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Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.
JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals.
Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.
JMIR Medical Informatics journal features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs (ready for deposit in PubMed Central/PubMed). The site is optimized for mobile and iPad use.
JMIR Medical Informatics adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics (http://www.jmir.org/issue/current).
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Objective: The timely and managed intervention reduces the consequences due to disease and sudden death of patients in emergency conditions. Monitoring and caring for the patients in emergency conditi...
Objective: The timely and managed intervention reduces the consequences due to disease and sudden death of patients in emergency conditions. Monitoring and caring for the patients in emergency conditions requires the rapid and correct decisions to maintain their lives. The present study aimed at modeling the wearable smart blanket system for monitoring the patients in the emergency conditions of ambulance. Method: The present study was applied and descriptive-developmental. Firstly, the requirements and features of wearable smart blanket system were elicited and secondly a smart blanket system was modeled by using the UML charts and elicited requirements. Finally, the designed architecture was evaluated by using ARID scenario-based method. Results: The functional requirements of wearable smart blanket system with its data elements and physical-structural features of this system as well as non-functional requirements were elicited. Based on the requirements and data elements elicited from the questionnaire, class diagram, activity, use case diagram, sequence, deployment, and component were drawn. Then, the ARID scenario-based evaluation method was used to show that the designed architecture can provide the expected scenarios from the proposed system by using the UML and the relationships between components, systems, and users from the structural and behavioral perspectives. Conclusion: wearable smart blanket system collects the data related to medical signals by the sensors installed on the blanket and such data are processed by the smart system. The obtained data about the conditions of patient help the physician in ambulance to intervene timely and rapidly without any delay.
Background: Electronic recording of vital sign observations (e-Obs) has become increasingly prevalent in hospital care. The evidence of clinical impact for these systems is mixed. Objective: To assess...
Background: Electronic recording of vital sign observations (e-Obs) has become increasingly prevalent in hospital care. The evidence of clinical impact for these systems is mixed. Objective: To assess the effect of e-Obs versus paper documentation (paper) on length of stay (time between trauma unit admission and ‘fit to discharge’) for trauma patients. Methods: A single centre randomised stepped-wedge study of e-Obs against paper in two 26-bed trauma wards at a medium-sized UK teaching hospital. Randomisation of the phased intervention order to the 12 study areas was computer-generated. The primary outcome was length of stay. Results: 1232 patient episodes were randomised (paper: 628, e-Obs: 604). There were 37 deaths in hospital, 21 in the Paper arm and 16 in the e-Obs arm. For discharged patients the median length of stay was 5.4 days (range: 0.2 to 79.0) on paper and 5.6 days (range: 0.1 to 236.7) on e-Obs arm. Competing risks regression analysis for time to discharge showed no difference between the treatment arms, subhazard ratio: 1.05 (0.82, 1.35) P=.68. More patient episodes contained an EWS≥3 using the e-Obs system than paper, subhazard ratio 1.63 (95% CI 1.28, 2.09 P<0.001). However, there was no difference in the time to the subsequent observation (‘escalation time’) hazard ratio 1.05 (95% CI 0.80, 1.38 P=.70). Conclusions: The phased introduction of an e-Obs documentation system was not associated with a change in length of stay. More patient episodes contained an EWS≥3 using the e-Obs system, but this was not associated with a change in ‘escalation time’. Clinical Trial: ISRCTN91040762
Background: The adoption and use of an Electronic Health Record can facilitate real-time access to key health information and support improved outcomes. Many Canadian provinces use interoperable Elect...
