Electronic Medical Records Research Articles

Impact of using dosing criteria to refine pharmacogenomic clinical decision support for tricyclic antidepressants.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. To evaluate the impact of dose-specific logic for tricyclic antidepressant (TCA) pharmacogenomic (PGx) clinical decision support (CDS). We aimed to provide guidance in an area with limited supporting literature, ensure optimal dosing through CDS, and limit alert fatigue. The primary outcome was the reduction in alerts prescribers encountered, while the secondary outcome included an analysis across specialties. A retrospective chart review was conducted to examine TCA PGx CDS before and after implementation of dosing criteria for alerts. Data were abstracted from the electronic medical record. A χ2 test was performed to analyze the frequency of alerts in behavioral health and other specialties. In the cohort lacking dose criteria, most TCA orders were for indications other than depression (76%) and guidelines would not apply to the majority of these orders. Using dosing criteria to refine CDS reduced the volume of TCA alerts by 74.8%. Alert volume decreased the most in specialties other than behavioral health due to prescriptions for indications other than anxiety or depression (P = 0.035). Dose-centric alerts may be used as a strategy to achieve optimal dosing. Alerting clinicians when dose modifications should occur contributes to getting the right dose to the right patient. Future efforts should focus on optimal dosing of medication through CDS enhancements.

Centenarians of the Basque Country are resilient to cancer.

Cancer is one of the leading causes of death and its prevalence increases with age. While centenarians exhibit extreme longevity and potential to avoid or delay aging-related diseases, their response to cancer is still barely explored. Our study took advantage of the Electronic Health Records to retrospectively compare the severity of cancer in centenarians (n = 649) and non-centenarians (n = 62,753) in the Basque Country (province of Gipuzkoa), Spain, through analyzing all the recorded diagnoses throughout their lifetime. Descriptive statistics were applied to discern differences between the two population groups in terms of prevalence of tumor types, number of diagnoses, and treatments. Survival analysis was performed through Kaplan-Meier estimator. We found that centenarians had fewer cancer diagnoses (17.1%, n = 111) than non-centenarians (40.5%, n = 25,405), and notably avoided the most aggressive cancer types and did not develop metastasis. Furthermore, they barely had records of treatments or drugs and had extended survival both since the first and last diagnosis of cancer. These results suggest resilience of the centenarians against malignant cancers explaining, in part, their extended longevity.

Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.

This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores, a widely adopted standard for cognitive assessment in patients with Alzheimer's disease, using natural language processing (NLP) and machine learning (ML) on structured and unstructured EHR data. We extracted demographic data, diagnoses, medications, and unstructured clinical visit notes from the EHRs. We used Latent Dirichlet Allocation (LDA) for topic modeling and Term-Frequency Inverse Document Frequency (TF-IDF) for n-grams. In addition, we extracted meta-features such as age, ethnicity, and race. Model training and evaluation employed eXtreme Gradient Boosting (XGBoost), Stochastic Gradient Descent Regressor (SGDRegressor), and Multi-Layer Perceptron (MLP). We analyzed 1654 clinical visit notes collected between September 2019 and June 2023 for 1000 Alzheimer's disease patients. The average MMSE score was 20, with patients averaging 76.4 years old, 54.7% female, and 54.7% identifying as White. The best-performing model (ie, lowest root mean squared error (RMSE)) is MLP, which achieved an RMSE of 5.53 on the validation set using n-grams, indicating superior prediction performance over other models and feature sets. The RMSE on the test set was 5.85. This study developed a ML method to predict MMSE scores from unstructured clinical notes, demonstrating the feasibility of utilizing NLP to support cognitive assessment. Future work should focus on refining the model and evaluating its clinical relevance across diverse settings. We contributed a model for automating MMSE estimation using EHR features, potentially transforming cognitive assessment for Alzheimer's patients and paving the way for more informed clinical decisions and cohort identification.

