Electronic Health Record Search Research Articles

Artificial Intelligence to Facilitate Clinical Trial Recruitment in Age-Related Macular Degeneration

ObjectiveRecent developments in artificial intelligence (AI) have positioned it to transform several stages of the clinical trial process. In this study, we explore the role of AI in clinical trial recruitment of individuals with geographic atrophy (GA), an advanced stage of age-related macular degeneration, amidst numerous ongoing clinical trials for this condition. DesignCross-sectional study.Subjects, Participants, and/or Controls: Retrospective dataset from the INSIGHT Health Data Research Hub at Moorfields Eye Hospital in London, United Kingdom, including 306,651 patients (602,826 eyes) with suspected retinal disease who underwent optical coherence tomography (OCT) imaging between 1 January 2008 and 10 April 2023. Methods, Intervention, or TestingA deep learning model was trained on OCT scans to identify patients potentially eligible for GA trials, using AI-generated segmentations of retinal tissue. This method's efficacy was compared against a traditional keyword-based electronic health record (EHR) search. A clinical validation with fundus autofluorescence (FAF) images was performed to calculate the positive predictive value (PPV) of this approach, by comparing AI predictions to expert assessments. Main Outcome MeasuresThe primary outcomes included the PPV of AI in identifying trial-eligible patients, and the secondary outcome was the intraclass correlation between GA areas segmented on FAF by experts and AI-segmented OCT scans. ResultsThe AI system shortlisted a larger number of eligible patients with greater precision (1,139, PPV: 63%; 95% CI: 54–71%) compared to the EHR search (693, PPV: 40%; 95% CI: 39–42%). A combined AI-EHR approach identified 604 eligible patients with a PPV of 86% (95% CI: 79–92%). Intraclass correlation of GA area segmented on FAF versus AI-segmented area on OCT was 0.77 (95% CI: 0.68–0.84) for cases meeting trial criteria. The AI also adjusts to the distinct imaging criteria from several clinical trials, generating tailored shortlists ranging from 438 to 1,817 patients. ConclusionsThis study demonstrates the potential for AI in facilitating automated pre-screening for clinical trials in GA, enabling site feasibility assessments, data-driven protocol design, and cost reduction. Once treatments are available, similar AI systems could also be used to identify individuals who may benefit from treatment.

Abstract 4827: Financial toxicity among cancer survivors during the COVID-19 pandemic

Abstract Background: Financial toxicity (FT), the financial impact of cancer and its treatments on patients’ employment, income, and health insurance, can have significant short- and long-term consequences for cancer survivors. With significant increases in cancer survivorship and the changing demographics of the United States, a need exists to identify those most susceptible to FT. This study evaluated FT prevalence during the COVID-19 pandemic and identified factors associated with greater FT risk. Methods: Data were collected from 1,147 cancer survivors recruited from previous National Cancer Institute-funded studies, from electronic health record searches for patients with cancer diagnoses at University of California, San Francisco (UCSF) and Mount Sinai Medical Center and Columbia University Medical Center in New York City, and the Dr. Susan Love Foundation for Breast Cancer Research. Adults, diagnosed with cancer and proficient in English, completed an online survey via the Research Electronic Data Capture (REDCap) system between May 27, 2020 and February 21, 2021. FT was assessed for the past 14 days using the validated 11-item COmprehensive Score for financial Toxicity (COST) measure. Patients were categorized by score: no FT (COST scores >25), mild FT (14-25), and moderate/severe FT (0-13). Using Pearson’s chi-square test of independence, and univariate ordinal logistic regression, the study evaluated sociodemographic and clinical characteristics associated with FT, including age, race and ethnicity, gender, household income, education, marital status, health insurance status, and cancer site. Results: The COST measure had excellent reliability for the sample (Cronbach’s alpha = 0.911). Overall, 9% of respondents reported moderate/severe FT (MSFT), 16% mild. Race/ethnicity, education level, annual household income, cancer site, and years from diagnosis (p-values ≤ 0.035) were associated with FT. Current health insurance coverage was not associated with FT (p=0.456). 18% Black, 13% Asian American, 17% mixed, and 20% other races/ethnicities reported MSFT, while 8% non-Hispanic White and 5% Hispanic respondents reported the same. 31% of survivors with annual household income <$40,000 reported MSFT vs. 7% with ≥$40,000 income. 14% of survivors with less than a college degree reported MSFT vs. 8% amongst those with a college degree or higher. For men, the odds of having FT (mild or MSFT) were 0.60 (95% CI 0.40, 0.90) times that of women. Survivors <50 years old at diagnosis had 7.53 (95% CI 4.09, 13.83) times the odds of FT (mild or MSFT) vs. those aged ≥75 years. Conclusions: These preliminary analyses from this cross-sectional study characterizes the prevalence and determinants of FT experienced by cancer survivors during the COVID-19 pandemic. The next steps will include multivariable analysis and comparison with pre-pandemic data, to identify those at greatest risk and inform interventions. Citation Format: Tanvi Srivastava, Salma Shariff-Marco, Samuel L. Washington, Christine Miaskowski, June M. Chan. Financial toxicity among cancer survivors during the COVID-19 pandemic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4827.