Background: The adoption and use of an Electronic Health Record can facilitate real-time access to key health information and support improved outcomes. Many Canadian provinces use interoperable Electronic Health Records (iEHRs) to facilitate Health Information Exchange (HIE), but, to date, the clinical use and utility of iEHRs has not been well-described. Objective: Our study's primary objective was to describe the use and reported utility of a provincial iEHR known as the Alberta Netcare Portal (ANP) in four urban Alberta emergency departments (EDs). The secondary objectives were to characterize the time spent using the respective electronic tools, and which aspects were perceived as most useful by ED physicians. Methods: Four EDs were included in the study, two using paper-based ordering (University of Alberta Hospital [UAH] and Grey Nuns Community Hospital [GNCH]) and two using a commercial vendor Clinical Information System (Peter Lougheed Centre [PLC] and Foothills Medical Centre [FMC]). Structured clinical observations of ANP use, semi-structured interviews, and system audit logs analysis were compared at the four sites from October 2014 to March 2016. Results: Observers followed 142 physicians for a total of 566 hours over 376 occasions. The median percentage of observed time spent using ANP was 8.5% at UAH (interquartile range IQR: 3.7% - 13.3%), 4.4% at GNCH (2.4%-4.4%), 4.6% at FMC (2.4%-7.6%), and 5.1% at PLC (3.0%-7.7%). By combining administrative and access audit data, the median number of ANP screens (i.e., results and reports displayed on a screen) accessed per patient visit were 20 at UAH (IQR: 6-67), 9 at GNCH (4-29), 7 at FMC (2-18) and 5 at PLC (2-14) indicating that clinicians found significant value in using ANP while providing ED care. To explore this hypothesis, semi-structured interviews were analyzed using an inductive approach. The themes that emerged from the interviews were that the ANP improved the quality and continuity of care and patient safety. Further enhancements related to medication management would support better outcomes for patients. Conclusions: This study shows that the iEHR is well utilized at the four sites studied and physicians participating in the study perceived ANP had a positive impact on knowledge of their patients, patient safety, and quality and continuity of care. Physicians described high utility and usability of ANP. More study about the clinical impacts of using iEHRs in the Canadian context, including longer term impacts on quality of practice and safety are required.
Background: Participant recruitment, especially for frail elderly hospitalized patients, remains one of the greatest challenges for many research groups. Traditional recruitment methods such as chart...
Background: Participant recruitment, especially for frail elderly hospitalized patients, remains one of the greatest challenges for many research groups. Traditional recruitment methods such as chart reviews or word of mouth notifications for patients in the inpatient setting are often inefficient, low-yielding, time consuming and expensive. Silent Best Practice Alert (BPA) systems have previously been used to improve clinical care but not in clinical research. Objective: This pilot project examined a new EPIC BPA system developed to identify potentially eligible participants in real time to help research teams maximize recruitment accuracy and efficiency of resources. We hypothesized that this tool would reduce the daily screening time, the number of missed potential participants as well as the overall cost needed to recruit the targeted number of patients. Methods: The BPA system was jointly developed by a clinical research and electronic medical records implementation/management team at Partners Healthcare. The was developed and pilot tested in an observational clinical trial to enroll patients admitted for acute exacerbation of chronic pulmonary disease (COPD). We compared the BPA system with our usual method of patient identification (chart reviews and word of mouth referrals) and evaluated for daily screening time, number of missed potential participants as well as the overall cost needed to recruit the targeted number of patients. Results: 559 potentially eligible patients were identified through the two screening methods compared. Of those, 460 patients were identified by both methods, with 99 found by just the Epic Workbench Method and 42 identified by just the silent BPA method. Of the 99 identified by the Epic Workbench, only 12 (12.12%) were considered eligible. Of the 42 identified by the silent BPA method, 30 (71.43%) were considered eligible. A total of 319 “Eligible” patients were identified, and of those 60 participants enrolled in the Emerald-COPD Study. Since implementation, the silent BPA system has found an equivalent of 3 additional patients per week. From the comparison, the silent BPA screening method was shown to be approximately 4 times (23.58%) faster than our previous screening method, projected to save 442.5 hours over the duration of the study. Conclusions: Automation of the recruitment process has allowed us to identify potential participants in real time and avoid missing patients. Silent BPA screening is a considerably faster method which allows for more efficient use of resources. This innovative and instrumental functionality can be specified to the needs of other research studies hoping to utilize the electronic medical records system for participant recruitment.