CareCloud says one EHR environment hit in New Jersey CareCloud says one EHR environment was disrupted for about eight hours as it investigates whether patient data was accessed or exfiltrated.

CareCloud says one EHR environment hit in New Jersey #CareCloud #EHR #UnauthorizedAccess #NewJersey #SEC #DataExposure dysruptionhub.com/carecloud-ehr-outage-new...

If Healthcare is Connected in 2026… Why Are Doctors Still Missing The Full Picture?

Our latest blog: medkaz.com/if-healthcar.... #interoperability #EHR #patients #healthcare

Validate User

📢ICYMI: NORC #ImpSci, Yale School of Medicine, & Elimu Informatics piloted an app that integrates patient-contributed postpartum BP data into the EHR to improve monitoring of hypertensive disorders of pregnancy.

🔗 doi.org/10.1093/jami...
#DigitalHealth #MaternalHealth #EHR #FHIR #PublicHealth

#SoHEU Country Health Profile spotlight 🔦Greece

🇬🇷 Happy National Day, Greece! The 2025 #SoHEU Country Health Profile highlights Greece's push to modernise its #healthsystem, including digitalisation projects and full rollout of electronic medical records #EHR in 2025
👉 tinyurl.com/SOHEU2025

EHR Security and Medical Device Protection in Healthcare | Windows for Business Learn how to strengthen EHR security and medical device cybersecurity to protect patient data and support healthcare with best IT security practices.

Endpoint security for healthcare IT: Protecting devices and patient data #hit #clinicalworkflows #healthcareIT #healthdata #hitsecurity #healthsecurity #EHR #HealthcareInnovation

www.microsoft.com/en-us/window...

🚨🚨TWO new eMERGE papers today that explore genome-informed risk assessments!
#PRS #genomics #EHR

Perplexity introduced Perplexity Health, a personalized tool for Pro and Max subscribers in the US.


Read Full Article: deccanfounders.com/2026/21/n...

#DeccanFounders #AI #HealthAI #Perplexity #MedicalRecords #EHR #Wearables

Ending the Voicemail Bottleneck: How Voice AI Is Transforming Patient Access - MedCity News Beyond simply recording or transcribing messages to lower call volumes, truly autonomous voice AI puts patients in the driver’s seat of their own healthcare. It processes patient requests and informat...

How Voice AI Transforming Patient Access
#AI #EHR #Healthcare

medcitynews.com/2026/03/endi...

My abstract has been accepted for presentation at R/Medicine 2026.

I’ll be my R package, medicalcoder. www.peteredewitt.com/medicalcoder/

Thank you @rconsortium.bsky.social for putting on the conference!

#rstats #RMedicine #HealthInformatics #EHR #ClinicalResearch

PointClickCare Unveils Advanced EHR for Enhanced Senior Care with AI Integration Discover how PointClickCare's new EHR for practice groups integrates AI workflows to elevate care in senior living settings, improving efficiency and outcomes.

PointClickCare Unveils Advanced EHR for Enhanced Senior Care with AI Integration #Canada #Toronto #AI-driven #EHR #PointClickCare

Digitizing Care Delivery with EHR Software in Modern Healthcare EHR software drives efficient, data-driven healthcare by improving clinical workflows, interoperability, patient engagement, and regulatory compliance across...

Digitizing Care Delivery with EHR Software in Modern Healthcare #EHR #healthcare

www.healthcaretechoutlook.com/news/digitiz...

EHR fragmentation offers an opportunity to enhance care coordination and experience Harmonizing electronic health record platforms and their legacy data tames complexity and enables easier patient access to information and greater patient trust in the healthcare system, says NewYork-...

EHR fragmentation offers an opportunity to enhance care coordination and experience #EHR #healthcare

www.healthcareitnews.com/news/ehr-fra...

How EHR Data Helps Behavioral Health Practices Grow and Improve Running a behavioral health practice isn’t just about providing great care — it’s also about understanding what’s working and what isn’t…

How EHR Data Helps Behavioral Health Practices Grow and Improve

itranscript360.medium.com/how-ehr-data...

#HealthTech #EHRIntegration #EHR #healthcare #itranscript360 #MedicalTranscription

Selling AI-driven EHR + practice ops 🏥
• Avg deal $50K
• 20% commission (~$10K)
• Mixed leads + SME demos
• U.S. medical practices

Enterprise healthcare sale.
https://bit.ly/47mUgZD

#HealthTech #EHR #SaaSSales

Hiring Medical Records Specialists 🏥

Seeking experts in DRG coding, EHR systems, document management, and healthcare data to support AI-driven healthcare projects.

