#PostImplementation
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #SCCT2026 #CVRad #radiology
July 11, 2026 at 3:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #SCCT2026 #CVRad #radiology
July 13, 2026 at 3:15 AM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #CT #ML #MachineLearning
August 8, 2026 at 11:15 AM
This is a big effect

increased transplants for Black transplant candidates after GFR formula adjustment

jamanetwork.com/journals/jam...

in @jamainternalmed.com

#NephSky
March 9, 2026 at 8:02 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #ESSR2026 #ESSR26 #MSKRad #radiology
June 18, 2026 at 7:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #UltraCon2026 #ultrasound #USRad #radiology
May 27, 2026 at 3:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #ESSR2026 #ESSR26 #MSKRad #radiology
June 20, 2026 at 7:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #CIR2026 #radiología #radiology
May 16, 2026 at 11:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #CT #ML #MachineLearning
August 16, 2026 at 11:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #ChestRad #ML #MachineLearning
August 14, 2026 at 7:15 PM
Quantifying postimplementation AI-radiologist concordance for pulmonary embolism detection on pulmonary angiography exams https://doi.org/10.1148/ryai.250017 #CT #ChestRad #MachineLearning
August 11, 2026 at 7:15 PM
minimize the burden of healthcare... "Self-scheduling was linked to increased screening mammography completion rates postimplementation when compared to traditional scheduling." pubmed.ncbi.nlm.nih.gov/40044309/
Using Self-Scheduling to Improve Screening Mammography Completion Rates - PubMed
Self-scheduling was linked to increased screening mammography completion rates postimplementation when compared to traditional scheduling.
pubmed.ncbi.nlm.nih.gov
March 12, 2025 at 10:19 AM
Post-implementation reviews are crucial for assessing new systems! 🚀 They help identify cost savings, efficiency, and experience improvements. Focus on KPIs, gaps, and change management. Boost your digital transformation with us! #DigitalTransformation #PostImplementation #InternalAudit #AltumWave
March 19, 2025 at 1:15 PM
NEW: Implementation of #PassiveDeterioration Index Alerts in an Intermediate Care Unit: A Failed Early Warning System Strategy www.thieme-connect.de/products/ejo...