Health Disparities in Hospitalized Pediatric Patients with Autism Spectrum Disorder and COVID-19

Background/Objectives: Pediatric patients with autism spectrum disorder (ASD) face unique challenges, especially amongst individuals from historically minoritized racial groups. ASD has also been associated with an increased mortality from COVID-19. This study aims to explore the differences in sociodemographic factors and health outcomes (as measured by length of stay) amongst hospitalized pediatric patients with COVID-19 infections and a diagnosis of ASD compared to individuals with a COVID-19 infection alone; Methods: We performed a retrospective cohort study examining pediatric patients (ages birth to 21) who were hospitalized with a diagnosis of ASD and COVID-19 compared to patients with a diagnosis of COVID-19 alone between January 2019 and June 2023 using Epic Systems Corporation’s Cosmos, a de-identified dataset aggregated from electronic health record data. We examined differences in demographic factors and length of stay (LOS) between groups by utilizing chi-square and Wilcoxon rank sum tests. Multiple logistic regression models were utilized to assess the association between length of stay and diagnosis; Results: A total of 21,708 distinct pediatric patients with a diagnosis of ASD and COVID-19 or COVID-19 alone were included in the analytical dataset. Patients with ASD and COVID-19, compared to patients with COVID-19 alone, had a higher proportion of individuals identifying as male and White. Patients with COVID-19 alone, compared to individuals with ASD and COVID-19, had higher proportions of individuals identifying as Black or African American. Higher proportions of individuals with ASD and COVID-19 had public insurance, compared to individuals with COVID-19 alone. Having a diagnosis of ASD and COVID, after controlling for covariates, was associated with higher odds of having a length of stay greater than the three days (cutoff value determined by the median LOS of three days) compared to having a diagnosis of COVID alone (aOR 1.19, 95% CI 1.04–1.35); Conclusions: Our study highlights the health disparities experienced during hospitalizations by pediatric patients with ASD and COVID-19. Further studies should address barriers and support health outcomes for pediatric patients with ASD.

An Efficient EHR Secure Exchange Among Healthcare Servers Using Light Weight Scheme

This work addresses the critical need for secure and patient-controlled Electronic Health Records (EHR) migration among healthcare hospitals' cloud servers (HHS). The relevant approaches often lack robust access control and leave data vulnerable during transfer. Our proposed scheme empowers patients to delegate EHR migration to a trusted Third-Party Hospital (TTPH); which is the Certification Authority (CA) while enforcing access control. The system leverages asymmetric encryption utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA), EEC and ECDSA added robust security and lightness EHR sharing. Patient and user privacy is managed due to anonymity through cryptographic hashing for data protection and utilizes mutual authentication for secure communication. Formal security analysis using the Scyther tool and informal analysis was conducted to validate the system's robustness. The proposed scheme achieved EHR integrity due to the verification of the communicated HHS and ensuring the integrity of the HHS digital certificate during EHR migration. Ultimately, the result achieved in the proposed work demonstrated the scheme's high balance between data security and accuracy of communication, where the best result obtained represented 7.7/ ms as computational cost and 1248 /bits as communication cost compared with the relevant approaches.

Linking national primary care electronic health records to individual records from the U.S. Census Bureau's American Community Survey: evaluating the likelihood of linkage based on patient health.

