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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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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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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Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI. Objective: The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement. Methods: A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage. Results: Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age. Conclusions: This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.
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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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Interview: Richard Vijverberg promoveerde op 31 januari 2022 aan de Vrije Universiteit op zijn proefschrift Care needs of children and adolescents in psychiatry. Steps towards personalized mental healthcare.
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The shift toward prevention and self-management in health hinges upon a massive realization of behavior change, which involves the use of virtual coaches. Increasing availability of data from mobile devices and techniques for real time analysis provide new opportunities for personalizing virtual coaches. We propose an architecture that takes advantage of those developments. We identify the required knowledge and methods to develop a flexible ecosystem for rapid prototyping of personalized virtual coaches.
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Living a sedentary lifestyle is one of the major causes of numerous health problems. To encourage employees to lead a less sedentary life, the Hanze University started a health promotion program. One of the interventions in the program was the use of an activity tracker to record participants' daily step count. The daily step count served as input for a fortnightly coaching session. In this paper, we investigate the possibility of automating part of the coaching procedure on physical activity by providing personalized feedback throughout the day on a participant's progress in achieving a personal step goal. The gathered step count data was used to train eight different machine learning algorithms to make hourly estimations of the probability of achieving a personalized, daily steps threshold. In 80% of the individual cases, the Random Forest algorithm was the best performing algorithm (mean accuracy = 0.93, range = 0.88–0.99, and mean F1-score = 0.90, range = 0.87–0.94). To demonstrate the practical usefulness of these models, we developed a proof-of-concept Web application that provides personalized feedback about whether a participant is expected to reach his or her daily threshold. We argue that the use of machine learning could become an invaluable asset in the process of automated personalized coaching. The individualized algorithms allow for predicting physical activity during the day and provides the possibility to intervene in time.
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Abstract Background: Approximately one-third of all patients with schizophrenia are treatment resistant. Worldwide, undertreatment with clozapine and other effective treatment options exist for people with treatment-resistant schizophrenia (TRS). In this respect, it appears that regular health care models do not optimally fit this patient group. The Collaborative Care (CC) model has proven to be effective for patients with severe mental illness, both in primary care and in specialized mental health care facilities. The key principles of the CC model are that both patients and informal caregivers are part of the treatment team, that a structured treatment plan is put in place with planned evaluations by the team, and that the treatment approach is multidisciplinary in nature and uses evidence-based interventions. We developed a tailored CC program for patients with TRS. Objective: In this paper, we provide an overview of the research design for a potential study that seeks to gain insight into both the process of implementation and the preliminary effects of the CC program for patients with TRS. Moreover, we aim to gain insight into the experiences of professionals, patients, and informal caregivers with the program. Methods: This study will be underpinned by a multiple case study design (N=20) that uses a mixed methods approach. These case studies will focus on an Early Psychosis Intervention Team and 2 Flexible Assertive Community treatment teams in the Netherlands. Data will be collected from patient records as well as through questionnaires, individual interviews, and focus groups. Patient recruitment commenced from October 2020. Results: Recruitment of participants commenced from October 2020, with the aim of enrolling 20 patients over 2 years. Data collection will be completed by the end of 2023, and the results will be published once all data are available for reporting. Conclusions: The research design, framed within the process of developing and testing innovative interventions, is discussed in line with the aims of the study. The limitations in clinical practice and specific consequences of this study are explained.
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