How Likes and Retweets Impacted Our Patients During the COVID-19 Pandemic.

The growing dependence on social media for health-related information boomed during the COVID-19 pandemic, posing unprecedented challenges in navigating the vast amounts of information available right at our fingertips. Social media had a major impact on clinical decision-making affecting individuals, communities, and societies at large. In this review, we discuss the role of social media in amplifying information and misinformation as well as factors contributing to its reliance and prevalence. We review how medical providers have been impacted by this changing landscape, useful communication strategies to employ with in-office patient encounters, and how we can be active players in using social media as a tool for health promotion, correcting misinformation, and preparing for future pandemics.

Heterogeneity of Drug Allergies and Reaction Lists in Two U.S. Health Care Systems' Electronic Health Records.

BACKGROUND: Health care institutions have their own "picklist" for clinicians to document adverse drug reactions (ADRs) into the electronic health record (EHR) allergy list. Whether the lack of a nationally standardized picklist impacts clinician data entries is unknown. OBJECTIVES: The objective of this study was to assess the impact of defined reaction picklists on clinical documentation and, therefore, downstream analytics and clinical research using these data at two institutions. METHODS: ADR data were obtained from the EHRs of patients who visited the emergency department or outpatient clinics at Brigham and Women's Hospital (BWH) and University of Colorado Hospital (UCH) from 2013 to 2018. Reported drug class ADR prevalences were calculated. We investigated the reactions on each picklist and compared the top 40 reactions at each institution, as well as the top 10 reactions within each drug class. RESULTS: Of 2,160,116 patients, 640,444 (30%) had 928,973 active drug allergies. The most commonly reported drug class allergens were similar between BWH and UCH. BWH's picklist had 48 reactions, and UCH's had 160 reactions; 29 reactions were shared by both picklists. While the top four reactions overall (rash, GI upset/nausea/vomiting, hives, itching) were identical between sites, reactions by drug class exhibited greater documentation diversity. For example, while the summed prevalence of swelling-related reactions to angiotensin-converting-enzyme inhibitors was comparable across sites, swelling was represented by two terms ("swelling," "angioedema") at BWH but 11 terms at UCH (e.g., "swelling," "edema," by body locality). CONCLUSION: The availability and granularity of reaction picklists impact ADR documentation in the EHR by health care providers; picklists may partially explain variations in reported ADRs across health care systems.

Improving Allergy Documentation: A Retrospective Electronic Health Record System-Wide Patient Safety Initiative.

OBJECTIVES: Documentation of allergies in a coded, non-free-text format in the electronic health record (EHR) triggers clinical decision support to prevent adverse events. Health system-wide patient safety initiatives to improve EHR allergy documentation by specifically decreasing free-text allergy entries have not been reported. The goal of this initiative was to systematically reduce free-text allergen entries in the EHR allergy module. METHODS: We assessed free-text allergy entries in a commercial EHR used at a multihospital integrated health care system in the greater Boston area. Using both manual and automated methods, a multidisciplinary consensus group prioritized high-risk and frequently used free-text allergens for conversion to coded entries, added new allergen entries, and deleted duplicate allergen entries. Environmental allergies were moved to the patient problem list. RESULTS: We identified 242,330 free-text entries, which included a variety of environmental allergies (42%), food allergies (18%), contrast media allergies (13%), "no known allergy" (12%), drug allergies (2%), and "no contrast allergy" (2%). Most free-text entries were entered by medical assistants in ambulatory settings (34%) and registered nurses in perioperative settings (20%). We remediated a total of 52,206 free-text entries with automated methods and 79,578 free-text entries with manual methods. CONCLUSIONS: Through this multidisciplinary intervention, we identified and remediated 131,784 free-text entries in our EHR to improve clinical decision support and patient safety. Additional strategies are required to completely eliminate free-text allergy entry, and establish systematic, consistent, and safe guidelines for documenting allergies.

Symptom monitoring after coronavirus disease 2019 (COVID-19) vaccination in a large integrated healthcare system: Separating symptoms from severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection.