To evaluate the likelihood of linking electronic health records (EHRs) to restricted individual-level American Community Survey (ACS) data based on patient health condition. Electronic health records (2019-2021) are derived from a primary care registry collected by the American Board of Family Medicine. These data were assigned anonymized person-level identifiers (Protected Identification Keys [PIKs]) at the U.S. Census Bureau. These records were then linked to restricted individual-level data from the ACS (2005-2022). We used logistic regressions to evaluate match rates for patients with health conditions across a range of severity: hypertension, diabetes, and chronic kidney disease. Among more than 2.8 million patients, 99.2% were assigned person-level identifiers (PIKs). There were some differences in the odds of receiving an identifier in adjusted models for patients with hypertension (OR = 1.70, 95% CI: 1.63, 1.77) and diabetes (OR = 1.17, 95% CI: 1.13, 1.22), relative to those without. There were only small differences in the odds of matching to ACS in adjusted models for patients with hypertension (OR = 1.03, 95% CI: 1.03, 1.04), diabetes (OR = 1.02, 95% CI: 1.01, 1.03), and chronic kidney disease (OR = 1.05, 95% CI: 1.03, 1.06), relative to those without. Our work supports evidence-building across government consistent with the Foundations for Evidence-Based Policymaking Act of 2018 and the goal of leveraging data as a strategic asset. Given the high PIK and ACS match rates, with small differences based on health condition, our findings suggest the feasibility of enhancing the utility of EHR data for research focused on health.

Maintaining Integrity and Confidentiality of Patients’ Records Using an Enhanced Security Technique

Medical record storage on paper is currently being phased out and replaced by more sophisticated Electronic Health Record (EHR) systems. However, the ease of access to data and the digitization of medical records also come with the potential of misuse of personally identifiable information and healthcare data breaches. How technology will protect patient privacy is one of the primary concerns about EHRs. Network connectivity is another major issue, therefore keeping private health information online may expose it to major information leaks to external parties. Around the world, data management and privacy are major concerns. The main concerns that prevent businesses from using cloud computing are security and information authenticity, as they fear that data may be lost to unauthorized parties. The quantity of patient-oriented data in the healthcare system is continuously increasing, and the current medical systems are confronted with security issues such as weak access control, data breaches or unauthorized disclosure, and insufficient authorization and authentication. An Enhanced Security Model was created in this study to secure and protect Electronic Health Records. The records were encrypted for security and privacy utilizing the Advanced Encryption Standard (AES), One Time Password (OTP), and National Identity Number (NIN). The system was designed using Object Oriented Analysis and Design Methodology (OOADM). The New System improved patient record security by utilizing NIN for cloud identity management, OTP for authentication, and AES for privacy and security. While the MySQL server was used to implement the database, HTML, CSS, PHP, and JavaScript were used to program the system. Comparing the new system to the old system, the results of the performance assessment analysis based on security, user-friendliness, dependability, and privacy show that the new system has very good performance efficiency and integrity.

Service evaluation of the research outputs for 23/24 at a large London teaching hospital

Abstract Introduction The recent report of a UK survey of pharmacy professionals’ involvement in research1 found only small numbers of the pharmacy workforce are currently undertaking research. A number of reasons for this are identified and the report contains a list of recommendations to support the embedding of research into pharmacy careers.1 Within the pharmacy department at King’s College Hospital NHS Foundation Trust (KCH) all research proposals are presented at the pharmacy research and audit group and a log is kept of department research outputs by the clinical academic research lead. The analysis of this data will provide a benchmark. For the purposes of this study, research encompasses audit, service evaluation and research studies as defined by the Health Research Authority defining research table.2 Aim To identify, over the financial year 23/24, the frequency of different types of research outputs from the pharmacy department at KCH broken down by output type, specialty and role. Methods Regular emails were sent April 23 – March 24 to remind staff to identify and share research outputs with the clinical academic research lead. Outputs received were circulated by newsletter to encourage and motivate others. The clinical academic research lead engaged with individual pharmacy teams throughout the year to encourage and support research outputs. Research output data was collected, April 23 – March 24, on an Excel spreadsheet including staff name, role, specialty, type of research output and date the output was completed. Research outputs were categorised into published articles, published abstracts, attendance at conference, abstracts presented at conference and presentations at conference or national webinar. Ethics was not required as the study is defined as a service evaluation. Results There were a total of 89 research outputs by the pharmacy department across the year. These were broken down into published articles (20), published abstracts (16), attendance at conference (24), abstracts presented at conference (26) and presentations at conference or national webinar (3). The two specialty teams who produced or took part in the most research outputs over the year were critical care (15) and liver (11). Consultants pharmacists were involved in the most research activity (32) followed closely by principal pharmacists (26), specialist pharmacists (25) and the deputy chief pharmacists (19). Pharmacy technicians, pharmacists taking part in the STEP programme and non-registered pharmacy staff scored the least in terms of research activity relative to size of staff group. Consultant pharmacists and principle pharmacists were the groups that published the most articles (8 each). Discussion and conclusion The trust implemented a new electronic patient record system during the year which may have impacted the number of research outputs. A limitation to this study is that there are likely to be unrecorded research outputs. The data broken down by specialty and role will allow the pharmacy management group and clinical academic research lead to support, engage and motivate in those areas to allow staff to have the time, skills and guidance to carry out research activities. The results can be used by other healthcare organisations to benchmark against.

