INTRODUCTION:Clinical decision support (CDS) is increasingly delivered through distributed architectures that connect electronic health record (EHR) workflows to external services and community partners. While these designs enable rapid deployment and interoperability, they also introduce new failure modes that can silently disrupt time‑sensitive care processes. Practical, real‑world descriptions of these distributed CDS malfunctions remain limited. CASE REPORT:We describe 3 malfunctions in a distributed CDS system used to support smoking cessation referrals. The issues reflected common distributed‑system failure modes, including clock drift, timing‑related data availability problems, and asynchronous processing across partner systems. CONCLUSION AND RECOMMENDATIONS:Given the implications software architecture can have on distributed systems, it is critical to expand the definition of what constitutes the CDS system to include components outside the EHR, including those of third-party partners system. Further, monitoring techniques for distributed systems may also require multiple methods to account for differences in how each component can fail.

The Electronic Medical Records and Genomics (eMERGE) Network developed and implemented a genome-informed risk assessment (GIRA) to communicate genomic (polygenic risk scores [PRSs], integrated risk scores [IRSs], and monogenic results), clinical, and family history-based risk for 11 chronic diseases and provide recommended healthcare recommendations. GIRA reports have now been returned to 23,840 participants and their providers in a large prospective cohort study. We present here the study design and analysis framework for assessing the attributable impact of GIRA return. Pre-specified outcomes include (1) provider/participant adoption of recommended healthcare actions, (2) new diagnosis of disease, (3) treatment initiation/intensification, and (4) clinical outcomes (surrogate markers or clinical events). We assess outcomes in high risk vs. not-high-risk participants, adjusting for covariates. We evaluate the effect of PRS/IRS at pre-established high-risk thresholds using regression discontinuity (RD), a quasi-experimental method that mimics randomization near a cutoff, enabling estimation of causal effects and controlling for unobserved confounders. Monogenic and family history-based risk stratification are analyzed using logistic regression. With 23,840 participants and 12 months of follow-up, the study is powered to detect differences of 2%-11% with 80% power (α = 0.05 in the adoption outcome). Longer follow-up will be required to enable assessment of new disease diagnosis, treatment changes, and clinical outcomes. Through innovative RD analyses and defined outcomes and comparison groups, this study will provide new insights into the real-world clinical impact of genomic risk assessment, address critical evidence gaps, advance understanding of genomic medicine outcomes, and inform future research.

Smoking is associated with severe health consequences. Secondhand smoke exposure among children increases the risk of sudden infant death syndrome, chronic respiratory diseases such as asthma, and lung cancer in adulthood. For many parents, pediatricians are the primary source of interaction with the health care system. Nevertheless, in pediatric settings, appropriate tobacco treatments are rarely, if ever, provided to parents who smoke. To best address tobacco use among parents, it is ideal to develop scalable solutions that are coordinated across health systems, community partners, and national services within pediatric settings. We describe our experience in developing and implementing a parent tobacco treatment platform within a pediatric institution that leverages multiple international standards to support interoperability, with the overarching goal of providing a model for how such work can be approached. The clinical decision support (CDS) system includes clinician- and patient-facing components, connects parents to 3 different treatment options (nicotine replacement therapy, text-based counseling, and telephonic counseling), and incorporates 3 international standards (Fast Healthcare Interoperability Resources [FHIR], SMART on FHIR, and CDS Hooks). FHIR is used across all components. SMART on FHIR is limited to the clinician-facing tool, and CDS Hooks is used in the patient-facing portion. While health care interoperability standards supported a significant portion of the overall system, nonstandard technologies and enhancements of existing standards were also required. Furthermore, no connections with community partners could use existing interoperability standards. Over one year, the CDS was used in 194,946 visits, identified 7847 parents who smoked, and connected 2954 parents to 6320 distinct treatment services, a significant improvement compared to prior efforts. Our project demonstrates that building CDS systems using international standards, such as SMART on FHIR, FHIR, and CDS Hooks, is possible, but challenges remain. Limits in the CDS Hooks standard to support common workflows and a lack of communication standards used by third parties outside the health care system represent areas for future work. To support these requirements, additional electronic health record–specific records and communication mechanisms are required.