OBJECTIVE: To describe the incidence of systemic overlap and typical coronavirus disease 2019 (COVID-19) symptoms in healthcare personnel (HCP) following COVID-19 vaccination and association of reported symptoms with diagnosis of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in the context of public health recommendations regarding work exclusion. DESIGN: This prospective cohort study was conducted between December 16, 2020, and March 14, 2021, with HCP who had received at least 1 dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine. SETTING: Large healthcare system in New England. INTERVENTIONS: HCP were prompted to complete a symptom survey for 3 days after each vaccination. Reported symptoms generated automated guidance regarding symptom management, SARS-CoV-2 testing requirements, and work restrictions. Overlap symptoms (ie, fever, fatigue, myalgias, arthralgias, or headache) were categorized as either lower or higher severity. Typical COVID-19 symptoms included sore throat, cough, nasal congestion or rhinorrhea, shortness of breath, ageusia and anosmia. RESULTS: Among 64,187 HCP, a postvaccination electronic survey had response rates of 83% after dose 1 and 77% after dose 2. Report of ≥3 lower-severity overlap symptoms, ≥1 higher-severity overlap symptoms, or at least 1 typical COVID-19 symptom after dose 1 was associated with increased likelihood of testing positive. HCP with prior COVID-19 infection were significantly more likely to report severe overlap symptoms after dose 1. CONCLUSIONS: Reported overlap symptoms were common; however, only report of ≥3 low-severity overlap symptoms, at least 1 higher-severity overlap symptom, or any typical COVID-19 symptom were associated with infection. Work-related restrictions for overlap symptoms should be reconsidered.

Association of Self-reported High-Risk Allergy History With Allergy Symptoms After COVID-19 Vaccination.

Importance: Allergic history in individuals with confirmed anaphylaxis to a messenger RNA (mRNA) COVID-19 vaccine is common. However, the risk factors for allergy symptoms after receiving the vaccine are unknown. Objective: To assess the association between self-reported history of high-risk allergy and self-reported allergic reactions after mRNA COVID-19 vaccination of health care employees. Design, Setting, and Participants: This cohort study obtained demographic, medical, and vaccine administration data of employees of Mass General Brigham from the institutional electronic health record. Employees who received at least 1 dose of an mRNA COVID-19 vaccine between December 14, 2020, and February 1, 2021, and who completed at least 1 postvaccination symptom survey in the 3 days after vaccination were included. Exposures: Self-reported history of high-risk allergy, defined as a previous severe allergic reaction to a vaccine, an injectable medication, or other allergen. Main Outcomes and Measures: The primary outcome was 1 or more self-reported allergic reactions in the first 3 days after dose 1 or dose 2 of an mRNA COVID-19 vaccine. Multivariable log binomial regression was used to assess the association between allergic reactions and high-risk allergy status. Results: A total of 52 998 health care employees (mean [SD] age, 42 [14] years; 38 167 women [72.0%]) were included in the cohort, of whom 51 706 (97.6%) received 2 doses of an mRNA COVID-19 vaccine and 474 (0.9%) reported a history of high-risk allergy. Individuals with vs without a history of high-risk allergy reported more allergic reactions after receiving dose 1 or 2 of the vaccine (11.6% [n = 55] vs 4.7% [n = 2461]). In the adjusted model, a history of high-risk allergy was associated with an increased risk of allergic reactions (adjusted relative risk [aRR], 2.46; 95% CI, 1.92-3.16), with risk being highest for hives (aRR, 3.81; 95% CI, 2.33-6.22) and angioedema (aRR, 4.36; 95% CI, 2.52-7.54). Conclusions and Relevance: This cohort study found that self-reported history of high-risk allergy was associated with an increased risk of self-reported allergic reactions within 3 days of mRNA COVID-19 vaccination. However, reported allergy symptoms did not impede the completion of the 2-dose vaccine protocol among a cohort of eligible health care employees, supporting the overall safety of mRNA COVID-19 vaccine.

The Importance of a Timely Second Dose of the 2021 COVID-19 mRNA Vaccine Depends on the Protection Afforded by a First Dose and Subsequent Risk of Anaphylaxis.

Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents our greatest hope to combat the devastating coronavirus disease 2019 (COVID-19) pandemic. Amid ongoing global vaccination efforts, rare cases of severe allergic reactions to COVID-19 mRNA vaccines have received significant attention. Although the exact nature of these reactions may be heterogeneous, various approaches exist to engage with patients, communities, public health departments, primary care providers, and other clinicians in a multidisciplinary approach to advance population health. Whereas it is optimal for patients to receive COVID-19 vaccination as outlined in emergency use authorizations, second-dose deferral of mRNA vaccines may be a consideration within a shared decision-making paradigm of care in select circumstances characterized by high durable first-vaccine-dose protection and significant elevations of vaccine anaphylaxis risk. Still, the durability of protection afforded by a single dose of a COVID-19 mRNA vaccine is uncertain, and alternative approaches to complete vaccination, including precautionary use of a COVID-19 viral vector vaccine, also remain patient-preference-sensitive options. There is an urgent need to define correlates of COVID-19 immunity and the level of longer-term protection afforded by COVID-19 vaccination.

mRNA Vaccines to Prevent COVID-19 Disease and Reported Allergic Reactions: Current Evidence and Suggested Approach.