Cluster of Nontoxigenic Corynebacterium diphtheriae Infective Endocarditis and Rising Background C. diphtheriae Cases-Seattle, Washington, 2020-2023.

Nontoxigenic Corynebacterium diphtheriae, often associated with wounds, can rarely cause infective endocarditis (IE). Five patients with C. diphtheriae IE were identified within 12 months at a Seattle-based hospital system. We reviewed prior C. diphtheriae-positive cultures to determine if detections had increased over time and evaluated epidemiologic trends. We conducted a formal electronic health record search to identify all patients aged ≥18 years with C. diphtheriae detected in a clinical specimen (ie, wound, blood, sputum) between 1 September 2020 and 1 April 2023. We collected patient demographics, housing status, comorbidities, substance-use history, and level of medical care required at detection. We extracted laboratory data on susceptibilities of C. diphtheriae isolates and on other pathogens detected at the time of C. diphtheriae identification. Between 1 September 2020 and 1 April 2023, 44 patients (median age, 44 years) had a C. diphtheriae-positive clinical culture, with most detections occurring after March 2022. Patients were predominantly male (75%), White (66%), unstably housed (77%), and had a lifetime history of injecting drugs (75%). Most C. diphtheriae-positive cultures were polymicrobial, including wound cultures from 36 (82%) patients and blood cultures from 6 (14%) patients, not mutually exclusive. Thirty-four patients (77%), including all 5 patients with C. diphtheriae IE, required hospital admission for C. diphtheriae or a related condition. Of the 5 patients with IE, 3 died of IE and 1 from COVID-19. Findings suggest a high-morbidity outbreak disproportionately affecting patients who use substances and are unstably housed.

Arthrocentesis of suspected septic sternoclavicular arthritis: microbial yield and predictors of culture positivity.

Evaluate the microbial yield and factors predicting culture positivity for image-guided arthrocentesis of suspected septic sternoclavicular (SC) arthritis. An electronic health record search identified image-guided SC joint aspirations for suspected septic arthritis. Data was extracted by retrospective chart review including patient demographics, procedure characteristics, pre-procedure lab testing, joint culture results, final SC joint diagnoses and any effect of positive synovial cultures on subsequent antibiotic therapy. Factors associated with positive joint fluid cultures were assessed using a Chi-squared test for categorical predictors and logistic regression for continuous predictors. A total of 31 SC arthrocenteses met inclusion criteria with most (81%) performed using ultrasound guidance. Synovial fluid was successfully aspirated in 19/31 (61%) of cases, and in all other cases lavage fluid was successfully obtained. Synovial cultures were positive in 9/31 (29%) of cases. A final diagnosis of septic arthritis was assigned to 20/31 cases (65%) in which 9/20 (45%) had positive synovial cultures. There was no statistically significant association between synovial culture positivity and risk factors for septic arthritis, positive blood cultures, pre-aspiration antibiotics and whether synovial fluid or lavage fluid was cultured. Serum white blood cell count (WBC) and erythrocyte sedimentation rate (ESR) demonstrated statistically significant positive correlation with positive synovial cultures. Arthrocentesis is effective for microbial speciation in SC septic arthritis, and diagnostic yield may be increased with lavage when encountering a dry tap. Normal serum WBC and ESR values indicate an extremely low likelihood of positive synovial cultures.

Identification of Persons Living with Dementia Using the Electronic Health Record

AbstractBackgroundAlzheimer’s disease and related dementias (ADRD) are underdiagnosed in the primary care setting. Proactive screening for cognitive impairment and subsequent evaluation and diagnosis of patients who screen positive are not routinely and reliably performed. As a result, identification of persons living with dementia (PLWD) for enrollment in clinical programs, clinical trials, and research studies can be challenging. The electronic health record (EHR) represents a potentially viable tool to efficiently and accurate identify PLWD.MethodsIn a large academic health care system in the U.S., we performed an EPIC EHR search for PLWD with the intent of enrolling them in an outpatient dementia care management program. The EHR algorithm used the following criteria for dementia: (1) an ICD‐10 dementia diagnosis in the problem list or past medical history or (2) an FDA‐approved drug on their active medication list. We performed chart review for patients who were identified to have potential dementia using this algorithm to confirm dementia diagnosis is documented in clinical notes.ResultsA total of 985 patients were identified by EHR criteria as potentially having dementia. After chart review, 747 (75.8%) were confirmed to have dementia documented in their clinical history and progress notes. One hundred thirty (13.2%) did not have a confirmed dementia diagnosis, 58 (5.9%) had an incomplete dementia evaluation, and 50 (5.0%) had only mild cognitive impairment. In addition, 55 (5.6%) were deceased.ConclusionWe found that an EHR algorithm can identify patients with dementia in a health plan population. This model may be a useful tool for a focused recruitment of potential participants in clinical trials, research studies, and clinical programs.