Unexpected Pathology During Pelvic Organ Prolapse Repair in an Urban Population.

This study quantifies the occult pathology risk among our urogynecologic patient population and highlights the importance of preoperative counseling, particularly in patients who have been underrepresented in prior studies. The aim of the study was to estimate unexpected gynecologic pathology incidence among a low-risk, racially, and ethnically representative patient population undergoing surgery for symptomatic pelvic organ (POP) prolapse. This was a retrospective study of patients undergoing hysterectomy for POP at an urban academic medical center. Patients with abnormal preoperative pathologic evaluation were excluded. Data were abstracted from the electronic health record, including demographic and clinical history, preoperative laboratory evaluation, and clinical risk factors for gynecologic malignancy. Two hundred ninety-nine nononcologic patients who underwent POP repair with hysterectomy were assessed. Thirty-six percent of patients identified as Hispanic, 17% as non-Hispanic Black, and 38% as non-Hispanic White. Twenty-three percent of patients reported abnormal uterine bleeding, 36% underwent a preoperative ultrasound examination, and 15% underwent endometrial biopsy. Two patients (0.9%) were diagnosed with endometrial carcinoma. Two patients (0.9%) were diagnosed with cervical dysplasia. No patients with concurrent oophorectomy or salpingectomy had ovarian or tubal pathology. The overall incidence of unexpected gynecologic pathology at the time of hysterectomy for prolapse was 1.7%. The rate of endometrial cancer in our cohort is on the higher end of previously published data, although absolute rates of unanticipated malignancy remain low. Future studies should examine the pathological findings of larger, racially, and ethnically diverse cohorts of patients undergoing POP surgery with hysterectomy, which can aid in providing relevant estimates for preoperative counseling.

Artificial Intelligence (AI)-Driven Frailty Prediction Using Electronic Health Records in Hospitalized Patients With Cardiovascular Disease.

This study aimed to create a deep learning model for predicting phenotypic physical frailty from electronic medical record information in patients with cardiovascular disease. This single-center retrospective study enrolled patients who could be assessed for physical frailty according to cardiovascular health study criteria (25.5% [691/2,705] of the patients were frail). Patients were randomly separated for training (Train set: 80%) and validation (Test set: 20%) of the deep learning model. Multiple models were created using LightGBM, random forest, and logistic regression for deep learning, and their predictive abilities were compared. The LightGBM model had the highest accuracy (in a Test set: F1 score 0.561; accuracy 0.726; area under the curve of the receiver operating characteristics [AUC] 0.804). These results using only commonly used blood biochemistry test indices (in a Test set: F1 score 0.551; accuracy 0.721; AUC 0.793) were similar. The created models were consistently and strongly associated with physical functions at hospital discharge, all-cause death, and heart failure-related readmission. Deep learning models derived from large sample sizes of phenotypic physical frailty have shown good accuracy and consistent associations with prognosis and physical functions.

Treatment outcomes of non-curative endoscopic submucosal dissection for superficial gastric neoplasia: A retrospective study at a tertiary care center in the United States.

Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer; additional treatment may be recommended for patients in whom resection is not curative per the American Society for Gastrointestinal Endoscopy guidelines. The aim of this study was to assess treatment outcomes of ESD for gastric neoplasia, with a focus on cases of non-curative resection. This was a retrospective study of all individuals undergoing ESD for the treatment of gastric adenocarcinoma or dysplasia in a high-volume tertiary care center in the United States. Data on patient demographic characteristics, clinical history, lesion characteristics, and procedural and clinical outcomes were collected from the electronic medical record. Among 82 cases undergoing ESD for the management of gastric neoplasia, 32 cases resulted in non-curative resection. 20 of these non-curative cases did not get additional treatment, among which recurrence occurred in two cases with positive horizontal margins only. These patients did not show lymph node metastasis and underwent further endoscopic or surgical resection. There was no recurrence in 11 cases with undifferentiated carcinomas of ≤2 cm in size. Although this study was limited by its retrospective design, small sample size, and follow-up duration, our findings suggest that a risk-adapted strategy could be employed for certain patients undergoing non-curative ESD per American Society for Gastrointestinal Endoscopyguidelines, with close follow-up instead of routine surgery in select cases with favorable features. Further studies are needed to refine the criteria for additional treatment after non-curative ESD in Western populations.

Prognostic Awareness and Knowledge of Acute Exacerbation in Patients Dying with Interstitial Lung Disease: A Nationwide Survey.

Accurate prognostic awareness (PA) and knowledge of the disease are critical for decision-making regarding treatment options, advance care planning, and end-of-life care. However, they have not been investigated in patients with interstitial lung disease (ILD). To determine the prevalence of patients with ILD who have accurate PA and/or knowledge of acute exacerbation. In addition, to determine whether accurate PA is associated with end-of-life medical interventions and quality of dying and death. Through a nationwide bereavement survey, we examined the prevalence of accurate PA and knowledge of acute exacerbation (AE) in patients with ILD who died in acute general hospitals between January 2018 and February 2020. Patients' PA and knowledge were assessed from the perspective of the bereaved. We also quantified the quality of dying and death from the perspective of the bereaved using three scales, the Good Death Inventory, the Quality of Dying and Death (QODD) questionnaire, and the single-item QODD overall score, and obtained information on end-of-life interventions from the electronic medical record. We examined the associations of accurate PA with end-of-life interventions and quality of dying and death. A total of 296 patients whose caregivers completed questionnaires were analyzed. One hundred sixty-three patients (55.1%, 95% confidence interval [CI] = 49.2-60.8) who died of ILD had accurate PA and 138 (46.9%, 95% CI = 35.9-47.4) recognized that their disease could have AE. Multivariate regression analysis showed that accurate PA was associated with significantly fewer intensive care unit (ICU) deaths (odds ratio = 0.28, 95% CI = 0.10-0.82, P = 0.02). Patients with accurate PA had better quality of dying and death on all the three scales. Approximately half of the patients who died of ILD did not recognize that their disease could lead to death or AE. The lower number of ICU deaths and better quality of dying and death in patients with accurate PA suggest the potential benefits of obtaining accurate PA in patients with ILD.

Clinical and biologic profiles of patients with acute respiratory distress syndrome by prevalence of chronic obstructive pulmonary disease or emphysema; a cohort study

