Structure and Funding of Clinical Informatics Fellowships: A National Survey of Program Directors.

BACKGROUND: In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures. OBJECTIVES: The aim of our study was to characterize CI fellowship program features, including governance structures, funding sources, and expenses. METHODS: We created a cross-sectional online REDCap survey with 44 items requesting information on program administration, fellows, administrative support, funding sources, and expenses. We surveyed program directors of programs accredited by the Accreditation Council for Graduate Medical Education between 2014 and 2021. RESULTS: We invited 54 program directors, of which 41 (76%) completed the survey. The average administrative support received was $27,732/year. Most programs (85.4%) were accredited to have two or more fellows per year. Programs were administratively housed under six departments: Internal Medicine (17; 41.5%), Pediatrics (7; 17.1%), Pathology (6; 14.6%), Family Medicine (6; 14.6%), Emergency Medicine (4; 9.8%), and Anesthesiology (1; 2.4%). Funding sources for CI fellowship program directors included: hospital or health systems (28.3%), clinical departments (28.3%), graduate medical education office (13.2%), biomedical informatics department (9.4%), hospital information technology (9.4%), research and grants (7.5%), and other sources (3.8%) that included philanthropy and external entities. CONCLUSION: CI fellowships have been established in leading academic and community health care systems across the country. Due to their unique training requirements, these programs require significant resources for education, administration, and recruitment. There continues to be considerable heterogeneity in funding models between programs. Our survey findings reinforce the need for reformed federal funding models for informatics practice and training.

Defining Electronic Health Record Standards for Child Health: A State-of-the-Art Review.

BACKGROUND: Improving child health using health information technology (IT) requires a unique set of functionalities that are built into the electronic health record (EHR) and are used to support patient care. In this article, we review and discuss the milestones preceding the development of a new child health EHR standard and describe the salient features of this contemporary standard. METHODS AND RESULTS: The Health Level Seven Pediatric Care Health IT Functional Profile (HL7 PCHIT FP) is an informative standard that encompasses the EHR functions required to care for patients less than 21 years of age in any clinical setting, developed to address the pediatric-specific functionality gaps in the EHR. It includes criteria that support communication between providers and all caregivers, inclusion of pediatric-specific vital signs and diagnosis, support for transition to adult care, and support for reporting and documentation of child abuse or neglect including communication with involved authorities. EHR functionalities for documentation and reporting of newborn screening tests with follow-up for abnormal results and functionality for children with special health care needs with support for identifying patients who may benefit from care coordination are also incorporated, in addition to school-based linkages enabling communication between the health care system and their school environment. CONCLUSION: The HL7 PCHIT FP is envisioned to be another vital step towards improving pediatric health by enhancing EHRs to address the unique health IT needs of children and their health providers. While the HL7 PCHIT FP is the most recently published standard on pediatric EHR systems, standards development is an iterative process, and recommendations for continuous refinement and additional functionalities for the next standards release are encouraged.

Elective operations delay and emergency department visits and inpatient admissions during COVID-19.

Introduction: At the beginning of the COVID-19 pandemic, many hospitals postponed elective operations for a 12-week period in early 2020. During this time, there was concern that the delay would lead to worse health outcomes. The objective of this study is to analyze the effect of delaying operations during this period on ED (Emergency Department) visits and/or urgent IP (Inpatient) admissions. Methods: Electronic Health Record (EHR) data on canceled elective operations between 3/17/20 to 6/8/20 was extracted and a descriptive analysis was performed looking at patient demographics, delay time (days), procedure type, and procedure on rescheduled, completed elective operations with and without a related ED visit and/or IP admission during the delay period. Results: Only 4 out of 197 (2.0%) operations among 4 patients out of 186 patients (2.0%) had an ED visit or IP admission diagnosis related to the postponed operation. When comparing the two groups, the 4 patients were older and had a longer median delay time compared to the 186 patients without an ED visit or IP admission. Conclusion: Postponement of certain elective operations may be done with minimal risk to the patient during times of crisis. However, this minimal risk may be due to the study site's selection of elective operations to postpone. For example, none of the elective operations canceled or postponed were cardiovascular operations, which have worse health outcomes when delayed.

