Empowered patients and informal care-givers as partners?-a survey study of healthcare professionals' perceptions.

BACKGROUND: More knowledge is needed regarding the perceptions of healthcare professionals when encountering empowered patients and informal caregivers in clinical settings. This study aimed to investigate healthcare professionals' attitudes towards and experiences of working with empowered patients and informal caregivers, and perception of workplace support in these situations. METHODS: A multi-centre web survey was conducted using a non-probability sampling of both primary and specialized healthcare professionals across Sweden. A total of 279 healthcare professionals completed the survey. Data was analysed using descriptive statistics and Thematic analysis. RESULTS: Most respondents perceived empowered patients and informal caregivers as positive and had to some extent experience of learning new knowledge and skills from them. However, few respondents stated that these experiences were regularly followed-up at their workplace. Potentially negative consequences such as increased inequality and additional workload were, however, mentioned. Patients' engagement in the development of clinical workplaces was seen as positive by the respondents, but few had own experience of such engagement and considered it difficult to be achieved . CONCLUSION: Overall positive attitudes of healthcare professionals are a fundamental prerequisite to the transition of the healthcare system recognizing empowered patients and informal caregivers as partners.

User experience of self-reported computerized medical history taking for acute chest pain: The Clinical Expert Operating System Chest Pain Danderyd Study.

BACKGROUND AND OBJECTIVE: Chest pain is one of the most common complaints in emergency departments (EDs). Self-reported computerized history taking (CHT) programmes can be used for interpretation of the clinical significance of medical information coming directly from patients. The adoption of CHT in clinical practice depends on reactions and attitudes to the technology from patients and their belief that the technology will have benefits for their medical care. The study objective was to explore the user experience of the self-reported CHT programme Clinical Expert Operating System (CLEOS) in the setting of patients visiting an ED for acute chest pain. METHODS: This qualitative interview study is part of the ongoing CLEOS-Chest Pain Danderyd Study. A subset (n = 84) of the larger sample who had taken part in self-reported history taking during waiting times at the ED were contacted by telephone and n = 54 (64%) accepted participation. An interview guide with open-ended questions was used and the text was analysed using directed content analysis. RESULTS: The patients' experiences of the CLEOS programme were overall positive although some perceived it as extensive. The programme was well accepted and despite the busy environment, patients were highly motivated and deemed it helpful to make a diagnosis. Six categories of user experience emerged: The clinical context, The individual context, Time aspect, Acceptability of the programme, Usability of the programme and Perceptions of usefulness in a clinical setting. CONCLUSIONS: The programme was well accepted by most patients in the stressful environment at ED although some found it difficult to answer all the questions. Adjustments to the extent of an interview to better suit the context of the clinical use should be a future development of the programme. The findings suggest that CHT programmes can be integrated as a standard process for collecting self-reported medical history data in the ED setting.

Use of Self-Reported Computerized Medical History Taking for Acute Chest Pain in the Emergency Department - the Clinical Expert Operating System Chest Pain Danderyd Study (CLEOS-CPDS): Prospective Cohort Study.