#MedSky #MachineLearning #AlertFatigue #DecisionSupport #CDS
August 30, 2025 at 9:56 PM
JMIR HumanFactors: Examining Telemedicine Adoption After the COVID-19 Pandemic and Evaluating the Impact of a Virtual Hospital on Clinician Engagement: Longitudinal Survey Study
Examining Telemedicine Adoption After the COVID-19 Pandemic and Evaluating the Impact of a Virtual Hospital on Clinician Engagement: Longitudinal Survey Study
Background: After the emergence of telemedicine as a major health care delivery mode during the COVID-19 pandemic, Sheba Medical Center (SMC) rapidly transitioned its outpatient clinics to telemedicine. A postimplementation satisfaction study revealed that while nearly 90% of patients reported a positive experience, only 38% of clinicians expressed high satisfaction. SMC soon established Sheba BEYOND, a dedicated virtual hospital. This initiative was accompanied by extensive efforts to improve the telemedicine experience. In 2025, a follow-up survey addressing clinician satisfaction and acceptance was conducted. Objective: This study aimed to explore whether clinician satisfaction improved and which barriers to clinician engagement persisted. Methods: An anonymous survey was distributed via a link to the staff of SMC’s outpatient clinics. The survey inquired about user experience with the telemedicine digital platform, integration in workflow, barriers to use, perceived benefit to patients, and overall satisfaction. Clinicians who never or rarely perform telemedicine visits were classified as nonusers; all others were classified as users. The questionnaire included 21 questions, 2 additional questions for nonusers, and 5 additional questions for users. Overall satisfaction was ranked on a 10-point Likert scale. Descriptive statistics were calculated using SPSS (version 29.02; IBM Corp) and Microsoft Excel. A chi-square test of independence was used for categorical variables. We used a 2-tailed t test, with a probability of
dlvr.it
September 9, 2026 at 8:14 PM
New in JMIR Nursing: Inpatient #nurses’ Anticipatory Perspectives on Assistive Robots: Qualitative Study #Nursing #Healthcare #AssistiveRobots #PatientCare #NurseLife
Inpatient #nurses’ Anticipatory Perspectives on Assistive Robots: Qualitative Study
Background: Assistive robots have been proposed to support #nursing work by offloading routine, logistical, and physically demanding tasks. However, existing research has largely focused on postimplementation acceptance or usability, with fewer studies examining how #nurses conceptualize assistive robots before routine deployment, particularly in settings where exposure remains limited. Objective: This study aimed to explore inpatient #nurses’ anticipatory perspectives on assistive robots and to examine how perceived benefits, concerns, and implementation conditions are constructed at the preimplementation stage. Methods: A qualitative descriptive study was conducted using semistructured, face-to-face interviews with 16 registered #nurses aged 21 to 32 years from 4 general medical wards in a public tertiary hospital in Singapore. At the time of data collection, assistive robots had not been routinely implemented; participants’ exposure was limited to pilots, demonstrations, and indirect sources. Interview transcripts were analyzed using reflexive thematic analysis. Results: Participants’ accounts reflected anticipatory acceptance characterized by cautious optimism regarding the potential of assistive robots to support #nursing work, alongside concurrent concerns about safety, professional identity, relational care, and implementation feasibility. Four themes were developed: anticipatory optimism shaped by indirect exposure; negotiating uncertainty, safety, and professional boundaries; imagining assistive robots as workload and workflow support; and conditions for responsible implementation. Concerns centered on professional identity, patient safety, ethical boundaries, loss of human touch, technical reliability, cost-effectiveness, and organizational feasibility. Participants viewed assistive robots as acceptable only if they were integrated into #nursing workflows, preserved clinical judgment and relational care, and were supported by training, technical infrastructure, leadership commitment, and clear governance. Conclusions: #nurses’ anticipatory perspectives suggest that acceptance of assistive robots depends not only on perceived usefulness, but also on alignment with professional values, patient safety, relational care, and organizational readiness. Early #nurse involvement, human-centered implementation, structured training, and clear governance are needed to ensure that assistive robots augment rather than undermine #nursing practice.
dlvr.it
August 26, 2026 at 2:12 PM
JMIR HumanFactors: Anesthesia Providers’ Perspectives on the Redesigned Philips Acoustic Alarm System: Qualitative Pre- and Postimplementation Study
Anesthesia Providers’ Perspectives on the Redesigned Philips Acoustic Alarm System: Qualitative Pre- and Postimplementation Study
Background: Alarm fatigue caused by frequent or false alarms poses a persistent threat to patient safety. Despite technological progress, alarm acoustics remain largely unchanged and are often perceived as disruptive. To address this, Philips redesigned its patient monitoring alarm sounds through a user-centered approach aimed at improving priority differentiation and reducing emotional strain. Objective: This study provides insights into human-technology interaction by examining anesthesia providers’ experiences with the original and updated alarms, with a focus on emotional responses, #usability, and guidance for the user-centered design of future clinical alarm systems. Methods: This single-center qualitative study involved anesthesia providers who completed an online questionnaire before and after the implementation of the updated Philips alarms. Only those who completed the pre-implementation phase participated in the postimplementation phase. The questionnaire included 4 open-ended questions addressing perceptions of the current alarm sounds, suggestions for improvement, design expectations, and attitudes toward an alarm-free operating room. Responses were analyzed using thematic analysis to identify key #usability and emotional response themes. Results: A total of 90 eligible anesthesia providers participated in the preimplementation phase, and 77 (85.6%) participated in the postimplementation phase. Positive emotional responses increased in the postimplementation phase, whereas concerns regarding alarm functionality also became more prominent. Before the introduction of the updated alarm sounds, participants predominantly called for softer sounds. Following implementation, the most frequently expressed concern shifted to the need for clearer prioritization of alarms. Across both phases, the primary expectation remained the alarms’ ability to effectively capture attention. The concept of an alarm-free operating room elicited concerns about increased workload and potential risks to patient safety. Conclusions: The redesigned alarm sounds were perceived more positively in terms of emotional acceptance; however, they did not improve the recognition of alarm priority. The modest acoustic changes did not address the broader issue of alarm overload. Suggestions such as visual-only alerts for low-priority alarms show potential but must be balanced with patient safety standards. Future alarm development should combine user feedback with expert-driven and evidence-based approaches to improve both #usability and clinical effectiveness.
dlvr.it
April 1, 2026 at 3:24 PM
New in JMIR: Postimplementation Evaluation in Assisted Living Facilities of an #eHealth ##Medical Device Developed to Predict and Avoid Unplanned #Hospitalizations: Pragmatic Trial
Postimplementation Evaluation in Assisted Living Facilities of an #eHealth ##Medical Device Developed to Predict and Avoid Unplanned #Hospitalizations: Pragmatic Trial
Background: The proportion of very old adults in the population is increasing, representing a significant challenge. Due to their vulnerability, there is a higher frequency of unplanned #Hospitalizations in this population, leading to adverse events.…
dlvr.it
December 10, 2024 at 8:04 PM
Parts 1-2/2 — EFTA00190224.jpg
#epsteinweb #efta00190224
https://epsteinweb.org
Available in the iOS app store now!
https://apps.apple.com/us/app/epstein-web/id6758880661
April 25, 2026 at 11:35 PM
Impact of multifaceted clinical decision support and education on antibiotic duration in outpatients with respiratory tract infections in Saudi Arabia: a prospective pre- and postimplementation study doi.org/10.1017/ash....
Impact of multifaceted clinical decision support and education on antibiotic duration in outpatients with respiratory tract infections in Saudi Arabia: a prospective pre- and postimplementation study | Antimicrobial Stewardship & Healthcare Epidemiology | Cambridge Core
Impact of multifaceted clinical decision support and education on antibiotic duration in outpatients with respiratory tract infections in Saudi Arabia: a prospective pre- and postimplementation study…
doi.org
November 20, 2025 at 10:55 AM
Here is what was trying to be negotiated behind the scenes: "A uniform delay of SNAP benefit and administrative cost sharing requirements until 2030, using FY 2027 Quality Control data to ensure accountability based on stable, postimplementation conditions"

