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Objective: Most preventable adverse drug events and medication errors occur during medication ordering. Medication order entry and clinical decision support are available on paper or as computerized systems. In this post-hoc analysis we investigated frequency and clinical impact of blood glucose (BG) documentation- and user-related calculation errors as well as workflow deviations in diabetes management. We aimed to compare a paper-based protocol to a computerized medication management system combined with clinical workflow and decision support.Methods: Seventy-nine hospitalized patients with type 2 diabetes mellitus were treated with an algorithm driven basal-bolus insulin regimen. BG measurements, which were the basis for insulin dose calculations, were manually entered either into the paper-based workflow protocol (PaperG: 37 patients) or into GlucoTab(®)-a mobile tablet PC based system (CompG: 42 patients). We used BG values from the laboratory information system as a reference. A workflow simulator was used to determine user calculation errors as well as workflow deviations and to estimate the effect of errors on insulin doses. The clinical impact of insulin dosing errors and workflow deviations on hypo- and hyperglycemia was investigated.Results: The BG documentation error rate was similar for PaperG (4.9%) and CompG group (4.0%). In PaperG group, 11.1% of manual insulin dose calculations were erroneous and the odds ratio (OR) of a hypoglycemic event following an insulin dosing error was 3.1 (95% CI: 1.4-6.8). The number of BG values influenced by insulin dosing errors was eightfold higher than in the CompG group. In the CompG group, workflow deviations occurred in 5.0% of the tasks which led to an increased likelihood of hyperglycemia, OR 2.2 (95% CI: 1.1-4.6).Discussion: Manual insulin dose calculations were the major source of error and had a particularly strong influence on hypoglycemia. By using GlucoTab(®), user calculation errors were entirely excluded. The immediate availability and automated handling of BG values from medical devices directly at the point of care has a high potential to reduce errors. Computerized systems facilitate the safe use of more complex insulin dosing algorithms without compromising usability. In CompG group, missed or delayed tasks had a significant effect on hyperglycemia, while in PaperG group insufficient precision of documentation times limited analysis. The use of old BG measurements was clinically less relevant.Conclusion: Insulin dosing errors and workflow deviations led to measurable changes in clinical outcome. Diabetes management systems including decision support should address nurses as well as physicians in a computerized way. Our analysis shows that such systems reduce the frequency of errors and therefore decrease the probability of hypo- and hyperglycemia. [ABSTRACT FROM AUTHOR]

Background: The adoption and use of health information technology (IT) continues to grow around the globe. In Switzerland, the government nor professional associations have to this day provided incentives for health IT adoption.Objective: We aim to assess the proportion of physicians who are routinely working with electronic health data and describe to what extent physicians exchange electronic health data with peers and other health care providers. Additionally, we aim to estimate the effect of physicians' attitude towards health IT on the adoption of electronic workflows.Methods: Between May and July 2013, we conducted a cross-sectional survey of 1200 practice based physicians in Switzerland. Respondents were asked to report on their technical means and where applicable their paper-based workarounds to process laboratory data, examination results, referral letters and physician's letters. Physicians' view of barriers and facilitators towards health IT use was determined by a composite score.Results: A response rate of 57.1% (n=685) was reached. The sample was considered to be representative for physicians in Swiss ambulatory care. 35.2% of the respondents documented patients' health status with the help of a longitudinal semi-structured electronic text record generated by one or more encounters in the practice. Depending on the task within a workflow, around 11-46% of the respondents stated to rely on electronic workflow practices to process laboratory and examination data and dispatch referral notes and physician's letters. The permanent use of electronic workflow processes was infrequent. Instead, respondents reported paper-based workarounds affecting specific tasks within a workflow. Physicians' attitude towards health IT was significantly associated with the adoption of electronic workflows (OR 1.04-1.31, p<0.05), but the effect sizes of factors related to the working environment (e.g., regional factors, medical specialty, type of practice) were larger.Conclusion: At present, only a few physicians in Swiss ambulatory care routinely work with electronic health data. Until more of their peers participate in electronic exchange of structured clinical information, most physicians will continue to stay in paper-based systems and workarounds. The survey found that physicians with a positive attitude towards health IT were more likely to adopt electronic workflows, but the impact is minor. It will likely be necessary to introduce financial incentives and develop national standards in order to promote the adoption by a critical mass of practicing clinicians. [ABSTRACT FROM AUTHOR]

Introduction: Currently, there are few evidence-based guidelines to inform optimal clinical data-entry template design that maximizes usability while reducing unintended consequences. This study explored the impact of data-entry template design and anesthesia provider workload on documentation accuracy, documentation efficiency, and user-satisfaction to identify the most beneficial data-entry methods for use in future documentation interface design.Methodology: A study using observational data collection and psychometric instruments (for perceived workload and user-satisfaction) was conducted at three hospitals using different methods of data-entry for perioperative documentation (auto-filling with unstructured data, computer-assisted data selection with semi-structured documentation, and paper-based documentation). Nurse anesthetists at each hospital (N = 30) were observed completing documentation on routine abdominal surgical cases.Results: Auto-filling (61.2%) had the lowest documentation accuracy scores compared to computer-assisted (81.3%) and paper-based documentation (76.2%). Computer-assisted data-entry had the best documentation efficiency scores and required the least percentage of the nurse anesthetists' time (9.65%) compared to auto-filling (11.43%) and paper-based documentation (15.23%). Paper-based documentation had the highest perceived workload scores (M = 288, SD = 88) compared to auto-filling (M = 160, SD = 93, U = 16.5, p < 0.01) and computer assisted data-entry (M = 93, SD = 50, U = 4.0, P < 0.001).Conclusions: Auto-filling with unstructured data needs to be used sparingly because of its low documentation accuracy. Computer-assisted data entry with semi-structured data needs to be further study because of its better documentation accuracy, documentation efficiency, and perceived workload. [ABSTRACT FROM AUTHOR]