IntroductionAcute respiratory distress syndrome (ARDS) is characterized by diffuse lung injury. The impact of pre-existing chronic obstructive pulmonary disease (COPD) or emphysema on ARDS pathogenesis is not well characterized.MethodsSecondary analysis of ARDS patients enrolled in the Acute Lung Injury Registry and Biospecimen Repository at the University of Pittsburgh between June 2012 and September 2021. Patients were categorized into two mutually exclusive groups by the prevalence of COPD or emphysema at the time of ARDS diagnosis. The COPD/emphysema group comprised ARDS patients with radiological evidence of emphysema, chart diagnosis of COPD, or both. Demographics, lung mechanics, and clinical outcomes were obtained from the electronic medical record. Host-response biomarkers known to have validated associations with ARDS were previously measured in plasma and lower respiratory tract samples using a customized Luminex assay. Continuous and categorical variables were compared between groups with and without COPD/emphysema.Results217 patients with ARDS were included in the study, 57 (27%) had COPD/emphysema. Patients with COPD/emphysema were older (median 62 [interquartile range 55–69] versus 53 [41–64] years, p < 0.01), more likely to be male (62% vs. 44%, p = 0.02) and had a higher prevalence of congestive heart failure (25% vs. 4%, p < 0.01) compared to patients without COPD/emphysema. Baseline demographics, laboratory parameters, and mechanical ventilatory characteristics were otherwise similar between the two groups. No difference in 90-day mortality was observed between groups; however, patients with COPD/emphysema had shorter duration of intensive care unit (ICU) stay (median 10 [7–18] versus 16 [9–28] days, p = 0.04) and shorter duration of mechanical ventilation (median 7 [4–16] vs. 12 [6–20] days, p = 0.01). Host response biomarkers in serum and lower respiratory tract samples did not significantly differ between groups.ConclusionARDS patients with COPD or emphysema had similar respiratory mechanics, host response biomarker profiles, and mortality compared to those without COPD or emphysema but with a shorter median duration of mechanical ventilation and ICU length of stay. Future studies should address differences in clinical and biological responses by disease severity, and should investigate the impact of severity of COPD and emphysema on mechanical ventilation and targeted therapeutic strategies in ARDS.Clinical trial numberNot applicable

System-Wide, Electronic Health Record-Based Medication Alerts for Appropriate Prescribing of Direct Oral Anticoagulants: Pilot Randomized Controlled Trial.

While direct oral anticoagulants (DOACs) have improved oral anticoagulation management, inappropriate prescribing remains prevalent and leads to adverse drug events. Antithrombotic stewardship programs seek to enhance DOAC prescribing but require scalable and sustainable strategies. We present a pilot, prescriber-level randomized controlled trial to assess the effectiveness of electronic health record (EHR)-based medication alerts in a large health system. The pilot assessed prescriber responses to alerts for initial DOAC prescription errors (apixaban and rivaroxaban). A user-centered, multistage design process informed alert development, emphasizing clear indication, appropriate dosing based on renal function, and drug-drug interactions. Alerts appeared whenever a DOAC was being prescribed in a way that did not follow package label instructions. Clinician responses measured acceptability, accuracy, feasibility, and utilization of the alerts. The study ran from August 1, 2022, through April 30, 2023. Only 1 prescriber requested trial exclusion, demonstrating acceptability. The error rate for false alerts due to incomplete data was 6.6% (16/243). Two scenarios with alert design and/or execution errors occurred but were quickly identified and resolved, underlining the importance of a responsive quality assurance process in EHR-based interventions. Trial feasibility issues related to alert-data capture were identified and resolved. Trial feasibility was also assessed with balanced randomization of prescribers and the inclusion of various alerts across both medications. Assessing utilization, 34.2% (83/243) of the encounters (with 134 prescribers) led to a prescription change. The pilot implementation study demonstrated the acceptability, accuracy, feasibility, and estimates of the utilization of EHR-based medication alerts for DOAC prescriptions and successfully established just-in-time randomization of prescribing clinicians. This pilot study sets the stage for large-scale, randomized implementation evaluations of EHR-based alerts to improve medication safety. ClinicalTrials.gov NCT05351749; https://clinicaltrials.gov/study/NCT05351749.

Racial and Ethnic Disparities in Referral Rejection from Postacute Care Facilities among People with Opioid Use Disorder in Massachusetts.

