fields—especially conversation designers—to explore the power of design in developing a trustworthy, user-centered chatbot experience tailored to survivors' needs. Through an iterative process of research, co-creation, prototyping, and evaluation, we aim to integrate safe and effective digital support into mental healthcare. Our overarching goal is to bridge the gap between digital healthcare and the creative sector, fostering long-term collaboration. By combining clinical expertise with design innovation, we seek to develop personalized tools that ethically and effectively support individuals with mental health problems.
In Nederland leven 300.000 mensen met de gevolgen van een beroerte. De voornaamste problemen na een beroerte worden veroorzaakt door het niet meer goed kunnen lopen en staan. Opnieuw leren lopen is dan ook een van de primaire doelstellingen gedurende het revalidatietraject. Na ontslag ondervindt 60% nog steeds rest verschijnselen. Daarnaast hebben mensen na een beroerte een hoge kans op terugval. Zo hebben ze een hoge kans op een recidief beroerte maar ook valincidenten hebben consequenties voor achteruitgang. Ongeveer 150.000 mensen in de chronische fase na beroerte valt minstens twee keer per jaar. Een val kan de oorzaak zijn van botbreuken, chronische invaliditeit en zelfs van sterfte. Het doel van dit project is het ontwikkelen en implementeren van een objectief meetsysteem binnen het klinisch revalidatietraject na een beroerte. Dit meetsysteem is gebaseerd op een bewegingssensor en is in staat de kwaliteit van lopen en balans betrouwbaar te meten. Door eenduidig, gestructureerd en objectief te meten verzamelen we normdata. Met deze normdata kunnen we aan het einde van dit project; de progressie monitoren, een prognose stellen, subgroepen maken en het risico op vallen voorspellen tijdens de revalidatie. Hiermee willen revalidatie na beroerte verder personaliseren en dus verbeteren. Dit project bestaat uit zes werkpakketten. Werkpakket 1 begint met de ontwikkeling van valide en betrouwbare meetopstelling welke goed haalbaar is in de revalidatie instellingen. In werkpakketten 2 tm 5 wordt normdata verzameld conform het meetprotocol van werkpakket 1. Werkpakket 2 en 4 richten zich op de ontwikkeling van het systeem en klinische waardevolle informatie zoals progressie, prognose en valrisico. Werkpakket 3 en 5 richten zich op het vergelijken en toevoegen van het systeem ten opzichte van de huidige meetinstrumenten. Werkpakket 6 helpt bij het omzetten van ruwe sensor data tot daadwerkelijke bruikbare informatie over kwaliteit van lopen en balans en gepersonaliseerde predictiemodellen.
