Correction: Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study  

JMIR Formative Res: Correction: Personalized Diabetes Treatment Support Using Large Language Models Fine-Tuned on Electronic Health Records: Development and Evaluation Study #Diabetes #HealthTech #PersonalizedMedicine #AIinHealthcare #ElectronicHealthRecords

Day to day, teams actually lean on EHRs, secure messaging, task dashboards, and portals na to keep care moving, hát.

#ElectronicHealthRecords #SecureMessaging #Telehealth

🏆 #PreprintOfTheWeek on #ScienceOpen
"Optimizing Cloud Infrastructure for Large-Scale Electronic Health Record Systems"

Congrats from the Editors of SO #Preprints to the authors Alex Meyer, Max Lillian.

Discover the full preprint.
#CloudOptimization #ElectronicHealthRecords

Image: file folders with a laptop; Wisc.Jobs

Dept of Health Svs is hiring an #ElectronicHealthRecords #EHR #TechnicalDirector to manage & implement the DHS Connect system (Oracle Health Millennium health record software). $48-$55.07/hr +benefits. Apply by 2/6. #WIjobs #GovJobs #AdminJobs https://ow.ly/A34b50Y6soG

🌍 24th Global Summit on Nursing Education & Health Care
📍 Tokyo, Japan |
🗓 October 19–20, 2026
🔗 Website:
nursingeducation.inovineconferences.com

#digitalhealthliteracy #disasternursing #humanitariannursing #electronichealthrecords #emergencynursing

Pit River Health Service cyber incident disrupts records access in California Pit River Health Service in California says a cyber incident disrupted EHR and Dentrix access; some data was copied as systems are restored.

Pit River Health Service cyber incident disrupts records access in California #PitRiverHealthService #CybersecurityIncident #ElectronicHealthRecords #Dentrix #DataExfiltration #California dysruptionhub.com/pit-river-health-cyber-i...

Image: file folders with a laptop; Wisc.Jobs

Dept of Health Svs is hiring the #Director for the Office of #ElectronicHealthRecords to manage the operation of an EHR system at seven DHS facilities. Up to $59.88 /hr based on qualifications +great benefits. Apply by 11/24. #WIjobs #govjobs #RecordsJobs https://ow.ly/H7NO50XuljK

New Editorial Explores the Double-Edged Sword of AI Scribes in Health Care | Newswise A new editorial published in JMIR Medical Informatics examines the rapid rise of ambient artificial intelligence (AI) scribes—technologies designed to automate clinical documentation and ease the admi...

New Editorial Explores the Double-Edged Sword of AI Scribes in Health Care
www.newswise.com/articles/new...
#ambientaiscribes #ClinicalDocumentation #LargeLanguageModels #ElectronicHealthRecords #medicolegalimplications #patientsafety

Cedars-Sinai Advances Knowledge of Machine Learning and Big Data in Medicine | Newswise Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using machine learning and big data to improve healthcare and medical research. Both s...

Cedars-Sinai Advances Knowledge of Machine Learning and Big Data in Medicine
www.newswise.com/articles/ced...

#machinelearning #BigData #MedicalResearch #ElectronicHealthRecords #bloodsugarlevels #AcademicMedicine

Five popular open-source large language models (LLMs) and six different extraction methods were compared.
doi.org/10.1111/epi....

#epilepsy #Epilepsia #ILAE #electronichealthrecords #largelanguagemodels #naturallanguageprocessing #LLM

