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BACKGROUND AND OBJECTIVES: Adolescent strengths and risks are not routinely captured in systematized and actionable ways in pediatric primary care. To address this problem, we developed a comprehensive adolescent health questionnaire (AHQ) integrated within the electronic health record and evaluated the AHQ's impact on collection of information on prioritized health-related domains. METHODS: We developed and pilot tested the AHQ. We then scaled and assessed the AHQ's impact on data collection. AHQ development used innovation methods and measured feasibility and acceptability outcomes. Scaling and postscaling outcomes included Reach, Effectiveness, Adoption, Implementation, Maintenance and Sustainability measures: Reach (total questionnaires completed), Effectiveness (capture of key information across health domains pre- vs post-AHQ scaling), Adoption (proportion of practices that adopted the AHQ), Implementation (proportion of eligible adolescents who completed the AHQ), and Maintenance (monthly completion rates). RESULTS: AHQ development led to a tool that was feasible and acceptable for use. During scaling (October 2020-December 2021), 22 147 questionnaires were completed by 20 749 unique adolescents aged 13 to 21 years at their preventive visit. Comparing pre- versus post-AHQ scaling data, use of the AHQ increased collection of information across domains, especially for strengths, gun safety, substance use, sexual activity, sexual orientation, and gender identity, from ranges of 0%-25% to 92%-95%. All 31 practices adopted the AHQ with completion at 88.7% of visits (n = 24 968). Two years postscaling, completion rates were >91% per month. CONCLUSIONS: We successfully developed, scaled, and maintained an AHQ in a widely-used electronic health record system, a model for improving adolescent care and foundation for developing future interventions.

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OBJECTIVE: We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. MATERIALS AND METHODS: We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work. RESULTS: We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care. DISCUSSION: Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. CONCLUSION: By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.

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Technology continues to impact healthcare around the world. This provides great opportunities, but also risks. These risks are compounded in low-resource settings where errors in planning and implementation may be more difficult to overcome. Global Health Informatics provides lessons in both opportunities and risks by building off of general Global Health. Global Health Informatics also requires a thorough understanding of the local environment and the needs of low-resource settings. Forming effective partnerships and following the lead of local experts are necessary for sustainability; it also ensures that the priorities of the local community come first. There is an opportunity for partnerships between low-resource settings and high income areas that can provide learning opportunities to avoid the pitfalls that plague many digital health systems and learn how to properly implement technology that truly improves healthcare.

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OBJECTIVE: Patient attribution, or the process of attributing patient-level metrics to specific providers, attempts to capture real-life provider-patient interactions (PPI). Attribution holds wide-ranging importance, particularly for outcomes in graduate medical education, but remains a challenge. We developed and validated an algorithm using EHR data to identify pediatric resident PPIs (rPPIs). METHODS: We prospectively surveyed residents in three care settings to collect self-reported rPPIs. Participants were surveyed at the end of primary care clinic, emergency department (ED), and inpatient shifts, shown a patient census list, asked to mark the patients with whom they interacted, and encouraged to provide a short rationale behind the marked interaction. We extracted routine EHR data elements, including audit logs, note contribution, order placement, care team assignment, and chart closure, and applied a logistic regression classifier to the data to predict rPPIs in each care setting. We also performed a comment analysis of the resident-reported rationales in the inpatient care setting to explore perceived patient interactions in a complicated workflow. RESULTS: We surveyed 81 residents over 111 shifts and identified 579 patient interactions. Among EHR extracted data, time-in-chart was the best predictor in all three care settings (primary care clinic: odds ratio [OR] = 19.36, 95% confidence interval [CI]: 4.19-278.56; ED: OR = 19.06, 95% CI: 9.53-41.65' inpatient: OR = 2.95, 95% CI: 2.23-3.97). Primary care clinic and ED specific models had c-statistic values > 0.98, while the inpatient-specific model had greater variability (c-statistic = 0.89). Of 366 inpatient rPPIs, residents provided rationales for 90.1%, which were focused on direct involvement in a patient's admission or transfer, or care as the front-line ordering clinician (55.6%). CONCLUSION: Classification models based on routinely collected EHR data predict resident-defined rPPIs across care settings. While specific to pediatric residents in this study, the approach may be generalizable to other provider populations and scenarios in which accurate patient attribution is desirable.

