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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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Background: Early efforts to incorporate telemedicine in the Emergency Department (ED) focused on providing remote consultation services to EDs with limited resources. With continued ED overcrowding,...
Background: Early efforts to incorporate telemedicine in the Emergency Department (ED) focused on providing remote consultation services to EDs with limited resources. With continued ED overcrowding, some EDs have used telemedicine to increase providers during surges of patient visits and offer scheduled “home” face to face on-screen visits. We used remote on-screen telemedicine providers in the “screening-in-triage” role during hours in which our ED did not previously have in-person screening. Objective: Compare efficiency and patient safety of in-person screening vs telescreening Methods: This is a retrospective, matched cohort study to compare the performance of real-time remote telescreening to in-person screening at a single urban academic ED. 337 screening hours were compared to 315 equivalent proximate hours of telescreening. Participants were selected from an ED convenience sample. Using electronic medical records we compared patients screened per hour, rates of patients leaving without being seen (LWBS), rates of analgesia ordered and proportion of patients with chest pain being ordered a standard set of tests and medications. Results: Over the 22 weeks of our study in-person screeners evaluated 1933 participants over 337 hours, 5.7 patients-per-hour, while telescreeners saw 1497 patients over 315 hours, 4.9 patients per hour, (p<0.001). However, for the final three weeks of the evaluation, the rates were not statistically different (5.5 v 5.3) (p=0.66). Fewer patients LWBS during in-person screening compared to telescreening hours, (2.6 vs. 3.8%; p=0.03). Yet, when compared to prior year date and time-matched data, implementation of telescreening from 1-3am, a time when in-person screening was not used, decreased the rate of LWBS from 25.1% to 4.5%, p<0.001. Analgesia was ordered more frequently by telescreeners, 51 vs 32%, p<0.001. Screeners ordered a full chest pain bundle for those presenting with chest pain and triaged to an ESI level 3-5 34% of the time compared to telescreeners ordering 37%, p=0.18. Conclusions: While the rate of patients seen per hour during telescreening was lower throughout the course of our study, this effect was driven by early differences and by the last three weeks the rates of patients screened was not statistically different between in-person and telescreening. Significantly, adding telescreening during 1-3am on weekdays, a time when screening did not previously occur, we were able to decrease the rates of LWBS from 25.1% to 4.5%. More analgesia was ordered by telescreeners but this is driven by established practice patterns of the telescreening providers. No difference was observed for rates of ordering a standard set of labs, imaging and medications for those screened with a chief complaint of chest pain. Telescreening was an effective and safe way for this ED to expand the hours in which patients were screened by a health care provider in triage.
Background: Informed consent is a complex process to help patients engage in care processes and reach the best treatment decisions. There are many limitations to the conventional consent process that...
Background: Informed consent is a complex process to help patients engage in care processes and reach the best treatment decisions. There are many limitations to the conventional consent process that is based on oral discussion of information related to treatment procedures by the healthcare provider. A conclusive body of research supports the effectiveness of multimedia patient decision aids (PtDAs) in the consent process in terms of patient satisfaction, increased knowledge about the procedure, reduced anxiety level, and higher engagement in the decision-making. little information is available about the effectiveness of multimedia PtDAs in the consent process of invasive therapeutic procedures such as the peripherally inserted central venous catheter or PICC. Objective: This study examined the effectiveness of a multimedia PtDA to supplement the consent process of the PICC for patients in 10 acute and intensive care units in terms of knowledge recall, knowledge retention, satisfaction with the consent process, and satisfaction with the multimedia PtDA. Methods: This is a pre-post study that included 130 patients for whom a PICC was ordered. Patients in the control group (N= 65) received the conventional consent process for the PICC, while patients in the intervention group (N= 65) received the multimedia PtDA to support the consent process of a PICC. All patients were surveys for knowledge recall and retention about the procedure and satisfaction with the consent process. Patients in the intervention group were also surveyed for their satisfaction with the multimedia PtDA. Results: In comparison to the control group, the intervention group scored around 2 points higher on knowledge recall (t = 4.9, P = .0001) and knowledge retention (t = 4.8, P = .0001). All patients in the intervention group were highly satisfied with the multimedia PtDA with a mean score above 4.5 out of 5 on all items. Items with the highest mean scores were related to the effect of the multimedia PtDA on knowledge retention (mean=4.9, SD=0.2), patient readiness (mean=4.8, SD= 0.5), and complete understanding of procedure complications (mean=4.8, SD= 0.4) and patient role in maintaining the safety of the PICC (mean=4.8, SD= 0.5). Patients in the two groups were highly satisfied with the consent process. However, 10 (out of 65) patients in the control group (15%) reported the followings were omitted from the discussion: patient and provider role in the safety of the PICC, other treatment options, and common side effects. Two of the patients also commented that they were not ready to engage in the discussion. Conclusions: Multimedia PtDA is an effective standardized, structured, self-paced learning tool to supplement the consent process of the PICC and improve patient satisfaction with the process, knowledge recall, and knowledge retention.
Background: Electronic medical records (EMRs) contain a wealth of information that can support data-driven decision making in healthcare policy design and service planning. Although research using EMR...
Background: Electronic medical records (EMRs) contain a wealth of information that can support data-driven decision making in healthcare policy design and service planning. Although research using EMRs has become increasingly prevalent, challenges such as coding inconsistency, data validity and lack of suitable measures in important domains still hinder the progress. Objective: Our objective is to design a structured way to process records in administrative EMR systems for health services research and assess validity in selected areas. Methods: Based on a local hospital EMR system in Singapore, we developed a structured framework for EMR data processing, including standardization and phenotyping of diagnosis codes, construction of cohort with multi-level views, and generation of variables and proxy measures to supplement primary data. Disease complexity was estimated by Charlson Comorbidity Index (CCI) and Polypharmacy Score (PPS), while socioeconomic status (SES) was estimated by housing type. Validity of modified diagnosis codes and derived measures were investigated. Results: Visit level (N=7,778,761) and patient level records (n=549,109) were generated. Diagnosis codes were standardized to ICD-9-CM with a mapping rate of 97.5%. 97.4% of the ICD-9-CM codes were phenotyped successfully using Clinical Classification Software (CCS). Diagnosis codes that underwent modification (truncation or zero-addition) in standardization and phenotyping procedures had the modification validated by physicians, with validity rates of more than 90%. Disease complexity measures (CCI and PPS) and SES were found to be valid and robust after a correlation analysis and a multivariate regression analysis. CCI and PPS were correlated with each other, and positively correlated with healthcare utilization measures. Larger housing type was associated with lower government subsidies received, suggesting association with lower SES. Profile of constructed cohorts showed differences in disease prevalence, disease complexity and hospital utilization was found in those aged above 65 and those below. Conclusions: The framework proposed in this study would be useful for other researchers working with EMR data for health services research. Further analyses would be needed to better understand differences observed in the cohorts.