Assessing, updating and utilising primary care smoking records for lung cancer screening

BackgroundLung cancer screening with low-dose computed tomography for high-risk populations is being implemented in the UK. However, inclusive identification and invitation of the high-risk population is a major challenge for equitable lung screening implementation. Primary care electronic health records (EHRs) can be used to identify lung screening-eligible individuals based on age and smoking history, but the quality of EHR smoking data is limited. This study piloted a novel strategy for ascertaining smoking status in primary care and tested EHR search combinations to identify those potentially eligible for lung cancer screening.MethodsSeven primary care General Practices in South Wales, UK were included. Practice-level data on missing tobacco codes in EHRs were obtained. To update patient EHRs with no tobacco code, we developed and tested an algorithm that sent a text message request to patients via their GP practice to update their smoking status. The patient’s response automatically updated their EHR with the relevant tobacco code. Four search strategies using different combinations of tobacco codes for the age range 55-74+ 364 were tested to estimate the likely impact on the potential lung screening-eligible population in Wales. Search strategies included: BROAD (wide range of ever smoking codes); VOLUME (wide range of ever-smoking codes excluding “trivial” former smoking); FOCUSED (cigarette-related tobacco codes only), and RECENT (current smoking within the last 20 years).ResultsTobacco codes were not recorded for 3.3% of patients (n = 724/21,956). Of those with no tobacco code and a validated mobile telephone number (n = 333), 55% (n = 183) responded via text message with their smoking status. Of the 183 patients who responded, 43.2% (n = 79) had a history of smoking and were potentially eligible for lung cancer screening. Applying the BROAD search strategy was projected to result in an additional 148,522 patients eligible to receive an invitation for lung cancer screening when compared to the RECENT strategy.ConclusionAn automated text message system could be used to improve the completeness of primary care EHR smoking data in preparation for rolling out a national lung cancer screening programme. Varying the search strategy for tobacco codes may have profound implications for the size of the population eligible for lung-screening invitation.

P013 A three-year audit of dose tapering biologic medications in a rheumatology service

Abstract Background/Aims Dose tapering of biologic therapies is supported by both ACR and EULAR guidelines. Identification of appropriate patients may deliver cost savings whilst minimising the risk of disease flare. To audit dose tapering activity for patients treated with bDMARD for rheumatoid (RA), psoriatic arthritis (PsA) and ankylosing spondylosis (AS) meeting locally agreed criteria over three years. Methods All patients treated with a bDMARD for RA, PsA or AS fulfilling criteria for dose tapering between 1st October 2019 - 1st October 2021 were identified from electronic health records (EHR). Rituximab patients were excluded due to reactive treatment responding to flare. Patients were required to have been on their bDMARD for = > one year, not prescribed oral steroids / treated with parenteral steroids in the past six months, no swollen joints in the past six months, and not failed dose tapering in the previous year. RA patients were ineligible if DAS ≥3.2 in the previous year; PsA if their biologic was prescribed by dermatology /active psoriasis; AS patients if BASDAI score of > 4 in past year. Records were flagged to prompt a shared decision-making discussion between the treating clinician and patient during routine appointments; additional patients were identified through clinical assessment. Failing dose tapering was defined as a post tapering flare requiring dose increase within one year. Patients were tapered by increasing the interval of a bDMARD. Results The number of patients that dose tapered increased from 24 in 2019 to 51 in 2021, making a total estimated NHS list saving of up to £170,000 per annum. (Table 1). Tapering was unsuccessful for 7/116 (6%) due to post tapering flares. Patients flaring after tapering were reassessed urgently and had their bDMARD dose reviewed. More patients were eligible than identified from EHR search due to missing data in coding; 787 (61%) across all years. Conclusion Dose tapering was well tolerated in eligible patients making this a safe and acceptable initiative. Use of EHR data and behavioural prompts for clinicians supported this in practice. Cost savings were reinvested to increase pharmacy support for homecare prescription management. Disclosure H. Light: None. J. Firth: None. J. Bluett: Grants/research support; JB has received a research grant from Pfizer. Other; JB has received travel/conference fees from UCB, Pfizer and Eli Lilly. K. Kinsey: None.

Designing an Optimized Electronic Health Record Search Strategy to Identify Patients with Peanut Food Protein Induced Enterocolitis Syndrome (FPIES)

While peanut FPIES is increasingly reported, its true frequency is challenging to measure systematically. We sought to design a strategy to facilitate accurate identification of patients with peanut FPIES utilizing the electronic health record (EHR).