Introduction: Members of the healthcare team must access and share patient information to coordinate interprofessional collaborative practice (ICP). Although some evidence suggests that electronic health records (EHRs) contribute to in-team communication breakdowns, EHRs are still widely hailed as tools that support ICP. If EHRs are expected to promote ICP, researchers must be able to longitudinally study the impact of EHRs on ICP across communication types, users, and physical locations.Objective: This paper presents a data collection and analysis tool, named the Map of the Clinical Interprofessional Communication Spaces (MCICS), which supports examining how EHRs impact ICP over time, and across communication types, users, and physical locations.Methods: The tool's development evolved during a large prospective longitudinal study conducted at a Canadian pediatric academic tertiary-care hospital. This two-phased study [i.e., pre-implementation (phase 1) and post implementation (phase 2)] of an EHR employed a constructivist grounded theory approach and triangulated data collection strategies (i.e., non-participant observations, interviews, think-alouds, and document analysis). The MCICS was created through a five-step process: (i) preliminary structural development based on the use of the paper-based chart (phase 1); (ii) confirmatory review and modification process (phase 1); (iii) ongoing data collection and analysis facilitated by the map (phase 1); (iv) data collection and modification of map based on impact of EHR (phase 2); and (v) confirmatory review and modification process (phase 2).Results: Creating and using the MCICS enabled our research team to locate, observe, and analyze the impact of the EHR on ICP, (a) across oral, electronic, and paper communications, (b) through a patient's passage across different units in the hospital, (c) across the duration of the patient's stay in hospital, and (d) across multiple healthcare providers. By using the MCICS, we captured a comprehensive, detailed picture of the clinical milieu in which the EHR was implemented, and of the intended and unintended consequences of the EHR's deployment. The map supported our observations and analysis of ICP communication spaces, and of the role of the patient chart in these spaces.Conclusions: If EHRs are expected to help resolve ICP challenges, it is important that researchers be able to longitudinally assess the impact of EHRs on ICP across multiple modes of communication, users, and physical locations. Mapping the clinical communication spaces can help EHR designers, clinicians, educators and researchers understand these spaces, appreciate their complexity, and navigate their way towards effective use of EHRs as means for supporting ICP. We propose that the MCICS can be used "as is" in other academic tertiary-care pediatric hospitals, and can be tailored for use in other healthcare institutions. [ABSTRACT FROM AUTHOR]

Purposes: This study aimed to compare between electronic medication administration records and paper-based records in the nursing time spent on various activities in a medication round and the medication administration processes followed by nurses in an Australian residential aged care home. It also aimed to identify the benefits and unintended adverse consequences of using the electronic medication administration records.Methods: Time-motion observation, taking of field notes, informal conversation and document review were used to collect data in two units of a residential aged care home. Each unit had one nurse administer medication. Seven nurses were observed over 12 morning shifts. Unit 1 used electronic medication administration records and Unit 2 used paper-based records.Results: No significant difference between the two units was found in the nursing time spent on various activities in a medication round, including documentation, verbal communication, medication administration, infection control and transit. Comparison of the medication administration processes between the electronic and paper-based medication administration records identified a procedural problem which violated the organization's documentation requirement. This problem was documenting before providing medication to a resident when using the paper-based records. It was not observed with the electronic medication administration records. Benefits of introducing the electronic medication administration records included improving nurses' compliance with documentation requirements, freedom from the error of signing twice, reducing the possibility of forgetting to medicate a resident, facilitating nurses to record the time of medication administration to a resident and increasing documentation space. Unintended adverse consequences of introducing the electronic medication administration records included inadequate information about residents, late addition of a new resident's medication profile in the records and nurses' forgetting to medicate a resident due to power outage of the portable device.Conclusions: The electronic medication administration records may not change nursing time spent on various activities in a medication round or substantially alter the medication administration processes, but can generate both benefits and unintended adverse consequences. Future research may investigate whether and how the adverse consequences can be prevented. [ABSTRACT FROM AUTHOR]

Background: In dentistry, the use of electronic patient records for research is underexplored. The aim of this paper is to describe a case study process of obtaining research data (sociodemographic, clinical and workforce) from electronic primary care dental records, and outlining data cleaning and validation strategies. This study was undertaken at the University of Portsmouth Dental Academy (UPDA), which is a centre of education, training and provision of state funded services (National Health Services). UPDA's electronic patient management system is R4/Clinical +. This is a widely used system in general dental practices in the UK.Method: A two-phase process, involving first Pilot and second Main data extraction were undertaken. Using System Query Language (SQL), data extracts containing variables related to patients' demography, socio-economic status and dental care received were generated. A data cleaning and validation exercise followed, using a combination of techniques including Maletic and Marcus's (2000) general framework for data cleaning and Rahm and Haido's (2010) principles of data cleaning.Results: The findings of the case study support the use of a two-phase data extraction process. The data validation processes highlighted the need for both manual and analytical strategies when cleaning these data. Finally, the process demonstrated that electronic dental records can be validated and used for epidemiological and heath service research. The potential to generalise findings is great due to the large number of records. There are, however, limitations to the data which need to be considered, relating to quality (data input), database structure and interpretation of data codes.Conclusion: Electronic dental records are useful in health service research, epidemiological studies and skill mix research. Researchers should work closely with clinicians, managers and software developers to ensure that the data generated are accurate, valid and generalisable. Following data extraction the researchers need to adapt stringent validation and data cleaning strategies to guarantee that the extracted electronic data are accurate. [ABSTRACT FROM AUTHOR]

