Daily Healthcare Practice Research Articles

The Integration of Artificial Intelligence in Physicians' Daily Practice for Diagnosis, Prediction, And Disease Management in the Arab World

Artificial intelligence (AI) is developing rapidly. Integrating AI into healthcare practices in the Arab world will transform diagnosis, prediction, and disease management. Today, countries such as Saudi Arabia and the United Arab Emirates (UAE) are at the forefront of AI adoption in healthcare, supported by strategic frameworks such as Saudi Arabia's Vision 2030 and the UAE National Artificial Intelligence Strategy 2031. However, adopting AI in daily healthcare practice on a large scale faces many obstacles that need to be overcome. Keywords: Artificial intelligence, AI, healthcare practice, diagnosis, prediction, and disease management, Arab world.

Maneuvering between cultures: The reception of hospice care in the Chinese medical community

The expansion of hospice care worldwide has been received differently by medical communities in different societies. Nonetheless, existing efforts to explain how culture affects the reception of hospice care are inadequate. On the basis of fieldwork conducted in Chinese medical institutions and care facilities between 2017 and 2022, this paper draws on a theoretical framework that distinguishes between declarative culture and nondeclarative culture at the personal level to explain the discrepancies between healthcare professionals’ beliefs regarding the value of hospice care and their daily healthcare practice. Moreover, this paper uses the concept of cultural scaffolding to demonstrate that the culture of hospice care and the culture of medical institutions are not separate, independent entities but rather evolve together to produce new and local forms of hospice care in the Chinese context. This analysis helps clarify the obstacles and opportunities associated with hospice care in China and contributes to existing research on the reception of hospice care worldwide.

An Interprofessional Faculty Development Program for Workplace-Based Learning.

Most faculty development programs in health professions education, pivotal in cultivating competent and effective teachers, focus on systematic, planned and formal learning opportunities. A large part of clinical teaching however, encompasses ad-hoc, informal and interprofessional workplace-based learning whereby individuals learn as part of everyday work activities. To fully harness the educational potential embedded in daily healthcare practices, prioritizing interprofessional faculty development for workplace-based learning is crucial. Utilizing the 'ADDIE' instructional design framework we developed, implemented and evaluated an interprofessional faculty development program for workplace-based learning. This program, encompassing seven formal training sessions each with a different theme and five individual workplace-based assignments, aimed to support clinical teachers in recognizing and optimizing informal learning. The pilot program (n = 10) and first two regular courses (n = 13 each) were evaluated using questionnaires containing Likert scale items and open textboxes for narrative comments. The quality and relevance of the program to the clinical work-place were highly appreciated. Additional valued elements included practical knowledge provided and tools for informal workplace-based teaching, the interprofessional aspect of the program and the workplace-based assignments. Since its development, the program has undergone minor revisions twice and has now become a successful interprofessional workplace-based alternative to existing faculty development programs. This faculty development program addresses the specific needs of healthcare professionals teaching in clinical settings. It stands out by prioritizing informal learning, fostering collaboration, and supporting integration of formal training into daily practice, ensuring practical application of learned knowledge and skills. Furthermore, it emphasizes interprofessional teaching and learning, enhancing workplace environments.

Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting.

The recent scientific literature abounds in proposals of seizure forecasting methods that exploit machine learning to automatically analyze electroencephalogram (EEG) signals. Deep learning algorithms seem to achieve a particularly remarkable performance, suggesting that the implementation of clinical devices for seizure prediction might be within reach. However, most of the research evaluated the robustness of automatic forecasting methods through randomized cross-validation techniques, while clinical applications require much more stringent validation based on patient-independent testing. In this study, we show that automatic seizure forecasting can be performed, to some extent, even on independent patients who have never been seen during the training phase, thanks to the implementation of a simple calibration pipeline that can fine-tune deep learning models, even on a single epileptic event recorded from a new patient. We evaluate our calibration procedure using two datasets containing EEG signals recorded from a large cohort of epileptic subjects, demonstrating that the forecast accuracy of deep learning methods can increase on average by more than 20%, and that performance improves systematically in all independent patients. We further show that our calibration procedure works best for deep learning models, but can also be successfully applied to machine learning algorithms based on engineered signal features. Although our method still requires at least one epileptic event per patient to calibrate the forecasting model, we conclude that focusing on realistic validation methods allows to more reliably compare different machine learning approaches for seizure prediction, enabling the implementation of robust and effective forecasting systems that can be used in daily healthcare practice.