Delivering an Electronic Health Record Based Educational Intervention Promoting Peri-Operative Non-Pharmacological Pain Care as Part of a Randomized Controlled Trial: Mixed Method Evaluation of Inpatient #nurses’ Perspectives Background: Best practice guidelines recommend educating surgical patients about non-pharmacological pain care (NPPC) techniques that can be used in addition to pain medication for peri-operative pain management, given the risks for opioid misuse following surgery. As part of the parent Non-pharmacologic Options in post-operative Hospital-based and Rehabilitation pain Management (NOHARM) clinical trial, we implemented the Healing After Surgery initiative, which leveraged the Epic electronic health record (EHR) to provide patients with education on NPPC techniques peri-operatively. We disseminated educational materials directly to patients via the EHR patient portal and prompted patients to select the techniques they were most interested in using, which auto populated the EHR so that their care team could view their preferences. We also built clinical decision support (CDS) elements in the EHR to prompt and support inpatient #nurses in providing patients with education and reinforcement for using their preferred NPPC techniques. Print materials, a website, a DVD, videos on hospital televisions, a toll-free number, and Zoom-based group calls provided additional education on NPPC techniques. Objective: The present study evaluated #nurses’ perceptions of barriers and facilitators to implementing the EHR-based Healing After Surgery initiative. Methods: We invited inpatient #nursing leaders and bedside #nurses to participate in a semi-structured interview. Inpatient #nursing leaders were invited to complete a brief survey that asked them to rate their agreement with seven items using a numeric rating sale (1 = not at all, 10 = a great deal). Results: Interview findings from 29 #nurses revealed: 1) #nurses gravitated towards providing NPPC techniques they were familiar with, 2) the initiative was patient-centric with opportunities to better engage patients, and 3) #nurses experienced challenges implementing and prioritizing the intervention in the inpatient setting due to competing demands in a pandemic and post-pandemic environment. Interviews revealed mixed effectiveness of implementation strategies. We received survey responses from 47 #nursing leaders who indicated that their staff knew about the Healing After Surgery initiative (mean = 7.53, SD= 1.77) and what they were expected to do (mean = 7, SD = 1.88). They thought the Healing After Surgery initiative supported patients’ pain management needs (mean = 6.76, SD = 2.24), endorsed it as a priority (mean = 7.02, SD = 2.56), and encouraged staff to support it (mean = 5.98, SD = 2.78). They indicated staff experienced some burden supporting the initiative (mean = 3.93, SD = 2.47), but supported some variation of the initiative continuing once the parent trial ended (mean = 7.72, SD = 2.62). Conclusions: #nurses understood the intervention’s benefit but struggled to implement unfamiliar NPPC techniques and prioritize the initiative due to other clinical demands. Additional implementation strategies may be needed to better engage patients and facilitate intervention delivery. Clinical Trial: ClinicalTrials.gov NCT05166356, https://clinicaltrials.gov/study/NCT05166356

New in JMIR Nursing: Delivering an Electronic Health Record Based Educational Intervention Promoting Peri-Operative Non-Pharmacological Pain Care as Part of a Randomized Controlled Trial: Mixed Method Evaluation of… #ElectronicHealthRecords #PainManagement #NonPharmacologicalCare #Surgery #Nursing

A white graphic with a laptop open to PhenoTips' Genomic Health Record's pedigree maker, showing a 4-generation, complex, annotated pedigree. Overlaid on top of the computer are multiple blue icons: a strand of DNA, a cancer awareness ribbon, a user folder, a pedigree, and a sending mail icon. Text to the right reads, "Center genomic care with the EHR-integrated Genomic Health Record."

#ElectronicHealthRecords are not designed for #genetics, but a #GenomicHealthRecord is.

Embedded within your #EHR, the #GHR is a searchable & structured database of patient records linked to family records, complete with all the tools necessary for digitization.

➡️ phenotips.com/core-genomic...

Implementing an Electronic Health Record System in a Tertiary Care Surgical Oncology Setup A Mixed Method Analysis
Abegunasekara, A., Asanthi, J. et al.
Paper
Details
#ElectronicHealthRecords #SurgicalOncology #TertiaryCareImplementation

New study maps four key pathways to Alzheimer’s disease – BioNews Central Researchers have identified four distinct pathways leading to Alzheimer's disease by analyzing electronic health records, providing new insights into how the condition develops over time. ...