BACKGROUND: Chest pain is one of the most common chief complaints in emergency departments (EDs). Collecting an adequate medical history is challenging but essential in order to use recommended risk scores such as the HEART score (based on history, electrocardiogram, age, risk factors, and troponin). Self-reported computerized history taking (CHT) is a novel method to collect structured medical history data directly from the patient through a digital device. CHT is rarely used in clinical practice, and there is a lack of evidence for utility in an acute setting. OBJECTIVE: This substudy of the Clinical Expert Operating System Chest Pain Danderyd Study (CLEOS-CPDS) aimed to evaluate whether patients with acute chest pain can interact effectively with CHT in the ED. METHODS: Prospective cohort study on self-reported medical histories collected from acute chest pain patients using a CHT program on a tablet. Clinically stable patients aged 18 years and older with a chief complaint of chest pain, fluency in Swedish, and a nondiagnostic electrocardiogram or serum markers for acute coronary syndrome were eligible for inclusion. Patients unable to carry out an interview with CHT (eg, inadequate eyesight, confusion or agitation) were excluded. Effectiveness was assessed as the proportion of patients completing the interview and the time required in order to collect a medical history sufficient for cardiovascular risk stratification according to HEART score. RESULTS: During 2017-2018, 500 participants were consecutively enrolled. The age and sex distribution (mean 54.3, SD 17.0 years; 213/500, 42.6% women) was similar to that of the general chest pain population (mean 57.5, SD 19.2 years; 49.6% women). Common reasons for noninclusion were language issues (182/1000, 18.2%), fatigue (158/1000, 15.8%), and inability to use a tablet (152/1000, 15.2%). Sufficient data to calculate HEART score were collected in 70.4% (352/500) of the patients. Key modules for chief complaint, cardiovascular history, and respiratory history were completed by 408 (81.6%), 339 (67.8%), and 291 (58.2%) of the 500 participants, respectively, while 148 (29.6%) completed the entire interview (in all 14 modules). Factors associated with completeness were age 18-69 years (all key modules: Ps<.001), male sex (cardiovascular: P=.04), active workers (all key modules: Ps<.005), not arriving by ambulance (chief complaint: P=.03; cardiovascular: P=.045), and ongoing chest pain (complete interview: P=.002). The median time to collect HEART score data was 23 (IQR 18-31) minutes and to complete an interview was 64 (IQR 53-77) minutes. The main reasons for discontinuing the interview prior to completion (n=352) were discharge from the ED (101, 28.7%) and tiredness (95, 27.0%). CONCLUSIONS: A majority of patients with acute chest pain can interact effectively with CHT on a tablet in the ED to provide sufficient data for risk stratification with a well-established risk score. The utility was somewhat lower in patients 70 years and older, in patients arriving by ambulance, and in patients without ongoing chest pain. Further studies are warranted to assess whether CHT can contribute to improved management and prognosis in this large patient group. TRIAL REGISTRATION: ClinicalTrials.gov NCT03439449; https://clinicaltrials.gov/ct2/show/NCT03439449. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-031871.

Influence of Human Factors on Cyber Security within Healthcare Organisations: A Systematic Review.

Background: Cybersecurity is increasingly becoming a prominent concern among healthcare providers in adopting digital technologies for improving the quality of care delivered to patients. The recent reports on cyber attacks, such as ransomware and WannaCry, have brought to life the destructive nature of such attacks upon healthcare. In complement to cyberattacks, which have been targeted against the vulnerabilities of information technology (IT) infrastructures, a new form of cyber attack aims to exploit human vulnerabilities; such attacks are categorised as social engineering attacks. Following an increase in the frequency and ingenuity of attacks launched against hospitals and clinical environments with the intention of causing service disruption, there is a strong need to study the level of awareness programmes and training activities offered to the staff by healthcare organisations. Objective: The objective of this systematic review is to identify commonly encountered factors that cybersecurity postures of a healthcare organisation, resulting from the ignorance of cyber threat to healthcare. The systematic review aims to consolidate the current literature being reported upon human behaviour resulting in security gaps that mitigate the cyber defence strategy adopted by healthcare organisations. Additionally, the paper also reviews the organisational risk assessment methodology implemented and the policies being adopted to strengthen cybersecurity. Methods: The topic of cybersecurity within healthcare and the clinical environment has attracted the interest of several researchers, resulting in a broad range of literature. The inclusion criteria for the articles in the review stem from the scope of the five research questions identified. To this end, we conducted seven search queries across three repositories, namely (i) PubMed®/MED-LINE; (ii) Cumulative Index to Nursing and Allied Health Literature (CINAHL); and (iii) Web of Science (WoS), using key words related to cybersecurity awareness, training, organisation risk assessment methodologies, policies and recommendations adopted as counter measures within health care. These were restricted to around the last 12 years. Results: A total of 70 articles were selected to be included in the review, which addresses the complexity of cybersecurity measures adopted within the healthcare and clinical environments. The articles included in the review highlight the evolving nature of cybersecurity threats stemming from exploiting IT infrastructures to more advanced attacks launched with the intent of exploiting human vulnerability. A steady increase in the literature on the threat of phishing attacks evidences the growing threat of social engineering attacks. As a countermeasure, through the review, we identified articles that provide methodologies resulting from case studies to promote cybersecurity awareness among stakeholders. The articles included highlight the need to adopt cyber hygiene practices among healthcare professionals while accessing social media platforms, which forms an ideal test bed for the attackers to gain insight into the life of healthcare professionals. Additionally, the review also includes articles that present strategies adopted by healthcare organisations in countering the impact of social engineering attacks. The evaluation of the cybersecurity risk assessment of an organisation is another key area of study reported in the literature that recommends the organisation of European and international standards in countering social engineering attacks. Lastly, the review includes articles reporting on national case studies with an overview of the economic and societal impact of service disruptions encountered due to cyberattacks. Discussion: One of the limitations of the review is the subjective ranking of the authors associated to the relevance of literature to each of the research questions identified. We also acknowledge the limited amount of literature that focuses on human factors of cybersecurity in health care in general; therefore, the search queries were formulated using well-established cybersecurity related topics categorised according to the threats, risk assessment and organisational strategies reported in the literature.