Evaluation of the use of COVID-19 vaccines in patients treated with immunotherapy.

e18781 Background: Immunotherapy can boost a patient’s immune system to bring about anti-tumor activity and may theoretically exaggerate the inflammatory immune response to infection or vaccinations. Conversely, vaccination may enhance immune activity in patients on immunotherapy. Currently, there are limited safety data in patients treated with immunotherapy who received COVID-19 vaccines. Methods: An IRB-approved retrospective review of Dana-Farber Cancer Institute patients treated with PD-1 checkpoint inhibitors and received COVID-19 vaccines was performed. The primary endpoint was the incidence rate of immune-related adverse events (irAEs) pre- and post- COVID-19 vaccinations. An Electronic Health Record search identified all patients who completed COVID-19 vaccines between 12/1/2020 and 3/31/2021 and received anti-PD-1 monotherapy between 10/1/2020 and 5/31/2021. Medical record review identified timing, occurrence, and grading of irAEs as defined by clinicians or Common Terminology Criteria for Adverse Events (CTCAE), version 5.0. Results: A total of 229 patients were included in the study. The most common underlying cancers were lung (32%) and melanoma (26%). The majority of patients had Pfizer-BioNTech COVID-19 vaccine; 64% of all patients received the third dose of vaccine. The median duration of treatment was 15 months, and median duration of follow-up was 19 months. Among the study cohort, 120 irAEs occurred before vaccination (any grade); 30 (25%) were grade 1, 35 (29%) were grade 2, 11 (9%) were grade 3 or 4, and 44 (37%) were ungraded. The main types of irAEs were skin toxicities (37% of all irAEs) followed by thyroid dysfunction (22%) and colitis (11%). Of the 75 irAEs that occurred after vaccination, 24 (32%) were grade 1, 16 (21%) were grade 2, 16 (21%) were grade 3 or 4, and 19 (26%) were ungraded. The main irAEs types were skin toxicity (31% of all irAEs) followed by thyroid dysfunction (13%) and hepatic toxicity (12 %). The all-grade pre- and post-vaccine irAE incidence rates per 100 patient-months were 4.13 and 5.09, respectively. Within this cohort, there were 0.96 (95% CI -0.362-2.284, p = 0.15) more irAEs post vaccine per 100 patient-months of anti-PD-1 therapy. Conclusions: The data weakly suggested that there is a higher incidence of irAEs post COVID-19 vaccine; however, the comparison did not achieve statistical significance. Further analysis of other patient characteristics will help to determine if any specific patterns are observed.[Table: see text]

Surgical Outcomes After Bucket-Handle Meniscal Repairs: Analysis of a Large Contained Cohort

Background: Representing approximately 10% of all meniscal tears, bucket-handle meniscal tears (BHMTs) are large longitudinal vertical tears that have an attached fragment flipped into the intercondylar notch. Meniscectomy often results in significant meniscal loss and increased joint loading. Alternatively, meniscal repair attempts to restore the function of the meniscus and aims to preserve joint mechanics. Purpose: To evaluate the long-term risk of subsequent ipsilateral knee surgery in patients who underwent a bucket-handle meniscal repair (BHMR), and to assess risk factors associated with subsequent knee surgical intervention. Study Design: Case series; Level of evidence, 4. Methods: We performed an electronic health record search for all patients aged 12 to 65 years who underwent arthroscopic knee meniscal repairs for BHMT (2011-2018). We excluded patients who had a previous BHMR, did not have magnetic resonance imaging of the knee within 60 days before BHMR, lacked active membership in Kaiser insurance in the year before and after BHMR, or underwent meniscectomy before BHMR. All patients were followed until December 31, 2019, with censoring at death or membership disenrollment. Primary outcomes included ipsilateral knee procedures overall and by type (ie, repeat meniscal repair and meniscectomy); secondary outcomes included other surgical interventions of the same knee, any contralateral knee surgery, deep surgical-site infection, and deep venous thrombosis or pulmonary embolism. Results: The final cohort included 1359 patients with a median age of 24 years (interquartile range [IQR], 17-34) who underwent BHMR for a BHMT. During the follow-up period (median, 50.2 months [IQR, 32.3-60.6]), 495 subsequent ipsilateral procedures were performed in 274 (20.2%) patients, and the median time to the first procedure was 10.6 months (IQR, 4.1-23.5). An overall 59 (4.3%) patients underwent repeat meniscal repair, and 165 (12.1%) had a subsequent meniscectomy of the same knee. Significant risk factors for subsequent ipsilateral procedures included younger age, 12 to 18 years (adjusted odds ratio [aOR], 5.77 [95% CI, 1.84-18.08]) and 19 to 30 years (aOR, 3.65 [95% CI, 1.17-11.36]), as well as normal and overweight body mass index (aOR, 2.84 [95% CI, 1.29-6.23] and 2.34 [95% CI, 1.06-5.17], respectively). Patients undergoing concomitant anterior cruciate ligament reconstruction (ACLR) at the initial BHMR had a lower risk of undergoing subsequent surgery (aOR, 0.66 [95% CI, 0.49-0.87]) than those without concomitant ACLR. Conclusion: This is the largest reported study on outcomes after BHMR in a contained cohort. One-fifth of patients underwent subsequent ipsilateral surgery during follow-up, with 4.3% receiving a repeat meniscal repair and 12.1% experiencing a meniscectomy. Risk factors for subsequent surgery of the same knee included younger age and normal or overweight body mass index. Concomitant ACLR at time of BHMR reduced the risk of subsequent reoperation.

