Electronic Health Record Activity Research Articles

Measuring Documentation Burden in Healthcare.

The enactment of the Health Information Technology for Economic and Clinical Health Act and the wide adoption of electronic health record (EHR) systems have ushered in increasing documentation burden, frequently cited as a key factor affecting the work experience of healthcare professionals and a contributor to burnout. This systematic review aims to identify and characterize measures of documentation burden. We integrated discussions with Key Informants and a comprehensive search of the literature, including MEDLINE, Embase, Scopus, and gray literature published between 2010 and 2023. Data were narratively and thematically synthesized. We identified 135 articles about measuring documentation burden. We classified measures into 11 categories: overall time spent in EHR, activities related to clinical documentation, inbox management, time spent in clinical review, time spent in orders, work outside work/after hours, administrative tasks (billing and insurance related), fragmentation of workflow, measures of efficiency, EHR activity rate, and usability. The most common source of data for most measures was EHR usage logs. Direct tracking such as through time-motion analysis was fairly uncommon. Measures were developed and applied across various settings and populations, with physicians and nurses in the USA being the most frequently represented healthcare professionals. Evidence of validity of these measures was limited and incomplete. Data on the appropriateness of measures in terms of scalability, feasibility, or equity across various contexts were limited. The physician perspective was the most robustly captured and prominently focused on increased stress and burnout. Numerous measures for documentation burden are available and have been tested in a variety of settings and contexts. However, most are one-dimensional, do not capture various domains of this construct, and lack robust validity evidence. This report serves as a call to action highlighting an urgent need for measure development that represents diverse clinical contexts and support future interventions.

Changes in Healthcare Utilization After Lifestyle Intervention for Weight Loss

This study evaluates the real-world impact of a lifestyle change program (LCP) on healthcare utilization in a large health system. Using electronic health record data from a large health system in northern California, U.S., LCP participant and propensity-score-matched nonparticipant outcomes were compared in the second year post-participation: (1) overall healthcare utilization and (2) utilization and medications related to cardiometabolic conditions and obesity. Adult LCP participants between 2010 and 2017 were identified and matched 1:1 with replacement to comparable nonparticipants. Participants without electronic health record activity in the 12-36 months before baseline, or with conditions or procedures associated with substantial weight change, were excluded. Statistical analysis and modeling were performed in 2021-22. Compared to matched nonparticipants, LCP participants in the 12-24 months post-baseline were more likely to have specialty-care visits (+4.7%, 95% CI +1.8%, +7.6%), electronic communications (8.6%, 95% CI +5.6%, +11.7%), and urgent-care visits (+6.5%, 95% CI +3.0%, 10.0%). Participants also had more office visits for cardiometabolic conditions and obesity (+1.72 visits/patient, 95% CI +1.05, +2.39). Compared with matched nonparticipants, LCP participation was associated with higher utilization of outpatient services post-participation. Additional research could assess whether this indicates an increase in preventive care that could lead to improved future outcomes.

EPH61 Uptake of the Post COVID-19 Condition ICD-10-CM Diagnosis Code By Social Factors

Post-COVID conditions (PCC) are increasingly reported in people who had COVID. Certain racial or socioeconomic groups may be at greater risk for PCC and less likely to seek care. We examined the uptake of the new ICD-10-CM diagnosis code for PCC in routine clinical practice in the United States and how it varied by race and payer group. Using the Optum® de-identified Electronic Health Record (EHR) dataset, we identified patients with an ICD-10-CM code for PCC (U09.9) between October 1, 2021, through March 31, 2022, with 6 months of prior EHR activity. The earliest diagnosis defined the index date. All concurrent diagnoses were measured on the index date. Prior COVID diagnosis was assessed using all available data before the index date. There were 23,647 patients: 9.9% were African American, 12.1% had Medicaid, and 2.4% were uninsured. There was an overrepresentation of white patients among those with PCC (78.6% compared with 69.6% of the overall EHR in 2021). More African American (24.1%), Medicaid (23.1%), and uninsured (27.5%) patients were diagnosed in the inpatient setting or emergency department than whites (14.0%) and commercially insured patients (10.0%). Among racial groups, African Americans had the highest percentage of documented prior COVID diagnosis at 63.6%. Of concurrent diagnoses, shortness of breath and acute respiratory failure with hypoxia were higher among African Americans (13.9% and 6.1%, respectively) than whites (11.5% and 4.3%, respectively). The same pattern was seen when comparing Medicaid and uninsured to commercial payors. The PCC code was used differently across racial groups and payor types and captures varying manifestations of PCC. The differences in diagnosis locations underscore the importance of using data capturing all care settings when conducting studies using this code. Subgroup analyses are important for future studies using U09.9 due to variability in code application.