Background: The effectiveness of the clinical decision support systems (CDSSs) is hampered by frequent workflow interruptions and alert fatigue because of alerts with little or no clinical relevance. In this paper, we reported a methodology through which we applied knowledge from the clinical context and the international recommendations to develop a potential drug-drug interaction (pDDI) CDSS in the field of kidney transplantation.Methods: Prescriptions of five nephrologists were prospectively recorded through non-participatory observations for two months. The Medscape multi-drug interaction checker tool was used to detect pDDIs. Alongside the Stockley's drug interactions reference, our clinicians were consulted with respect to the clinical relevance of detected pDDIs. We performed semi-structured interviews with five nephrologists and one informant nurse. Our clinically relevant pDDIs were checked with the Dutch "G-Standard". A multidisciplinary team decided the design characteristics of pDDI-alerts in a CDSS considering the international recommendations and the inputs from our clinical context. Finally, the performance of the CDSS in detecting DDIs was evaluated iteratively by a multidisciplinary research team.Results: Medication data of 595 patients with 788 visits were collected and analyzed. Fifty-two types of interactions were most common, comprising 90% of all pDDIs. Among them 33 interactions (comprising 77% of all pDDIs) were rated as clinically relevant and were included in the CDSS's knowledge-base. Of these pDDIs, 73% were recognized as either pseudoduplication of drugs or not a pDDI when checked with the Dutch G-standard. Thirty-three alerts were developed and physicians were allowed to customize the appearance of pDDI-alerts based on a proposed algorithm.Conclusion: Clinical practice contexts should be studied to understand the complexities of clinical work and to learn the type, severity and frequency of pDDIs. In order to make the alerts more effective, clinicians' points of view concerning the clinical relevance of pDDIs are critical. Moreover, flexibility should be built into a pDDI-CDSS to allow clinicians to customize the appearance of pDDI-alerts based on their clinical context. [ABSTRACT FROM AUTHOR]

Background and Objective: The condition of vessel of the human eye is an important factor for the diagnosis of ophthalmological diseases. Vessel segmentation in fundus images is a challenging task due to complex vessel structure, the presence of similar structures such as microaneurysms and hemorrhages, micro-vessel with only one to several pixels wide, and requirements for finer results.Methods: In this paper, we present a multi-scale deeply supervised network with short connections (BTS-DSN) for vessel segmentation. We used short connections to transfer semantic information between side-output layers. Bottom-top short connections pass low level semantic information to high level for refining results in high-level side-outputs, and top-bottom short connection passes much structural information to low level for reducing noises in low-level side-outputs. In addition, we employ cross-training to show that our model is suitable for real world fundus images.Results: The proposed BTS-DSN has been verified on DRIVE, STARE and CHASE_DB1 datasets, and showed competitive performance over other state-of-the-art methods. Specially, with patch level input, the network achieved 0.7891/0.8212 sensitivity, 0.9804/0.9843 specificity, 0.9806/0.9859 AUC, and 0.8249/0.8421 F1-score on DRIVE and STARE, respectively. Moreover, our model behaves better than other methods in cross-training experiments.Conclusions: BTS-DSN achieves competitive performance in vessel segmentation task on three public datasets. It is suitable for vessel segmentation. The source code of our method is available at: https://github.com/guomugong/BTS-DSN. [ABSTRACT FROM AUTHOR]

This paper examines the paper of Haux et al. in this issue of this journal. It gives some background on specifics of the German health care system, which underlie the theses and prognoses proposed by Haux et al. In analogy to a forecast of the future of health informatics, which is now 10 years old, I then suggest that these attempts meet two types of challenges:•that of overestimating the positive effects of recent advances, which later are found not to scale up; and•that of blind spots with respect to unforeseen significant advances.The attempt to find indications of such in the projections of Haux et al. leads, among other, to the conclusion that the projections of direct linkages between patients and care providers may be overoptimistic. As to wheather the deviating opinions matter in the end, it is concluded that the technology advances may require less attention that the restructuring of the health care system required to take advantage of the advances of technology. [Copyright &y& Elsevier]

Introduction: Mobile devices and software are now available with sufficient computing power, speed and complexity to allow for real-time interpretation of radiology exams. In this paper, we perform a multivariable user study that investigates concordance of image-based diagnoses provided using mobile devices on the one hand and conventional workstations on the other hand.Methods: We performed a between-subjects task-analysis using CT, MRI and radiography datasets. Moreover, we investigated the adequacy of the screen size, image quality, usability and the availability of the tools necessary for the analysis. Radiologists, members of several teams, participated in the experiment under real work conditions. A total of 64 studies with 93 main diagnoses were analyzed.Results: Our results showed that 56 cases were classified with complete concordance (87.69%), 5 cases with almost complete concordance (7.69%) and 1 case (1.56%) with partial concordance. Only 2 studies presented discordance between the reports (3.07%). The main reason to explain the cause of those disagreements was the lack of multiplanar reconstruction tool in the mobile viewer. Screen size and image quality had no direct impact on the mobile diagnosis process.Conclusion: We concluded that for images from emergency modalities, a mobile interface provides accurate interpretation and swift response, which could benefit patients' healthcare. [ABSTRACT FROM AUTHOR]