The use of electronic health records for recruitment in clinical trials: a mixed methods analysis of the Harmony Outcomes Electronic Health Record Ancillary Study

BackgroundThe electronic health record (EHR) contains a wealth of clinical data that may be used to streamline the identification of potential clinical trial participants. However, there is little empirical information on site-level facilitators of and barriers to optimal use of EHR systems with respect to trial recruitment.MethodsWe conducted qualitative focus groups and quantitative surveys as part of the EHR Ancillary Study, which is being conducted alongside the multicenter, global, Harmony Outcomes Trial comparing albiglutide to standard care for the prevention of cardiovascular events in type 2 diabetes. Subject matter experts used findings from focus groups to draft a 20-question survey examining the use of the EHR for participant identification, common site recruitment strategies, and variation in perceived barriers to optimal use of the EHR. The final survey was fielded with 446 site investigators actively enrolling participants in the main trial.ResultsNearly two-thirds of respondents were study coordinators (63.2%), 23.1% were principal investigators, and 13.7% held other research roles. Approximately half of the respondents reported using the EHR to find potential trial participants. Of these, 79.4% reported using EHR searches in conjunction with other recruitment methods, including reviewing of upcoming clinic schedules (75.3%) and contacting past trial participants (71.2%). Important barriers to optimal use of the EHR included the lack of availability of certain research-focused EHR modules and limitations on the ability to contact patients cared for by other providers. Of survey respondents who did not use the EHR to find potential participants, one-quarter reported that the EHR was not accessible in their country; this finding varied from 2.6% of respondents in North America to 50% of respondents in the Asia Pacific.ConclusionsWhile EHR screening was commonly used for recruitment in a cardiovascular outcomes trial, important technical, governance, and regulatory barriers persist. Multifaceted, scalable, and customizable strategies are needed to support the optimal use of the EHR for trial participant identification.Trial registrationClinicalTrials.gov NCT02465515. Registered on 8 June 2015

Low Prevalence of Extraesophageal Gastrointestinal Pathology in Patients with Eosinophilic Esophagitis.

Limited data are available to support current guidelines recommendations on obtaining gastric and duodenal biopsies of patients with clinical and histologic manifestations consistent with eosinophilic esophagitis (EoE) to rule out eosinophilic gastritis (EG) or duodenitis (EoD). Our study examined the prevalence of concomitant extraesophageal, gastrointestinal pathology to better characterize the diagnostic yield of additional biopsies. This was a single-center, retrospective study which utilized ICD 9 codes (530.13) and search queries of pathology reports ("Eosinophilic esophagitis," "EoE") to identify EoE patients. Patient endoscopy reports, pathology reports, and office notes were manually reviewed to characterize cases. The electronic health record search yielded 1,688 EoE adults. In those who had extra-esophageal biopsies obtained, EG was identified in 34 (3.4%), H. pylori in 45 (4.6%), EoD in 27 (3.3%), and histology consistent with celiac disease in 20 (2.5%). Endoscopic abnormalities were found in the stomach of 92% of patients with EoE and EG and in the duodenum of 50% of patients with EoE and EoD. Symptoms of dyspepsia and/or abdominal pain occurred in a significantly greater proportion of patients with extraesophageal disease (64% vs. 19% in EoE group, p < 0.001). Overall, extraesophageal pathology would have been missed in 1.4% of patients lacking either symptoms or endoscopic signs suggestive of extraesophageal disease. The yield of gastric and duodenal biopsies in adults with EoE is low, with 6.5% of patients demonstrating histologic features of celiac disease, Helicobacter pylori, EG, and/or EoD. Biopsies of extraesophageal, gastrointestinal sites in patients with suspected or previously diagnosed EoE should consider symptom and endoscopy manifestations as well as the potential impact of histopathologic findings on clinical management.

Risk of adverse pregnancy outcomes in Japanese systemic lupus erythematosus patients with prior severe organ manifestations: A single-center retrospective analysis.

Systemic lupus erythematosus (SLE) increases the incidence of adverse pregnancy outcomes (APOs). Nevertheless, most of the data on SLE pregnancies were derived from database studies in which details of the pregnancies were unavailable, and no consensus exists on the risk of APO in patients with prior severe organ manifestations. SLE patients followed by rheumatologists and gynecologists throughout pregnancy at our institute were retrospectively identified, and their data between April 2003 and December 2020 were reviewed from electronic records. We assigned patients based on the presence of prior severe organ manifestation (renal/neurological manifestation, prior treatment with methylprednisolone pulse therapy/prednisolone 1 mg/kg/day/biological or cytotoxic therapy) and compared the incidence of overall and serious APO (maternal death, pregnancy loss, preterm birth <32 weeks, birthweight <1500 g, Apgar score <7 at 5 min and birth defect). This study included 34 pregnancies in 32 patients; 23 pregnancies in 22 patients were classified as SLE with prior severe organ manifestation. There was no statistical difference in the incidence of overall APO between the two groups (52.2% vs 45.5%, P = 1). Among patients with prior severe organ manifestation, 17.4% had serious APO. A detailed electronic health record search revealed specific causes of APO in all pregnancies with serious APO, except the presence of prior severe organ manifestation. The incidence of overall APO in SLE patients was not affected by prior severe organ manifestation. Although the incidence of serious APOs increased in patients with previous severe organ manifestation, there were other risk factors for poor pregnancy outcomes besides prior lupus severity. Therefore, proper management by rheumatologists and gynecologists may enable patients with prior severe organ manifestation to safely deliver healthy babies.