The aim of the study was to examine the association between Black, White, and Hispanic or Latino race and ethnicity and referral rejection from private postacute care facilities among hospitalized individuals with opioid use disorder (OUD). In this retrospective cohort study, we linked electronic postacute care referrals from Boston Medical Center in 2018 to electronic medical record data, which we used to ascertain OUD status and race and ethnicity. Using multivariable logistic regression, we examined the association between Black, White, and Hispanic or Latino race and ethnicity and referral rejection, adjusting for individual-level characteristics including medication for opioid use disorder treatment type and for facility-level factors using facility random effects. We identified 159 hospitalizations from 141 individuals with OUD referred to private postacute medical care, corresponding to 1272 referrals to 244 facilities. Hospitalizations comprised 53 (33%) non-Hispanic Black, 28 (18%) Hispanic or Latino, and 78 (49%) non-Hispanic White individuals. In adjusted analyses, referrals for non-Hispanic Black individuals had significantly higher odds of rejection compared to referrals for non-Hispanic White individuals (adjusted odds ratio 1.83, 95% confidence interval [1.24, 2.69], P = 0.002). There were no significant differences between referrals for Hispanic or Latino individuals and non-Hispanic White individuals (adjusted odds ratio 1.11, 95% confidence interval [0.67, 1.84], P = 0.69). Among people with OUD referred to private postacute care in Massachusetts, non-Hispanic Black individuals were more likely to be rejected compared to non-Hispanic White individuals, demonstrating racism in postacute care admissions. Efforts to address discrimination against people with OUD in postacute care admissions must also address racial equity.

Multidimensional and Longitudinal Impact of a Genetic Diagnosis for Critically Ill Infants.

Many genetic conditions present in the NICU, where a diagnostic evaluation is pursued. However, understanding of the impact of a genetic diagnosis on clinical outcomes and health-related quality of life for these infants remains incomplete. We therefore evaluated parent-reported outcomes complemented by clinical outcomes measures over one year for a cohort of infants in the NICU undergoing genetic evaluation. Prospective cohort study evaluating outcomes after genetics consultation in a level IV NICU via parent report and electronic medical record review. Eligible infants were genetically undiagnosed at enrollment. Parent surveys were administered at baseline and 3, 6, and 12 months following enrollment and assessed genetic testing utility as well as parent-reported infant health-related quality of life using the Infant Toddler Quality of Life Questionnaire. A total of 110 infant-parent pairs were enrolled. Infants had a median age at enrollment of 15 days (interquartile range 8-37.75). At baseline, 74% (81/110) of parents endorsed high importance of finding a genetic diagnosis, but perceived importance significantly decreased over time. Over the study period, 38 infants received a molecular diagnosis per parent report, although this was discordant with electronic medical record review. Identification of a diagnosis did not significantly impact health-related quality of life across most domains, which was lower overall than population norms. A genetic diagnosis is highly desired by parents in the NICU, though waning interest over time for undiagnosed families may reflect parental emotional adaptation and acceptance. Additional supports are needed to improve perceived quality of life.

Promoting Race and Ethnic Diversity in a Hospital-Based Randomized Clinical Trial to Address Untreated Alcohol Use Disorder: Initial Lessons Learned.

