36 research outputs found

    Who Opens Alerts to Physicians? (And Who Doesn’t?)

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    Background: Electronic medical records (EMR) provide opportunities to implement systems of information flow, such as alerts to providers. Methods: Within a group practice with an EMR, we conducted a trial of automated alerts to the in-baskets of primary care physicians and staff when patients were discharged from hospital to home. We generated alerts for new medications or monitoring needs. Staff received alerts to schedule office visits. Using EMR “digital crumbs”, we tracked when alerts were viewed. We analyzed the impact of physician age, gender, department, and employment status (full-time, part-time) as well as patient conditions (age, gender, comorbidity, and number of office visits in the previous year) on timely opening. Results: Of 763 alerts to physicians, 616 (81%) were opened within one day. Characteristics associated with timely opening were age \u3c 50 (OR 1.7, 95% CI 1.1, 2.6) and full-time employment (OR 2.9, 95% CI 1.6, 5.2). Of 1928 alerts to staff, 1173 (61%) were opened within one day. Staff of male physicians were more likely to open the alerts within one day (OR 1.8, 95% CI 1.4, 2.4) as were working for the Family Medicine department (OR 1.9, 95% CI 1.3, 2.6) or a sub-specialty department (OR 16.6, 95% CI 2.3, 122.3). Staff of full-time physicians were less likely to open alerts (OR 0.64, 95% CI 0.47, 0.87). Adjusting for patient characteristics had no impact on results. Conclusion: Special efforts may be required to reach physicians working part-time and older physicians. Characteristics related to staff opening of alerts are specific to this group practice, but the high level of variability across physician types and departments is likely to be an issue in many settings. Design of a system directed at reaching staff quickly may require in-depth assessment of work flow and communication patterns in clinical department

    Improving Rates of Influenza Vaccination Through Electronic Health Record Portal Messages, Interactive Voice Recognition Calls and Patient-Enabled Electronic Health Record Updates: Protocol for a Randomized Controlled Trial

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    BACKGROUND: Clinical decision support (CDS), including computerized reminders for providers and patients, can improve health outcomes. CDS promoting influenza vaccination, delivered directly to patients via an electronic health record (EHR) patient portal and interactive voice recognition (IVR) calls, offers an innovative approach to improving patient care. OBJECTIVE: To test the effectiveness of an EHR patient portal and IVR outreach to improve rates of influenza vaccination in a large multispecialty group practice in central Massachusetts. METHODS: We describe a nonblinded, randomized controlled trial of EHR patient portal messages and IVR calls designed to promote influenza vaccination. In our preparatory phase, we conducted qualitative interviews with patients, providers, and staff to inform development of EHR portal messages with embedded questionnaires and IVR call scripts. We also provided practice-wide education on influenza vaccines to all physicians and staff members, including information on existing vaccine-specific EHR CDS. Outreach will target adult patients who remain unvaccinated for more than 2 months after the start of the influenza season. Using computer-generated randomization and a factorial design, we will assign 20,000 patients who are active users of electronic patient portals to one of the 4 study arms: (1) receipt of a portal message promoting influenza vaccines and offering online appointment scheduling; (2) receipt of an IVR call with similar content but without appointment facilitation; (3) both (1) and (2); or (4) neither (1) nor (2) (usual care). We will randomize patients without electronic portals (10,000 patients) to (1) receipt of IVR call or (2) usual care. Both portal messages and IVR calls promote influenza vaccine completion. Our primary outcome is percentage of eligible patients with influenza vaccines administered at our group practice during the 2014-15 influenza season. Both outreach methods also solicit patient self-report on influenza vaccinations completed outside the clinic or on barriers to influenza vaccination. Self-reported data from both outreach modes will be uploaded into the EHR to increase accuracy of existing provider-directed EHR CDS (vaccine alerts). RESULTS: With our proposed sample size and using a factorial design, power calculations using baseline vaccination rate estimates indicated that 4286 participants per arm would give 80% power to detect a 3% improvement in influenza vaccination rates between groups (alpha=.05; 2-sided). Intention-to-treat unadjusted chi-square analyses will be performed to assess the impact of portal messages, either alone or in combination with the IVR call, on influenza vaccination rates. The project was funded in January 2014. Patient enrollment for the project described here completed in December 2014. Data analysis is currently under way and first results are expected to be submitted for publication in 2016. CONCLUSIONS: If successful, this study\u27s intervention may be adapted by other large health care organizations to increase vaccination rates among their eligible patients. CLINICALTRIAL: ClinicalTrials.gov NCT02266277; https://clinicaltrials.gov/ct2/show/NCT02266277 (Archived by WebCite at http://www.webcitation.org/6fbLviHLH)

    Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study

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    BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians\u27 (PCPs\u27) opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs\u27 InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients\u27 posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs\u27 follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

    Electronic Health Record Portal Messages and Interactive Voice Response Calls to Improve Rates of Early Season Influenza Vaccination: Randomized Controlled Trial

