Purpose: To describe nurses' support interventions for medication adherence, and patients' experiences and desired improvements with this care. Patients and methods: A two-phase study was performed, including an analysis of questionnaire data and conducted interviews with members of the care panel of the Netherlands Patients Federation. The questionnaire assessed 14 types of interventions, satisfaction (score 0-10) with received interventions, needs, experiences, and desired improvements in nurses' support. Interviews further explored experiences and improvements. Data were analyzed using descriptive statistics and a thematic analysis approach. Results: Fifty-nine participants completed the questionnaire, and 14 of the 59 participants were interviewed. The satisfaction score for interventions was 7.9 (IQR 7-9). The most common interventions were: "noticing when I don't take medication as prescribed" (n = 35), "helping me to find solutions to overcome problems with using medications" (n = 32), "helping me with taking medication" (n = 32), and "explaining the importance of taking medication at the right moment" (n = 32). Fifteen participants missed ≥1 of the 14 interventions. Most mentioned the following: "regularly asking about potential problems with medication use" (33%), "regularly discussing whether using medication is going well" (29%), and "explaining the importance of taking medication at the right moment" (27%). Twenty-two participants experienced the following as positive: improved self-management of adequate medication taking, a professional patient-nurse relationship to discuss adherence problems, and nurses' proactive attitude to arrange practical support for medication use. Thirteen patients experienced the following as negative: insufficient timing of home visits, rushed appearance of nurses, and insufficient expertise about side effects and taking medication. Suggested improvements included performing home visits on time, more time for providing support in medication use, and more expertise about side effects and administering medication. Conclusion: Overall, participants were satisfied, and few participants wanted more interventions. Nurses' support improved participants' self-management of medication taking and enabled patients to discuss their adherence problems. Adequately timed home visits, more time for support, and accurate medication-related knowledge are desired.
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BACKGROUND: Patients are increasingly expected to take an active role in their own care. Participation in nursing documentation can support patients to take this active role since it provides opportunities to express care needs and preferences. Yet, patient participation in electronic nursing documentation is not self-evident.OBJECTIVE: To explore how home-care patients perceive their participation in electronic nursing documentation.METHODS: Semi-structured interviews were conducted with 21 home-care patients. Interview transcripts were analysed in an iterative process based on the principles of reflexive inductive thematic analysis.RESULTS: We identified a typology with four patient types: 'high need, high ability', 'high need, low ability', 'low need, high ability' and 'low need, low ability'. Several patients felt a need for participation because of their personal interest in health information. Others did not feel such a need since they trusted nurses to document the information that is important. Patients' ability to participate increased when they could read the documentation and when nurses helped them by talking about the documentation. Barriers to patients' ability to participate were having no electronic devices or lacking digital skills, a lack of support from nurses and the poor usability of electronic patient portals.CONCLUSION: Patient participation in electronic nursing documentation varies between patients since home-care patients differ in their need and ability to participate. Nurses should tailor their encouragement of patient participation to individual patients' needs and abilities. Furthermore, they should be aware of their own role and help patients to participate in the documentation.PATIENT OR PUBLIC CONTRIBUTION: Home-care patients were involved in the interviews.
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Background: Home care professionals regularly observe drug-related problems during home care provision. Problems related to the process of the medication therapy could involve discrepancies in medication prescriptions between the hospital discharge letter and the medication administration record lists (MARL) or insufficient drug delivery. The objective of this study is to determine the potential clinical consequences of medication process problems observed by home care professionals, since those consequences have not been assessed before. Methods: A retrospective descriptive study design was performed. An expert panel performed an assessment procedure on the clinical consequences of medication process problems. Such problems were reported by home care professionals during routine care (May 2016 until May 2017) using the eHOME system, which is a digital system developed to assist in the reporting and monitoring of drug-related problems. Using a three-point scale, an expert panel assessed the potential clinical consequences of those medication process problems among older home care patients (aged 65 years and over). Results: 309 medication process problems in 120 out of 451 patients were assessed for potential discomfort or clinical deterioration. The problems involved the following: medication discrepancies (new prescription not listed on the MARL [n = 69, 36.7%]; medication stopped by the prescriber but still listed on the MARL [n = 43, 22.9%]; discrepant time of intake [n = 25, 13.3%]; frequency [n = 24, 12.8%]; and dose [n = 21, 11.2%], therapeutic duplication listed on the MARL [n = 5, 2.6%]; and discrepant information on route of administration [n = 1, 0.5%]); an undelivered MARL [n = 103, 33.3%]; undelivered medication [n = 16, 5.2%]; and excessive medication delivery [n = 2, 0.7%]. Furthermore, 180 (58.2%) out of 309 medication process problems were assessed as having the potential for moderate or severe discomfort or clinical deterioration in patients. Conclusions: The majority of medication process problems may result in patient discomfort or clinical deterioration.