The U.S. Food and Drug Administration (FDA) has recently issued an Emergency Use Authorization (EUA) for 2 highly effective coronavirus disease 2019 (COVID-19) vaccines from Pfizer-BioNTech and Moderna. This has brought hope to millions of Americans in the midst of an ongoing global pandemic. The FDA EUA guidance for both vaccines is to not administer the vaccine to individuals with a known history of a severe allergic reaction (eg, anaphylaxis) to any component of the COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) additionally advises individuals with a history of an immediate allergic reaction to a vaccine or injectable or any history of anaphylaxis be observed for 30 minutes after COVID-19 vaccination. All other individuals should be observed for 15 minutes after COVID-19 vaccination. Staff at vaccine clinics must be able to identify and manage anaphylaxis. Post-FDA EUA, despite very strong safety signals in both phase 3 trials, reports of possible allergic reactions have raised public concern. To provide reassurance and support during widespread global vaccination, allergists must offer clear guidance to individuals based on the best information available, but also in accordance with the broader recommendations of regulatory agencies. This review summarizes vaccine allergy epidemiology and proposes drug and vaccine allergy expert opinion informed risk stratification for Allergy specialist use in conjunction with guidance of public health and regulatory authorities. The risk stratification schema guide care for (1) individuals with different allergy histories to safely receive their first mRNA COVID-19 vaccine and (2) individuals who develop a reaction to their first dose of mRNA COVID-19 vaccine.

Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals.

Importance: Although critical to patient safety, health care-related allergic reactions are challenging to identify and monitor. Objective: To develop a deep learning model to identify allergic reactions in the free-text narrative of hospital safety reports and evaluate its generalizability, efficiency, productivity, and interpretability. Design, Setting, and Participants: This cross-sectional study analyzed hospital safety reports filed between May 2004 and January 2019 at Brigham and Women's Hospital and between April 2006 and June 2018 at Massachusetts General Hospital in Boston. Training and validating a deep learning model involved extracting safety reports using 101 expert-curated keywords from Massachusetts General Hospital (data set I). The model was then evaluated on 3 data sets: reports without keywords (data set II), reports from a different time frame (data set III), and reports from a different hospital (Brigham and Women's Hospital; data set IV). Statistical analyses were performed between March 1, 2019, and July 18, 2020. Main Outcomes and Measures: The area under the receiver operating characteristic curve and area under the precision-recall curve were used on data set I. The precision at top-k was used on data sets II to IV. Results: A total of 299 028 safety reports with 172 854 patients were included. Of these patients, 86 544 were women (50.1%) and the median (interquartile range [IQR]) age was 59.7 (43.8-71.6) years. The deep learning model achieved an area under the receiver operating characteristic curve of 0.979 (95% CI, 0.973-0.985) and an area under the precision-recall curve of 0.809 (95% CI, 0.773-0.845). The model achieved precisions at the top 100 model-identified cases of 0.930 in data set II, 0.960 in data set III, and 0.990 in data set IV. Compared with the keyword-search approach, the deep learning model reduced the number of cases for manual review by 63.8% and identified 24.2% more cases of confirmed allergic reactions. The model highlighted important words (eg, rash, hives, and Benadryl) in prediction and extended the list of expert-curated keywords through an attention layer. Conclusions and Relevance: This study showed that a deep learning model can accurately and efficiently identify allergic reactions using free-text narratives written by a variety of health care professionals. This model could be used to improve allergy care, potentially enabling real-time event surveillance and guidance for medical errors and system improvement.

Conducting Safety Research Safely: A Policy-Based Approach for Conducting Research with Peer Review Protected Material.

A multidisciplinary team developed a policy-based approach that provides guidance for using peer review protected information for safety research while maintaining peer review privilege. The approach includes project approval by an ad hoc review committee, signed confidentiality agreements by investigators and study staff, early removal of case identification numbers, standards for maintaining data security, and publication of aggregate data without data set sharing. By describing this procedure and embedding into an institutional policy on Data for Performance Improvement, the team encourages other institutions to develop similar policies consistent with their state regulations.