Human-centered design (HCD) methods in machine learning generally focus on workflow, user interfaces, and data visualizations, but there is the potential to apply these methods to inform the model development and testing process.This study aimed to demonstrate the potential of HCD methods to support the design and testing of machine learning models developed for clinical decision-making.In preparing for formative user testing of clinician facing representations of a machine learning model for detecting sepsis in neonatal intensive care unit (NICU) patients, we discovered that interactive low fidelity mockups using real patient data revealed potential model anomalies. To further investigate these potential anomalies, we utilized the qualitative analysis of interviews with 31 NICU clinicians concerning their experience with neonatal sepsis. The review process was conducted by a multidisciplinary team with members having expertise in neonatology, informatics, data science, and human computer interaction (HCI). Anomalies identified via the mockups and interview analysis were further analyzed by inspections of patient charts and model features and code.The HCD-facilitated review revealed anomalies in three categories: (1) feature inclusion and exclusion, (2) feature importance, and (3) model stability over time. Data entry errors in the electronic health record and their impact on model output were also noted. The review resulted in 41 changes to the model.The discovery of over 41 opportunities to improve our prediction model was a serendipitous by-product of the HCD process. Our results suggest that HCD can be applied not only to model display design and measures of explainability, but to the development and evaluation of the model itself. This case report also demonstrates the need for a multidisciplinary team of clinicians, data scientists, and HCI experts in identifying and addressing issues involving machine learning model performance.

OBJECTIVE:To assess language accessibility of selected community-based programs serving families who speak Spanish, Somali, or Vietnamese in 2 large US cities. METHODS:We conducted a cross-sectional evaluation of selected community-based programs identified using online directories used by health systems seeking to address unmet social needs among pediatric patients. We reviewed program websites and telephone menus for language accessibility and surveyed program staff about language access for service delivery. RESULTS:Out of 179 community-based programs identified, 126 had unique websites (40% were available in languages other than English). One hundred and seventy-eight had working telephone numbers, of which 57% directed callers to a telephone menu. More than half (58%) of telephone menus had an option for language selection, almost exclusively Spanish. Of 136 programs that completed the telephone-based survey, 65% reported bilingual staff, and 46% reported working with interpreters for service delivery in Spanish. For service delivery in Somali, 9% reported bilingual staff, and 57% reported interpreters. For service delivery in Vietnamese, 16% reported bilingual staff, and 57% reported interpreters. A subset of programs reported no ability to support service delivery in Spanish (20%), Somali (32%), or Vietnamese (32%). CONCLUSIONS:Community-based programs may not have the language-related resources necessary to support families who speak Spanish, Somali, or Vietnamese. Health systems should consider confirming language access and/or providing language support when referring patients to community resources.

Experiences sharing complex workflow-integrated clinical decision support (CDS) across health systems are sparse and not well reported. This case study presents the sharing of a hybrid electronic health record (EHR)-native and SMART-compatible CDS tool for automating provision of smoking cessation treatment for caregivers during pediatric visits.We conducted a comprehensive needs assessment using sociotechnical frameworks to identify workflow gaps and technical requirements. A multidisciplinary team of clinical informaticians, software developers, and EHR analysts guided the technology transfer. Iterative testing and feedback informed modifications. The evaluation tracked questionnaire uptake, tobacco use identification rates, and treatment acceptance metrics.The needs assessment revealed critical artifacts such as data architecture, source code repositories, and regulatory requirements, which informed adaptations for the recipient health system. In the preimplementation phase, JXPORT was identified for transferring EHR-native components and the EHR's Active Guidelines Framework was needed to extend the Fast Healthcare Interoperability Resources standard with ordering, posting flowsheet values, and launching activities in the embedded web application. The implementation process resulted in key modifications including same-day nicotine replacement therapy delivery through internal pharmacy services and optimized questionnaire design to improve usability. At the source system, 5.8% (n = 3,391) of caregivers reported active tobacco use with 46.9% (n = 1,590) accepting cessation resources. At the recipient system, 24.3% (n = 167) of caregivers listed tobacco use and 28.1% (n = 47) accepted treatment.The cross-system sharing of eCEASE serves as a nascent model for disseminating complex CDS tools and highlighted opportunities for improvement. Future work should focus on creating validated dissemination frameworks and improving use of standards for EHR integration.