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Given the ubiquitous nature of information systems in modern health care, interest in the pursuit of formal training in clinical informatics is increasing. This interest is not restricted to generalists-informatics training is increasingly being sought by future subspecialists. The traditional structure of Accreditation Council on Graduate Medical Education subspecialty training requires completion of both clinical and clinical informatics fellowship programs, and understandably lacks appeal due to the time commitment required. One approach to encourage clinical informatics training is to integrate it with clinical fellowships in order to confer dual-board eligibility. In this perspective, we describe 3 successful petitions for combined training in clinical informatics in order to support other programs and the American Board of Preventive Medicine in establishing pathways for training subspecialists in clinical informatics.

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Objective: Electronic health record (EHR) simulation with realistic test patients has improved recognition of safety concerns in test environments. We assessed if simulation affects EHR use patterns in real clinical settings. Materials and Methods: We created a 1-hour educational intervention of a simulated admission for pediatric interns. Data visualization and information retrieval tools were introduced to facilitate recognition of the patient's clinical status. Using EHR audit logs, we assessed the frequency with which these tools were accessed by residents prior to simulation exposure (intervention group, pre-simulation), after simulation exposure (intervention group, post-simulation), and among residents who never participated in simulation (control group). Results: From July 2015 to February 2017, 57 pediatric residents participated in a simulation and 82 did not. Residents were more likely to use the data visualization tool after simulation (73% in post-simulation weeks vs 47% of combined pre-simulation and control weeks, P <. 0001) as well as the information retrieval tool (85% vs 36%, P < .0001). After adjusting for residents' experiences measured in previously completed inpatient weeks of service, simulation remained a significant predictor of using the data visualization (OR 2.8, CI: 2.1-3.9) and information retrieval tools (OR 3.0, CI: 2.0-4.5). Tool use did not decrease in interrupted time-series analysis over a median of 19 (IQR: 8-32) weeks of post-simulation follow-up. Discussion: Simulation was associated with persistent changes to EHR use patterns among pediatric residents. Conclusion: EHR simulation is an effective educational method that can change participants' use patterns in real clinical settings.

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Opportunities for education in clinical informatics exist throughout the spectrum of formal education extending from high school to postgraduate training. However, physicians in residency represent an underdeveloped source of potential informaticians. Despite the rapid growth of accredited fellowship programs since clinical informatics became a board-eligible subspecialty in 2011, few resident physicians are aware of their role at the intersection of clinical medicine and health information technology or associated opportunities. In an effort to educate and engage residents in clinical informatics, Children's Hospital of Philadelphia has developed a three-pronged model: (1) an elective rotation with hands-on project experience; (2) a longitudinal experience that offers increased exposure and mentorship; and (3) a resident founded and led working group in clinical informatics. We describe resident participation in these initiatives and lessons learned, as well as resident perceptions of how these components have positively influenced informatics knowledge and career choices. Since inception of this model, five residents have pursued the clinical informatics fellowship. This educational model supports resident involvement in hospital-wide informatics efforts with tangible projects and promotes wider engagement through educational opportunities commensurate with the resident's level of interest.

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Understanding the information-seeking preferences and Internet access habits of the target audiences for a patient portal is essential for successful uptake. The resource must deliver culturally and educationally appropriate information via technology that is accessible to the intended users and be designed to meet their needs and preferences. Providers must consider multiple perspectives when launching a portal and make any needed adjustments once the launch is underway. We report results of a study of 270 parents and caregivers of paediatric patients in a major health system during the process of implementing a patient portal. Through a 26-question paper-and-pencil survey, data were collected on participant demographics, Internet access and use, health information-seeking behaviours, health literacy, and potential use of a patient portal. Results indicate a positive attitude towards portal use but also suggest that low health literacy may be a key issue to portal adoption.