Objective: The Learning Health System (LHS) requires integration of research into routine practice. 'eSource' or embedding clinical trial functionalities into routine electronic health record (EHR) systems has long been put forward as a solution to the rising costs of research. We aimed to create and validate an eSource solution that would be readily extensible as part of a LHS.Materials and Methods: The EU FP7 TRANSFoRm project's approach is based on dual modelling, using the Clinical Research Information Model (CRIM) and the Clinical Data Integration Model of meaning (CDIM) to bridge the gap between clinical and research data structures, using the CDISC Operational Data Model (ODM) standard. Validation against GCP requirements was conducted in a clinical site, and a cluster randomised evaluation by site nested into a live clinical trial.Results: Using the form definition element of ODM, we linked precisely modelled data queries to data elements, constrained against CDIM concepts, to enable automated patient identification for specific protocols and pre-population of electronic case report forms (e-CRF). Both control and eSource sites recruited better than expected with no significant difference. Completeness of clinical forms was significantly improved by eSource, but Patient Related Outcome Measures (PROMs) were less well completed on smartphones than paper in this population.Discussion: The TRANSFoRm approach provides an ontologically-based approach to eSource in a low-resource, heterogeneous, highly distributed environment, that allows precise prospective mapping of data elements in the EHR.Conclusion: Further studies using this approach to CDISC should optimise the delivery of PROMS, whilst building a sustainable infrastructure for eSource with research networks, trials units and EHR vendors. [ABSTRACT FROM AUTHOR]

Background and Objective: Different review articles support the usefulness and effectiveness of mindfulness techniques in health and wellbeing. In this paper we present a first prototype of a mobile application to help with the training and practice of mindfulness, taking into account the lacks detected in a previous literature review. Our aim was to measure acceptance and perceived quality, as well as gather data about app usage. Their dependence on demographic variables and the change in mindful level was also measured.Materials and Methods: Two versions of a new application were developed, "Mindfulness" and "Mindfulness Sci". The application has been tested in two pilot studies: in traditional face-to-face mindfulness groups and in individual and independent use.Results: 3977 users were involved in this study: 26 in the first trial during an 8-week usage period and 3951 in the second trial during 17 months. In the first study, participants assessed the app with high scores. They considered it as a helping tool for mindfulness practice, user-friendly and with high quality of use. The positive perception was maintained after 8-weeks meditation workshops, and participants considered that its use could contribute to obtain benefits for mental and physical health. In the second study, we found rather weak associations between usage time and age, nationality and educational level. The mindful level showed a weak positive correlation with the session accomplished but slightly above the boundary of statistical significance (p-value=0.051). Videos and information stood out as the most accessed resources.Conclusions: Up to our knowledge, this is the first app developed with the help of health professionals in Spanish that could be used with a general aim, in health and wellbeing. The results are promising with a positive evaluation in face-to-face and independent use situations. Therefore, the number of potential users is enormous in a global worldwide context. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this study is to evaluate the effectiveness and efficiency of privacy-preserving data cubes of electronic medical records (EMRs). An EMR data cube is a complex of EMR statistics that are summarized or aggregated by all possible combinations of attributes. Data cubes are widely utilized for efficient big data analysis and also have great potential for EMR analysis. For safe data analysis without privacy breaches, we must consider the privacy preservation characteristics of the EMR data cube. In this paper, we introduce a design for a privacy-preserving EMR data cube and the anonymization methods needed to achieve data privacy. We further focus on changes in efficiency and effectiveness that are caused by the anonymization process for privacy preservation. Thus, we experimentally evaluate various types of privacy-preserving EMR data cubes using several practical metrics and discuss the applicability of each anonymization method with consideration for the EMR analysis environment.Methods: We construct privacy-preserving EMR data cubes from anonymized EMR datasets. A real EMR dataset and demographic dataset are used for the evaluation. There are a large number of anonymization methods to preserve EMR privacy, and the methods are classified into three categories (i.e., global generalization, local generalization, and bucketization) by anonymization rules. According to this classification, three types of privacy-preserving EMR data cubes were constructed for the evaluation. We perform a comparative analysis by measuring the data size, cell overlap, and information loss of the EMR data cubes.Results: Global generalization considerably reduced the size of the EMR data cube and did not cause the data cube cells to overlap, but incurred a large amount of information loss. Local generalization maintained the data size and generated only moderate information loss, but there were cell overlaps that could decrease the search performance. Bucketization did not cause cells to overlap and generated little information loss; however, the method considerably inflated the size of the EMR data cubes.Conclusions: The utility of anonymized EMR data cubes varies widely according to the anonymization method, and the applicability of the anonymization method depends on the features of the EMR analysis environment. The findings help to adopt the optimal anonymization method considering the EMR analysis environment and goal of the EMR analysis. [ABSTRACT FROM AUTHOR]