RedCom: A strategy for reduced metabolic modeling of complex microbial communities and its application for analyzing experimental datasets from anaerobic digestion.

Constraint-based modeling (CBM) is increasingly used to analyze the metabolism of complex microbial communities involved in ecology, biomedicine, and various biotechnological processes. While CBM is an established framework for studying the metabolism of single species with linear stoichiometric models, CBM of communities with balanced growth is more complicated, not only due to the larger size of the multi-species metabolic network but also because of the bilinear nature of the resulting community models. Moreover, the solution space of these community models often contains biologically unrealistic solutions, which, even with model linearization and under application of certain objective functions, cannot easily be excluded. Here we present RedCom, a new approach to build reduced community models in which the metabolisms of the participating organisms are represented by net conversions computed from the respective single-species networks. By discarding (single-species) net conversions that violate a minimality criterion in the exchange fluxes, it is ensured that unrealistic solutions in the community model are excluded where a species altruistically synthesizes large amounts of byproducts (instead of biomass) to fulfill the requirements of other species. We employed the RedCom approach for modeling communities of up to nine organisms involved in typical degradation steps of anaerobic digestion in biogas plants. Compared to full (bilinear and linearized) community models, we found that the reduced community models obtained with RedCom are not only much smaller but allow, also in the largest model with nine species, extensive calculations required to fully characterize the solution space and to reveal key properties of communities with maximum methane yield and production rates. Furthermore, the predictive power of the reduced community models is significantly larger because they predict much smaller ranges of feasible community compositions and exchange fluxes still being consistent with measurements obtained from enrichment cultures. For an enrichment culture for growth on ethanol, we also used metaproteomic data to further constrain the solution space of the community models. Both model and proteomic data indicated a dominance of acetoclastic methanogens (Methanosarcinales) and Desulfovibrionales being the least abundant group in this microbial community.

From Information Seekers to Innovators: Qualitative Analysis Describing Experiences of the Second Generation of E-Patients.