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We conducted a national study to assess the numbers and diversity of applicants for 2016 and 2017 clinical informatics fellowship positions. In each year, we collected data on the number of applications that programs received from candidates who were ultimately successful vs. unsuccessful. In 2017, we also conducted an anonymous applicant survey. Successful candidates applied to an average of 4.2 and 5.5 programs for 2016 and 2017, respectively. In the survey, unsuccessful candidates reported applying to fewer programs. Assuming unsuccessful candidates submitted between 2-5 applications each, the total applicant pool numbered 42-69 for 2016 (competing for 24 positions) and 52-85 for 2017 (competing for 30 positions). Among survey respondents (n=33), 24% were female, 1 was black and none were Hispanic. We conclude that greater efforts are needed to enhance interest in clinical informatics among medical students and residents, particularly among women and members of underrepresented minority groups.

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INTRODUCTION: Vaccine acceptance is a critical component of sustainable immunization programs, yet rates of vaccine hesitancy are rising. Increased access to misinformation through media and anti-vaccine advocacy is an important contributor to hesitancy in the United States and other high-income nations with robust immunization programs. Little is known about the content and effect of information sources on attitudes toward vaccination in settings with rapidly changing or unstable immunization programs. OBJECTIVE: The objective of this study was to explore knowledge and attitudes regarding vaccines and vaccine-preventable diseases among caregivers and immunization providers in Botswana, the Dominican Republic, and Greece and examine how access to information impacts reported vaccine acceptance. METHODS: We conducted 37 focus groups and 14 semi-structured interviews with 96 providers and 153 caregivers in Botswana, the Dominican Republic, and Greece. Focus groups were conducted in Setswana, English, Spanish, or Greek; digitally recorded; and transcribed. Transcripts were translated into English, coded in qualitative data analysis software (NVivo 10, QSR International, Melbourne, Australia), and analyzed for common themes. RESULTS: Dominant themes in all three countries included identification of health care providers or medical literature as the primary source of vaccine information, yet participants reported insufficient communication about vaccines was available. Comments about level of trust in the health care system and government contrasted between sites, with the highest level of trust reported in Botswana but lower levels of trust in Greece. CONCLUSIONS: In Botswana, the Dominican Republic, and Greece, participants expressed reliance on health care providers for information and demonstrated a need for more communication about vaccines. Trust in the government and health care system influenced vaccine acceptance differently in each country, demonstrating the need for country-specific data that focus on vaccine acceptance to fully understand which drivers can be leveraged to improve implementation of immunization programs.

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BACKGROUND: Video-capable mobile phones are widely available, but few studies have evaluated their use in telephone triage for pediatric patients. We assessed the feasibility, acceptability, and utility of videos sent via mobile phones to enhance pediatric telephone triage for an underserved population with asthma. MATERIALS AND METHODS: We recruited children who presented to an urban pediatric emergency department with an asthma exacerbation along with their parent/guardian. Parents and the research team each obtained a video of the child's respiratory exam, and the research team conducted a concurrent in-person rating of respiratory status. We measured the acceptability of families sending videos as part of telephone triage (survey) and the feasibility of this approach (rates of successful video transmission by parents to the research team). To estimate the utility of the video in appropriately triaging children, four clinicians reviewed each video and rated whether they found the video reassuring, neutral, or raising concerns. RESULTS: Among 60 families (78% Medicaid, 85% Black), 80% of parents reported that sending a video would be helpful and 68% reported that a nurse's review of a video would increase their trust in the triage assessment. Most families (75%) successfully transmitted a video to the research team. All clinician raters found the video reassuring regarding the severity of the child's asthma exacerbation for 68% of children. CONCLUSIONS: Obtaining mobile phone videos for telephone triage is acceptable to families, feasible, and may help improve the quality of telephone triage in an urban, minority population.