Satisfaction and use of the didactic simulator for learning the nursing process: an observational study

IntroductionThe implementation of Information and Communication Technology (ICT) in daily healthcare practice has become standardized. In relation to education within the nursing degree, ICTs make it possible to carry out practical immersion training from the” classroom or from any other place with an Internet connection, as evidenced by circumstances that have occurred in recent years, such as the pandemic caused by COVID-19.ObjectiveDesign and assess a didactic simulation program for the training of the nursing process that promotes learning in the nursing careMethodologyThe methodological approach is quantitative and it is a descriptive cross-sectional study. The sampling method used was non-probabilistic by convenience.ResultsWhen observing the comparison of the averages of student satisfaction with respect to the didactic simulator, it is worth mentioning that all the items are above 2.80 on a score in which “0” is the minimum value and “5” the maximum value.The results of the use of the computer tool by the students, we highlight as significant data that all the items present an average equal to or lower than 3.04 out of 7, where “1” corresponds to a lot of use and “7” to little use.ConclusionThe implication of ICT in the teaching–learning process among Nursing Degree students, it is considered optimal. when analyzing the answers obtained in the items that refer to a higher ease in the execution of development of Care plans, a fundamental work in Nursing performance.

Training nurses to facilitate and implement CURA in palliative care institutions: development and evaluation of a blended learning program

BackgroundHealthcare professionals in palliative care are found to be confronted with moral challenges on a frequent basis. CURA is a low-threshold instrument for dialogical ethical reflection that was developed to deal with these challenges. A previous study identified the need of healthcare professionals to be trained to introduce CURA in their organization, initiate and facilitate reflections with CURA, and contribute to the implementation of CURA. The aim of this study was to develop and evaluate a training for professionals to become ‘CURA-ambassadors’.MethodsThe training was developed in a participatory way in two cycles. We trained 72 healthcare professionals. The training was evaluated by means of a questionnaire and six semi-structured interviews.ResultsThe study resulted in a blended learning training combining training sessions with an e-module and with practicing with organizing and facilitating CURA in daily healthcare practice. The main objectives of the training are to enable CURA-ambassadors to introduce CURA within their organization, initiate and facilitate ethical reflections using CURA, and contribute to the implementation of CURA. Participants were generally positive about the training program and the trainers. Technical difficulties related to the e-module were mentioned as main point of improvement.DiscussionThe training program can generate ownership, responsibility, and competency among CURA-ambassadors, which are essential foundations for implementing complex interventions in healthcare practice. The training program received positive evaluations shortly after completing the program. This study adds to our understanding of what is needed for healthcare professionals to use CURA, in order to support them in dealing with moral challenges and to foster their moral resilience. Further research is needed to assess whether participants experience the training as sufficient and effective when using and implementing CURA structurally in their organizations over a longer period of time.

Predicting non-improvement of symptoms in daily mental healthcare practice using routinely collected patient-level data: a machine learning approach.

Anxiety and mood disorders greatly affect the quality of life for individuals worldwide. A substantial proportion of patients do not sufficiently improve during evidence-based treatments in mental healthcare. It remains challenging to predict which patients will or will not benefit. Moreover, the limited research available on predictors of treatment outcomes comes from efficacy RCTs with strict selection criteria which may limit generalizability to a real-world context. The current study evaluates the performance of different machine learning (ML) models in predicting non-improvement in an observational sample of patients treated in routine specialized mental healthcare. In the current longitudinal exploratory prediction study diagnosis-related, sociodemographic, clinical and routinely collected patient-reported quantitative outcome measures were acquired during treatment as usual of 755 patients with a primary anxiety, depressive, obsessive compulsive or trauma-related disorder in a specialized outpatient mental healthcare center. ML algorithms were trained to predict non-response (< 0.5 standard deviation improvement) in symptomatic distress 6 months after baseline. Different models were trained, including models with and without early change scores in psychopathology and well-being and models with a trimmed set of predictor variables. Performance of trained models was evaluated in a hold-out sample (30%) as a proxy for unseen data. ML models without early change scores performed poorly in predicting six-month non-response in the hold-out sample with Area Under the Curves (AUCs) < 0.63. Including early change scores slightly improved the models' performance (AUC range: 0.68-0.73). Computationally-intensive ML models did not significantly outperform logistic regression (AUC: 0.69). Reduced prediction models performed similar to the full prediction models in both the models without (AUC: 0.58-0.62 vs. 0.58-0.63) and models with early change scores (AUC: 0.69-0.73 vs. 0.68-0.71). Across different ML algorithms, early change scores in psychopathology and well-being consistently emerged as important predictors for non-improvement. Accurately predicting treatment outcomes in a mental healthcare context remains challenging. While advanced ML algorithms offer flexibility, they showed limited additional value compared to traditional logistic regression in this study. The current study confirmed the importance of taking early change scores in both psychopathology and well-being into account for predicting longer-term outcomes in symptomatic distress.