Background: Serious games (SGs) are a type of simulation technology that may provide nursing students with the opportunity to practice their clinical reasoning and decision-making skills in a safe and authentic environment. Despite the growing number of SGs developed for healthcare professionals, few SGs are video based or address the domain of home health care.Aims: This paper aims to describe the design, development, and usability evaluation of a video based SG for teaching clinical reasoning and decision-making skills to nursing students who care for patients with chronic obstructive pulmonary disease (COPD) in home healthcare settings.Methods: A prototype SG was developed. A unified framework of usability called TURF (Task, User, Representation, and Function) and SG theory were employed to ensure a user-centered design. The educational content was based on the clinical decision-making model, Bloom's taxonomy, and a Bachelor of Nursing curriculum. A purposeful sample of six participants evaluated the SG prototype in a usability laboratory. Cognitive walkthrough evaluations, a questionnaire, and individual interviews were used for the usability evaluation. The data were analyzed using qualitative deductive content analysis based on the TURF framework elements and related usability heuristics.Results: The SG was perceived as being realistic, clinically relevant, and at an adequate level of complexity for the intended users. Usability issues regarding functionality and the user-computer interface design were identified. However, the SG was perceived as being easy to learn, and participants suggested that the SG could serve as a supplement to traditional training in laboratory and clinical settings.Conclusions: Using video based scenarios with an authentic COPD patient and a home healthcare registered nurse as actors contributed to increased realism. Using different theoretical approaches in the SG design was considered an advantage of the design process. The SG was perceived as being useful, usable, and satisfying. The achievement of the desired functionality and the minimization of user-computer interface issues emphasize the importance of conducting a usability evaluation during the SG development process. [ABSTRACT FROM AUTHOR]

Objective: This paper presents an empirical study of a formative mobile-based assessment approach that can be used to provide students with intelligent diagnostic feedback to test its educational effectiveness.Method: An audience response system called SIDRA was integrated with a neural network-based data analysis to generate diagnostic feedback for guided learning. A total of 200 medical students enrolled in a General and Descriptive Anatomy of the Locomotor System course were taught using two different methods. Ninety students in the experimental group used intelligent SIDRA (i-SIDRA), whereas 110 students in the control group received the same training but without employing i-SIDRA.Results: In the students' final exam grades, a statistically significant difference was found between those students that used i-SIDRA as opposed to a traditional teaching methodology (T(162)=2.597; p=0.010). The increase in the number of correct answers during the feedback guided learning process from the first submission to the last submission in four multiple choice question tests was also analyzed. There were average increases of 20.00% (Test1), 11.34% (Test2), 8.88% (Test3) and 13.43% (Test4) in the number of correct answers. In a questionnaire rated on a five-point Likert-type scale, the students expressed satisfaction with the content (M=4.2) and feedback (M=3.5) provided by i-SIDRA and the methodology (M=4.2) used to learn anatomy.Conclusions: The use of audience response systems enriched with feedback such as i-SIDRA improves medical degree students' performance as regards anatomy of the locomotor system. The knowledge state diagrams representing students' behavior allow instructors to study their progress so as to identify what they still need to learn. [ABSTRACT FROM AUTHOR]

Early (or preclinical) diagnosis of Parkinson's disease (PD) is crucial for its early management as by the time manifestation of clinical symptoms occur, more than 60% of the dopaminergic neurons have already been lost. It is now established that there exists a premotor stage, before the start of these classic motor symptoms, characterized by a constellation of clinical features, mostly non-motor in nature such as Rapid Eye Movement (REM) sleep Behaviour Disorder (RBD) and olfactory loss. In this paper, we use the non-motor features of RBD and olfactory loss, along with other significant biomarkers such as Cerebrospinal fluid (CSF) measurements and dopaminergic imaging markers from 183 healthy normal and 401 early PD subjects, as obtained from the Parkinson's Progression Markers Initiative (PPMI) database, to classify early PD subjects from normal using Naïve Bayes, Support Vector Machine (SVM), Boosted Trees and Random Forests classifiers. We observe that SVM classifier gave the best performance (96.40% accuracy, 97.03% sensitivity, 95.01% specificity, and 98.88% area under ROC). We infer from the study that a combination of non-motor, CSF and imaging markers may aid in the preclinical diagnosis of PD. [ABSTRACT FROM AUTHOR]

Background: Although telehealth offers an improved approach to providing healthcare services, its adoption by end users remains slow. With an older population as the main target, these traditionally conservative users pose a big challenge to the successful implementation of innovative telehealth services.Objectives: The objective of this study was to develop and empirically test a model for predicting the factors affecting older users' acceptance of Home Telehealth Services (HTS).Methods: A survey instrument was administered to 400 participants aged 50 years and above from both rural and urban environments in Slovenia. Structural equation modeling was applied to analyze the causal effect of seven hypothesized predicting factors. HTS were introduced as a bundle of functionalities, representing future services that currently do not exist. This enabled users' perceptions to be measured on the conceptual level, rather than attitudes to a specific technical solution.Results: Six relevant predictors were confirmed in older users' HTS acceptance behavior, with Performance Expectancy (r=0.30), Effort Expectancy (r=0.49), Facilitating Conditions (r=0.12), and Perceived Security (r=0.16) having a direct impact on behavioral intention to use HTS. In addition, Computer Anxiety is positioned as an antecedent of Effort Expectancy with a strong negative influence (r=-0.61), and Doctor's Opinion influence showed a strong impact on Performance Expectancy (r=0.31). The results also indicate Social Influence as an irrelevant predictor of acceptance behavior. The model of six predictors yielded 77% of the total variance explained in the final measured Behavioral Intention to Use HTS by older adults.Conclusion: The level at which HTS are perceived as easy to use and manage is the leading acceptance predictor in older users' HTS acceptance. Together with Perceived Usefulness and Perceived Security, these three factors represent the key influence on older people's HTS acceptance behavior. When promoting HTS, interventions should focus to portray it as secure. Marketing interventions should focus also on promoting HTS among health professionals, using them as social agents to frame the services as useful and beneficial. The important role of computer anxiety may result in a need to use different equipment such as a tablet computer to access HTS. Finally, this paper introduces important methodological guidelines for measuring perceptions on a conceptual level of future services that currently do not exist. [ABSTRACT FROM AUTHOR]