BACKGROUND: Current health care systems are rarely designed to meet the needs of people living with chronic conditions. However, some patients and informal caregivers are not waiting for the health care system to redesign itself. These individuals are sometimes referred to as e-patients. The first generation of e-patients used the internet for finding information and for communicating with peers. Compared with the first generation, the second generation of e-patients collects their own health data and appears to be more innovative. OBJECTIVE: The aim of this study was to describe the second generation of e-patients through exploration of their active engagement in their self-care and health care. METHODS: Semistructured interviews were conducted with 10 patients with chronic conditions and 5 informal caregivers. They were all recruited through a Web-based advertisement. Data were analyzed according to the framework analysis approach, using the 3 concepts of the self-determination theory-autonomy, relatedness, and competence-at the outset. RESULTS: Study participants were actively engaged in influencing their self-care and the health care system to improve their own health, as well as the health of others. This occurred at different levels, such as using their own experience when giving presentations and lectures to health care professionals and medical students, working as professional peers in clinical settings, performing self-tracking, contributing with innovations, and being active on social media. When interaction with health care providers was perceived as being insufficient, the participants sought support through their peers, which showed strong relatedness. Competence increased through the use of technology and learning experiences with peers. Their autonomy was important but was sometimes described as involuntary and to give up was not an option for them. CONCLUSIONS: Like the first generation of e-patients, the participants frequently searched for Web-based information. However, the second generation of e-patients also produce their own health data, which they learn from and share. They also engage in the innovation of digital tools to meet health-related needs. Utilizing technological developments comes naturally to the second generation of e-patients, even if the health care system is not prepared to support them under these new circumstances.

Accessing and sharing health information for post-discharge stroke care through a national health information exchange platform - a case study.

BACKGROUND: Patients and citizens need access to their health information to get a retrospective as well as a prospective view on their care and rehabilitation processes. However, patients' health information is stored in several health information systems and interoperability problems often hamper accessibility. In Sweden a national health information exchange (HIE) platform has been developed that enables information exchange between different health information systems. The aim of this study is to explore the opportunities and limitations of accessing and interacting with important health information through the Swedish national HIE platform. METHODS: A single case study approach was used for this study as an in-depth understanding of the subject was needed. A fictive patient case with a pseudo-name was created based on an interview with a stroke coordinator in Stockholm County. Information access through the national health information exchange platform and available service contracts and application programming interfaces were studied using different scenarios. RESULTS: Based on the scenarios created in this study, patients would be able to access some health related information from their electronic health records using the national health information exchange platform. However, there is necessary information which is not retrievable as it is either stored in electronic health records and eHealth services which are not connected to the national health information exchange platform or there is no service contract developed for these types of information. In addition, patients are not able to share information with healthcare professionals. CONCLUSION: The national Swedish HIE platform provides the building blocks needed to allow patients online access to their health information in a fragmented and distributed health system. However, more complex interaction scenarios allowing patients to communicate with their health care providers or to update their health related information are not yet supported. Therefore it is of great importance to involve patients throughout the design and evaluation of eHealth services on both national and local levels to ensure that their needs for interoperability and information exchange are met.

Man vs machine in emergency medicine - a study on the effects of manual and automatic vital sign documentation on data quality and perceived workload, using observational paired sample data and questionnaires.

BACKGROUND: Emergency medicine is characterized by a high patient flow where timely decisions are essential. Clinical decision support systems have the potential to assist in such decisions but will be dependent on the data quality in electronic health records which often is inadequate. This study explores the effect of automated documentation of vital signs on data quality and workload. METHODS: An observational study of 200 vital sign measurements was performed to evaluate the effects of manual vs automatic documentation on data quality. Data collection using questionnaires was performed to compare the workload on wards using manual or automatic documentation. RESULTS: In the automated documentation time to documentation was reduced by 6.1 min (0.6 min vs 7.7 min, p <  0.05) and completeness increased (98% vs 95%, p <  0.05). Regarding workflow temporal demands were lower in the automatic documentation workflow compared to the manual group (50 vs 23, p <  0.05). The same was true for frustration level (64 vs 33, p <  0.05). The experienced reduction in temporal demands was in line with the anticipated, whereas the experienced reduction in frustration was lower than the anticipated (27 vs 54, p < 0.05). DISCUSSION: The study shows that automatic documentation will improve the currency and the completeness of vital sign data in the Electronic Health Record while reducing workload regarding temporal demands and experienced frustration. The study also shows that these findings are in line with staff anticipations but indicates that the anticipations on the reduction of frustration may be exaggerated among the staff. The open-ended answers indicate that frustration focus will change from double documentation of vital signs to technical aspects of the automatic documentation system.