Role-Perceptions of Dutch Spiritual Caregivers in Implementing Multidisciplinary Spiritual Care: A National Survey.

During the course of their disease, patients are, apart from suffering physical discomfort, also confronted with psychological, social, and spiritual challenges. However, healthcare professionals often lack the knowledge and skills to address the spiritual dimension and are in need of support for taking this responsibility. Spiritual caregivers are experts in spiritual care, but their contribution to the integration of this care by other healthcare professionals is largely unknown. The aim of this study was to investigate how Dutch spiritual caregivers view their role in increasing the integration of spiritual care in daily healthcare practice as provided by other healthcare professionals in the Netherlands, and how they address this role. An online survey was conducted from May until June 2021 among spiritual caregivers working in Dutch healthcare. Data were analysed using descriptive statistics. The majority of the 174 respondents answered that they already fulfil a role in the integration of spiritual care by, for example, providing education, coaching on the job, or participating in multidisciplinary consultation. However, the majority of respondents experienced barriers to their contribution, such as confusion of terminology and use of language while collaborating with other healthcare professionals and reluctance to share information. While spiritual caregivers realise having the potential to make important contributions to the further process of integration of spiritual care into the daily practice of other healthcare professionals, some practices and perceptions, especially from within their own discipline, may hamper this.

Software-related challenges in Swedish healthcare through the lens of incident reports: A desktop study.

To identify a subset of software issues occurring in daily Swedish healthcare practice and devise a set of local solutions to overcome the challenges. A sample of 46 incident reports was collected from one of Sweden's national incident reporting repositories, ranging from June 2019 to December 2021. The reports were first subjected to an algorithm to identify if they were health information technology-related incidents and were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the software-related incidents. The incidents associated with software issues were then subjected to thematic analysis, in which themes were extracted and presented under the category assigned by the existing framework used. Of 46 reports, 45 (with one exception) were included using the algorithm. Of 45 incidents, 31 software-related incidents were identified using the classification system. Six types of software issues were identified, including software functionality (n = 10), interface with other software systems or components (n = 10), system configuration (n = 7), interface with devices (n = 2), record migration (n = 1) and increased volume of transactions (n = 1). Each issue was further categorised into different themes; for example, software interface-related problems were grouped into 'two patients being active in the system simultaneously' (n = 6) and 'transfer of patient information' (n = 4). The study provided some insights into software issues and relevant consequences. A set of local solutions were devised to overcome the present challenges encountered in Swedish healthcare in their daily clinical practice. Systematic identification and characterisation of such software challenges should be a routine part of clinical practice for all major health information technology implementations.

Toward Successful Implementation of Artificial Intelligence in Health Care Practice: Protocol for a Research Program.

BackgroundThe uptake of artificial intelligence (AI) in health care is at an early stage. Recent studies have shown a lack of AI-specific implementation theories, models, or frameworks that could provide guidance for how to translate the potential of AI into daily health care practices. This protocol provides an outline for the first 5 years of a research program seeking to address this knowledge-practice gap through collaboration and co-design between researchers, health care professionals, patients, and industry stakeholders.ObjectiveThe first part of the program focuses on two specific objectives. The first objective is to develop a theoretically informed framework for AI implementation in health care that can be applied to facilitate such implementation in routine health care practice. The second objective is to carry out empirical AI implementation studies, guided by the framework for AI implementation, and to generate learning for enhanced knowledge and operational insights to guide further refinement of the framework. The second part of the program addresses a third objective, which is to apply the developed framework in clinical practice in order to develop regional capacity to provide the practical resources, competencies, and organizational structure required for AI implementation; however, this objective is beyond the scope of this protocol.MethodsThis research program will use a logic model to structure the development of a methodological framework for planning and evaluating implementation of AI systems in health care and to support capacity building for its use in practice. The logic model is divided into time-separated stages, with a focus on theory-driven and coproduced framework development. The activities are based on both knowledge development, using existing theory and literature reviews, and method development by means of co-design and empirical investigations. The activities will involve researchers, health care professionals, and other stakeholders to create a multi-perspective understanding.ResultsThe project started on July 1, 2021, with the Stage 1 activities, including model overview, literature reviews, stakeholder mapping, and impact cases; we will then proceed with Stage 2 activities. Stage 1 and 2 activities will continue until June 30, 2026.ConclusionsThere is a need to advance theory and empirical evidence on the implementation requirements of AI systems in health care, as well as an opportunity to bring together insights from research on the development, introduction, and evaluation of AI systems and existing knowledge from implementation research literature. Therefore, with this research program, we intend to build an understanding, using both theoretical and empirical approaches, of how the implementation of AI systems should be approached in order to increase the likelihood of successful and widespread application in clinical practice.International Registered Report Identifier (IRRID)PRR1-10.2196/34920