Healthcare resource use for pediatric low-grade glioma care: A cohort of linked electronic health records and claims data.

10038 Background: Pediatric low-grade glioma (pLGG) is the most common brain tumor in children and is associated with persistent long-term tumor- and treatment-related morbidities. This study aims to characterize the costs associated with the treatment of pLGG. Methods: A retrospective study using the Optum de-identified Market Clarity Dataset linked claims (commercial, Medicare Advantage and Managed Medicaid beneficiaries) and electronic health records (EHRs) of cases ≤18 years of age, with an ICD-10 code for brain neoplasm and ≥1 physician notes between January 2017 and June 2018 was performed. Index date was the first claim or EHR with an ICD-10 code for brain neoplasm. Natural language processing was used to identify pLGG-relevant data from physician notes. The observation period included 3 months prior to index date and 6-month segments from index date for 36 months. Cases had either continuous insurance coverage or continuous EHR activity during this period. Results for procedures and medication use were reported as averages throughout the 36-month post-index follow-up period. Results: A total of 154 patients with pLGG were identified. Median age was 11 years (range 2–18). Among the cohort, 49% (n=76) were female; 75% (n=116) were non-Hispanic white, 13% (n=20) Hispanic, 5% (n=7) African American, 1% (n=1) Asian and 6% (n=10) other/unknown. Of benefits, 56% had commercial and 44% Medicaid. Brain imaging and neuropsychological evaluations were performed at least once in 85% and 57% of the cohort, respectively. Among pLGG relevant medications, 57% of the cohort used analgesics, 45% anti-emetics, 32% anxiolytics, and 29% anticonvulsants. A total of 100 patients received ≥1 pLGG disease control treatments: Of these, 53% underwent emergency brain surgery, 24% had planned brain surgery, 14% received chemotherapy, and 6% received targeted therapy. Of the 100 patients who received disease control treatments, 57% relapsed after first-line treatment; 37% of patients received 2 lines of therapy, and 20% of patients received ≥3 lines of therapy. Conclusions: Our findings show that patients with pLGG often require long-term medical care and high levels of healthcare resources to treat their disease and its sequalae. Additionally, a majority will relapse and face a higher burden of disease. Further studies using integrated data sources are warranted to help us understand the burden of pLGG and inform evidence-based health care planning for these patients.

416 On-Call Junior Neurosurgery Residents Spend 9 Hours of Their On-Call Shift Actively Using the Electronic Health Record

INTRODUCTION: The Electronic Health Record (EHR) is central to clinical workflow, yet few studies to date have explored EHR usage patterns among neurosurgery trainees. METHODS: We utilized the EHR audit logs, time-stamped records of user activities, to review EHR usage of PGY-2 and 3 neurosurgery residents scheduled for 1 or more on-call days across 2 calendar years at the University of California San Francisco. We focused on the PGY-2 and 3 years, which in our training program represent the primary participants in the in-house on-call pool. RESULTS: Over 723 call days, 12 different residents took at least one on-call shift. The median (IQR) number of minutes that residents spent per on-call shift actively using the EHR was 536.8 (203.5), while interacting with an average (SD) of 68.1 (14.7) patient charts. There was no significant difference between active EHR time between residents as PGY-2 and PGY-3 on paired t-tests. Residents spent the most time on the following EHR activities: patient reports, notes, order management, patient list, and chart review. CONCLUSIONS: Residents spent, on average, 9 hours of their on-call shift actively using the EHR, and there was no improved efficiency as residents gained experience. We noted several areas of administrative EHR burden which could be reduced.

Monitoring the Implementation of Tobacco Cessation Support Tools: Using Novel Electronic Health Record Activity Metrics.

