Background: The current COVID-19 pandemic requires sustainable behavior change to mitigate the impact of the virus. A phenomenon which has arisen in parallel with this pandemic is an infodemic-an overabundance of information, of which some is accurate and some is not, making it hard for people to find trustworthy and reliable guidance to make informed decisions. This infodemic has also been found to create distress and increase risks for mental health disorders, such as depression and anxiety. Aim: To propose practical guidelines for public health and risk communication that will enhance current recommendations and will cut through the infodemic, supporting accessible, reliable, actionable, and inclusive communication. The guidelines aim to support basic human psychological needs of autonomy, competence, and relatedness to support well-being and sustainable behavior change. Method: We applied the Self-Determination Theory (SDT) and concepts from psychology, philosophy and human computer interaction to better understand human behaviors and motivations and propose practical guidelines for public health communication focusing on well-being and sustainable behavior change. We then systematically searched the literature for research on health communication strategies during COVID-19 to discuss our proposed guidelines in light of the emerging literature. We illustrate the guidelines in a communication case study: wearing face-coverings. Findings: We propose five practical guidelines for public health and risk communication that will cut through the infodemic and support well-being and sustainable behavior change: (1) create an autonomy-supportive health care climate; (2) provide choice; (3) apply a bottom-up approach to communication; (4) create solidarity; (5) be transparent and acknowledge uncertainty.
BackgroundClinical decision support systems (DSS) aimed at supporting diagnosis are not widely used. This is mainly due to usability issues and lack of integration into clinical work and the electronic health record (EHR). In this study we examined the usability and acceptability of a diagnostic DSS prototype integrated with the EHR and in comparison with the EHR alone.MethodsThirty-four General Practitioners (GPs) consulted with 6 standardised patients (SPs) using only their EHR system (baseline session); on another day, they consulted with 6 different but matched for difficulty SPs, using the EHR with the integrated DSS prototype (DSS session). GPs were interviewed twice (at the end of each session), and completed the Post-Study System Usability Questionnaire at the end of the DSS session. The SPs completed the Consultation Satisfaction Questionnaire after each consultation.ResultsThe majority of GPs (74%) found the DSS useful: it helped them consider more diagnoses and ask more targeted questions. They considered three user interface features to be the most useful: (1) integration with the EHR; (2) suggested diagnoses to consider at the start of the consultation and; (3) the checklist of symptoms and signs in relation to each suggested diagnosis. There were also criticisms: half of the GPs felt that the DSS changed their consultation style, by requiring them to code symptoms and signs while interacting with the patient. SPs sometimes commented that GPs were looking at their computer more than at them; this comment was made more often in the DSS session (15%) than in the baseline session (3%). Nevertheless, SP ratings on the satisfaction questionnaire did not differ between the two sessions.ConclusionsTo use the DSS effectively, GPs would need to adapt their consultation style, so that they code more information during rather than at the end of the consultation. This presents a potential barrier to adoption. Training GPs to use the system in a patient-centred way, as well as improvement of the DSS interface itself, could facilitate coding. To enhance patient acceptability, patients should be informed about the potential of the DSS to improve diagnostic accuracy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-017-0477-6) contains supplementary material, which is available to authorized users.
BackgroundObservational and experimental studies of the diagnostic task have demonstrated the importance of the first hypotheses that come to mind for accurate diagnosis. A prototype decision support system (DSS) designed to support GPs’ first impressions has been integrated with a commercial electronic health record (EHR) system.AimTo evaluate the prototype DSS in a high-fidelity simulation.Design and settingWithin-participant design: 34 GPs consulted with six standardised patients (actors) using their usual EHR. On a different day, GPs used the EHR with the integrated DSS to consult with six other patients, matched for difficulty and counterbalanced.MethodEntering the reason for encounter triggered the DSS, which provided a patient-specific list of potential diagnoses, and supported coding of symptoms during the consultation. At each consultation, GPs recorded their diagnosis and management. At the end, they completed a usability questionnaire. The actors completed a satisfaction questionnaire after each consultation.ResultsThere was an 8–9% absolute improvement in diagnostic accuracy when the DSS was used. This improvement was significant (odds ratio [OR] 1.41, 95% confidence interval [CI] = 1.13 to 1.77, P<0.01). There was no associated increase of investigations ordered or consultation length. GPs coded significantly more data when using the DSS (mean 12.35 with the DSS versus 1.64 without), and were generally satisfied with its usability. Patient satisfaction ratings were the same for consultations with and without the DSS.ConclusionThe DSS prototype was successfully employed in simulated consultations of high fidelity, with no measurable influences on patient satisfaction. The substantially increased data coding can operate as motivation for future DSS adoption.