www.ncsl.org/resources/de...
NCSL Reiterates SNAP Concerns
The Honorable John Boozman Chair, Senate Committee on Agriculture, Nutrition & Forestry Washington, DC 20510 The Honorable Amy Klobuchar Ranking Member, Senate Committee on Agriculture, Nutrition & F...
www.ncsl.org
May 1, 2026 at 6:19 PM
APP-led COpAT program cut follow-up time from 20.1 to 9.1 days ⏳, boosted 14-day visits from 42% to 83% 📈, and TOC pharmacy involvement rose from 8% to 42% 💊.##idsky
Can implementation of a complex outpatient antimicrobial therapy program reduce readmissions for patients with bone and joint infections?
View abstract Objective:Evaluate whether a complex outpatient antimicrobial therapy (COpAT) program led by advanced practice providers (APPs) conducting transition-of-care (TOC) services improves post discharge patient follow-up and reduces hospital readmission.Design:Pre- and postimplementation cohort study comparing outcomes 6 months before and 5 months after COpAT launch.Setting:706-bed tertiary university teaching hospital.Patients:Adult patients admitted to the hospital with bone and joint infections, seen by our inpatient infectious disease consultation service and discharged with at least fourteen days of antimicrobial therapy, with follow-up at our specialized musculoskeletal infectious diseases clinic.Intervention:The APP led pilot COpAT program was launched on March 1st, 2024, with a multidisciplinary team including an infectious diseases physician, APP, nurse, medical assistant, and TOC pharmacists. Patients enrolled at hospital discharge and were scheduled for APP-led TOC visits within fourteen days, followed by a physician visit.Results:The pre- and post-intervention groups included 100 and 135 patients, respectively. Mean postdischarge follow-up time decreased from 20.1 to 9.1 days (P < .001), and patients seen within fourteen days increased from 42% to 83% (P < .001). Readmission rates and emergency room visits did not change significantly. TOC pharmacy engagement rose from 8% to 42% (P < .001), and both TOC pharmacy and APP interventions frequently addressed medication errors, side effects, and treatment modifications.Conclusion:A structured, COpAT program with APP and TOC pharmacy involvement optimizes postdischarge follow-up, strengthens antimicrobial outpatient monitoring, and supports timely intervention for patients with complex infections.
www.cambridge.org
January 27, 2026 at 2:00 AM