Clinical decision support (CDS) tools in electronic health records (EHRs) are often used as core strategies to support quality improvement programs in the clinical setting. Monitoring the impact (intended and unintended) of these tools is crucial for program evaluation and adaptation. Existing approaches for monitoring typically rely on health care providers' self-reports or direct observation of clinical workflows, which require substantial data collection efforts and are prone to reporting bias. This study aims to develop a novel monitoring method leveraging EHR activity data and demonstrate its use in monitoring the CDS tools implemented by a tobacco cessation program sponsored by the National Cancer Institute's Cancer Center Cessation Initiative (C3I). We developed EHR-based metrics to monitor the implementation of two CDS tools: (1) a screening alert reminding clinic staff to complete the smoking assessment and (2) a support alert prompting health care providers to discuss support and treatment options, including referral to a cessation clinic. Using EHR activity data, we measured the completion (encounter-level alert completion rate) and burden (the number of times an alert was fired before completion and time spent handling the alert) of the CDS tools. We report metrics tracked for 12 months post implementation, comparing 7 cancer clinics (2 clinics implemented the screening alert and 5 implemented both alerts) within a C3I center, and identify areas to improve alert design and adoption. The screening alert fired in 5121 encounters during the 12 months post implementation. The encounter-level alert completion rate (clinic staff acknowledged completion of screening in EHR: 0.55; clinic staff completed EHR documentation of screening results: 0.32) remained stable over time but varied considerably across clinics. The support alert fired in 1074 encounters during the 12 months. Providers acted upon (ie, not postponed) the support alert in 87.3% (n=938) of encounters, identified a patient ready to quit in 12% (n=129) of encounters, and ordered a referral to the cessation clinic in 2% (n=22) of encounters. With respect to alert burden, on average, both alerts fired over 2 times (screening alert: 2.7; support alert: 2.1) before completion; time spent postponing the screening alert was similar to completing (52 vs 53 seconds) the alert, and time spent postponing the support alert was more than completing (67 vs 50 seconds) the alert per encounter. These findings inform four areas where the alert design and use can be improved: (1) improving alert adoption and completion through local adaptation, (2) improving support alert efficacy by additional strategies including training in provider-patient communication, (3) improving the accuracy of tracking for alert completion, and (4) balancing alert efficacy with the burden. EHR activity metrics were able to monitor the success and burden of tobacco cessation alerts, allowing for a more nuanced understanding of potential trade-offs associated with alert implementation. These metrics can be used to guide implementation adaptation and are scalable across diverse settings.

Effectiveness and Safety of Rivaroxaban Versus Warfarin among Nonvalvular Atrial Fibrillation Patients with Concomitant Obstructive Sleep Apnea

Background Obstructive sleep apnea (OSA) is associated with an increased incidence of atrial fibrillation (AF), hypertension, diabetes, heart failure, coronary heart disease, stroke, and death. We sought to evaluate the effectiveness and safety of rivaroxaban versus warfarin in nonvalvular AF (NVAF) patients with concomitant OSA. Methods This was an analysis of electronic health record (EHR) data from November 2010 to December 2021. We included adults with NVAF and OSA at baseline, newly initiated on rivaroxaban or warfarin, and with ≥12 months of prior EHR activity. Patients with valvular disease, alternative indications for oral anticoagulation, or who were pregnant were excluded. The incidence rates of developing stroke or systemic embolism (SSE) and bleeding-related hospitalization were evaluated. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using propensity score-overlap weighted proportional hazards regression. Multiple sensitivity and subgroup analyses were performed. Results We included 21,940 rivaroxaban (20.1% at the 15 mg dose) and 38,213 warfarin (time-in-therapeutic range = 47.3 ± 28.3%) patients. Rivaroxaban was found to have similar hazard of SSE compared to warfarin (HR = 0.92, 95% CI = 0.82-1.03). Rivaroxaban was associated with a reduced rate of bleeding-related hospitalizations (HR = 0.85, 95% CI = 0.78-0.92) versus warfarin, as well as reductions in intracranial (HR = 0.76, 95% CI = 0.62-0.94) and extracranial (HR = 0.89, 95%CI = 0.81-0.97) bleeding. Upon sensitivity analysis restricting the population to men with a CHA 2 DS 2 VASc score ≥2 or women with a score ≥3, rivaroxaban was associated with a significant 33% risk reduction in SSE and 43% reduction in the risk of bleeding-related hospitalization. No significant interaction for the SSE or bleeding-related hospitalization outcomes was observed upon subgroup analyses. Conclusion Among patients with NVAF and OSA, rivaroxaban had similar SSE risk versus warfarin but was associated with reductions in any intracranial and extracranial bleeding-related hospitalizations. Rivaroxaban was associated with significant reductions in SSE and bleeding-related hospitalizations when the study population was restricted to patients with a moderate-to-high risk of SSE. These data should provide prescribers with additional confidence in selecting rivaroxaban in NVAF patients who have OSA at the time of anticoagulation initiation.

Where Is the Digitally Silent Provider? Development and Validation of a Team-Centered Electronic Health Record Attribution Model for Supervising Residents.