Economic analysis of a single institutional review board data exchange standard in multisite clinical studies.

BACKGROUND: Single Institutional Review Boards (sIRB) are not achieving the benefits envisioned by the National Institutes of Health. The recently published Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) data exchange standard seeks to improve sIRB operational efficiency. METHODS AND RESULTS: We conducted a study to determine whether the use of this standard would be economically attractive for sIRB workflows collectively and for Reviewing and Relying institutions. We examined four sIRB-associated workflows at a single institution: (1) Initial Study Protocol Application, (2) Site Addition for an Approved sIRB study, (3) Continuing Review, and (4) Medical and Non-Medical Event Reporting. Task-level information identified personnel roles and their associated hour requirements for completion. Tasks that would be eliminated by the data exchange standard were identified. Personnel costs were estimated using annual salaries by role. No tasks would be eliminated in the Initial Study Protocol Application or Medical and Non-Medical Event Reporting workflows through use of the proposed data exchange standard. Site Addition workflow hours would be reduced by 2.50 h per site (from 15.50 to 13.00 h) and Continuing Review hours would be reduced by 9.00 h per site per study year (from 36.50 to 27.50 h). Associated costs savings were $251 for the Site Addition workflow (from $1609 to $1358) and $1033 for the Continuing Review workflow (from $4110 to $3076). CONCLUSION: Use of the proposed HL7 FHIR® data exchange standard would be economically attractive for sIRB workflows collectively and for each entity participating in the new workflows.

Covid-19 Positivity Differences Among Patients of a Rural, Southern US State Hospital System Based on Population Density, Rural-Urban Classification, and Area Deprivation Index.

In this study we examined the correlation of COVID-19 positivity with area deprivation index (ADI), social determinants of health (SDOH) factors based on a consumer and electronic medical record (EMR) data and population density in a patient population from a tertiary healthcare system in Arkansas. COVID-19 positivity was significantly associated with population density, age, race, and household size. Understanding health disparities and SDOH data can add value to health and the creation of trustable AI.

Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children's Hospital.

Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children's Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.

Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review.

BACKGROUND: SARS-CoV-2, the novel coronavirus responsible for COVID-19, has caused havoc worldwide, with patients presenting a spectrum of complications that have pushed health care experts to explore new technological solutions and treatment plans. Artificial Intelligence (AI)-based technologies have played a substantial role in solving complex problems, and several organizations have been swift to adopt and customize these technologies in response to the challenges posed by the COVID-19 pandemic. OBJECTIVE: The objective of this study was to conduct a systematic review of the literature on the role of AI as a comprehensive and decisive technology to fight the COVID-19 crisis in the fields of epidemiology, diagnosis, and disease progression. METHODS: A systematic search of PubMed, Web of Science, and CINAHL databases was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify all potentially relevant studies published and made available online between December 1, 2019, and June 27, 2020. The search syntax was built using keywords specific to COVID-19 and AI. RESULTS: The search strategy resulted in 419 articles published and made available online during the aforementioned period. Of these, 130 publications were selected for further analyses. These publications were classified into 3 themes based on AI applications employed to combat the COVID-19 crisis: Computational Epidemiology, Early Detection and Diagnosis, and Disease Progression. Of the 130 studies, 71 (54.6%) focused on predicting the COVID-19 outbreak, the impact of containment policies, and potential drug discoveries, which were classified under the Computational Epidemiology theme. Next, 40 of 130 (30.8%) studies that applied AI techniques to detect COVID-19 by using patients' radiological images or laboratory test results were classified under the Early Detection and Diagnosis theme. Finally, 19 of the 130 studies (14.6%) that focused on predicting disease progression, outcomes (ie, recovery and mortality), length of hospital stay, and number of days spent in the intensive care unit for patients with COVID-19 were classified under the Disease Progression theme. CONCLUSIONS: In this systematic review, we assembled studies in the current COVID-19 literature that utilized AI-based methods to provide insights into different COVID-19 themes. Our findings highlight important variables, data types, and available COVID-19 resources that can assist in facilitating clinical and translational research.