Apply now 👇
tinyurl.com/Health-Infor...

#MedicalRecords #HealthInformationManagement #EHR #MedicalCoding #HealthcareJobs #HealthTech

Diagram comparing longitudinal vs encounter-level comorbidity detection using ICD-10 codes across five patient encounters. Top panel (Longitudinal): The patient initially has uncomplicated diabetes (E11.9). Later an encounter includes E11.22 and K72.10, indicating complex diabetes and severe liver disease. Using longitudinal logic, these conditions persist in later encounters even when only E11.9 appears, preserving severity and correctly flagging severe liver disease. Bottom panel (Encounter-level): Each encounter is evaluated independently. Diabetes changes from uncomplicated → complex → back to uncomplicated when E11.9 reappears, and severe liver disease is never flagged because its code does not repeat. Message: Ignoring patient history can downgrade severity or fail to identify comorbidities.

Graphic showing how the medicalcoder R package controls comorbidity detection using the flag.method argument. Left side: A sample dataset of patient encounters with variables patid, encid, icd10code, and poa, containing ICD-10 codes such as E11.9, K72.10, and E11.22. Below the dataset are two example R code blocks calling medicalcoder::comorbidities(): flag.method = "current" (default), producing encounter-level comorbidity flags. flag.method = "cumulative", producing patient-level flags that preserve comorbidities across encounters. Right side: the medicalcoder hex logo and labels explaining that current = encounter-level and cumulative = longitudinal history preserving. The graphic illustrates that longitudinal comorbidity tracking in medicalcoder is controlled by a single argument.

Same ICD codes. Same patient. Different risk profiles.

Encounter-level comorbidity logic assumes ICD codes are re-reported every visit. They usually aren’t.

medicalcoder handles this

📦install.packages("medicalcoder")

#rstats #HealthInformatics #EHR #ClinicalResearch #RiskAdjustment #PublicHealth

RE: https://mstdn.social/@hkrn/116194398720416621

#Cerner is up for grabs from Oracle? Aside from Epic (the privately held #EHR software #saas), who'd be in the market?

The image shows three graphs labeled A, B, and C, titled 'WCMC in-site', 'LMH validation', and 'BMH validation'. Each graph plots 'Sensitivity' vs. '1 - Specificity', comparing 'XGBoost', 'Without blood test', 'Only BP', 'Without BP', 'RF', and 'LR' models with AUC values.

Dynamic, short-term prediction of #Preeclampsia in late gestation using routinely collected #EHR data was feasible and demonstrated strong performance and generalizability in a multisite cohort study.

ja.ma/3ORTvS7

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study Background: Chronic back pain is a severe health condition with underlying biopsychosocial factors that make diagnosis difficult, and pain chronicity has been shown to be an important variable for studying patient outcomes. Due to the absence of standardized criteria, pain chronicity needs to be manually annotated by clinicians in electronic health records (EHRs), which is not only time consuming but also has the potential to introduce variability in analysis and interpretation among practitioners. Objective: Pain chronicity is not typically recorded in EHRs and currently needs to be manually annotated by experts. Using a dataset from an interdisciplinary spine clinic consisting of 386 patients manually annotated for pain chronicity by clinical experts, this study has two objectives: (1) to examine the relationship between expert-annotated chronicity and social determinant variables present in EHRs and (2) to evaluate the #feasibility of extracting pain chronicity from the EHR without expert annotation. Methods: We used a supervised machine learning model, specifically univariate regression, to examine associations between clinician-annotated pain chronicity values and the structured variables present in EHRs. Next, we trained a random forest model to predict pain chronicity by using both structured and unstructured data extracted by clinical Text Analysis and Knowledge Extraction System, a natural language processing (NLP) tool. The features extracted included clinical keywords; duration of pain reported; and the International Classification of Diseases, Tenth Revision codes. The model was assessed using the Pearson correlation coefficient and mean absolute error (MAE). Results: The study analyzed 386 patients (mean age 60.2 years, SD 16.1 years and median age 62.0 years, IQR 48.8-72.0 years) from the San Francisco Bay Area, with 62.7% (n=242) identifying as women. Our univariate regression analysis identified structured EHR variables associated with pain chronicity, which include pain severity before the last visit (P=.006), number of imaging orders (P=.006), number of visits to the neurology department (P=.01), and Medi-Cal insurance coverage (P=.03). Our random forest model using structured data showed a strong correlation of 0.887 (P