Providing trainees with data and benchmarks on their own patient populations is an Accreditation Council for Graduate Medical Education core residency requirement. Leveraging electronic health records (EHRs) for this purpose relies on correctly attributing patients to the trainees responsible for their care. EHR activity logs are useful for attributing interns to inpatients but not for attributing supervising residents, who often have no inpatient EHR usage obligations, and therefore may generate no digital "footprints" on a given patient-day from which to ascertain attribution. The authors developed and tested a novel team-centered binary logistic regression model leveraging EHR activity logs from July 1, 2018, to June 30, 2019, for pediatric hospital medicine (PHM) supervising residents at the University of California, San Francisco. Unlike patient-centered models that determine daily attribution according to the trainee generating the greatest relative activity in individual patients' charts, the team-centered approach predicts daily attribution based on the trainee generating EHR activity across the greatest proportion of a team's patients. To assess generalizability, the authors similarly modeled supervising resident attribution in adult hospital medicine (AHM) and orthopedic surgery (OS). For PHM, AHM, and OS, 1,100, 1,399, and 803 unique patient encounters and 29, 62, and 10 unique supervising residents were included, respectively. Team-centered models outperformed patient-centered models for the 3 specialties, with respective accuracies of 85.4% versus 72.4% (PHM), 88.7% versus 75.4% (AHM), and 69.3% versus 51.6% (OS; P < .001 for all). AHM and PHM models demonstrated relative generalizability to one another while OS did not. Validation at other institutions will be essential to understanding the potential for generalizability of this approach. Accurately attributed data are likely to be trusted more by trainees, enabling programs to operationalize feedback for use cases including performance measurement, case mix assessment, and postdischarge opportunities for follow-up learning.

On-Call Junior Neurosurgery Residents Spend 9 hours of Their On-Call Shift Actively Using the Electronic Health Record.

The electronic health record (EHR) is central to clinical workflow, yet few studies to date have explored EHR usage patterns among neurosurgery trainees. To describe the amount of EHR time spent by postgraduate year (PGY)-2 and PGY-3 neurosurgery residents during on-call days and the distribution of EHR activities in which they engage. This cohort study used the EHR audit logs, time-stamped records of user activities, to review EHR usage of PGY-2 and PGY-3 neurosurgery residents scheduled for 1 or more on-call days across 2 calendar years at the University of California San Francisco. We focused on the PGY-2 and PGY-3, which, in our training program, represent the primary participants in the in-house on-call pool. Over 723 call days, 12 different residents took at least one on-call shift. The median (IQR) number of minutes that residents spent per on-call shift actively using the EHR was 536.8 (203.5), while interacting with an average (SD) of 68.1 (14.7) patient charts. There was no significant difference between Active EHR Time between residents as PGY-2 and PGY-3 on paired t -tests. Residents spent the most time on the following EHR activities: patient reports, notes, order management, patient list, and chart review. Residents spent, on average, 9 hours of their on-call shift actively using the EHR, and there was no improved efficiency as residents gained experience. We noted several areas of administrative EHR burden, which could be reduced.

S280 Appropriateness of Scheduled 5-Year Colorectal Cancer Surveillance Colonoscopies at an Academic Medical Center

Introduction: Prudent adenoma detection and family history assessment results in increased surveillance colonoscopies for colorectal cancer screening (CRC), where recommended intervals for follow-up colonoscopies are based on prior colonoscopy findings (i.e., polyp number, size, pathology) as well as family history. Previous studies based on retrospective electronic health data determined that surveillance colonoscopies are often performed earlier than recommended intervals based on guidelines. These procedures expose patients to procedural risks, inconvenience with scheduling and unnecessary preps, and add to healthcare costs, as well as increase caseload for endoscopy centers that often have limited capacity. In the context of updated surveillance guidelines that lengthen follow-up intervals for some adenomas, we sought to assess the proportion of 5-year surveillance colonoscopies scheduled without appropriate indication. Methods: We conducted a retrospective cohort study of all outpatient endoscopic procedures scheduled in a tertiary, academic medical center over a 4-week period (4/25/22-5/20/22). We screened for cases that had an active Electronic Health Record (EHR) flag for 5-year screening colonoscopy and were classified by the ordering provider as having a screening, non-diagnostic indication, and then confirmed the EHR flag and indication with chart review. Two physicians conducted chart review of last colonoscopy and ordering provider documentation to evaluate indication and appropriateness for 5-year screening based on US Multi-Society Task Force February 2020 guidelines. Results: The 4-week period included 2,222 total procedures scheduled, of which 149 were colonoscopies scheduled for 5-year surveillance. Of these, 57% (85/149) were inappropriate based on current guidelines, which accounts for 4% (85/2,222) of total cases. 74% (63/85) of inappropriate cases were due to not meeting polyp-based guidelines, where 65% (55/85) was due to the 2020 change in guidelines. 24% (20/85) were based on inappropriately applied family history. (Figure) Conclusion: A majority of cases scheduled for 5-year surveillance were not indicated, where most were inappropriate based on updated polyp-based guidelines. Interventions targeting these cases and assessing overall appropriateness of cases may reduce patient harm and increase the capacity for necessary procedures.Figure 1.: (a) Appropriateness of Scheduled 5-Year Surveillance Colonoscopies (b) Reasons for Inappropriate Colonoscopy Scheduling

Time Spent by Intensive Care Unit Nurses on the Electronic Health Record.