Background: It is conjectured that providing feedback on physicians' prescribing behavior improves quality of drug prescriptions. However, the effectiveness of feedback provision and mode of feedback delivery is not well understood. The objective of this study was to assess and compare the effect of traditional paper letters (TPL) and short text message (STM) feedback on general practitioners' prescribing behavior of parenteral steroids (PSs).Methods: In a single-blind randomized controlled trial, 906 general practitioners (GPs) having at least 10 monthly prescriptions were randomly recruited into two interventions and one control study arms with 1:1 allocation, stratified by percentage of prescriptions. The intervention was the provision of 3 feedback messages containing prescribing indices in TPL and STM (in the first two arms) versus the control arm (CG) with an interval of 3 months between these messages. We calculated the PS Defined Daily Dose (DDD) for every GP, every month, and compared between the 3 arms, before and after the interventions. The expected primary outcome was to reduce prescription of parenteral steroids by participants. The study was performed in the Kerman Social Security Organization in Iran.Results: A total of 906 GPs were selected for the trial, but only 721 of them (TPL=191, STM=228, CG=302) were recruited for the 1st feedback. The mean age of GPs was 44 and 59% of them were male. The prescribed parenteral steroid DDDs at baseline were similar (TPL=121.62, STM=127.49, CG=115.68, P>0.5). At the end of the study, DDDs in the TPL and STM arms were similar (TPL=104.38, STM=101.90, P>0.9) but DDDs in each intervention arm was statistically significantly lower than in CG (CG=156.17, P<0.0001). Being in TPL and STM arms resulted in 36.1 and 41.7 units of decrease in DDD respectively, compared to the control arm (P<0.02 and P<0.005) after the one-year duration of the study.Conclusion: Feedback by TPLs and STMs on prescribing performance effectively reduced prescribing PSs by GPs. STM, being a cheap and fast tool, is potentially powerful and efficient for drug prescription rationalization. [ABSTRACT FROM AUTHOR]

Context: The recurrence of past security breaches in healthcare showed that lessons had not been effectively learned across different healthcare organisations. Recent studies have identified the need to improve learning from incidents and to share security knowledge to prevent future attacks. Generic Security Templates (GSTs) have been proposed to facilitate this knowledge transfer. The objective of this paper is to evaluate whether potential users in healthcare organisations can exploit the GST technique to share lessons learned from security incidents.Methodology: We conducted a series of case studies to evaluate GSTs. In particular, we used a GST for a security incident in the US Veterans' Affairs Administration to explore whether security lessons could be applied in a very different Chinese healthcare organisation.Results: The results showed that Chinese security professional accepted the use of GSTs and that cyber security lessons could be transferred to a Chinese healthcare organisation using this approach. The users also identified the weaknesses and strengths of GSTs, providing suggestions for future improvements.Conclusion: Generic Security Templates can be used to redistribute lessons learned from security incidents. Sharing cyber security lessons helps organisations consider their own practices and assess whether applicable security standards address concerns raised in previous breaches in other countries. The experience gained from this study provides the basis for future work in conducting similar studies in other healthcare organisations. [ABSTRACT FROM AUTHOR]

Background: Despite the growing interest in health data science education, it is not embedded in undergraduate medical curricula and little is known about best teaching practices. This paper presents a highly innovative course in a UK university that introduces undergraduate medical students to data science. It also discusses a study on student perspectives on the learning and teaching of health data science.Methods: The pedagogical design elements of the Data Science in Medicine course are discussed, along with its syllabus, assessment methodology and flipped classroom delivery. The course has been offered to approximately 630 students over three years. Student perspectives were investigated through three focus groups with the participation of 19 students across different study years in medicine. An experiment was conducted regarding instructor-led vs. video-based modalities of online programming labs, with the participation of 8 students.Results: The course has led to improved data competency among medical students and to a positive change in their opinions about data science. Motivating the course and showing relevance to clinical practice was one of the biggest challenges. Statistics was perceived by focus group participants as an essential data skill. Including data science in the medical curriculum was perceived as important by Year 1 students, while opinions varied between Year 4/5 participants. Video-based online labs were preferred over instructor-led online labs, and they were found to be more useful and enjoyable, without leading to any significant difference in academic performance.Conclusions: Teaching data science to undergraduate medicine students is highly desirable and feasible. We recommend including statistics in the curriculum and practical skill development through simple and clinically-relevant data science tasks, supported through video-based online labs. Further reporting on similar courses is needed, as well as larger-scale studies on student perspectives. [ABSTRACT FROM AUTHOR]

Time plays an important role in medicine, both the past and the future. The medical history of a patient represents the past, which needs to be understood by the physician to make the right decisions. The past contains two different kinds of information: measured data (such as blood pressure) and incidents (such as seizures). Planning therapies, on the other hand, requires looking into the future to a certain extent. Visual representations exist for both the past and the future, and they are very useful for getting a better understanding of data or a plan. This paper surveys visualization techniques for both data analysis and planning, and compares them based on a number of criteria. [Copyright &y& Elsevier]

We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE project. Our approach is based on using the Unified Medical Language System (UMLS) as the primary source of semantic data. Documents and queries are annotated with multiple layers of linguistic information. Linguistic processing includes part-of-speech tagging, morphological analysis, phrase recognition and the identification of medical terms and semantic relations between them. The paper describes experiments in monolingual and cross-language document retrieval, performed on a corpus of medical abstracts. Results show that linguistic processing, especially lemmatization and compound analysis for German, is a crucial step in achieving a good baseline performance. On the other hand, they show that semantic information, specifically the combined use of concepts and relations, increases the performance in monolingual and cross-language retrieval. [Copyright &y& Elsevier]