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Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
For English see below In dit project werkt het Lectoraat ICT-innovaties in de Zorg van hogeschool Windesheim samen met zorganisaties de ZorgZaak, De Stouwe, en IJsselheem en daarnaast Zorgcampus Noorderboog, Zorgtrainingscentrum Regio Zwolle, Patiëntenfederatie NPCF, VitaalThuis, ActiZ, Vilans, V&VN, Universiteit Twente en het Lectoraat Innoveren in de Ouderenzorg van Windesheim aan het in staat stellen van wijkverpleegkundigen om autonoom en doelmatig, op basis van klinisch redeneren, eHealth te indiceren en in te zetten bij cliënten. De aanleiding voor dit project wordt gevormd door de wijzigingen per 1 januari 2015 in de Zorgverzekeringswet. Wijkverpleegkundigen zijn sindsdien zelf verantwoordelijk voor de indicatiestelling en zorgtoewijzing voor verzorging en verpleging thuis: zij moeten bepalen welke zorg hun cliënten nodig hebben gezien hun individuele situaties, en hoe die zorg het best geleverd kan worden. Zorgverzekeraars leggen hierbij minimumeisen op, o.a. met betrekking tot de inzet van eHealth. Wijkverpleegkundigen hebben op dit moment echter niet of nauwelijks ervaring met het inzetten en toepassen van technologische toepassingen zoals eHealth. Vraagarticulatie leidde tot de volgende praktijkvraagstelling: 1. Hoe kunnen wijkverpleegkundigen worden voorzien in hun informatiebehoefte over eHealth? 2. Hoe kunnen wijkverpleegkundigen worden ondersteund in hun klinisch redeneren over het inzetten van eHealth bij hun cliënten? 3. Hoe kunnen wijkverpleegkundigen worden ondersteund bij het inzetten van eHealth in hun zorgproces? Het project levert hiertoe drie bijdragen: - De eerste bijdrage is een duurzaam geborgde keuzehulp (een app voor tablet of smartphone) waarmee wijkverpleegkundigen toegang hebben tot de benodigde informatie over eHealth-toepassingen en die aansluit bij de manier waarop wijkverpleegkundigen zorg indiceren (bijvoorbeeld door relaties te leggen tussen NIC-interventies en bijpassende eHealth-toepassingen). - Informatievoorziening is niet een afdoende antwoord op de handelingsverlegenheid van de wijkverpleegkundige omdat eHealth sterk in ontwikkeling is en blijft waardoor er altijd een discrepantie zal bestaan tussen de beschikbare en de benodigde informatie. . De tweede bijdrage van dit project is daarom kennis over (en inzicht in) het klinisch redeneren over de inzet van eHealth. Deze kennis wordt in het project doorvertaald naar een trainingsmodule die erop is gericht om het klinisch redeneren van wijkverpleegkundigen over het inzetten van eHealth en andere thuiszorgtechnologie bij hun cliënten te versterken. - De derde bijdrage van dit project omhelst inbedding van bovengenoemde resultaten in het verpleegkunde-onderwijs van onder meer Windesheim en in nascholingstrajecten voor wijkverpleegkundigen. Voor duurzame, bredere inbedding in het onderwijs wordt samengewerkt met regionale zorgonderwijsnetwerken. In this project the research group IT-innovations in Health Care of Windesheim University of Applied Sciences cooperates with care organisations de ZorgZaak, De Stouwe, and IJsselheem, and stakeholders Zorgcampus Noorderboog, Zorgtrainingscentrum Regio Zwolle, Patiëntenfederatie NPCF, VitaalThuis, ActiZ, Vilans, V&VN, University of Twente, and research group Innovation of Care of Older Adults of Windesheim to enable home care nurses to autonomously and adequately, based on clinical reasoning, allocate eHealth and implement it in patient care. The motivation behind this project lies in the alterations in the care insurance legislation per January 2015. Since then, home care nurses are responsible for the care allocation of all care at home: they determine which care their clients require, taking into account the individual situations, and how this care can best be delivered. Care insurance companies impose minimum requirements for this allocation of home care, among others concerning the implementation of eHealth. Home care nurses, however, have no or limited information about and experience with technical applications like eHealth. Articulation of the demands of home care nurses resulted in the following questions: 1. How can home care nurses be provided with information concerning eHealth? 2. How can home care nurses be supported in their clinical reasoning about the deployment of eHealth by their patients? 3. How can home care nurses be supported when deploying eHealth in their care process? This project contributes in three ways: " The first contribution is a sustainable selection tool (an app for tablet or smartphone) to be used by home care nurses to provide them with the required information about eHealth applications. This selection tool will work in accordance with how home care nurses allocate care, e.g. by relating NIC-interventions to matching eHealth applications. " Providing information is an insufficient, although necessary, answer to the demands of home care nurses because of continuously developing eHealth applications. Hence, the second contribution of this project is knowledge about (and insight in) the clinical reasoning about the deployment of eHealth. This knowledge will be converted into a training module aimed at strengthening the clinical reasoning about the deployment of eHealth by their patients. " The third contribution of this project concerns embedding the selection tool and the training module in regular education (among others at Windesheim) and in refresher courses for home care nurses. Cooperation with regional care education networks will ensure sustainable and broad embedding of both the selection tool and the training module.
The findings suggests that participation in music practices can significantly support caregivers' and nurses' contact with the people to whom they give care and the healthcare professionals' insights into the patients' and residents' personhood. Music can create experienced changes in the care environment through kairotic moments of connectivity and intimacy of the musical interaction. The music sessions support and reinforce the person-centred values of care delivery.The meaning of participatory music practices for the well-being and learning of healthcare professionals working with ageing patients and nursing home residents.