Use, Impact, Weaknesses, and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient's record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient's record. Conclusion Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering.

Abstract PS7-07: Predicting breast cancer risk for women veterans

Abstract BackgroundAccurate breast cancer risk assessment allows personalized approach in breast cancer screening and/or prevention. Breast cancer risk prediction models have been developed. Independent prospective validation however was needed before broad clinical applications. The Department of Veterans Affairs (VA) Million Veteran Program (MVP) is one of the largest biobanks in the world. Important attributes include: large sample size (&amp;gt;830,000, April 20), national coverage, multi-ethnic representation, access to bio-specimens from which multi-omics measurements have been conducted, thousands of biomedical phenotypes derived from our baseline and life style surveys and electronic health records (EHR). About 9% of MVP registrants are women. Breast cancer risk prediction models were evaluated in a prospective cohort of women in MVP. MethodologyMore than 350000 MVP participants completed genotyping to date. Breast cancer diagnoses were captured from the EHR. Ethnicity was determined by a supervised learning algorithm, Harmonized Ancestry and Race/Ethnicity (HARE), that used genetically inferred ancestry to refine self-identified race/ethnicity. Clinical breast cancer risk prediction instruments were based on personal health, lifestyle, demographics, family history, and environmental exposure. Polygenic Risk Score used in this study is comprised of 313 single nucleotide polymorphisms (PRS313). Clinical risk models tested were: BPC3, Lit and Breast Cancer Risk Assessment Tool (BCRAT, a version of the Gail’s model). The BPC3 and Lit models were tested by deploying the iCARE (Individualized Cancer Absolute Risk Estimator) with or without incorporation of PRS313. The BCRAT was deployed in the R package “BCRA” (Breast Cancer Risk Assessment v. 2.1 by F. Zhang). The performance of the risk prediction models was assessed by Area under the Receiver Operating Characteristic Curve (AUC-ROC). The observed absolute risk over expected absolute risk was compared for each decile. Results35133 genetic females were identified without a prior breast cancer diagnosis. By HARE definition, 10717 were African Americans (AA), 317 non-Hispanic Asians (ASIAN), 19941 non-Hispanic whites (EU), 1803 Hispanic (HIS) and 1355 unassigned. The median age of this cohort at MVP entry was 55. 369 subjects developed incident breast cancers with a median follow up of 4 years. These new cases were identified from Cancer Registry (292 cases) and EHR search for compatible ICD plus CPT codes (77 cases). The breast cancer incidence rate was 2.6/1000/year. iCARE-lit model was tested in 2731 AA women (38 incident breast cancers), 9027 EU women (111 incident breast cancers), and 10254 non-AA women (122 incident breast cancers) that had comprehensive risk factor evaluation (&amp;lt;4 missing). The AUC with the iCARE-lit model alone is 0.569 for AA, 0.563 for EU, and 0.565 for non-AA. Incorporation of PRS313 into the iCARE-lit model improved the AUC to 0.573 for AA, 0.645 for EU and 0.638 for non-AA. Additionally, iCARE-lit plus PRS313 estimated that 15% (AA), 7.3% (EU) and 7.7% (non-AA) of the women would have a lifetime risk of &amp;gt;20%. The iCARE-BPC3 had similar performance as iCARE-lit. The AUC of BCRAT alone was 0.648 for EU (20550 with 179 incident breast cancers) and 0.661 for AA (10462 with 96 incident breast cancers). Incorporation of PRS313 to BCRAT improved the AUC to 0.682 (EU) and 0.658 (AA). BCRAT plus PRS313 estimated that 5.6% (AA) and 4.4% (EU) of the women would have a lifetime risk of &amp;gt;20%. DiscussionWe prospectively evaluated and validated the performance of breast cancer risk prediction models as reported from case control studies. Longer follow up of more women in MVP will provide better assessment esp. for AA women. Prospective validation of these risk prediction models provides strong rationale for further development of these models in the clinical setting. Citation Format: Shiuh-Wen Luoh, Cynthia Brandt, Sally Haskell, Lina Gao, Byung Park, Paul Spellman, Saiju Pyarajan, Million Veteran Program, Nallakkandi Rajeevan, Jessica Minnier. Predicting breast cancer risk for women veterans [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-07.