Emergency Information Forms for Children With Medical Complexity: A Qualitative Study.

OBJECTIVES: Children with medical complexity (CMC) are at risk for poor outcomes during medical emergencies. Emergency information forms (EIFs) provide essential medical information for CMC during emergencies; however, they are not widely used. We sought to identify factors related to optimal care for CMC to inform development of EIFs for CMC. METHODS: We interviewed 26 stakeholders, including parents of CMC, healthcare providers, health information technology, and privacy compliance experts. We inquired about barriers and facilitators to emergency care of CMC, as well as the desired content, structure, ownership, and maintenance of an EIF. Audio recordings were transcribed and analyzed inductively for common themes using thematic analysis techniques. RESULTS: Providers identified problems with documentation and poor caregiver understanding as major barriers to care. Parents reported poor provider understanding of their child's condition as a barrier. All groups reported that summary documents facilitate quality care. Recommended content included demographic/contact information, medical history, medications, allergies, advance directives, information about the patient's disease, and an action plan for anticipated emergencies. Twenty-three participants indicated a preference for electronic EIFs; 19 preferred a Web-based EIF that syncs with the medical record, with paper or portable electronic copies. Although 13 participants thought that EIFs should be patient owned to ensure availability during emergencies, 19 expected medical providers to create and update EIFs. CONCLUSIONS: Stakeholders interviewed reported a preference for Web-based, sync-capable EIFs with portable copies. Emergency information forms could be maintained by providers but owned by patients to optimize emergency care and align with the concept of the medical home.

Emergency Department Directors Are Willing to Expand Reproductive Health Services for Adolescents.

STUDY OBJECTIVE: Nearly 20 million adolescents receive emergency department (ED) care each year, many of whom have untreated reproductive health issues. ED visits represent an opportunity to provide appropriate care, however, ED physician reproductive health care practices and capabilities in the United States have not been described. We sought to characterize pediatric ED director's individual practice and ED system resources for providing adolescent reproductive health care. DESIGN, SETTING, PARTICIPANTS, AND INTERVENTIONS: We invited pediatric ED division and/or medical directors nationally to participate in an anonymous, online survey. MAIN OUTCOME MEASURES: Outcomes included ED directors' personal practice regarding providing adolescent patients reproductive health care, and their ED's resources and standard practice regarding screening adolescents for sexually transmitted infections (STIs) and other reproductive health concerns. RESULTS: One hundred thirty-five of 442 (30.5%) ED directors responded. Respondents were 73% (90/124) male, with a median of 18 (interquartile range, 13-23) years of experience and 63% (84/134) working in urban EDs. Seventy-one percent (90/130) preferred face-to-face interviews for obtaining a sexual history, but only 59% (77/130) of participants "always ask parents to leave the room for sensitive questions." Eighty-four percent (106/127) were receptive to pregnancy prevention interventions being initiated in the ED, with 75% (80/106) of those willing to provide an intervention. Only 16% (21/128) indicated their ED has a universal STI screening program, and only 18% (23/126) "always" successfully notify patients of a positive STI test. CONCLUSION: ED directors are comfortable providing adolescent reproductive health care, and many individual- and ED-level opportunities exist to provide improved reproductive health care for adolescents in the ED.

Remission in Pediatric Inflammatory Bowel Disease Correlates With Prescription Refill Adherence Rates.