Researchers have identified four distinct #pathways leading to #AlzheimersDisease by analyzing #ElectronicHealthRecords, providing new insights into how the condition develops over time. 
#CognitiveImpairment #Dementia

Study using All of Us data reveals major sociodemographic gaps in family health history access and EHR capture - risking wider health inequities in cancer and diabetes care. bit.ly/4eEDqb1 #GIMO #BreastCancer #ColorectalCancer #Diabetes #ElectronicHealthRecords

#HealthcareInnovation #DigitalHealth #Telemedicine #ElectronicHealthRecords #HealthTech #AIinHealthcare #HealthcareTechnology #DigitalTransformation #PatientCare #MedicalTechnology

Strategies and Tools for Electronic Health Records and Physician Workflow Alignment: Protocol for a Scoping Review <div xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="section"> <a class="named-anchor" id="d15593805e262"> <!-- named anchor --> </a> ...

'Strategies and Tools for #ElectronicHealthRecords and Physician Workflow Alignment: #Protocol for a Scoping Review' - an @jmirpub.bsky.social #Research Protocols article on #ScienceOpen:

🔗 www.scienceopen.com/document?vid...

Every click counts—learn how to streamline your EHR use and focus more on patient care.

Learn more here: www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

Outcomes of an Advanced Epic Personalization Course on Clinician Efficiency through Use of Electronic Medical Records: Retrospective Study Background: Since Singapore’s first migration to Epic in 2022, we have been conducting an advanced Epic personalisation course twice a year for healthcare professionals with at least 3 months of experience using Epic. Electronic Medical Records education is an under-recognised pillar in reducing Health Information Technology-related stress and burnout. Objective: The course intent is to improve clinician efficiency through customisation and personalisation of Epic interfaces. Our hypothesis was that trained clinicians, compared to their colleagues, would demonstrate significant quantitative improvements in Epic utilisation after our course. Methods: We performed a retrospective analysis from July 2022 to January 2024, of 17 clinicians amongst 77 individuals who attended our course. Course recruitment was done through electronic digital mailers sent out on the local hospital announcement channels. Interested clinicians were able register for our course via the National University Of Singapore website. Our one day course involves physical lessons and interprofessional case-based discussions, emphasising a wide range of high-yielding Epic functionalities with practice exercises, such as drafting referral letter templates. Three months of pre-and-post course Epic usage statistics of the trained clinicians were retrieved based on aggregate data provided by Epic Singapore. Performance metrics included documentation length, time spent in Epic functionalities and usage of SmartPhrases, order sets and preference lists. Results: At 3 months post-course, documentation length decreased by 45.8% versus an increase of 22.2% among controls. Trained clinicians had a 2.47 fold increased usage of order sets from 16.2% to 40% and a 49.9% increase in orders from preference lists after the course from 35.1% to 52.6%. In total, trained clinicians had a 1.8 fold increased usage in orders from preference list or order sets after the course from 51.4% to 92.6%. The number of SmartPhrases created by trained clinicians was 5.64 times more than controls in addition to a 5.57 fold more utilisation of Quick Filters than controls. Moreover, time in Chart Review per day decreased by 29.3% among trained clinicians versus an increase of 14.6% among controls. Compared to controls, trained clinicians spent 36.7% less time in Epic system per day, 56.6% less time on Notes per day, and 57.5% less time on Orders per day. Conclusions: Overall, trained clinicians became more efficient in their use of Epic, such as reduced time spent in various functionalities of Epic. Increased employment of Smart Tools including SmartPhrases and quick filters was also observed amongst trained clinicians, which was effective in reducing total usage time. Our results thus demonstrated broad improvements across multiple physician efficiency metrics for participating clinicians of our advanced Epic personalisation course. This may contribute to improving mental health for healthcare professionals and enhanced productivity within healthcare systems.