In this paper we describe Tagged Information Management System (TIMS), an integrated knowledge management system for the domain of molecular biology and biomedicine, in which terminology-driven literature mining, knowledge acquisition (KA), knowledge integration (KI), and XML-based knowledge retrieval are combined using tag information management and ontology inference. The system integrates automatic terminology acquisition, term variation management, hierarchical term clustering, tag-based information extraction (IE), and ontology-based query expansion. TIMS supports introducing and combining different types of tags (linguistic and domain-specific, manual and automatic). Tag-based interval operations and a query language are introduced in order to facilitate KA and retrieval from XML documents. Through KA examples, we illustrate the way in which literature mining techniques can be utilised for knowledge discovery from documents. [Copyright &y& Elsevier]

This paper reviews the research and development around a consumer health informatics system CHESS (The Comprehensive Health Enhancement Support System) developed and tested by the Center for Health Systems Research and Analysis at the University of Wisconsin. The review places particular emphasis on what has been found with regard to the acceptance and use of such systems by high risk and underserved groups. [ABSTRACT FROM AUTHOR]

Background: Bayesian modelling and statistical text analysis rely on informed probability priors to encourage good solutions.Objective: This paper empirically analyses whether text in medical discharge reports follow Zipf's law, a commonly assumed statistical property of language where word frequency follows a discrete power-law distribution.Method: We examined 20,000 medical discharge reports from the MIMIC-III dataset. Methods included splitting the discharge reports into tokens, counting token frequency, fitting power-law distributions to the data, and testing whether alternative distributions-lognormal, exponential, stretched exponential, and truncated power-law-provided superior fits to the data.Result: Discharge reports are best fit by the truncated power-law and lognormal distributions. Discharge reports appear to be near-Zipfian by having the truncated power-law provide superior fits over a pure power-law.Conclusion: Our findings suggest that Bayesian modelling and statistical text analysis of discharge report text would benefit from using truncated power-law and lognormal probability priors and non-parametric models that capture power-law behavior. [ABSTRACT FROM AUTHOR]

Background: The introduction of a paper-based Community Case Management (CCM) in Malawi has contributed to a reduction of child morbidity and mortality rates. In addition, the introduction of electronic Community Case Management (eCCM) (smartphones with built in CCM apps) may help to reduce the under-five mortality rates even further.Purpose: It is not uncommon for Apps with a similar area of interest to develop different features to assist the end users. Such differences between Apps may have a significant role to play in its overall adoption and integration. The purpose of this research was to explore end users perspectives of two eCCM decision support tools developed and implemented by the Supporting LIFE project (SL eCCM App) and D-Tree International's (Mangologic eCCM App)in Northern Malawi.Methods: A mixed methods approach was applied, involving a survey of 109 users (106 Health Surveillance Assistants (HSAs), and 3 Integrated Management of Childhood Il6lnesses (IMCI) coordinators). This was followed up with semi-structured interviews with 34 respondents (31 HSAs, and 3 IMCI coordinators). Quantitative data was analyzed using SPSS version 20 where descriptive statistics and Chi-Squared tests were generated. Qualitative data were analyzed based on thematic analysis.Results: Participants reported that both Apps could assist the HSAs in the management of childhood illnesses. However, usability differed between the two apps where the Supporting LIFE eCCM App was found to be easier to use (61%) compared to the Mangologic eCCM App (4%). Both Apps were perceived to provide credible and accurate information.Conclusion: It is essential that the quality of the data within Mobile Health (mHealth) Apps is high, however even Apps with excellent levels of data quality may not succeed if the overall usability of the App is low. Therefore it is essential that the Apps has high levels of data quality, usability and credibility. The results of this study will help inform mobile Health (mHealth) App designers in developing future eCCM Apps as well as researchers and policy makers when considering the adoption of mHealth solutions in the future in Malawi and other LMICs. [ABSTRACT FROM AUTHOR]

Objective: The main objective of this paper is the reduction of the COVID-19 pandemic spread by increasing the degree of social distancing by using and upgrading the existing Medical Information System (MIS).Material and Methods: The existing MIS MEDIS.NET, currently used in the largest health center in the Balkans, has been adapted and further developed.Results: During the adaptation of existing MIS MEDIS.NET 4 new and 9 existing modules were developed. A quick questionnaire for the smart triage of patients was also implemented.Discussion: The adapted MIS successfully influenced the reduction of social contacts within the Health Center Nis. The need for the arrival of children and their parents to receive appropriate health certificates for the school enrolment is reduced. The therapy of chronic patients has been prolonged for 6 months via an electronic prescription. An online service for the communication between patients and the chosen physicians is provided. Possible social contacts and exposure to the viral environment of patients are reduced by making appointments in extended slots and at determined physical locations. Patients are notified per SMS or email about the availability of chosen and physician on duty. The social distancing of patients and physicians is also established by sending laboratory analyses per email or SMS. Keeping the central registry for COVID-19 is enabled throughout the country.Conclusion: The smart adaptation of MIS, and its collaboration with other state systems can significantly influence the reduction of social contacts and thus mitigate the consequences of COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background and Objective: The workings of medical educational tools are implemented using a myriad of approaches ranging from presenting static content to immersing students in gamified virtual-reality environments. The objective of this paper is to explore whether and how different approaches for designing medical educational tools affect students' learning performance.Materials and Methods: Four versions of an educational tool for the study of clinical cases were implemented: a 2D version, a gamified 2D version, a gamified 3D version, and a gamified immersive-virtual-reality version. All complying with the same functional requirements. Each version was used and evaluated by an independent group of students. The participants (n = 78) evaluated the applications regarding usefulness, usability, and gamification. Afterward, the students took an exam to assess the retention of information on the clinical cases presented.Results: One-sample Wilcoxon signed-rank tests confirmed that the participants perceived that it was at least quite likely that gamification helped improved their learning. In addition, based on the participants' perception, the gamification of the immersive-virtual-reality version helped the most to improve their learning performance in comparison with the gamified 2D and 3D versions.Conclusions: Regardless of whether different versions of a medical educational tool (complying with the same functional requirements) are perceived as equally useful and usable, the design approach (either 2D, 3D, or immersive-virtual-reality with or without gamification) affects students' retention of information on clinical cases. [ABSTRACT FROM AUTHOR]