Patient access to their own electronic health records (EHRs) is likely to become an integral part of healthcare systems worldwide. It has the potential to decrease the healthcare provision costs, improve access to healthcare data, self-care, quality of care, and health and patient-centered outcomes. This systematic literature review is aimed at identifying the impact in terms of benefits and issues that have so far been demonstrated by providing patients access to their own EHRs, via providers' secure patient portals from primary healthcare centers and hospitals. Searches were conducted in PubMed, MEDLINE, CINHAL, and Google scholar. Over 2000 papers were screened and were filtered based on duplicates, then by reading the titles and finally based on their abstracts or full text. In total, 74 papers were retained, analyzed, and summarized. Papers were included if providing patient access to their own EHRs was the primary intervention used in the study and its impact or outcome was evaluated. The search technique used to identify relevant literature for this paper involved input from five experts. While findings from 54 of the 74 papers showed positive outcome or benefits of patient access to their EHRs via patient portals, 10 papers have highlighted concerns, 8 papers have highlighted both and 2 have highlighted absence of negative outcomes. The benefits range from re-assurance, reduced anxiety, positive impact on consultations, better doctor-patient relationship, increased awareness and adherence to medication, and improved patient outcomes (e.g., improving blood pressure and glycemic control in a range of study populations). In addition, patient access to their health information was found to improve self-reported levels of engagement or activation related to self-management, enhanced knowledge, and improve recovery scores, and organizational efficiencies in a tertiary level mental health care facility. However, three studies did not find any statistically significant effect of patient portals on health outcomes. The main concerns have been around security, privacy and confidentiality of the health records, and the anxiety it may cause amongst patients. This literature review identified some benefits, concerns, and attitudes demonstrated by providing patients' access to their own EHRs. This access is often part of government strategies when developing patient-centric self-management elements of a sustainable healthcare system. The findings of this review will give healthcare providers a framework to analyze the benefits offered by promoting patient access to EHRs and decide on the best approach for their own specialties and clinical setup. A robust cost-benefit evaluation of such initiatives along with its impact on major stakeholders within the healthcare system would be essential in KEYWORDS Electronic healthcare record; literature review; patient access; benefits; access to EHRs; patient portals CONTACT Archana Tapuria
Domestic “vaccine passports” are being implemented across the world as a way of increasing vaccinated people’s freedom of movement and to encourage vaccination. However, these vaccine passports may affect people’s vaccination decisions in unintended and undesirable ways. This cross-sectional study investigated whether people’s willingness and motivation to get vaccinated relate to their psychological needs (autonomy, competence and relatedness), and how vaccine passports might affect these needs. Across two countries and 1358 participants, we found that need frustration—particularly autonomy frustration—was associated with lower willingness to get vaccinated and with a shift from self-determined to external motivation. In Israel (a country with vaccine passports), people reported greater autonomy frustration than in the UK (a country without vaccine passports). Our findings suggest that control measures, such as domestic vaccine passports, may have detrimental effects on people’s autonomy, motivation, and willingness to get vaccinated. Policies should strive to achieve a highly vaccinated population by supporting individuals’ autonomous motivation to get vaccinated and using messages of autonomy and relatedness, rather than applying pressure and external controls.
Background Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.
BackgroundStroke, like many long-term conditions, tends to be managed in isolation of its associated risk factors and multimorbidity. With increasing access to clinical and research data there is the potential to combine data from a variety of sources to inform interventions to improve healthcare. A ‘Learning Health System’ (LHS) is an innovative model of care which transforms integrated data into knowledge to improve healthcare. The objective of this study is to develop a process of engaging stakeholders in the use of clinical and research data to co-produce potential solutions, informed by a LHS, to improve long-term care for stroke survivors with multimorbidity.MethodsWe used a stakeholder engagement study design informed by co-production principles to engage stakeholders, including service users, carers, general practitioners and other health and social care professionals, service managers, commissioners of services, policy makers, third sector representatives and researchers. Over a 10 month period we used a range of methods including stakeholder group meetings, focus groups, nominal group techniques (priority setting and consensus building) and interviews. Qualitative data were recorded, transcribed and analysed thematically.Results37 participants took part in the study. The concept of how data might drive intervention development was difficult to convey and understand. The engagement process led to four priority areas for needs for data and information being identified by stakeholders: 1) improving continuity of care; 2) improving management of mental health consequences; 3) better access to health and social care; and 4) targeting multiple risk factors. These priorities informed preliminary design interventions. The final choice of intervention was agreed by consensus, informed by consideration of the gap in evidence and local service provision, and availability of robust data. This shaped a co-produced decision support tool to improve secondary prevention after stroke for further development.ConclusionsStakeholder engagement to identify data-driven solutions is feasible but requires resources. While a number of potential interventions were identified, the final choice rested not just on stakeholder priorities but also on data availability. Further work is required to evaluate the impact and implementation of data-driven interventions for long-term stroke survivors.
BackgroundThis study examines the development of the connected health (CH) research landscape with a view to providing an overview of the existing CH research. The research field of CH has experienced rapid growth coinciding with increasing pressure on health care systems to become more proactive and patient centered.ObjectiveThis study aimed to assess the extent and coverage of the current body of knowledge in CH. In doing so, we sought to identify specific topics that have drawn the attention of CH researchers and to identify research gaps, in particular those offering opportunities for further interdisciplinary research.MethodsA systematic mapping study that combined scientific contributions from research in the disciplines of medicine, business, computer science, and engineering was used. Overall, seven classification criteria were used to analyze the papers, including publication source, publication year, research type, empirical type, contribution type, research topic, and the medical condition studied.ResultsThe search resulted in 208 papers that were analyzed by a multidisciplinary group of researchers. The results indicated a slow start for CH research but showed a more recent steady upswing since 2013. The majority of papers proposed health care solutions (77/208, 37.0%) or evaluated CH approaches (49/208, 23.5%). Case studies (59/208, 28.3%) and experiments (55/208, 26.4%) were the most popular forms of scientific validation used. Diabetes, cancer, multiple sclerosis, and heart conditions were among the most prevalent medical conditions studied.ConclusionsWe conclude that CH research has become an established field of research that has grown over the last five years. The results of this study indicate a focus on technology-driven research with a strong contribution from medicine, whereas the business aspects of CH have received less research attention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.