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    BACKGROUND: Patient reminders for influenza vaccination, delivered via an electronic health record patient portal and interactive voice response calls, offer an innovative approach to engaging patients and improving patient care. OBJECTIVE: The goal of this study was to test the effectiveness of portal and interactive voice response outreach in improving rates of influenza vaccination by targeting patients in early September, shortly after vaccinations became available. METHODS: Using electronic health record portal messages and interactive voice response calls promoting influenza vaccination, outreach was conducted in September 2015. Participants included adult patients within a large multispecialty group practice in central Massachusetts. Our main outcome was electronic health record-documented early influenza vaccination during the 2015-2016 influenza season, measured in November 2015. We randomly assigned all active portal users to 1 of 2 groups: (1) receiving a portal message promoting influenza vaccinations, listing upcoming clinics, and offering online scheduling of vaccination appointments (n=19,506) or (2) receiving usual care (n=19,505). We randomly assigned all portal nonusers to 1 of 2 groups: (1) receiving interactive voice response call (n=15,000) or (2) receiving usual care (n=43,596). The intervention also solicited patient self-reports on influenza vaccinations completed outside the clinic. Self-reported influenza vaccination data were uploaded into the electronic health records to increase the accuracy of existing provider-directed electronic health record clinical decision support (vaccination alerts) but were excluded from main analyses. RESULTS: Among portal users, 28.4% (5549/19,506) of those randomized to receive messages and 27.1% (5294/19,505) of the usual care group had influenza vaccinations documented by November 2015 (P=.004). In multivariate analysis of portal users, message recipients were slightly more likely to have documented vaccinations when compared to the usual care group (OR 1.07, 95% CI 1.02-1.12). Among portal nonusers, 8.4% (1262/15,000) of those randomized to receive calls and 8.2% (3586/43,596) of usual care had documented vaccinations (P=.47), and multivariate analysis showed nonsignificant differences. Over half of portal messages sent were opened (10,112/19,479; 51.9%), and over half of interactive voice response calls placed (7599/14,984; 50.7%) reached their intended target, thus we attained similar levels of exposure to the messaging for both interventions. Among portal message recipients, 25.4% of message openers (2570/10,112) responded to a subsequent question on receipt of influenza vaccination; among interactive voice response recipients, 72.5% of those reached (5513/7599) responded to a similar question. CONCLUSIONS: Portal message outreach to a general primary care population achieved a small but statistically significant improvement in rates of influenza vaccination (OR 1.07, 95% CI 1.02-1.12). Interactive voice response calls did not significantly improve vaccination rates among portal nonusers (OR 1.03, 95% CI 0.96-1.10). Rates of patient engagement with both modalities were favorable. TRIAL REGISTRATION: ClinicalTrials.gov NCT02266277; https://clinicaltrials.gov/ct2/show/NCT02266277. Lloyd Fisher, Peggy Preusse, Devi Sundaresan, Lawrence Garber, Kathleen M Mazor, Sarah L Cutrona. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.09.2020

    Intervention to Reduce Adverse Outcomes among Older Adults Discharged from Skilled Nursing Facilities to Home

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    Background: Older adults may be at risk for adverse outcomes after discharge from skilled nursing facilities (SNF), but little research has focused on this transition. Objective: To assess the impact of an alert system on the rates of adverse outcomes among older adults discharged from SNFs to home. Methods: Within a multispecialty group practice, we tracked 30-day re-hospitalizations after SNF discharges during an intervention that provided discharge alerts to primary care physicians. We compared them to discharges from the pre-intervention period matched on age, gender and SNF. For the first 100 intervention discharges and their matches, we performed chart reviews to identify adverse drug events (ADEs). Multivariate analyses controlled for age, gender and intervention status. Results: We matched 313 intervention SNF discharges to 313 previous discharges. There was a slight reduction in the rate of 30-day re-hospitalization (30% vs. 31%) adjusted. Within the ADE study, 30% of the discharges during the intervention period and 30% of matched discharges had ADEs within 45 days. Among the 83 ADEs identified, 28% were deemed preventable; 69% resulted in symptom duration more than one day; 69% occurred within the first 14 days after discharge. This was a highly vulnerable population: mean age 82.5 (standard deviation (SD) 6.7); mean number of prescribed medications 11.9 (SD 8); 17% had Charlson Comorbidity Scores of ≥4. Common clinical conditions included myocardial infarction (24%), heart failure (22%), COPD (23%), and major depression (28%). Patients with scores of ≥4 were more likely to experience an ADE than those with lower scores (adjusted OR 2.5 (CI 1.2, 5.5), RD 0.21). Conclusion: Simply providing alerts when these vulnerable patients are discharged from SNFs is not sufficient to lower rates of adverse outcomes. Further research is required to track trajectories and identify additional points for interventions

    Fabrication of an Electrocatalyst Based on Rare Earth Manganites Incorporated with Carbon Nanofiber Hybrids: An Efficient Electrochemical Biosensor for the Detection of Anti-Inflammatory Drug Mefenamic Acid