The amount of time spent on the electronic health record is often cited as a contributing factor to burnout and work-related stress in nurses. Increased electronic health record use also reduces the time nurses have for direct contact with patients and families. There has been minimal investigation into the amount of time intensive care unit nurses spend on the electronic health record. To quantify the amount of time spent by intensive care unit nurses on the electronic health record. In this observational study, active electronic health record use time was analyzed for 317 intensive care unit nurses in a single institution from January 2019 through July 2020. Monthly data on electronic health record use by nurses in the medical, neurosurgical, and surgical-trauma intensive care units were evaluated. Full-time intensive care unit nurses spent 28.9 hours per month on the electronic health record, about 17.5% of their clinical shift, for a total of 346.3 hours per year. Part-time nurses and those working as needed spent 20.5 hours per month (17.6%) and 7.4 hours per month (14.2%) on the electronic health record, respectively. Neurosurgical and medical intensive care unit nurses spent 25.0 hours and 19.9 hours per month, respectively. Nurses averaged 23 clicks per minute during use. Most time was spent on the task of documentation at 12.3 hours per month, which was followed by medical record review at 2.6 hours per month. Intensive care unit nurses spend at least 17% of their shift on the electronic health record, primarily on documentation. Future interventions are necessary to reduce time spent on the electronic health record and to improve nurse and patient satisfaction.

The Impact of an Organization-Wide Electronic Health Record (EHR) System Upgrade on Physicians' Daily EHR Activity Time: An EHR Log Data Study

Abstract Objective This article assesses the impact of a health care organization's electronic health record (EHR) upgrade on providers' daily EHR activity time. Methods Daily EHR activity time (minutes/day) was acquired through EHR log data that automatically tracks user activity. Subjects were attending and resident physicians in the departments of family medicine, hospitalist medicine, and the neonatal intensive care unit working in the inpatient setting. The EHR upgrade occurred in August 2020, and the comparison groups were pre-upgrade (May 31, 2020–July 25, 2020) and post-upgrade (August 30, 2020–October 31, 2020). A two-tailed, two-sample t-test was used to assess statistical significance. Results The pre-upgrade group had 146 users, and the post-upgrade group had 140 users. There was no statistically significant difference between the pre-upgrade group (mean (M): 104.74 minutes/day, standard deviation [SD]: 70.64) and post-upgrade group (M: 103.38 minutes/day, SD: 64.77), even after splitting the data by user type and user type and department. Conclusion This study showed no significant difference in daily EHR activity time post-upgrade. More research is needed to truly understand the impact of EHR upgrades on user efficiency. Understanding the content of each upgrade might be key in understanding their effect on users, and we hope to explore that in the future.

Effect of Patient Portal Messaging Before Mailing Fecal Immunochemical Test Kit on Colorectal Cancer Screening Rates

Colorectal cancer (CRC) screening reduces CRC mortality; however, screening rates remain well below the national benchmark of 80%. To determine whether an electronic primer message delivered through the patient portal increases the completion rate of CRC screening in a mailed fecal immunochemical test (FIT) outreach program. In this randomized clinical quality improvement trial at the University of California, Los Angeles Health of 2339 patients enrolled in a FIT mailing program from August 28, 2019, to September 20, 2020, patients were randomly assigned to either the control or intervention group, and the screening completion rate was measured at 6 months. Participants were average-risk managed care patients aged 50 to 75 years, with a valid mailing address, no mailed CRC outreach in the previous 6 months, and an active electronic health record (EHR) patient portal who were due for CRC screening. Data were analyzed on an intention-to-treat basis. Eligible patients were randomly assigned to receive either (1) the standard FIT mailed outreach (control group) or (2) the standard FIT mailed outreach plus an automated primer to notify patients of the upcoming mailed FIT sent through the electronic patient portal (intervention group). The primary outcome was the screening completion rate (ie, returning the FIT). Secondary outcomes were (1) were the time to CRC screening from the FIT mailing date, (2) screening modality completed, and (3) the effect of opening the electronic primer on screening completion rate. The study included 2339 patients (1346 women [57.5%]; mean [SD] age, 58.9 [7.5] years). The screening completion rate was higher in the intervention group than in the control group (37.6% [445 of 1182] vs 32.1% [371 of 1157]; P = .005). The time to screening was shorter in the intervention group than in the control group (adjusted hazard ratio, 1.24; 95% CI, 1.08-1.42; P = .003). The proportion of each screening test modality completed was similar in both groups. In a subanalysis of the 900 of 1182 patients (76.1%) in the intervention group who opened the patient portal primer message, there was a 7.3-percentage point (95% CI, 2.3-12.4 percentage points) increase in CRC screening (local mean treatment effect; P = .004). Implementation of an electronic patient portal primer message in a mailed FIT outreach program led to a significant increase in CRC screening and improvement in the time to screening completion. The findings provide an evidence base for additional refinements to mailed FIT outreach quality improvement programs in large health systems. ClinicalTrials.gov Identifier: NCT05115916.