Documented Reasons of Cancellation and Rescheduling of Telehealth Appointments During the Pandemic.

Background and Objective: The COVID-19 pandemic increased the use of telehealth around the world. The aim is to minimize health care service disruption as well as reducing COVID-19 exposure. However, one of the major operational concerns is cancellations and rescheduling (C/Rs). C/Rs may create additional burden and cost to the patient, provider, and the health system. Our aim is to understand the reasons for C/Rs of the telehealth session after the scheduled start time. Materials and Methods: We reviewed electronic health records (EHRs) to identify the C/R reasons for behavioral health and speech language pathology departments. Documented C/Rs in the medical charts were identified from EHR by using a keyword-based and Natural Language Processing (NLP)-supported EHR search engine. From the search results, we randomly selected 200 notes and conducted a thematic analysis. Results: We identified four themes explaining C/R reasons. Most frequent theme was "technicality" (47, 36%), followed by "engagement" (34, 25%), "scheduling" (31, 24%), and "unspecified" (20, 15%). The findings showed that technical reasons are the leading cause of C/Rs, constituting 36% of the cases (95% confidence interval [CI]: 29-43%). Notably, "engagement" constituted a sizeable 25% (95% CI: 19-31%) of C/Rs, as a result of the inability to engage a patient to complete the telehealth session. Conclusions: The study shows that engagement is one of the new challenges to the pediatric telehealth visits. Future studies of new engagement models are needed for the success of telehealth. Our findings will help fill the literature gaps and may help with enhancing the digital experience for both caregivers and providers, reducing wasted time and resources due to preventable C/Rs, improving clinical operation efficiency, and treatment adherence.

Estimating Aspirin Overuse for Primary Prevention of Atherosclerotic Cardiovascular Disease (from a Nationwide Healthcare System)

The American College of Cardiology and American Heart Association recently published guidelines narrowing the indications for low-dose aspirin use. The suitability of the electronic health record (EHR) to identify patients for low-dose aspirin deprescribing is unknown. To apply the 3 low-dose aspirin guidelines to EHR data, the guidelines were deconstructed into components from their narrative text and assigned computer-interpretable definitions based on electronic data interchange standards. These definitions were used to search EHR data to identify patients for aspirin deprescribing. To verify EHR records for low-dose aspirin, we then compared the records with a survey of patients' self-reported use of low-dose aspirin. Of the 3 aspirin guidelines, only 1 had a definition suitable for EHR implementation. The other 2 contained difficult-to-implement phrases (e.g., "higher ASCVD risk", "increased bleeding risk"). An EHR search with the single implementable guideline identified 86,555 people for possible aspirin deprescribing (2% of 5,598,604). Only 676 of 1,135 (60%) patients who self-reported taking low-dose aspirin had an active EHR record for low-dose aspirin at that time. Limitations exist when using EHR data to identify patients for possible low-dose aspirin deprescribing such as incomplete EHR capture of and the interpretation of non-specific terminology when translating guidelines into an electronic equivalent. In conclusion, data show many people unnecessarily take low-dose aspirin.

Using de-identified electronic health records to research mental health supported housing services: A feasibility study.

Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical studies of their effectiveness due to the logistic challenges and costs of standard research methods. The Clinical Record Interactive Search (CRIS) tool, developed to de-identify and interrogate routinely recorded electronic health records, may provide an alternative to evaluate supported housing services. The feasibility of using the Camden and Islington NHS Foundation Trust CRIS database to identify a sample of users of mental health supported accommodation services. Two approaches to data interrogation and case identification were compared; using structured fields indicating individual's accommodation status, and iterative development of free text searches of clinical notes referencing supported housing. The data used were recorded over a 10-year-period (01-January-2008 to 31-December-2017). Both approaches were carried out by one full-time researcher over four weeks (150 hours). Two structured fields indicating accommodation status were found, 2,140 individuals had a value in at least one of the fields representative of supported accommodation. The free text search of clinical notes returned 21,103 records pertaining to 1,105 individuals. A manual review of 10% of the notes indicated an estimated 733 of these individuals had used a supported housing service, a positive predictive value of 66.4%. Over two-thirds of the individuals returned in the free text search (768/1,105, 69.5%) were identified via the structured fields approach. Although the estimated positive predictive value was relatively high, a substantial proportion of the individuals appearing only in the free text search (337/1,105, 30.5%) are likely to be false positives. It is feasible and requires minimal resources to use de-identified electronic health record search tools to identify large samples of users of mental health supported housing using structured and free text fields. Further work is needed to establish the availability and completion of variables relevant to specific clinical research questions in order to fully assess the utility of electronic health records in evaluating the effectiveness of these services.

Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults.