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Tuberculosis (TB) contact tracing is typically conducted in resource-limited settings with paper forms, but this approach may be limited by inefficiencies in data collection, storage, and retrieval and poor data quality. In Botswana, we developed, piloted, and evaluated a mobile health (mHealth) approach to TB contact tracing that replaced the paper form-based approach for a period of six months. For both approaches, we compared the time required to complete TB contact tracing and the quality of data collected. For the mHealth approach, we also administered the Computer System Usability Questionnaire to 2 health care workers who used the new approach, and we identified and addressed operational considerations for implementation. Compared to the paper form-based approach, the mHealth approach reduced the median time required to complete TB contact tracing and improved data quality. The mHealth approach also had favorable overall rating, system usefulness, information quality, and interface quality scores on the Computer System Usability Questionnaire. Overall, the mHealth approach to TB contact tracing improved on the paper form-based approach used in Botswana. This new approach may similarly benefit TB contact tracing efforts in other resource-limited settings.

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OBJECTIVE: The aim of the study was to characterize referral patterns and medical outcomes of children with head injury triaged by an after-hours call center of a large urban pediatric network, both before and after an institutional concussion initiative. The initiative included a revised call center triage algorithm referring patients with a suspected concussion to see a primary care provider (PCP) within 24 hours, concussion-specific continuing education for medical providers, and a new concussion information Web site. METHODS: Patients aged 5 to 18 years with head injury using the after-hours call center were identified by retrospective review of electronic medical records before (2011) and after (2012) the initiative. A random 50% sample was taken from each year for further analysis. RESULTS: A total of 127 and 159 eligible patient encounters were randomly selected from 2011 to 2012, respectively. From 2011 to 2012, PCP referrals significantly increased from 7% (95% confidence interval [CI], 4%-13%) to 38% (95% CI, 31%-45%), P < 0.001. Concussion diagnoses also significantly increased from 35% (95% CI, 27%-44%) to 58% (95% CI, 50%-66%), P < 0.001. Emergency department referrals and head computed tomography scans decreased but the differences were not statistically significant. No patients had intracranial injury on computed tomography. Most injuries were not sports related. CONCLUSIONS: After an institutional concussion initiative including implementation of a revised head trauma telephone triage algorithm, more head injuries were evaluated by PCPs and more concussions were ultimately diagnosed without an increase in emergency department referrals. Clinicians can benefit from continuing education and infrastructure to aid in initial concussion diagnosis and management.

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Information retrieval (IR) practice is invaluable in health care, where the growth of medical knowledge has long surpassed human memory capabilities, and health care workers often have unmet information needs. While the information and communications technology (ICT) revolution is improving, IR in the Western world, the global digital divide has never been wider. Low and Middle Income Countries (LMICs) have the least advanced ICT infrastructure and service provision, and are also burdened with the majority of the world's health issues and severe shortages of health care workers. Initiatives utilizing mobile technology in healthcare and public health (mHealth) have shown potential at addressing these inequalities and challenges. Using Botswana as a reference point, this paper aims to broadly describe the healthcare and ICT challenges facing LMICs, the promise of mHealth as a field in health informatics, and then propose health informatics solutions that specifically address IR content and needs. One solution proposes utilizing Unstructured Supplementary Service Data (USSD) for accessing treatment guidelines, and the other solution outlines applications of smart devices for IR.