OBJECTIVES: The aim of the study was to use pharmacy benefit management (PBM) prescription claims data to assess refill adherence in pediatric inflammatory bowel disease (IBD) and correlate adherence with clinical outcomes in pediatric IBD. METHODS: We identified 362 pediatric patients with IBD seen at Washington University from 9/1/2012 to 8/31/2013 and matched them within Express Scripts' member eligibility files for clients allowing use of prescription drug data for research purposes. Maintenance IBD medication possession ratios (MPR) were determined through PBM prescription claims data and chart review. Demographic and prospectively captured physician global assessments (PGA) were retrospectively extracted from the medical record. MPR was analyzed as continuous data and also dichotomized as greater or less than 80%. RESULTS: Among our 362 patients, we matched 228 (63%) within Express Scripts' eligibility data files. Of those, 78 patients were continuously eligible for benefits and had at least one outpatient prescription IBD medication prescribed. Their mean MPR was 0.63 ±â€Š0.31 (standard deviation) and 40% had an MPR ≥80%. Patients in clinical remission had a higher mean MPR than those with an active PGA (0.72 ±â€Š0.28 vs 0.51 ±â€Š0.32, P = 0.002) and patients whose MPR were ≥80% were more likely to have a PGA of remission than those with whose MPR were <80% (84% vs 43%, P = <0.001). CONCLUSIONS: We found a significant association between refill adherence and clinical remission. Nonadherence was common and was more common in adolescents. Use of PBM databases to identify and intervene on patients with poor adherence may improve outcomes in pediatric IBD.

Emergency Information Forms for Children With Medical Complexity: A Simulation Study.

BACKGROUND: Emergency information forms (EIFs) have been proposed to provide critical information for optimal care of children with medical complexity (CMC) during emergencies; however, their impact has not been studied. The objective of this study was to measure the impact and utility of EIFs in simulated scenarios of CMC during medical emergencies. METHODS: Twenty-four providers (12 junior, 12 experienced) performed 4 simulations of CMC, where access to an EIF was block randomized by group. Scenario-specific critical action checklists and consequential pathways were developed by content experts in simulation and pediatric subspecialists. Scenarios ended when all critical actions were completed or after 10 minutes, whichever came first. Two reviewers independently evaluated the video-recorded performances and calculated scenario-specific critical action scores. Performance in scenarios with and without an EIF was compared with Pearson's χ(2) and Mann-Whitney U tests. Interrater reliability was assessed with intraclass correlation. Each provider rated the utility of EIFs via exit questionnaires. RESULTS: The median critical action score in scenarios with EIFs was 84.2% (95% confidence interval [CI], 71.7%-94.1%) versus 12.5% (95% CI, 10.5%-35.3%) in scenarios without an EIF (P < .001); time to completion of scenarios was shorter (6.9 minutes [interquartile range 5.8-10 minutes] vs 10 minutes), and complication rates were lower (30% [95% CI, 17.4%-46.3%] vs 100% [95% CI, 92.2%-100%]) with EIFs, independent of provider experience. Interrater reliability was excellent (intraclass correlation = 0.979). All providers strongly agreed that EIFs can improve clinical outcomes for CMC. CONCLUSIONS: Using simulated scenarios of CMC, providers' performance was superior with an EIF. Clinicians evaluated the utility of EIFs very highly.

Factors associated with meaningful use incentives in children's hospitals.