JMIR Formative Res: Outcomes of an Advanced Epic Personalization Course on Clinician Efficiency through Use of Electronic Medical Records: Retrospective Study #Healthcare #ElectronicHealthRecords #ClinicianEfficiency #EpicCustomization #HealthIT

EHRs are more than digital charts—learn how to use them effectively in clinical practice.

Learn more here: www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

Struggling with EHRs? This tutorial helps medical professionals work more efficiently with digital systems.

Learn more here: www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

Mastering Electronic Health Records Tutorial - For Medical Professionals
Learn more here:
www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

Using Real Electronic Health Records in Undergraduate Education: Roundtable Discussion Background: Simulated electronic health records (EHRs) are used in structured teaching for healthcare students. In part, this addresses inconsistent student exposure to, and participation with EHRs whilst on clinical placements. However, simulated records are poor replacements for the complexity and volume of data encountered in real EHRs. Whilst routinely collected healthcare data is often used for research, secondary use does not extend to education. Within our project we are exploring the perceptions, governance and ethics required to support the use of donated real patient records within teaching. Objective: To explore the perspectives of healthcare professionals regarding the use of real patient records to deliver interprofessional EHR education to undergraduate healthcare students. Methods: We held 90-minute group discussions with ten healthcare professionals from nursing, pharmacy, medicine, and allied health disciplines. Results: There was consensus on the need to upskill healthcare students in the use of EHRs. Participants emphasised the value of teaching general EHR competencies and transferable skills to overcome the diversity in EHR systems. They highlighted key limitations in current EHR teaching due to accessibility issues, disparities within clinical teaching and curricular gaps on important topics such as clinical documentation and coding. Highlighted benefits of real EHRs in structured teaching included learning from the complexities and inaccuracies of real patient data, grasping real-world timeframes and better appreciation of multidisciplinary interactions. Concerns included exposing individual clinicians to unfounded scrutiny as well as the potential consequences of incidental findings within EHRs. The ethical implications of overlooking perceived errors within EHRs versus the impracticality of acting on these findings were discussed in detail. To mitigate concerns, it was suggested that data donors would be clearly informed and consented ensuring they understand that they will not be re-contacted should any such errors be found. Conclusions: Innovative solutions are needed to re-align healthcare education with clinical practice in rapidly evolving digital environments. Real patient records are the best resource for teaching students to competently handle complex and abundant real-world data. Our reflections highlight the processes and safeguards to consider when using real patient records to deliver EHR education to healthcare students.

JMIR Formative Res: Using Real Electronic Health Records in Undergraduate Education: Roundtable Discussion #ElectronicHealthRecords #HealthcareEducation #EHRs #InterprofessionalEducation #HealthcareProfessionals

Electronic Health Records can support smarter care—if you know how to use them well.

Learn more here: www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

Mastering EHR systems saves time and improves care. Start here with this practical tutorial.

Learn more here: www.youtube.com/watch?v=9ZQh...

#ElectronicHealthRecords #Technology #SkyHealthAcademy

“An automation framework for clinical codelist development validated with UK data from patients with multiple long-term conditions.” #polypharmacy #multimorbidity #ElectronicHealthRecords ‪@dynairx.bsky.social
doi.org/10.1186/s128...

How Virtual Medical Assistants Improve EHR and EMR Data Entry Processes Discover how Virtual Medical Assistants automate EHR and EMR data entry, boosting accuracy and efficiency in healthcare practices.

How Virtual Medical Assistants Improve EHR and EMR Data Entry Processes
staffingly.com/how-virtual-...

#VirtualMedicalAssistants #EHRDataEntry #EMRDataEntry #HealthcareAutomation #MedicalDataEntry #VirtualAssistantsInHealthcare #HealthTech #ElectronicHealthRecords #AutomatedHealthcare

Looking forward to this upcoming talk @oxforddemsci.bsky.social
Electronic Health Records for 20% of the Catalan population studying multimorbidity & mortality

#Demography #Morbidity #HealthInequality #EHR #ElectronicHealthRecords #DigitalHealth