This study aimed to describe initial experiences and lessons learned conducting a trial focused on recruiting racially and ethnically diverse hospitalized patients with untreated alcohol use disorder (AUD). The parent trial is comparing the effectiveness of strategies including Brief Negotiation Interview (BNI), facilitated initiation of medications for AUD, and computer-based training for cognitive behavioral therapy (CBT4CBT) on AUD treatment engagement post-hospitalization. Guided by the Framework for Reporting Adaptations and Modifications-Enhanced, we catalogued protocol changes and evaluated outcomes using study and electronic medical record data during the first 18 months of recruitment. Recipients: (1) Selected entry criterion to intentionally include individuals most likely impacted by structural racism, (2) developed multipronged recruitment approaches, and (3) selected bilingual, multicultural, and ethnically diverse research staff. Intervention: (1) Added scripts in the BNI to consider how cultural factors influence and how racism may impact, alcohol use, and AUD treatment engagement, (2) offered tablets as a compensation alternative with support for CBT4CBT initiation (as relevant), and (3) anticipate and troubleshoot internet access challenges. Setting: (1) Identified community-based AUD treatment options with Spanish-speaking services and (2) identified resources to address social determinants of health. Study: (1) Audited data to monitor whether diverse enrollment is occurring. Among n = 132 randomized as of March 1, 2024, 25% endorsed Black, 24% endorsed Latine, 58% endorsed White, 1% endorsed Indigenous, and 15% endorsed race not listed or declined to disclose. We observed no difference by race or ethnicity in recruitment or retention experiences. Multilevel practices within a hospital-based AUD-focused trial can promote recruitment and retention of a racially and ethnically diverse sample.

Examining Whether Patient Portal and Video Visit Use Differs by Race and Ethnicity Among Older Adults in a US Integrated Health Care Delivery System: Cross-Sectional Electronic Health Record and Survey-Based Study.

Health care systems are increasingly encouraging patients to use patient portals and participate in video visits. However, there is limited information about how portal use differs among older adults. This study aimed to understand how patient portal and video visit use differed by age, race, and ethnicity among older adult patients with access to the same digital health resources. This cross-sectional study used electronic health record and survey data for adults aged 65 to 85 years who were members of a large Northern California health care delivery system throughout 2019 and 2020. The electronic health record cohort (N=471,152) included 320,686 White, 35,892 Black, 44,922 Latino, 20,786 Chinese, 28,732 Filipino, 8473 South Asian, 6716 Japanese, 2930 Vietnamese, and 2015 Korean adults. Racial and ethnic group and age group (65 to 75 years vs 76 to 85 years) differences in having a patient portal account by December 2020, the performance of 2 portal activities (sending ≥1 message to a clinician in 2019 or 2020 and viewing ≥1 laboratory test result in 2020), and having ≥1 video visit during 2020 were examined. Modified log-Poisson regression was used to examine prevalence ratios for portal and video visit use, comparing racial and ethnic groups to White adults and Asian ethnic groups to Chinese adults after adjusting for sex and age. Data from a 2020 member survey were used to compare internet use factors among 2867 White, 306 Black, 343 Latino, 225 Chinese, and 242 Filipino adults. Black, Latino, and Filipino adults were less likely to have a patient portal account than White adults, and Filipino adults were less likely to have a patient portal account than Chinese adults. Black, Latino, Filipino, Korean, Vietnamese, and South Asian adults were less likely to have sent messages and viewed test results than White adults, while Chinese and Japanese adults' use of these features was similar to that of White adults. Filipino, Vietnamese, and Korean adults were less likely to have performed the aforementioned activities than Chinese adults. Video visit use was lower among Black and Latino adults and higher among Chinese and South Asian adults compared with White adults (aged 76 to 85 years) and lower among Filipino, Korean, and Vietnamese adults compared to Chinese adults. Survey data suggested that underlying differences in internet use may partially explain the lower use of messaging by Black, Latino, and Filipino adults compared with White and Chinese adults. Patient portal and video visit use differed by race, ethnicity, and age group among older adult patients with access to the same patient portal. Internet use factors may contribute to these differences. Differences in patient portal and video visit use across Asian subgroups underscore the importance of disaggregating use data by Asian ethnicity.

Identification of atypical pediatric diabetes mellitus cases using electronic medical records

IntroductionThere are no established methods to identify children with atypical diabetes for further study. We aimed to develop strategies to systematically ascertain cases of atypical pediatric diabetes using electronic medical...

Pronouns in the Electronic Medical Record: A Potential Pitfall.

Pronouns in the Electronic Medical Record: A Potential Pitfall.