BACKGROUND AND OBJECTIVE: Among children's hospitals, little is known about how barriers to electronic health record (EHR) adoption are related to meaningful use (MU) incentives. We investigated hospital success with MU incentive payments and determined associations with hospital-reported challenges and characteristics. METHODS: A survey administered to 224 Children's Hospital Association hospitals assessed a variety of potential challenges to achieving meaningful EHR use (eg, lack of access to capital) and specific MU criteria that would be challenging to fulfill (eg, implement clinical decision support rules). These results were combined with data on hospitals that received MU payments up to March 2014 and information on hospital characteristics. Associations between anticipated challenges, children's hospital type, and receipt of MU incentives were evaluated in bivariate and multivariate analyses. RESULTS: One hundred thirty-three children hospitals completed the survey (response rate 59.4%). Thirty-five percent of responding children's hospitals received MU incentive payments. The most frequently anticipated hospital challenges included the following: exchange clinical information with other providers outside your hospital system (49%), and generate numerator and denominator data for quality reporting directly from EHR (41%). Freestanding children's hospitals were more likely to indicate lack of relevance of MU criteria to pediatric care (odds ratio: 37.6 [95% confidence interval: 4.6-309.3]) and more likely to receive MU incentive payments (odds ratio: 26 [95% confidence interval: 5.2-130.6]). CONCLUSIONS: As of 2014, a minority of children's hospitals have successfully received MU incentive payments. Freestanding children's hospitals are more likely to report MU is not relevant to pediatric care and to succeed with MU incentive payments.

Impact of the meaningful use incentive program on electronic health record adoption by US children's hospitals.

OBJECTIVE: We determined adoption rates of pediatric-oriented electronic health record (EHR) features by US children's hospitals and assessed perceptions regarding the suitability of commercial EHRs for pediatric care and the influence of the meaningful use incentive program on implementation of pediatric-oriented features. MATERIALS AND METHODS: We surveyed members of the Children's Hospital Association. We measured adoption of 19 pediatric-oriented features and asked whether commercial EHRs include key pediatric-focused capabilities. We inquired about the meaningful use program's relevance to pediatrics and its influence on EHR implementation priorities. RESULTS: Of 164 general acute care children's hospitals, 100 (61%) responded to the survey. Rates of comprehensive (across all pediatric units) adoption ranged from 37% (age-, gender-, and weight-adjusted blood pressure percentiles and immunization contraindication warnings) to 87% (age in appropriate units). Implementation rates for several features varied significantly by children's hospital type. Nearly 60% of hospitals reported having EHRs that do not contain all features essential for high-quality care. A majority of hospitals indicated that the meaningful use program has had no effect on their adoption of pediatric features, while 26% said they have delayed or forgone incorporation of such features because of the program. CONCLUSIONS: Children's hospitals are implementing pediatric-focused features, but a sizable proportion still finds their systems suboptimal for pediatric care. The meaningful use incentive program is failing to promote and in some cases delaying uptake of pediatric-oriented features.

PEDSnet: a National Pediatric Learning Health System.

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network that provides the infrastructure to support a national pediatric LHS. A consortium consisting of PEDSnet, which includes eight academic medical centers, two existing disease-specific pediatric networks, and two national data partners form the initial partners in the National Pediatric Learning Health System (NPLHS). PEDSnet is implementing a flexible dual data architecture that incorporates two widely used data models and national terminology standards to support multi-institutional data integration, cohort discovery, and advanced analytics that enable rapid learning.

Electronic health record: integrating evidence-based information at the point of clinical decision making.

The authors created two tools to achieve the goals of providing physicians with a way to review alternative diagnoses and improving access to relevant evidence-based library resources without disrupting established workflows. The "diagnostic decision support tool" lifted terms from standard, coded fields in the electronic health record and sent them to Isabel, which produced a list of possible diagnoses. The physicians chose their diagnoses and were presented with the "knowledge page," a collection of evidence-based library resources. Each resource was automatically populated with search results based on the chosen diagnosis. Physicians responded positively to the "knowledge page."

Multi-Institutional Sharing of Electronic Health Record Data to Assess Childhood Obesity.