Applying openEHR's Guideline Definition Language to the SITS international stroke treatment registry: a European retrospective observational study.

BACKGROUND: Interoperability standards intend to standardise health information, clinical practice guidelines intend to standardise care procedures, and patient data registries are vital for monitoring quality of care and for clinical research. This study combines all three: it uses interoperability specifications to model guideline knowledge and applies the result to registry data. METHODS: We applied the openEHR Guideline Definition Language (GDL) to data from 18,400 European patients in the Safe Implementation of Treatments in Stroke (SITS) registry to retrospectively check their compliance with European recommendations for acute stroke treatment. RESULTS: Comparing compliance rates obtained with GDL to those obtained by conventional statistical data analysis yielded a complete match, suggesting that GDL technology is reliable for guideline compliance checking. CONCLUSIONS: The successful application of a standard guideline formalism to a large patient registry dataset is an important step toward widespread implementation of computer-interpretable guidelines in clinical practice and registry-based research. Application of the methodology gave important results on the evolution of stroke care in Europe, important both for quality of care monitoring and clinical research.

How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departments.

BACKGROUND: Vital sign data are important for clinical decision making in emergency care. Clinical Decision Support Systems (CDSS) have been advocated to increase patient safety and quality of care. However, the efficiency of CDSS depends on the quality of the underlying vital sign data. Therefore, possible factors affecting vital sign data quality need to be understood. This study aims to explore the factors affecting vital sign data quality in Swedish emergency departments and to determine in how far clinicians perceive vital sign data to be fit for use in clinical decision support systems. A further aim of the study is to provide recommendations on how to improve vital sign data quality in emergency departments. METHODS: Semi-structured interviews were conducted with sixteen physicians and nurses from nine hospitals and vital sign documentation templates were collected and analysed. Follow-up interviews and process observations were done at three of the hospitals to verify the results. Content analysis with constant comparison of the data was used to analyse and categorize the collected data. RESULTS: Factors related to care process and information technology were perceived to affect vital sign data quality. Despite electronic health records (EHRs) being available in all hospitals, these were not always used for vital sign documentation. Only four out of nine sites had a completely digitalized vital sign documentation flow and paper-based triage records were perceived to provide a better mobile workflow support than EHRs. Observed documentation practices resulted in low currency, completeness, and interoperability of the vital signs. To improve vital sign data quality, we propose to standardize the care process, improve the digital documentation support, provide workflow support, ensure interoperability and perform quality control. CONCLUSIONS: Vital sign data quality in Swedish emergency departments is currently not fit for use by CDSS. To address both technical and organisational challenges, we propose five steps for vital sign data quality improvement to be implemented in emergency care settings.

Post-discharge stroke patients' information needs as input to proposing patient-centred eHealth services.

BACKGROUND: Despite the potential of eHealth services to revolutionize the way healthcare and prevention is provided many applications developed for patients fail to deliver their promise. Therefore, the aim of this study is to use patient journey mapping to explore post-discharge stroke patients' information needs to propose eHealth services that meet their needs throughout their care and rehabilitation processes. METHODS: Three focus groups with younger (<65 years) and older (> = 65 years) stroke patients were performed. Content analysis was used to analyse the data. Stroke patients' information needs was explored using patient journey model. RESULTS: Four main events (discharge from hospital, discharge from rehab clinic, coming home, and clinical encounters) and two phases (at rehab clinic, at home) have been identified in patients' post-discharge journey. The main categories identified in this study indicate that patients not only need to have access to health related information about their care and rehabilitation processes but also practical guidance through healthcare and community services. Patients also have different information needs at different events and during different phases. Potential supportive eHealth services were suggested by the researchers considering different parts of the patients' journeys. CONCLUSIONS: Patient journey models and qualitative analysis of patients' information needs are powerful tools that can be used to improve healthcare from a patient perspective. As patients' understanding of their illness changes over time, their need of more flexible support throughout the care and rehabilitation processes increases. To design appropriate eHealth services that meet patients' information needs, it is imperative to understand the current care and rehabilitation processes and identify patients' information needs throughout their journey.

Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR's Guideline Definition Language.

BACKGROUND: Providing scalable clinical decision support (CDS) across institutions that use different electronic health record (EHR) systems has been a challenge for medical informatics researchers. The lack of commonly shared EHR models and terminology bindings has been recognised as a major barrier to sharing CDS content among different organisations. The openEHR Guideline Definition Language (GDL) expresses CDS content based on openEHR archetypes and can support any clinical terminologies or natural languages. Our aim was to explore in an experimental setting the practicability of GDL and its underlying archetype formalism. A further aim was to report on the artefacts produced by this new technological approach in this particular experiment. We modelled and automatically executed compliance checking rules from clinical practice guidelines for acute stroke care. METHODS: We extracted rules from the European clinical practice guidelines as well as from treatment contraindications for acute stroke care and represented them using GDL. Then we executed the rules retrospectively on 49 mock patient cases to check the cases' compliance with the guidelines, and manually validated the execution results. We used openEHR archetypes, GDL rules, the openEHR reference information model, reference terminologies and the Data Archetype Definition Language. We utilised the open-sourced GDL Editor for authoring GDL rules, the international archetype repository for reusing archetypes, the open-sourced Ocean Archetype Editor for authoring or modifying archetypes and the CDS Workbench for executing GDL rules on patient data. RESULTS: We successfully represented clinical rules about 14 out of 19 contraindications for thrombolysis and other aspects of acute stroke care with 80 GDL rules. These rules are based on 14 reused international archetypes (one of which was modified), 2 newly created archetypes and 51 terminology bindings (to three terminologies). Our manual compliance checks for 49 mock patients were a complete match versus the automated compliance results. CONCLUSIONS: Shareable guideline knowledge for use in automated retrospective checking of guideline compliance may be achievable using GDL. Whether the same GDL rules can be used for at-the-point-of-care CDS remains unknown.

User engagement with organizational mHealth stress management intervention - A mixed methods study.

Mobile health (mHealth) demonstrates great promise for providing effective and accessible interventions within an organizational context. Compared with traditional workplace interventions, mHealth solutions may be significantly more scalable and easier to standardize. However, inadequate user engagement is a major challenge with mHealth solutions that can negatively impact the potential benefits of an intervention. More research is needed to better understand how to ensure sufficient engagement, which is essential for designing and implementing effective interventions. To address this issue, this study employed a mixed methods approach to investigate what factors influence user engagement with an organizational mHealth intervention. Quantitative data were collected using surveys (n = 1267), and semi-structured interviews were conducted with a subset of participants (n = 17). Primary findings indicate that short and consistent interactions as well as user intention are key drivers of engagement. These results may inform future development of interventions to increase engagement and effectiveness.

Are medical history data fit for risk stratification of patients with chest pain in emergency care? Comparing data collected from patients using computerized history taking with data documented by physicians in the electronic health record in the CLEOS-CPDS prospective cohort study.

OBJECTIVE: In acute chest pain management, risk stratification tools, including medical history, are recommended. We compared the fraction of patients with sufficient clinical data obtained using computerized history taking software (CHT) versus physician-acquired medical history to calculate established risk scores and assessed the patient-by-patient agreement between these 2 ways of obtaining medical history information. MATERIALS AND METHODS: This was a prospective cohort study of clinically stable patients aged ≥ 18 years presenting to the emergency department (ED) at Danderyd University Hospital (Stockholm, Sweden) in 2017-2019 with acute chest pain and non-diagnostic ECG and serum markers. Medical histories were self-reported using CHT on a tablet. Observations on discrete variables in the risk scores were extracted from electronic health records (EHR) and the CHT database. The patient-by-patient agreement was described by Cohen's kappa statistics. RESULTS: Of the total 1000 patients included (mean age 55.3 ± 17.4 years; 54% women), HEART score, EDACS, and T-MACS could be calculated in 75%, 74%, and 83% by CHT and in 31%, 7%, and 25% by EHR, respectively. The agreement between CHT and EHR was slight to moderate (kappa 0.19-0.70) for chest pain characteristics and moderate to almost perfect (kappa 0.55-0.91) for risk factors. CONCLUSIONS: CHT can acquire and document data for chest pain risk stratification in most ED patients using established risk scores, achieving this goal for a substantially larger number of patients, as compared to EHR data. The agreement between CHT and physician-acquired history taking is high for traditional risk factors and lower for chest pain characteristics. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03439449.