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    Pharmaceutical and personal care products are emerging as a new category of environmental pollution. Analytical drug detection from a biological sample for detection is still crucial today. Mefenamic acid (MA) is an anti-inflammatory drug utilized for its antipyretic and analgesic properties, which is harmful to patients at higher dosages and is also recognized as a chemical pollutant that harms the environment. In this view, Dysprosium manganite/carbon nanofiber (DMO/CNF) was prepared by hydrothermal method for the electrochemical detection of MA. DMO/CNF/GCE exhibits high selectivity, excellent anti-interference, good stability, and reproducibility toward the detection of MA. The enhanced electrochemical performance of DMO/CNF/GCE was attributed to their synergetic interaction. Under optimized conditions, DMO/CNF/GCE shows a wide linear range of 0.01–741 μM and a low LOD of 0.009 μM. Satisfactory recoveries were obtained for human blood and tablet samples. Thus, the proposed DMO/CNF nanocomposite emerges as a promising material for the detection of MA

    Patient Portals: An Underused Resource for Improving Patient Engagement

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    The potential of patient portals to improve patient engagement and health outcomes has been discussed for more than a decade. The slow growth in patient portal adoption rates among patients and providers in the United States, despite external incentives, indicates that this is a complex issue. We examined evidence of patient portal use and effects with a focus on the pulmonary domain. We found a paucity of studies of patient portal use in pulmonary practice, and highlight gaps for future research. We also report on the experience of a pulmonary department using a patient portal to highlight the potential of these systems. Inc

    Targeting patients for early COVID-19 therapy; Pre-infection metabolic dysfunction, polycystic ovary syndrome and risk of severe disease in patients under 65: A Massachusetts community-based observational study.

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    IntroductionThe demographics of those developing severe coronavirus disease (COVID-19) outcomes are shifting to younger patients. In an observational study utilizing electronic health records from a Massachusetts group medical practice, we identified 5025 patients with confirmed COVID-19 from March 1 to December 18, 2020. Of these, 3870 were under 65 years of age. We investigated the hypothesis that pre-infection metabolic or immunologic dysregulation including polycystic ovary syndrome (PCOS) increased risk of serious COVID-19 outcomes in patients under 65 years of age.Materials and methodsWe compared those with COVID-19 related hospitalization or mortality to all other COVID-19 patients, using a case control approach. Using logistic regression and propensity score modeling, we evaluated risk of developing severe COVID-19 outcomes (hospitalization or death) in those with pre-infection comorbidities, metabolic risk factors, or PCOS.ResultsOverall, propensity score matched analyses demonstrated pre-infection elevated liver enzymes alanine aminotransferase (ALT) >40, aspartate aminotransferase (AST) >40 and blood glucose ≥215 mg/dL were associated with more severe COVID-19 outcomes, OR = 1.74 (95% CI 1.31, 2.31); OR = 1.98 (95% CI 1.52, 2.57), and OR = 1.55 (95% CI 1.08, 2.23) respectively. Elevated hemoglobin A1C or blood glucose levels were even stronger risk factors for severe COVID-19 outcomes among those aged ConclusionIncreased risk of severe COVID-19 outcomes in those < age 65 with pre-infection indicators of metabolic dysfunction heightens the importance of monitoring pre-infection indicators in younger patients for prevention and early treatment. The PCOS finding deserves further investigation. Meanwhile women who suffer from PCOS should be carefully evaluated and prioritized for earlier COVID-19 treatment and vaccination

    Tracking Health Care Team Response to Electronic Health Record Asynchronous Alerts: Role of In-Basket Message Burden

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    Background/Aims: Electronic health record (EHR)-based messaging allows communication of important patient information to primary care providers, but high message burdens may limit effectiveness and safety of this communication mode. Methods: We analyzed EHR data for 1,282 discharges of elderly patients (age ≥ 65) from a Massachusetts hospital in 2010–2011. For 799 of these discharges, time-sensitive automated EHR messages were generated on Day 3 postdischarge. These messages highlighted actionable concerns associated with medication changes and were sent to secure EHR In-Baskets belonging to the patients’ primary care physicians. We tracked timing of message reviews and calculated associations between primary care physician In-Basket message burden (i.e. number of messages in In-Basket at time of message delivery) and time to message opening. We also examined whether messages were opened by the intended physician, by a covering physician or by staff members. Results: Of the 799 messages, 376 (47.1%) were opened by the intended primary care physician within one business day, with an additional 2.0% (16) opened by covering physicians. In some cases, staff members opened messages and generated follow-up communication. These follow-up communications were read by the intended provider (2.8%, n = 22 messages) or a covering provider (0.9%, n = 7) within 24 hours of delivery. Overall, 41.1% of these time-sensitive messages were not opened by anyone within 24 hours; an additional 6.3% were opened by staff within the first 24 hours with no evidence that communications were passed along within the EHR. Rates of opening within 24 hours were inversely related to size of In-Basket at the time of message delivery, with 61.8% of messages opened within 24 hours among providers whose total number of In-Basket messages were in the bottom quartile (157 messages) (P \u3c 0.0001). Conclusion: Rates of opening of time-sensitive In-Basket messages were suboptimal; less than two-thirds of messages were opened within 24 hours. In-Basket message burden may impact physicians’ ability to devote timely attention to patient-related messages. Reducing In-Basket volume should be explored as a means of improving quality and safety of patient care
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