Background Body composition data from abdominal CT scans have the potential to opportunistically identify those at risk for future fracture. Purpose To apply automated bone, muscle, and fat tools to noncontrast CT to assess performance for predicting major osteoporotic fractures and to compare with the Fracture Risk Assessment Tool (FRAX) reference standard. Materials and Methods Fully automated bone attenuation (L1-level attenuation), muscle attenuation (L3-level attenuation), and fat (L1-level visceral-to-subcutaneous [V/S] ratio) measures were derived from noncontrast low-dose abdominal CT scans in a generally healthy asymptomatic adult outpatient cohort from 2004 to 2016. The FRAX score was calculated from data derived from an algorithmic electronic health record search. The cohort was assessed for subsequent future fragility fractures. Subset analysis was performed for patients evaluated with dual x-ray absorptiometry (n = 2106). Hazard ratios (HRs) and receiver operating characteristic curve analyses were performed. Results A total of 9223 adults were evaluated (mean age, 57 years ± 8 [standard deviation]; 5152 women) at CT and were followed over a median time of 8.8 years (interquartile range, 5.1-11.6 years), with documented subsequent major osteoporotic fractures in 7.4% (n = 686), including hip fractures in 2.4% (n = 219). Comparing the highest-risk quartile with the other three quartiles, HRs for bone attenuation, muscle attenuation, V/S fat ratio, and FRAX were 2.1, 1.9, 0.98, and 2.5 for any fragility fracture and 2.0, 2.5, 1.1, and 2.5 for femoral fractures, respectively (P < .001 for all except V/S ratio, which was P ≥ .51). Area under the receiver operating characteristic curve (AUC) values for fragility fracture were 0.71, 0.65, 0.51, and 0.72 at 2 years and 0.63, 0.62, 0.52, and 0.65 at 10 years, respectively. For hip fractures, 2-year AUC for muscle attenuation alone was 0.75 compared with 0.73 for FRAX (P = .43). Multivariable 2-year AUC combining bone and muscle attenuation was 0.73 for any fragility fracture and 0.76 for hip fractures, respectively (P ≥ .73 compared with FRAX). For the subset with dual x-ray absorptiometry T-scores, 2-year AUC was 0.74 for bone attenuation and 0.65 for FRAX (P = .11). Conclusion Automated bone and muscle imaging biomarkers derived from CT scans provided comparable performance to Fracture Risk Assessment Tool score for presymptomatic prediction of future osteoporotic fractures. Muscle attenuation alone provided effective hip fracture prediction. © RSNA, 2020 See also the editorial by Smith in this issue.

Emergency Department-based Intensive Care Unit Use Peaks Near Emergency Department Shift Turnover.

IntroductionThe Emergency Critical Care Center (EC3) is an emergency department-based intensive care unit (ED-ICU) designed to improve timely access to critical care for ED patients. ED patients requiring intensive care are initially evaluated and managed in the main ED prior to transfer to a separate group of ED-ICU clinicians. The timing of patient transfers to the ED-ICU may decrease the number of handoffs between main ED teams and have an impact on both patient outcomes and optimal provider staffing models, but has not previously been studied. We aimed to analyze patterns of transfer to the ED-ICU and the relationship with shift turnover times in the main ED. We hypothesized that the number of transfers to the ED-ICU increases near main ED shift turnover times.MethodsAn electronic health record search identified all patients managed in the ED and ED-ICU in 2016 and 2017. We analyzed the number of ED arrivals per hour, the number of ED-ICU consults per hour, the time interval from ED arrival to ED-ICU consult, the distribution throughout the day, and the relationship with shift turnover times in the main ED.ResultsA total of 160,198 ED visits were queried, of which 5308 (3.3%) were managed in the ED-ICU. ED shift turnover times were 7 am, 3 pm, and 11 pm. The mean number of ED-ICU consults placed per hour was 221 (85 standard deviation), with relative maximums occurring near ED turnover times: 10:31 pm–11:30 pm (372) and 2:31 pm–3:30 pm (365). The minimum was placed between 7:31 am – 8:30 am (88), shortly after the morning ED turnover time. The median interval from ED arrival time to ED-ICU consult order was 161 minutes (range 6–1,434; interquartile range 144–174). Relative minimums were observed for patients arriving shortly prior to ED turnover times: 4:31 am – 5:30 am (120 minutes [min]), 12:31 pm – 1:30 pm (145 min), and 9:31 pm – 10:30 pm (135 min). Relative maximums were observed for patients arriving shortly after ED turnover times: 7:31 am – 8:30 am (177 min), 4:31 pm – 5:30 pm (218 min), and 11:31 pm – 12:30 am (179 min).ConclusionED-ICU utilization was highest near ED shift turnover times, and utilization was dissimilar to overall ED arrival patterns. Patients arriving immediately prior to ED shift turnover received earlier consults to the ED-ICU, suggesting these patients may have been preferentially transferred to the ED-ICU rather than signed out to the next team of emergency clinicians. These findings may guide operational planning, staffing models, and timing of shift turnover for other institutions implementing ED-ICUs. Future studies could investigate whether an ED-ICU model improves critically ill patients’ outcomes by minimizing ED provider handoffs.