Background: There is growing emphasis on the role of digital solutions in supporting chronic disease management. This has the potential to increase the burden patients experience in managing their health by offloading care from the health system to patients. This paper explores the effects of virtual visits on patient burden using an explicit framework measuring both the work patients do to care for their health and the challenges they experience that exacerbate burden.Methods: This mixed methods study evaluates a large pilot implementation of virtual visits (video, audio, and asynchronous messaging with providers) in primary care in Ontario, Canada. Participants were recruited using convenience sampling from patients using a virtual visit platform to complete a semi-structured interview or a survey including a free-text response. We conducted 17 interviews and reviewed 427 free text responses related to explore patients' perceived value and burden of these visits. We used qualitative analyses to map patients' feedback on their experience to the framework on patient burden.Main Findings: Virtual visits appear to reduce the work patients must do to manage their care by 1) improving access, convenience, and time needed for medical appointments, and 2) making it easier to access information and support for chronic disease management. Virtual visits also alleviate patients' perceived burden by improving continuity of care, experience of care, and providing some cost savings.Conclusions: Virtual visits reduced overall patient burden of treatment by decreasing the required patient effort of managing medical appointments and monitoring their health, and by minimizing challenges experienced when accessing care. For regions that want to improve patient experience of care, virtual visits are likely to be of benefit. There is need for further research on the generalizability of the findings herein, particularly for high-needs populations under-represented such as those of low socioeconomic status and those in rural and remote locations. [ABSTRACT FROM AUTHOR]

Methods: The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible.Results: Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8).Conclusions: Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models. [ABSTRACT FROM AUTHOR]

Background: Non-adherence to tuberculosis (TB) treatment jeopardizes the individual's health and contributes to disease transmission and drug resistance. New patient-centered strategies are needed to improve TB treatment outcomes.Purpose: To convert and expand a texting-based intervention into a mobile optimized application (app), evaluate the feasibility of an added self-administered paper-based drug metabolite test, and identify needs and preferences to inform their iterative design.Methods: Qualitative methods using focus groups and field testing with patients in active TB treatment were used to gather initial input on the converted intervention design, content and issues using at home test strips to report medication adherence. Seven participants were recruited from an outpatient clinic within a regional public reference hospital specialized in respiratory diseases in Argentina. Thematic analyses were conducted on the transcripts and session notes.Results: Participants considered interactive communication, access to answers to frequently asked questions, and tracking of progress in treatment as important. Participants reported having many questions and uncertainties at initiation of treatment and emphasized a need for reliable information, assurance and support from both providers and peers. Other suggestions included streamlining the graphical user interface for easier and shorter data entry times and usability.Conclusions: Overall feedback from the participants regarding the intervention was positive, reporting that it was useful and relevant, and they were eager to contribute their ideas for improvement and additional functionality. Valuable feedback to improve functionality and meet the needs of end-users were obtained to inform the generation of new design ideas for refinement and testing in a pilot study. [ABSTRACT FROM AUTHOR]

Background: The Clinical Practice Research Datalink (CPRD) GOLD is an extremely influential U.K. primary care dataset for epidemiological research having a number of published papers based on its data much bigger than any other U.K. primary care dataset. The Office for National Statistics (ONS) death data for England can be linked to GOLD at the patient level and are considered the gold standard on mortality. GOLD, which also holds death data, has been recently assessed against ONS linked dataset and the accuracy of its dates of death has been deemed sufficient for the majority of observational studies. However, there is a lack of guidance on how to manage the challenges existing when ONS mortality and GOLD datasets are linked, including linkage coverage period, linkage correctness likelihood, linkage regional limitations and data discrepancy.Objectives: Provide reconciling guidelines on how to make maximum and at the same time trustworthy use of mortality information coming from both GOLD and ONS linked datasets with the aim of improving the quality, reproducibility, transparency and comparison of clinical research.Method and Results: We have developed recommendations on how to manage mortality data coming from both GOLD and linked ONS, taking into account linkage coverage period, linkage correctness likelihood, linkage regional limitations and data discrepancies between these two datasets. We have also implemented these guidelines in an SQL algorithm for researchers to use.Conclusion: We have provided detailed guidelines on the reconciliation of mortality data between GOLD and ONS linked death datasets, taking into account both their strengths and limitations. The consistent application of these guidelines made practical by an SQL algorithm, has the potential to improve clinical research quality, reproducibility, transparency and comparison. [ABSTRACT FROM AUTHOR]