Safety and efficacy of Hemocare®LACT on breast milk production and prolactin levels in postpartum mothers: An open-label, placebo controlled, randomized trial

BackgroundBreast-feeding provides optimal nutrition along with immune support to newborns and infants and a host of lifelong health benefits to mother and child. Unfortunately, in daily health care practice, there are increasing numbers of reports on unsuccessful breastfeeding related problems. Galactagogues are substances that stimulate milk production. Hemocare®LACT, is a product of MMC Pharmaceuticals Ltd to enhance the milk secretion in lactating women. ObjectiveTo evaluate the safety and efficacy of Hemocare®LACT capsules on prolactin levels, infant body weight and hemoglobin in lactating mothers. MethodsOpen-label, placebo controlled, pilot, randomized controlled trial was conducted in a tertiary care hospital. A total of 72 eligible mothers were randomized to placebo or Hemocare®LACT in the ratio of 1:1. Serum prolactin, hemoglobin levels and infant weight were evaluated at baseline, 30th day, 60th day and in the 90th day post commencement of treatment. ResultsA significant difference in infant weight was found from baseline to 90th day in Hemocare®LACT group (p<0.01). Similarly, statistically significant difference was found in prolactin levels at 90th day when compared to baseline (p<0.05). Hemoglobin levels well maintained in Hemocare®LACT group. ConclusionHemocare®LACT capsules increased prolactin levels and infants body weight in lactating mothers when compared to placebo with good tolerability.

What Has Changed in the Order and Chronology of Outbreak in Temporary Dentition?

In daily health care practice, it has been observed that there is a notable difference in the age at which the teeth erupt in patients, who do not comply with the established canons. This has sparked interest in the subject. Objective: to determine the changes in the order and chronology of the outbreak in the primary dentition at a national and international level.

How to relate to dialysis patients' fatigue - perspectives of dialysis nurses and renal health professionals: A qualitative study

BackgroundAlthough fatigue among the dialysis population is known as a severe and debilitating health problem, this symptom is often under recognized and undertreated. ObjectiveThis qualitative study aimed to gain a better understanding of how dialysis nurses and renal health professionals perceive and address dialysis patient's fatigue in renal care practice. DesignWe conducted a qualitative descriptive study to explore how nurses and renal health professionals perceive and address dialysis patients’ fatigue in their daily health care practices. A constructivist grounded theory approach guided analysis and conceptualisation of findings. Setting(s)This study took place at 13 academic and regional settings across the Netherlands. The study was approved by the Medical Ethics Committee (2015.049), on behalf of VU University medical center in Amsterdam. ParticipantsTwenty-one renal health professionals of various disciplines took part in interviews: ten dialysis nurses, four nephrologists, two physician assistants, five medical social workers. MethodsSemi-structured interviews were conducted in order to gain in-depth insight into the perspectives of dialysis nurses and renal health professionals. An inductive thematic analysis provided insight into health professionals’ stances toward dialysis patients’ fatigue in light of their daily care context and practices. ResultsTwo main themes emerged; 1) ‘Fatigue in the background’: Shows there is strong focus on medical-technical aspects of the disease. All health professionals perceive fatigue as an intangible symptom that is difficult to address, and falls outside their scope of responsibility and competence. Communication about fatigue among professionals and with patients is limited, pushing fatigue further into the background. 2) ‘Vulnerabilities in the background’: Especially nurses and social workers signal the accumulating vulnerabilities of dialysis patients and associate these with fatigue (old age, multimorbidities, financial and social problems). Although the need for psychological support is acknowledged, multiple vulnerabilities increase the complexity and intensity of care, and further strengthens the medical-technical focus of care and treatment. ConclusionsThere is a need to enable renal health professionals to communicate about the complex nature of fatigue in renal patients and stimulate interdisciplinary exchange and shared responsibility. Dialysis nurses have frequent contact with patients during dialysis treatment and are the first to notice when patients’ fatigue increases and their overall condition deteriorates. They can play an important role to go beyond the technological imperative of care and understand the lived experiences of patients within their social contexts.