Towards Accountable E-Health Policies in the Nordic Countries.

The Nordic Countries are seen as forerunners in the field of digital health technologies and national implementation has been guided by sector specific strategies for many years. In the context of new European legislation such as the European Health Data Space (EHDS), a review of the existing strategies is indicated. The objective of this policy analysis is to assess and compare the scope, ambitions and extent of accountability in national-level digital health policies in the Nordic countries. The scope of the policies from the five countries were largely centred around a) empowering and activating citizens; b) a shift towards prevention and digital first; c) supporting health operations; d) doing the groundwork; e) making health data more available in research and innovation workflows and f) supporting health personnel. Finland comes out as the most ambitious country with the aim to transform their health system by means of digitalisation. Both Finland and Iceland work towards prevention and the digital first ambition due to large populations in rural areas. These two countries also present the most accountable policies, meaning that their policy documents are the most transparent as to how they arrived at the conclusions and how they are to evaluate the achievements.

Citizens Access to Health Information in National Portals in the Nordic Countries.

National eHealth portals for citizens are available in the five Nordic countries. This study describes and compares the Nordic citizen portals and identifies variations in content access and functionality. The findings suggest that availability of information and services depend on the organisation of the health system, the connection to national health information exchange platforms and incentives for providing data and services.

Smart variant filtering - A blueprint solution for massively parallel sequencing-based variant analysis.

Massively parallel sequencing helps create new knowledge on genes, variants and their association with disease phenotype. This important technological advancement simultaneously makes clinical decision making, using genomic information for cancer patients, more complex. Currently, identifying actionable pathogenic variants with diagnostic, prognostic, or predictive impact requires substantial manual effort. Objective: The purpose is to design a solution for clinical diagnostics of lymphoma, specifically for systematic variant filtering and interpretation. Methods: A scoping review and demonstrations from specialists serve as a basis for a blueprint of a solution for massively parallel sequencing-based genetic diagnostics. Results: The solution uses machine learning methods to facilitate decision making in the diagnostic process. A validation round of interviews with specialists consolidated the blueprint and anchored it across all relevant expert disciplines. The scoping review identified four components of variant filtering solutions: algorithms and Artificial Intelligence (AI) applications, software, bioinformatics pipelines and variant filtering strategies. The blueprint describes the input, the AI model and the interface for dynamic browsing. Conclusion: An AI-augmented system is designed for predicting pathogenic variants. While such a system can be used to classify identified variants, diagnosticians should still evaluate the classification's accuracy, make corrections when necessary, and ultimately decide which variants are truly pathogenic.

Cathepsin D deficiency induces cytoskeletal changes and affects cell migration pathways in the brain.

Cathepsin D deficiency is a fatal neurodegenerative disease characterized by extreme loss of neurons and myelin. Our previous studies have demonstrated that structural and functional alterations in synapses are central to the disease pathogenesis. Therefore, we took a systematic approach to examine the synaptic proteome in cathepsin D knock-out mice, where the synaptic pathology resembles that of human patients. We applied quantitative mass spectrometry analysis on synaptosomal fractions isolated from cathepsin D knock-out and control mice at the age of 24 days. From the approximately 600 identified proteins, 43 were present in different amounts (P<0.05, measured in triple biological replicates) in cathepsin D knock-out mice compared to controls. We connected and bridged these 43 proteins using protein interaction data, and overlaid the network with brain specific gene expression information. Subsequently, we superimposed the network with Gene Ontology, pathway, phenotype and disease involvement, allowing construction of a dynamic, disease-protein centered network and prediction of functional modules. The measured changes in the protein levels, as well as some of the bioinformatically predicted ones, were confirmed by quantitative Western blotting or qualitative immunohistochemistry. This combined approach indicated alterations in distinct cellular entities, previously not associated with the disease, and including microtubule associated cytoskeleton and cell projection organization. Cell spreading and wound healing assays confirmed strongly compromised spatial orientation, associated with changes in distribution of focal adhesions and integrin assembly, in cathepsin D deficient cells. These changes might contribute to commencement of synaptic alterations and neuronal degeneration observed in cathepsin D deficiency.