While electronic health record (EHR)-based tools for refugee health screening exist, support for other immigrant children has lagged. Reasons include lack of time, difficulty determining screening eligibility, and lack of awareness of screening recommendations. EHR-based tools to promote immigrant child health screening (ICHS) can address these challenges, but guidance is needed for tools that are usable by clinicians and acceptable to immigrant families.Develop useful EHR-based tools to support ICHS while incorporating evaluation of acceptability, usability, and implementation effort.We followed a five-step human-centered design approach to develop EHR-based tools for ICHS. This included: (1) representative users completing semi-structured interviews. (2) Health professionals and community advisory groups providing ongoing guidance. (3) Developing a functional prototype. (4) Usability testing of the prototype. And (5) an assessment of the implementation effort involving a second site installation coupled with expert implementation time estimations.Sixteen interviewees discussed screening barriers and how EHR-based tools could support discussing nativity (country of birth). From the interview findings and in consultation with advisory group members, we developed an EHR-based toolkit including noninterruptive alerts, an order set, and a documentation prompt. Ten clinicians completed usability testing. All recognized the alert and asked country of birth. Most (9) were satisfied with the system. All felt it was easy to use, helpful, and would not hinder patient care. Content experts (n = 8) estimated installation times (range: 4-20 hours, median 10) with high levels of confidence (range: 1-5, median 4). A second-site test installation required 7.25 hours.Our EHR-based tools designed with the guidance of experts were highly rated on usability and can help clinicians identify patients eligible for ICHS in a sensitive manner. Installation testing demonstrated that this content could be implemented in a reasonable timeframe at external sites.

Background Primary care pediatricians play an important role in genetic testing, including referrals, test ordering, responding to results, assessing risk, treatment, and managing care. As genetic testing rapidly evolves to include new tests identifying patients at risk for certain conditions, alert-based clinical decision support is insufficient in assisting pediatric primary care providers in working with patients, parents, genetics, and other specialties. Supporting pediatricians in the return of these results requires addressing gaps in genetics training and integrating genetics into practice with education, information resources, and specialized tools. Objectives This study aimed to capture requirements for developing systems and processes to support primary care pediatricians in the return of genome-informed risk assessments. Methods We performed a requirements analysis to inform the design of clinical decision support tools and processes for pediatric providers of patients who received a genome informed risk assessment, a novel test that combines polygenic risk scores with patient and family histories to deliver a risk assessment for common medical conditions. We developed an interview guide consisting of scenario presentations, questionnaires, and semi-structured questions to elicit provider responses on a broad set of requirements to manage results with patients and caregivers. Results Twenty providers from 10 primary care pediatric practices within a single health system participated in the study. The findings demonstrated that providers feel responsible to be involved in the process of returning results but require a support system that integrates education, provider and patient information resources, effective communication with genetics, and electronic health record decision support tools that can accommodate a range of clinical scenarios and provider workflow preferences. Conclusion Supporting providers with the return of genetic testing results such as the genome informed risk assessment requires a comprehensive approach to decision support consisting of education, communication, and a comprehensive and integrated set of electronic health record tools.

Objective Experiences sharing complex workflow-integrated clinical decision support (CDS) across health systems are sparse and not well reported. This case study presents the sharing of a hybrid electronic health record (EHR)-native and SMART-compatible CDS tool for automating provision of smoking cessation treatment for caregivers during pediatric visits. Materials & Methods We conducted a comprehensive needs assessment using socio-technical frameworks to identify workflow gaps and technical requirements. A multidisciplinary team of clinical informaticians, software developers, and EHR analysts guided the technology transfer. Iterative testing and feedback informed modifications. The evaluation tracked questionnaire uptake, tobacco use identification rates, and treatment acceptance metrics. Results The needs assessment revealed critical artifacts such as data architecture, source code repositories, and regulatory requirements, which informed adaptations for the recipient health system. In the pre-implementation phase, JXPORT was identified for transferring EHR-native components and the EHR's Active Guidelines Framework was needed to extend the FHIR standard with ordering, posting flowsheet values, and launching activities in the embedded web application. The implementation process resulted in key modifications including same-day nicotine replacement therapy delivery through internal pharmacy services and optimized questionnaire design to improve usability. At the source system, 5.8% (n=3391) of caregivers reported active tobacco use with 46.9% (n=1590) accepting cessation resources. At the recipient system, 24.3% (n=167) of caregivers listed tobacco use and 28.1% (n=47) accepted treatment. Conclusions The cross-system sharing of eCEASE serves as a nascent model for disseminating complex CDS tools and highlighted opportunities for improvement. Future work should focus on creating validated dissemination frameworks and improving use of standards for EHR integration.