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Tuberculosis remains a leading cause of morbidity and mortality worldwide. In 2011, there were 8.7 million new cases and 1.4 million deaths from the disease, with >95% of these deaths taking place in low- and middle-income countries [1]. Contact tracing prevents the spread of tuberculosis by identifying and screening a case's contacts and referring symptomatic individuals to health care providers. Traditionally, contact tracing has been conducted with paper forms, which can lead to considerable inefficiencies in data collection, storage, and retrieval. These inefficiencies are problematic as tuberculosis can continue to spread if disruption of disease transmission is delayed. Mobile health approaches to tuberculosis contact tracing remain largely unaddressed and limited to management and monitoring of multidrug-resistant tuberculosis [2].To address these limitations, a mobile health application that digitizes and automates contact tracing was developed. This poster presents work currently underway to evaluate this new approach in Botswana, which has the tenth highest incidence rate of tuberculosis in the world [3]. Operational considerations for implementing a mobile health approach to contact tracing in resource-limited settings are also presented.

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OBJECTIVE: The goal was to assess the impact of influenza vaccine clinical alerts on missed opportunities for vaccination and on overall influenza immunization rates for children and adolescents with asthma. METHODS: A prospective, cluster-randomized trial of 20 primary care sites was conducted between October 1, 2006, and March 31, 2007. At intervention sites, electronic health record-based clinical alerts for influenza vaccine appeared at all office visits for children between 5 and 19 years of age with asthma who were due for vaccine. The proportion of captured immunization opportunities at visits and overall rates of complete vaccination for patients at intervention and control sites were compared with those for the previous year, after standardization for relevant covariates. The study had >80% power to detect an 8% difference in the change in rates between the study and baseline years at intervention versus control practices. RESULTS: A total of 23 418 visits and 11 919 children were included in the study year and 21 422 visits and 10 667 children in the previous year. The majority of children were male, 5 to 9 years of age, and privately insured. With standardization for selected covariates, captured vaccination opportunities increased from 14.4% to 18.6% at intervention sites and from 12.7% to 16.3% at control sites, a 0.3% greater improvement. Standardized influenza vaccination rates improved 3.4% more at intervention sites than at control sites. The 4 practices with the greatest increases in rates (>or=11%) were all in the intervention group. Vaccine receipt was more common among children who had been vaccinated previously, with increasing numbers of visits, with care early in the season, and at preventive versus acute care visits. CONCLUSIONS: Clinical alerts were associated with only modest improvements in influenza vaccination rates.

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Missed billing opportunities can be a negative outcome of the implementation of non-interfaced clinical and billing information systems. We describe a decision support system that prompts physicians with suggested billing options at the point of ordering nebulized medications. A baseline rate of 70% missed billing opportunities decreased to 38% with education alone and to 7% with an alert system. Decision support can best support billing opportunities when automated and appearing at the point of care.

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OBJECTIVE: An opportunity exists to use increasingly prevalent electronic health records to efficiently gather immunization, clinical, and demographic data to assess and subsequently reduce barriers to immunization. The objective of this study was to use data entered at the point of care within an electronic health record to identify factors that predispose children in an inner-city population to immunization delay. METHODS: Retrospective cohort data from an electronic health record were used to evaluate the association between demographic, clinical, and immunization variables on immunization delay at 24 months. Patients 2 to 5 years old as of May 31, 2003, with an office visit between May 31, 2002, and May 31, 2003, were selected (N = 5464). Univariate and multivariable models were developed to predict vaccination delay at 24 months per the Advisory Committee on Immunization Practices guidelines. RESULTS: Overall up-to-date immunization rates at 3, 7, 13, and 24 months were 75%, 45%, 82%, and 71%. Multivariable models using electronic health record data showed that early immunization status was the strongest predictor of immunization delay at 24 months. Multivariate analysis revealed that children who were inadequately immunized at 3 months of age were more than 4.5 times as likely to be immunization delayed at 24 months. In this analysis, patient and caregiver factors associated with immunization delay included insurance status and nonparent caregiver. Children who were premature were less likely to be delayed. CONCLUSIONS: Using an electronic health record with information entered at the point of care, we found that early immunization status is a strong predictor of immunization delay for young children that can be identified as early as 3 months of age. Electronic health records may prove useful to clinicians and health systems in identifying children at high risk for immunization delay.

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