Primary care physicians' electronic health record proficiency and efficiency behaviors and time interacting with electronic health records: a quantile regression analysis.

This study aimed to understand the association between primary care physician (PCP) proficiency with the electronic health record (EHR) system and time spent interacting with the EHR. We examined the use of EHR proficiency tools among PCPs at one large academic health system using EHR-derived measures of clinician EHR proficiency and efficiency. Our main predictors were the use of EHR proficiency tools and our outcomes focused on 4 measures assessing time spent in the EHR: (1) total time spent interacting with the EHR, (2) time spent outside scheduled clinical hours, (3) time spent documenting, and (4) time spent on inbox management. We conducted multivariable quantile regression models with fixed effects for physician-level factors and time in order to identify factors that were independently associated with time spent in the EHR. Across 441 primary care physicians, we found mixed associations between certain EHR proficiency behaviors and time spent in the EHR. Across EHR activities studied, QuickActions, SmartPhrases, and documentation length were positively associated with increased time spent in the EHR. Models also showed a greater amount of help from team members in note writing was associated with less time spent in the EHR and documenting. Examining the prevalence of EHR proficiency behaviors may suggest targeted areas for initial and ongoing EHR training. Although documentation behaviors are key areas for training, team-based models for documentation and inbox management require further study. A nuanced association exists between physician EHR proficiency and time spent in the EHR.

Real World Treatment Patterns and Outcomes of Venetoclax (Ven) and Hypomethylating Agents (HMA) in Patients with Newly Diagnosed Acute Myeloid Leukemia (AML) in the United States

Real World Treatment Patterns and Outcomes of Venetoclax (Ven) and Hypomethylating Agents (HMA) in Patients with Newly Diagnosed Acute Myeloid Leukemia (AML) in the United States

Thromboembolism, Bleeding, and Vascular Death Among Older and Younger Nonvalvular Atrial Fibrillation Patients with Type 2 Diabetes Receiving Rivaroxaban or Warfarin