Abstract Background Clinical decision support (CDS) is a promising intervention for improving uptake of HIV testing and pre-exposure prophylaxis (PrEP). However, little is known regarding provider perspectives on acceptability, appropriateness, and feasibility of CDS for HIV prevention in pediatric primary care, a key implementation setting. Methods This was a cross-sectional multiple methods study utilizing surveys and in-depth interviews with pediatricians to assess acceptability, appropriateness, and feasibility of CDS for HIV prevention, as well as to identify contextual barriers and facilitators to CDS. Qualitative analysis utilized work domain analysis and a deductive coding approach grounded in the Consolidated Framework of Implementation Research. Quantitative and qualitative data were merged to develop an Implementation Research Logic Model to conceptualize implementation determinants, strategies, mechanisms, and outcomes of potential CDS use. Results Participants (n = 26) were primarily white (92%), female (88%), and physicians (73%). Using CDS to improve HIV testing and PrEP delivery was perceived as highly acceptable (median score 5), IQR [4–5]), appropriate (5, IQR [4–5]), and feasible (4, IQR [3.75–4.75]) using a 5-point Likert scale. Providers identified confidentiality and time constraints as two key barriers to HIV prevention care spanning every workflow step. With respect to desired CDS features, providers sought interventions that were integrated into the primary care workflow, standardized to promote universal testing yet adaptable to the level of a patient’s HIV risk, and addressed providers’ knowledge gaps and bolstered self-efficacy in providing HIV prevention services. Conclusions This multiple methods study indicates that clinical decision support in the pediatric primary care setting may be an acceptable, feasible, and appropriate intervention for improving the reach and equitable delivery of HIV screening and PrEP services. Design considerations for CDS in this setting should include deploying CDS interventions early in the visit workflow and prioritizing standardized but flexible designs.

Objectives Clinical decision support (CDS) has promise for the implementation of antimicrobial stewardship programs (ASPs) in the emergency department (ED). We sought to assess the usability of a newly developed automated CDS to improve guideline-adherent antibiotic prescribing for pediatric community-acquired pneumonia (CAP) and urinary tract infection (UTI). Methods We conducted comparative usability testing between an automated, prototype CDS-enhanced discharge order set and standard order set, for pediatric CAP and UTI antibiotic prescribing. After an extensive user-centered design process, the prototype CDS was integrated into the electronic health record, used passive activation, and embedded locally adapted prescribing guidelines. Participants were randomized to interact with three simulated ED scenarios of children with CAP or UTI, across both systems. Measures included task completion, decision-making and usability errors, clinical actions (order set use and correct antibiotic selection), as well as objective measures of system usability, utility, and workload using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). The prototype CDS was iteratively refined to optimize usability and workflow. Results Usability testing in 21 ED clinical providers demonstrated that, compared to the standard order sets, providers preferred the prototype CDS, with improvements in domains such as explanations of suggested antibiotic choices (p < 0.001) and provision of additional resources on antibiotic prescription (p < 0.001). Simulated use of the CDS also led to overall improved guideline-adherent prescribing, with a 31% improvement for CAP. A trend was present toward absolute workload reduction. Using the NASA-TLX, workload scores for the current system were median 26, interquartile ranges (IQR): 11 to 41 versus median 25, and IQR: 10.5 to 39.5 for the CDS system (p = 0.117). Conclusion Our CDS-enhanced discharge order set for ED antibiotic prescribing was strongly preferred by users, improved the accuracy of antibiotic prescribing, and trended toward reduced provider workload. The CDS was optimized for impact on guideline-adherent antibiotic prescribing from the ED and end-user acceptability to support future evaluative trials of ED ASPs.

OBJECTIVE:State agencies have developed reporting systems of safety events that include events related to health information technology (HIT). These data come from hospital reporting systems where staff submit safety reports and nurses, in the role of safety managers, review, and code events. Safety managers may have varying degrees of experience with identifying events related to HIT. Our objective was to review events potentially involving HIT and compare those with what was reported to the state.METHODS:We performed a structured review of 1 year of safety events from an academic pediatric healthcare system. We reviewed the free-text description of each event and applied a classification scheme derived from the AHRQ Health IT Hazard Manager and compared the results with events reported to the state as involving HIT.RESULTS:Of 33,218 safety events for a 1-year period, 1247 included key words related to HIT and/or were indicated by safety managers as involving HIT. Of the 1247 events, the structured review identified 769 as involving HIT. In comparison, safety managers only identified 194 of the 769 events (25%) as involving HIT. Most events, 353 (46%), not identified by safety managers were documentation issues. Of the 1247 events, the structured review identified 478 as not involving HIT while safety managers identified and reported 81 of these 478 events (17%) as involving HIT.CONCLUSIONS:The current process of reporting safety events lacks standardization in identifying health technology contributions to safety events, which may minimize the effectiveness of safety initiatives.