Conditions for collaboration between higher education and healthcare providers organising clinical placements

PurposeClinical placement is an important formalised student activity for linking healthcare education and healthcare practices. The purpose of this study is to investigate the organising of clinical placements by examining conditions for collaboration between higher education and healthcare organisations.Design/methodology/approachThe study is based on interviews with central actors at a university and two healthcare organisations with official duties of organising clinical placements.FindingsThe findings indicate that collaboration in the organising of clinical placements is a complex matter of interconnected actors in different organisational positions, at both strategic and operative levels. The university and the healthcare organisations approached the clinical placement with a shared commitment.Practical implicationsThe findings provide important guidance for improving collaboration in the organising of clinical placements. This may have an impact on how contextual conditions of the educational framing and daily healthcare practices are viewed and how the interdependency between the long-term strategic issues and the short-term needs of healthcare organisations is approached.Originality/valueThis research emphasises the need for careful consideration of the collaborative practices on an organisational level between higher education and healthcare organisations as different needs, motives and logics have to be considered.

Effectiveness of Educational Interventions to Increase Knowledge of Evidence-Based Practice Among Nurses and Physiotherapists in Primary Health Care: Protocol for a Systematic Review.

BackgroundThe implementation of evidence-based practice (EBP) in daily health care practice is strongly encouraged; it is widely recognized as a means to improve the quality and safety of health care for patients and reduce avoidable costs. Primary care nurses and physiotherapists face numerous challenges in trying to ensure that they deliver effective daily care. Broadly promoted educational interventions aim to increase the integration and implementation of EBP in their daily practice.ObjectiveThis systematic review will retrieve and evaluate publications examining the effectiveness of educational interventions to increase the integration and implementation of EBP among nurses, nurse practitioners, and physiotherapists active in primary care.MethodsWe will conduct a systematic review of published articles in relevant professional, scientific journals (from their start dates) and in the following electronic databases, from inception until October 31, 2020: Medline Ovid SP (from 1946), PubMed (NOT Medline[sb]; from 1996), Embase.com (from 1947), CINAHL Ebesco (from 1937), the Cochrane Central Register of Controlled Trials Wiley (from 1992), PsycINFO Ovid SP (from 1806), Web of Science Core collection (from 1900), PEDro (from 1999), the JBI Database of Systematic Reviews and Implementation Reports (from 1998), and the Trip Database (from 1997). We will use the predefined search terms of “evidence-based practice,” “nurses,” or “physiotherapists” and combinations with other terms, such as “educational interventions.” We will also conduct a hand search of the bibliographies of all the relevant articles and a search for unpublished studies using Google Scholar, the ProQuest Dissertations and Theses dissemination, Mednar, WorldCat, OpenGrey, and Grey Literature Report. We will consider publications in English, French, German, and Portuguese.ResultsThe electronic database searches were completed in October 2020. Retrieved articles are currently being screened, and the entire study is expected to be completed by March 2021.ConclusionsThis systematic review will provide specific knowledge about the effectiveness of educational interventions to increase the implementation and integration of EBP in the daily practice of nurses and physiotherapists providing primary care services. Its findings will inform us about the types and frequencies of the most successful educational interventions.Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42017077309; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77309International Registered Report Identifier (IRRID)DERR1-10.2196/17621

Effectiveness and cost-effectiveness of the Assessment of Burden of Chronic Conditions (ABCC) tool in patients with COPD, asthma, diabetes mellitus type 2 and heart failure: protocol for a pragmatic clustered quasi-experimental study

IntroductionThe number of people that have one or multiple condition(s) with a chronic course is rising, which consequently challenges healthcare systems. Healthcare geared to long-term care should focus on patient-centredness,...

COVID-19: the impetus for change-sustaining healthcare team communication in times of social distancing.