JMIR Formative Res: Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study #ChronicPain #BackPain #HealthRecords #PainManagement #EHR

A graphic with a blue and purple gradient background. A white semi-circle in the top left corner contains the logo for the 2026 ACMG Annual Clinical Genetics Meeting, March 10-14, Exhibit dates March 11-13, Baltimore Convention Center, Baltimore, MD. The PhenoTips logo is in the bottom left corner. A dashed white line snakes around text reading "We're exhibiting at #ACMGMtg2026. Meet us in Baltimore" and ends in a white location marker above bold text reading "Booth #417"

Will you be attending #ACMGMtg2026? Visit Booth #417 to meet our team and explore our #GenomicHealthRecord.

Learn about our integrations with any #EHR / #EMR & our regional and national genomic digitization projects worldwide.

Book time with us: t.co/ZaNxKDLspV

NEW: Unlocking Practice Patterns at Scale: A Framework for Developing Clinical Insights Using Epic's Cosmos www.thieme-connect.de/products/ejo...

#MedSky #HealthIT #DigitalHealth #EHR

AI in Healthcare: Navigating the Risks with Expert Guidance - Health IT Consult AI in healthcare is not a question of if — it's a question of how. The organizations that thrive will be those that embrace innovation with expert guidance by their side.

🙋 Is your healthcare organization ready to adopt AI safely?

See how they do it 👉 healthitconsult.com/ai-in-health...

#HealthITConsult #HealthcareAI #AIStrategy #DigitalHealth #HealthIT #EHR #CyberSecurityHealthcare #HealthcareTransformation

I don’t know…and this is the “plain language” version.

But if I, as an adult with solid command of English can’t understand it easily, then what do people do who don’t speak English? What about homeless or mentally ill people?

It says there is a deadline of April 30th? #onpoli #EHR

If you have ever received one of these, or know what it means, can you tell me?

And yes Reporters it would help if you would ask the Ontario Privacy office and spread the word that even for highly educated patients, this is an extremely confusing document.
#onpoli #cdnpoli #privacy #EHR

Vendor Notebook: New announcements show connected care innovation New this month: Smart technology collaborations aim to enhance inpatient care, advance patient coordination and reduce clinical burdens with advanced AI.

Vendor Notebook: New announcements show connected care innovation #EHR #HIT #healthcareIT #HealthcareInnovation #Healthcare

www.healthcareitnews.com/news/vendor-...

Are your systems talking to each other, or are they working in silos? 📉 Disconnected data leads to provider burnout and patient frustration. As a leading Healthcare IT Advisory, we help systems master Health Data Management and EHR optimization. We ensure your technology works for your providers, not the other way around. Maximize your ROI and minimize clinical friction with expert Health IT Consulting. 🔗 See how we can help: https://healthitconsult.com/ #Interoperability #EHR #HealthData #HealthITConsulting #HealthcareManagement #DigitalHealth

Are your systems talking to each other, or are they working in silos? 📉

Maximize your ROI and minimize clinical friction with expert Health IT Consulting.

🔗 See how we can help: healthitconsult.com

#Interoperability #EHR #HealthData #HealthITConsulting #HealthcareManagement #DigitalHealth

Croissance et analyse du marché des services de santé ambulatoires 2035 La taille du marché des DSE ambulatoires a été estimée à 6,29 (milliards USD) en 2023. L’industrie du marché des DSE ambulatoires devrait passer de 7,51 (milliards USD) en 2024 à 30,9 (milliards USD) ...

Digital record systems are modernizing outpatient care & improving clinical documentation. #EHR #DigitalHealth www.wiseguyreports.com/fr/reports/a...

2035 年の外来 Ehr 市場の成長と分析 外来用エールの市場規模は、2023年に6.29億米ドルと推定されています。外来用エール市場産業は、2024年の7.51億米ドルから、2032年までに309億米ドルに成長すると予想されています。

🏥 Ambulatory EHR systems improve outpatient care management. Explore: www.wiseguyreports.com/ja/reports/a... #EHR

How Virtual Medical Scribes are Eliminating Physician Burnout and Improving Chart Accuracy Learn how virtual medical scribes reduce burnout and save clinicians hours daily by automating clinical notes.

The Complete Guide to Virtual Medical Scribes: AI vs. Human and EHR Integration.

shorturl.at/zJfAL

#guide #VirtualMedicalScribes #ai #ehr #blog #read #MindInventory