Background Research is needed to identify how clinical decision support (CDS) systems can support communication about and engagement with tobacco use treatment in pediatric settings for parents who smoke. We developed a CDS system that identifies parents who smoke, delivers motivational messages to start treatment, connects parents to treatment, and supports pediatrician-parent discussion.Objective The objective of this study is to assess the performance of this system in clinical practice, including receipt of motivational messages and tobacco use treatment acceptance rates.Methods The system was evaluated at one large pediatric practice through a single-arm pilot study from June to November 2021. We collected data on the performance of the CDS system for all parents. Additionally, we surveyed a sample of parents immediately after the clinical encounter who used the system and reported smoking. Measures were: (1) the parent remembered the motivational message, (2) the pediatrician reinforced the message, and (3) treatment acceptance rates. Treatments included nicotine replacement therapy, quitline referral (phone counseling), and/or SmokefreeTXT referral (text message counseling). We described survey response rates overall and with 95% confidence intervals (CIs).Results During the entire study period, 8,488 parents completed use of the CDS: 9.3% ( n = 786) reported smoking and 48.2% ( n = 379) accepted at least one treatment. A total of 102 parents who smoke who used the system were approached to survey 100 parents (98% response rate). Most parents self-identified as female (84%), aged 25 to 34 years (56%), and Black/African American (94%), and had children with Medicaid insurance (95%). Of parents surveyed, 54% accepted at least one treatment option. Most parents recalled the motivational message (79%; 95% CI: 71-87%), and 31% (95% CI: 19-44%) reported that the pediatrician reinforced the motivational message.Conclusion A CDS system to support parental tobacco use treatment in pediatric primary care enhanced motivational messaging about smoking cessation and evidence-based treatment initiation.

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.

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (similar to 2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided. (c) 2023 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.

PURPOSE:Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS:To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS:GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION:Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

OBJECTIVES: To assess the current landscape of clinical decision support (CDS) tools in PICUs in order to identify priority areas of focus in this field. DESIGN: International, quantitative, cross-sectional survey. SETTING: Role-specific, web-based survey administered in November and December 2020. SUBJECTS: Medical directors, bedside nurses, attending physicians, and residents/advanced practice providers at Pediatric Acute Lung Injury and Sepsis Network-affiliated PICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The survey was completed by 109 respondents from 45 institutions, primarily attending physicians from university-affiliated PICUs in the United States. The most commonly used CDS tools were people-based resources (93% used always or most of the time) and laboratory result highlighting (86%), with order sets, order-based alerts, and other electronic CDS tools also used frequently. The most important goal providers endorsed for CDS tools were a proven impact on patient safety and an evidence base for their use. Negative perceptions of CDS included concerns about diminished critical thinking and the burden of intrusive processes on providers. Routine assessment of existing CDS was rare, with infrequent reported use of observation to assess CDS impact on workflows or measures of individual alert burden. CONCLUSIONS: Although providers share some consensus over CDS utility, we identified specific priority areas of research focus. Consensus across practitioners exists around the importance of evidence-based CDS tools having a proven impact on patient safety. Despite broad presence of CDS tools in PICUs, practitioners continue to view them as intrusive and with concern for diminished critical thinking. Deimplementing ineffective CDS may mitigate this burden, though postimplementation evaluation of CDS is rare.

BACKGROUND:Helping parents quit smoking is a public health priority. However, parents are rarely, if ever, offered tobacco use treatment through pediatric settings. Clinical decision support (CDS) systems developed for the workflows of pediatric primary care may support consistent screening, treatment, and referral.OBJECTIVES:This study aimed to develop a CDS system by using human-centered design (HCD) that identifies parents who smoke, provides motivational messages to quit smoking (informed by behavioral science), and supports delivery of evidence-based tobacco treatment.METHODS:Our multidisciplinary team applied a rigorous HCD process involving analysis of the work environment, user involvement in formative design, iterative improvements, and evaluation of the system's use in context with the following three cohorts: (1) parents who smoke, (2) pediatric clinicians, and (3) clinic staff. Participants from each cohort were presented with scenario-based, high-fidelity mockups of system components and then provided input related to their role in using the CDS system.RESULTS:We engaged 70 representative participants including 30 parents, 30 clinicians, and 10 clinic staff. A key theme of the design review sessions across all cohorts was the need to automate functions of the system. Parents emphasized a system that presented information in a simple way, highlighted benefits of quitting smoking, and allowed direct connection to treatment. Pediatric clinicians emphasized automating tobacco treatment. Clinical staff emphasized screening for parent smoking via several modalities prior to the patient's visit. Once the system was developed, most parents (80%) reported that it was easy to use, and the majority of pediatricians reported that they would use the system (97%) and were satisfied with it (97%).CONCLUSION:A CDS system to support parental tobacco cessation in pediatric primary care, developed through an HCD process, proved easy to use and acceptable to parents, clinicians, and office staff. This preliminary work justifies evaluating the impact of the system on helping parents quit smoking.