Background: Advancing age and diabetes are common comorbidities among patients diagnosed with nonvalvular atrial fibrillation (NVAF). In separate subanalyses of the Rivaroxaban Once Daily, Oral, Direct Factor Xa Inhibition Compared With Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF), the relative efficacy and safety of rivaroxaban versus warfarin did not vary with by older (≥75 years old) or younger age (<75 years old) or with the presence or absence of diabetes. We sought to evaluate the impact of age on the comparative effectiveness and safety of rivaroxaban compared to warfarin in NVAF patients with comorbid diabetes treated in routine practiceMethods: We performed an analysis using Optum® De-Identified electronic health record (EHR) data from November 2010 to December 2019. This study included adults with NVAF and type 2 diabetes, newly started on either rivaroxaban or warfarin and who had ≥12-months of EHR activity. Patients who were pregnant, had alternative indications for oral anticoagulation or valvular heart disease were excluded. To allow for the assessment of statistical interaction in outcome rates across age groups, we propensity score-overlap weighted patients after stratification of eligible patients into older (≥80 years old) and younger (<80 years old) cohorts. Weighted incidence rates (%/year) of developing stroke or systemic embolism, or vascular death; hospitalization for major or clinically relevant nonmajor (CRNM) bleeding; and major adverse limb events (need for revascularization or major amputation of the lower limbs) for rivaroxaban and warfarin users with type 2 diabetes patients either ≥80 or <80 years old were reported. Propensity score-overlap weighted hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox regression employing a robust sandwich estimator. Patients were followed in the Cox regression models until time of outcome occurrence, end-of-EHR activity or end-of-data availability. P-values for interaction across age subgroups were adjusted to control for false discovery rates due to multiple hypothesis testing. A p-value <0.05 was considered statistically significant in all cases.Results: A total of 32,078 rivaroxaban (31% initiated on 15 mg dose) and 83,971 warfarin users (time-in-therapeutic range = 47±28%) with NVAF and comorbid type 2 diabetes were included in the present study. Mean follow-up time was 2.9±1.9 years for rivaroxaban and 2.9±2.0 years for warfarin patients. There were 31,941 patients (28%) aged ≥80 years who were initiated on either rivaroxaban (n=6,606) or warfarin (n=25,335). Older patients had a higher mean CHA 2DS 2VASc (4.4±1.2 versus 3.8±1.3) and modified HASBLED (1.7±0.7 versus 1.4±0.8) score compared to younger patients. Propensity score-overlap weighted analyses found no statistically significant interaction for the relative effectiveness or safety of rivaroxaban versus warfarin across the older or younger age groups for the outcomes of stroke, systemic embolism, or vascular death (HR=0.93; 95%CI, 0.87-1.00 versus HR=0.91; 95%CI, 0.86-0.96), hospitalization for major or CRNM bleeding (HR=1.06; 95%CI, 0.96-1.18 versus HR=0.90; 95%CI, 0.84-0.96) or major adverse limb events (HR=0.79; 95%CI, 0.68-0.94 versus HR=0.76; 95%CI, 0.70-0.83) (Table). Major and intracranial bleeding were also observed significantly less frequently with rivaroxaban compared to warfarin regardless of patient age.Conclusions: The effectiveness and safety of rivaroxaban relative to warfarin remained consistent across older and younger patient subgroups, supporting rivaroxaban as an alternative for elderly NVAF patients with concomitant type 2 diabetes (NCT04509193). [Display omitted] DisclosuresColeman: Alexion Pharmaceuticals: Research Funding; Janssen Scientific Affairs LLC: Consultancy, Honoraria, Research Funding; Bayer AG: Consultancy, Honoraria, Research Funding. Vardar: Bayer AG: Current Employment. Abdelgawwad: Bayer AG: Current Employment.

Hyperledger blockchain based secure storage of electronic health record system in edge nodes

An Electronic Health Record (EHR) is a database for storing patients medical information collected from different sources such as smart wearable devices, smart sensors and diagnostic imaging equipment. An EHR contains sensitive private information for the patients and the treatment of their diseases. Furthermore, it’s often shared among different members consists of healthcare providers, insurance companies, medical researchers, and others. The main difficulty for EHR information management is the result of gathering, storing, and sharing patient healthcare without affecting privacy and security. Blockchain has recently proposed an efficient way to manage EHR data. This paper provides hybrid architecture for EHR data management by using both Hyperledger blockchain network in on-chain and edge node in off-chain. In this architecture is used to authenticate user without affecting sensitive patient’s information and also used to authenticate the encrypted EHR information in edge node. In the on-chain approach EHR activities and Patient authentication activities are recorded in the blockchain for the purpose of accountability and traceability. Edge nodes stored the encrypted EHR data in the off-chain method. So the combination of on-chain and off-chain approaches only allows the authorized data user who has to meet the EHR access activities and to decrypt the EHR data. If the EHR information is alter by an unauthorized user, the hash code is newly generated which is different from old hash code stored in the blockchain. As the result the user can easily detect that their EHR information has been hacked.

Estimation of Surgical Resident Duty Hours and Workload in Real Time Using Electronic Health Record Data

To explore the use of electronic health record (EHR) data to estimate surgery resident duty hours and monitor real time workload. Retrospective analysis of resident duty hours logged using a voluntary global positioning system (GPS)-based smartphone application compared to duty hour estimates by an EHR-based algorithm. The algorithm estimated duty hours using EHR activity data and operating room logs. A dashboard was developed through Plan-Do-Study-Act cycles for real-time monitoring of workload. Single tertiary/quaternary medical center general surgery residency program with approximately 90 categorical, preliminary, and integrated residents at eight clinical sites. Categorical, preliminary, and integrated surgery residents of all clinical years who volunteered to pilot a GPS application to track duty hours. Of 2,623 work periods by 59 residents were logged with both methods. EHR-estimated work periods started later than GPS logs (median 0.3 hours, interquartile range [IQR] -0.1 - 0.3); EHR-estimated work periods ended earlier than GPS logs (median 0.1 hours, IQR -0.7 - 0.3); and EHR-estimated duty hour totals were less than totals logged by GPS (median -0.3 hours, IQR -0.8 - +0.1). Overall correlation between weekly duty hours logged by EHR and GPS was 0.79. Correlations between the 2 systems stratified from PGY-1 through PGY-5 were 0.76, 0.64, 0.82, 0.87, and 0.83, respectively. The algorithm identified six 80-hour workweek violations (averaged over 4 weeks), while GPS logs identified 8. EHR-based duty hours and operational data were integrated into a dashboard to enable real time monitoring of resident workloads. EHR-based estimation of surgical resident duty hours has good correlation with GPS-based assessment of duty hours and identifies most workweek duty hour violations. This approach allows for dynamic workload monitoring and may be combined with operational data to anticipate and prevent duty hour violations, thereby optimizing learning.