Cis-regulatory underpinnings of human GLI3 expression in embryonic craniofacial structures and internal organs.

The zinc finger transcription factor Gli3 is an important mediator of Sonic hedgehog (Shh) signaling. During early embryonic development Gli3 participates in patterning and growth of the central nervous system, face, skeleton, limb, tooth and gut. Precise regulation of the temporal and spatial expression of Gli3 is crucial for the proper specification of these structures in mammals and other vertebrates. Previously we reported a set of human intronic cis-regulators controlling almost the entire known repertoire of endogenous Gli3 expression in mouse neural tube and limbs. However, the genetic underpinning of GLI3 expression in other embryonic domains such as craniofacial structures and internal organs remain elusive. Here we demonstrate in a transgenic mice assay the potential of a subset of human/fish conserved non-coding sequences (CNEs) residing within GLI3 intronic intervals to induce reporter gene expression at known regions of endogenous Gli3 transcription in embryonic domains other than central nervous system (CNS) and limbs. Highly specific reporter expression was observed in craniofacial structures, eye, gut, and genitourinary system. Moreover, the comparison of expression patterns directed by these intronic cis-acting regulatory elements in mouse and zebrafish embryos suggests that in accordance with sequence conservation, the target site specificity of a subset of these elements remains preserved among these two lineages. Taken together with our recent investigations, it is proposed here that during vertebrate evolution the Gli3 expression control acquired multiple, independently acting, intronic enhancers for spatiotemporal patterning of CNS, limbs, craniofacial structures and internal organs.

Evaluation of an Electronic Care and Rehabilitation Planning Tool With Stroke Survivors With Aphasia: Usability Study.

BACKGROUND: Patients with chronic illnesses with physical and cognitive disabilities, particularly stroke survivors with aphasia, are often not involved in design and evaluation processes. As a consequence, existing eHealth services often do not meet the needs of this group of patients, which has resulted in a digital divide. OBJECTIVE: The aim of this study was to examine the effectiveness and user satisfaction of an electronic care and rehabilitation planning tool from the perspective of stroke survivors with aphasia. This would help us gain knowledge on how such a tool would need to be adapted for these patients for further development. METHODS: Usability tests were conducted with 9 postdischarge stroke survivors with aphasia. Effectiveness was measured using task-based tests, and user satisfaction was studied through qualitative interviews at the end of each test. All tests were audio recorded, and each test lasted approximately 1 hour. The data were analyzed using qualitative content analysis. As the tool can be used by stroke survivors either independently or with some support from their next of kin or care professionals, the research group decided to divide the participants into 2 groups. Group 1 did not receive any support during the tests, and group 2 received some minor support from the moderator. RESULTS: The results showed that the care and rehabilitation planning tool was not effective for stroke survivors with aphasia, as many participants in group 1 did not accomplish the tasks successfully. Despite several usability problems and challenges in using the tool because of patients' disabilities, the participants were positive toward using the tool and found it useful for their care and rehabilitation journey. CONCLUSIONS: There is a need to involve patients with chronic illnesses more in the design and evaluation processes of health information systems and eHealth services. eHealth services and health information systems designed for this group of patients should be more adaptable and flexible to provide them with appropriate functionalities and features, meet their needs, and be useful and easy to use. In addition, the design and evaluation processes should be adapted, considering the challenges of this patient group.