OBJECTIVE: To evaluate the validity of multi-institutional electronic health record (EHR) data sharing for surveillance and study of childhood obesity. METHODS: We conducted a non-concurrent cohort study of 528,340 children with outpatient visits to six pediatric academic medical centers during 2007-08, with sufficient data in the EHR for body mass index (BMI) assessment. EHR data were compared with data from the 2007-08 National Health and Nutrition Examination Survey (NHANES). RESULTS: Among children 2-17 years, BMI was evaluable for 1,398,655 visits (56%). The EHR dataset contained over 6,000 BMI measurements per month of age up to 16 years, yielding precise estimates of BMI. In the EHR dataset, 18% of children were obese versus 18% in NHANES, while 35% were obese or overweight versus 34% in NHANES. BMI for an individual was highly reliable over time (intraclass correlation coefficient 0.90 for obese children and 0.97 for all children). Only 14% of visits with measured obesity (BMI ≥95%) had a diagnosis of obesity recorded, and only 20% of children with measured obesity had the diagnosis documented during the study period. Obese children had higher primary care (4.8 versus 4.0 visits, p<0.001) and specialty care (3.7 versus 2.7 visits, p<0.001) utilization than non-obese counterparts, and higher prevalence of diverse co-morbidities. The cohort size in the EHR dataset permitted detection of associations with rare diagnoses. Data sharing did not require investment of extensive institutional resources, yet yielded high data quality. CONCLUSIONS: Multi-institutional EHR data sharing is a promising, feasible, and valid approach for population health surveillance. It provides a valuable complement to more resource-intensive national surveys, particularly for iterative surveillance and quality improvement. Low rates of obesity diagnosis present a significant obstacle to surveillance and quality improvement for care of children with obesity.

Seizure occurrence following nonoptimal anticonvulsant medication management during the transition into the hospital.

Previous work has shown that medication errors related to anticonvulsants are common during the transition into the hospital for pediatric patients. The purpose of this work was to evaluate whether children with epilepsy admitted for reasons other than epilepsy experience nonoptimal care in anticonvulsant medication management preceding the occurrence of seizures. Using a retrospective cohort of children with epilepsy admitted for reasons other than epilepsy, we created timelines from data in the medical record for the children who experienced seizures. These timelines included the timing and concentration of anticonvulsant administration and seizure occurrence. Three child neurologists independently identified whether nonoptimal care preceded the occurrence of seizures and potentially contributed to the occurrence of the seizure. Of 120 children, 18 experienced seizures and 12 experienced nonoptimal care in anticonvulsant management preceding seizure occurrence. Nonoptimal care that occurred during the transition into the hospital included missed doses of anticonvulsants, delays in administration during which seizures occurred, and patients inadvertently not receiving their home dosing of medication. Anticonvulsant medication errors are known to occur during the transition into the hospital. Here we present a case series of children who experienced nonoptimal care in anticonvulsant medication management who subsequently experienced seizures. Further work to identify how likely the outcome of seizures is following anticonvulsant medication errors, specifically focusing on timing as well as interventions to change the system issues that lead to these errors, is indicated.

Health information technology vendor selection strategies and total factor productivity.

OBJECTIVE: The aim of this study was to compare health information technology (HIT) adoption strategies' relative performance on hospital-level productivity measures. DATA SOURCES: The American Hospital Association's Annual Survey and Healthcare Information and Management Systems Society Analytics for fiscal years 2002 through 2007 were used for this study. STUDY DESIGN: A two-stage approach is employed. First, a Malmquist model is specified to calculate hospital-level productivity measures. A logistic regression model is then estimated to compare the three HIT adoption strategies' relative performance on the newly constructed productivity measures. PRINCIPAL FINDINGS: The HIT vendor selection strategy impacts the amount of technological change required of an organization but does not appear to have either a positive or adverse impact on technical efficiency or total factor productivity. CONCLUSIONS: The higher levels in technological change experienced by hospitals using the best of breed and best of suite HIT vendor selection strategies may have a more direct impact on the organization early on in the process. However, these gains did not appear to translate into either increased technical efficiency or total factor productivity during the period studied. Over a longer period, one HIT vendor selection strategy may yet prove to be more effective at improving efficiency and productivity.