The COVID-19 pandemic has challenged existing healthcare systems and has made prevention of healthcare personnel exposure a high priority. Essential healthcare services, including multi-disciplinary team (MDT) meetings that make medical decisions, are expected to continue uninterrupted in this time of social distancing. There are a multitude of virtual platforms available to enable remote MDT meetings, and the pandemic has accelerated their arrival into daily healthcare practice. While we deal with a pandemic crisis, we have comprehensively reviewed and reported on the popular platforms and services available for this purpose. While each platform has its own unique features and drawbacks, it is essential to liaise with information technology departments and data governance teams to understand the optimal platforms for use within each healthcare setting.Level of evidence: Not ratable

Bayesian networks in healthcare: Distribution by medical condition.

Bayesian networks (BNs) have received increasing research attention that is not matched by adoption in practice and yet have potential to significantly benefit healthcare. Hitherto, research works have not investigated the types of medical conditions being modelled with BNs, nor whether there are any differences in how and why they are applied to different conditions. This research seeks to identify and quantify the range of medical conditions for which healthcare-related BN models have been proposed, and the differences in approach between the most common medical conditions to which they have been applied. We found that almost two-thirds of all healthcare BNs are focused on four conditions: cardiac, cancer, psychological and lung disorders. We believe there is a lack of understanding regarding how BNs work and what they are capable of, and that it is only with greater understanding and promotion that we may ever realise the full potential of BNs to effect positive change in daily healthcare practice.

Self-reported attitudes, knowledge and skills of using evidence-based medicine in daily health care practice: A national survey among students of medicine and health sciences in Hungary.

In order to map attitudes, knowledge and skills related to evidence-based medicine (EBM) in students of medical and health sciences faculties, we performed an online survey during the spring semester 2019 in all medical and health sciences faculties in Hungary. In total, 1080 students of medicine and 911 students of health sciences completed the online questionnaire. The attitude towards EBM was generally positive; however, only a small minority of students rated their EBM-related skills as advanced. There were large differences in the understanding of different EBM-related terms, with 'sample size' as the term with the highest (65%) and 'intention-to-treat analysis' with the lowest (7%) proportion of medical students being able to properly explain the meaning of the expression. Medical students who already participated in some EBM training rated their skills in searching and evaluating medical literature and their knowledge of EBM-related terms significantly better and had a more positive attitude towards using EBM in the practice than students without previous EBM training. EBM trained medical students were more likely to choose online journals (17.5% compared to 23.9%, p<0.05) and professional guidelines (15.4% compared to 6.1%, p<0.001) instead of printed books (33.6% compared to 52.6, p<0.001) as the main source of healthcare information retrieval and used Pubmed/Medline, Medscape and the Cochrane Library to a significant higher rate than students without any previous EBM training. Healthcare work experience (OR = 1.59; 95% CI = 1.01-2.52), conducting student research (OR = 2.02; 95% CI = 1.45-2.82) and upper year university students (OR = 1.65; 95% CI = 1.37-1.98) were other factors significantly influencing EBM-related knowledge. We conclude that the majority of students of medical and health sciences faculties are keen to acquire EBM-related knowledge and skills during their university studies. Significantly higher EBM-related knowledge and skills among EBM trained students underline the importance of targeted EBM education, while parallel increase of knowledge and skills with increasing number of education years highlight the importance of integrating EBM terminology and concepts also into the thematic of other courses.

Facilitating ethical, legal, and professional deliberations to resolve dilemmas in daily healthcare practice: A case of driver with breakthrough seizures

ObjectiveThe present study was conducted among pharmacy students to use an 8-step systematic approach to facilitate discussions, deliberations, and decision-making on what to do when facing a dilemma of a patient with epilepsy who drives while having breakthrough seizures. MethodsA hypothetical case was developed using the 12-tips for developing dilemma case-based assessments in health education. A mixed method was used in this study. A serial group discussions based on the nominal group technique (NGT) method were applied. A thorough review of the literature and interviews with key experts in the domain (n = 12) were conducted to obtain pertinent data to inform discussions, deliberations, and decision-making. The analytic hierarchy process (AHP) was used to pairwise compare countervailing arguments and alternative courses of action. ResultsIn this study, 3 nominal groups were held, and for each 3, discussion rounds were conducted. A total of 27 panelists took part in the nominal groups. Compared with other alternative courses of action, significantly higher weight scores (p-value < 0.001) were given to the course action, “the pharmacist could counsel/educate the patient on the dangers/risks of driving while experiencing breakthrough seizures, inform the patient to refrain from driving in this period, and make a shared decision with the patient to refrain from driving in this period and inform the state authorities”. ConclusionThis study demonstrates that the 8-step approach when combined with the AHP can be a handy method in facilitating decision-making while addressing and resolving ethical/legal/professional dilemmas in daily healthcare practice.