Association Between Proficiency and Efficiency in Electronic Health Records Among Pediatricians at a Major Academic Health System.

Objective: The purpose of this study was to evaluate the variations in electronic health record (EHR) activity among General and Specialty pediatricians by investigating the time spent and documentation length, normalized for workload.Materials and Methods: We conducted a cross-sectional study of pediatric physicians using Epic EHR at a major Southeastern academic healthcare system. We collected user-level EHR activity data of 104 pediatric physicians over 91 days from April 1 to June 30, 2020.Results: Of the 104 pediatrics physicians, 56 (54%) were General pediatricians and 48 (46%) were Specialists pediatricians. General pediatricians spent an average of 17.6 min [interquartile range (IQR): 12.9–37] using the EHR per appointment, while Specialists spent 35.7 min (IQR: 28–48.4) per appointment.Significant negative associations were found between proficiency scores and the amount of time spent in the system for Generalists (p < 0.001). On the contrary, significant positive associations were found between proficiency scores and the amount of time spent in the system for Specialists (p < 0.01).Conclusions: We report an association between EHR proficiency and efficiency levels among pediatricians within the same healthcare system, receiving the same EHR training, and using the same EHR system. The profound differences in EHR activity suggest that higher priority should be given to redesigning EHR training methods to accommodate the learning needs of physicians.

Kidney, limb and ophthalmic complications, and death in patients with nonvalvular atrial fibrillation and type 2 diabetes prescribed rivaroxaban or warfarin: an electronic health record analysis

Background Patients with nonvalvular atrial fibrillation (NVAF) and type 2 diabetes are at risk of kidney, limb, and ophthalmic complications. We evaluated the rate of these complications and death in patients with NVAF and type 2 diabetes prescribed rivaroxaban or warfarin. Methods We analyzed Optum de-Identified electronic health record (EHR) data from 11/2010–12/2019. We included adults with NVAF and T2D newly initiated on rivaroxaban or warfarin with ≥12 months of prior EHR activity. Patients with another indication for anticoagulation, valve disease, history of end-stage renal disease, major adverse limb events (MALE), diabetic retinopathy or pregnancy were excluded. We evaluated the incidence rate of developing a composite outcome of >40% decrease in estimated glomerular filtration incidence rate (eGFR) from baseline, eGFR < 15 mL/minute/1.73 m2, need for dialysis or kidney transplant, MALE, diabetic retinopathy or death. Overlap weighting was used to balance baseline characteristics between cohorts while preserving sample size. Hazard ratios with 95% confidence intervals were calculated using propensity score-overlap weighted Cox regression. Results We included 24,912 rivaroxaban and 58,270 warfarin users. The mean ± standard deviation (SD) CHA2DS2VASc score was 4.3 ± 1.5 and modified HASBLED score was 1.5 ± 0.8. Thirty percent of rivaroxaban patients were started on 15 mg once daily, with the rest prescribed 20 mg once daily. Warfarin patients had a mean time in therapeutic range of 47 ± 28%. Patients were followed for a mean of 2.89 ± 1.95 years. Rivaroxaban was associated with a reduced hazard of the composite outcome (HR = 0.93, 95%CI = 0.91–0.95; absolute risk reduction = 1.97 events per 1000 patient-years; number needed-to-treat = 51) versus warfarin. Rivaroxaban was also associated with significant reductions in the relative hazard of > 40% decrease in eGFR from baseline (HR = 0.96), need for dialysis or renal transplant (HR = 0.81), and limb revascularization or major amputation (HR = 0.85). Death occurred at a lower incidence rate with rivaroxaban (HR = 0.92, 95%CI = 0.89–0.95). Conclusions Rivaroxaban was associated with reduced incidence rates of kidney and limb complications, and death in NVAF patients with type 2 diabetes compared to warfarin. ClinicalTrials.gov Identifier: NCT04509193