An Internet of Things Buttons to Measure and Respond to Restroom Cleanliness in a Hospital Setting: Descriptive Study.

BACKGROUND: Restroom cleanliness is an important factor in hospital quality. Due to its dynamic process, it can be difficult to detect the presence of dirty restrooms that need to be cleaned. Using an Internet of Things (IoT) button can permit users to designate restrooms that need cleaning and in turn, allow prompt response from housekeeping to maintain real-time restroom cleanliness. OBJECTIVE: This study aimed to describe the deployment of an IoT button-based notification system to measure hospital restroom cleanliness reporting system usage and qualitative feedback from housekeeping staff on IoT button use. METHODS: We deployed IoT buttons in 16 hospital restrooms. Over an 8-month period, housekeeping staff received real-time notifications and responded to button presses for restroom cleaning. All button presses were recorded. We reported average button usage by hospital area, time of day, and day of week. We also conducted interviews with housekeeping supervisors and staff to understand their acceptance of and experience with the system. RESULTS: Over 8 months, 1920 requests to clean restrooms in the main hospital lobby and satellite buildings were received. The hospital lobby IoT buttons received over half (N=1055, 55%) of requests for cleaning. Most requests occurred in afternoon hours from 3 PM to midnight. Requests for cleaning remained stable throughout the work week with fewer requests occurring over weekends. IoT button use was sustained throughout the study period. Interviews with housekeeping supervisors and staff demonstrated acceptance of the IoT buttons; actual use was centered around asynchronous communication between supervisors and staff in response to requests to clean restrooms. CONCLUSIONS: An IoT button system is a feasible method to generate on-demand request for restroom cleaning that is easy to deploy and that users will consistently engage with. Data from this system have the potential to enable responsive scheduling for restroom service and anticipate periods of high restroom utilization in a hospital.

Outcomes from an inpatient beta-lactam allergy guideline across a large US health system.

OBJECTIVE: To assess the safety of, and subsequent allergy documentation associated with, an antimicrobial stewardship intervention consisting of test-dose challenge procedures prompted by an electronic guideline for hospitalized patients with reported ß-lactam allergies. DESIGN: Retrospective cohort study. SETTING: Large healthcare system consisting of 2 academic and 3 community acute-care hospitals between April 2016 and December 2017. METHODS: We evaluated ß-lactam antibiotic test-dose outcomes, including adverse drug reactions (ADRs), hypersensitivity reactions (HSRs), and electronic health record (EHR) allergy record updates. HSR predictors were examined using a multivariable logistic regression model. Modification of the EHR allergy record after test doses considered relevant allergy entries added, deleted, and/or specified. RESULTS: We identified 1,046 test-doses: 809 (77%) to cephalosporins, 148 (14%) to penicillins, and 89 (9%) to carbapenems. Overall, 78 patients (7.5%; 95% confidence interval [CI], 5.9%-9.2%) had signs or symptoms of an ADR, and 40 (3.8%; 95% CI, 2.8%-5.2%) had confirmed HSRs. Most HSRs occurred at the second (ie, full-dose) step (68%) and required no treatment beyond drug discontinuation (58%); 3 HSR patients were treated with intramuscular epinephrine. Reported cephalosporin allergy history was associated with an increased odds of HSR (odds ratio [OR], 2.96; 95% CI, 1.34-6.58). Allergies were updated for 474 patients (45%), with records specified (82%), deleted (16%), and added (8%). CONCLUSION: This antimicrobial stewardship intervention using ß-lactam test-dose procedures was safe. Overall, 3.8% of patients with ß-lactam allergy histories had an HSR; cephalosporin allergy histories conferred a 3-fold increased risk. Encouraging EHR documentation might improve this safe, effective, and practical acute-care antibiotic stewardship tool.

Addressing Inpatient Beta-Lactam Allergies: A Multihospital Implementation.

Addressing inaccurate penicillin allergies is encouraged as part of antibiotic stewardship in the inpatient setting. However, implementing interventions targeted at the 10% to 15% of inpatients reporting a previous penicillin allergy can pose substantial logistic challenges. We implemented a computerized guideline for patients with reported beta-lactam allergy at 5 hospitals within a single health care system in the Boston area. In this article, we describe our implementation roadmap, including both successes achieved and challenges faced. We explain key implementation steps, including assembling a team, stakeholder engagement, developing or selecting an approach, spreading the change, establishing measures, and measuring impact. The objective was to detail the lessons learned while empowering others to be part of this important, multidisciplinary work to improve the care of patients with reported beta-lactam allergies.