Dataset Information

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

ABSTRACT: Overuse of cranial computed tomography scans in children with blunt head trauma unnecessarily exposes them to radiation. The Pediatric Emergency Care Applied Research Network (PECARN) blunt head trauma prediction rules identify children who do not require a computed tomography scan. Electronic health record (EHR) based clinical decision support (CDS) may effectively implement these rules but must only be provided for appropriate patients in order to minimize excessive alerts.To develop, implement and evaluate site-specific groupings of chief complaints (CC) that accurately identify children with head trauma, in order to activate data collection in an EHR.As part of a 13 site clinical trial comparing cranial computed tomography use before and after implementation of CDS, four PECARN sites centrally developed and locally implemented CC groupings to trigger a clinical trial alert (CTA) to facilitate the completion of an emergency department head trauma data collection template. We tested and chose CC groupings to attain high sensitivity while maintaining at least moderate specificity.Due to variability in CCs available, identical groupings across sites were not possible. We noted substantial variability in the sensitivity and specificity of seemingly similar CC groupings between sites. The implemented CC groupings had sensitivities greater than 90% with specificities between 75-89%. During the trial, formal testing and provider feedback led to tailoring of the CC groupings at some sites.CC groupings can be successfully developed and implemented across multiple sites to accurately identify patients who should have a CTA triggered to facilitate EHR data collection. However, CC groupings will necessarily vary in order to attain high sensitivity and moderate-to-high specificity. In future trials, the balance between sensitivity and specificity should be considered based on the nature of the clinical condition, including prevalence and morbidity, in addition to the goals of the intervention being considered.

SUBMITTER: Deakyne SJ

PROVIDER: S-EPMC4586340 | biostudies-other | 2015

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

Deakyne S J SJ Bajaj L L Hoffman J J Alessandrini E E Ballard D W DW Norris R R Tzimenatos L L Swietlik M M Tham E E Grundmeier R W RW Kuppermann N N Dayan P S PS

Applied clinical informatics 20150819 3

<h4>Background</h4>Overuse of cranial computed tomography scans in children with blunt head trauma unnecessarily exposes them to radiation. The Pediatric Emergency Care Applied Research Network (PECARN) blunt head trauma prediction rules identify children who do not require a computed tomography scan. Electronic health record (EHR) based clinical decision support (CDS) may effectively implement these rules but must only be provided for appropriate patients in order to minimize excessive alerts.< ...[more]

PMID: 26448796

Similar Datasets

Project description:IntroductionFor children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial.MethodsThirteen EDs participated in this trial. The 10 sites receiving the CDS intervention used the Epic(®) EHR. All sites implementing EHR-based CDS built the rules by using the vendor's CDS engine. Based on a sociotechnical analysis, we designed the CDS so that recommendations could be displayed immediately after any provider entered prediction rule data. One central site developed and tested the intervention package to be exported to other sites. The intervention package included a clinical trial alert, an electronic data collection form, the CDS rules and the format for recommendations.ResultsThe original PECARN head trauma prediction rules were derived from physician documentation while this pragmatic trial led each site to customize their workflows and allow multiple different providers to complete the head trauma assessments. These differences in workflows led to varying completion rates across sites as well as differences in the types of providers completing the electronic data form. Site variation in internal change management processes made it challenging to maintain the same rigor across all sites. This led to downstream effects when data reports were developed.ConclusionsThe process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial.

Project description:BackgroundCurrent management of children with minor head trauma (MHT) and intracranial injuries is not evidence-based and may place some children at risk of harm. Evidence-based electronic clinical decision support (CDS) for management of these children may improve patient safety and decrease resource use. To guide these efforts, we evaluated the sociotechnical environment impacting the implementation of electronic CDS, including workflow and communication, institutional culture, and hardware and software infrastructure, among other factors.MethodsBetween March and May, 2020 semi-structured qualitative focus group interviews were conducted to identify sociotechnical influences on CDS implementation. Physicians from neurosurgery, emergency medicine, critical care, and pediatric general surgery were included, along with information technology specialists. Participants were recruited from nine health centers in the United States. Focus group transcripts were coded and analyzed using thematic analysis. The final themes were then cross-referenced with previously defined sociotechnical dimensions.ResultsWe included 28 physicians and four information technology specialists in seven focus groups (median five participants per group). Five physicians were trainees and 10 had administrative leadership positions. Through inductive thematic analysis, we identified five primary themes: (1) clinical impact; (2) stakeholders and users; (3) tool content; (4) clinical practice integration; and (5) post-implementation evaluation measures. Participants generally supported using CDS to determine an appropriate level-of-care for these children. However, some had mixed feelings regarding how the tool could best be used by different specialties (e.g. use by neurosurgeons versus non-neurosurgeons). Feedback from the interviews helped refine the tool content and also highlighted potential technical and workflow barriers to address prior to implementation.ConclusionsWe identified key factors impacting the implementation of electronic CDS for children with MHT and intracranial injuries. These results have informed our implementation strategy and may also serve as a template for future efforts to implement health information technology in a multidisciplinary, emergency setting.

Project description:BackgroundUse of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool.ObjectivesThe objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use.MethodsThis mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed.ResultsAmong 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert-video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low.ConclusionsAn eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians.

Project description:BackgroundThe CDC's Family History Public Health Initiative encourages adoption and increase awareness of family health history. To meet these goals and develop a personalized medicine implementation science research agenda, the Genomedical Connection is using an implementation research (T3 research) framework to develop and integrate a self-administered computerized family history system with built-in decision support into 2 primary care clinics in North Carolina.Methods/designThe family health history system collects a three generation family history on 48 conditions and provides decision support (pedigree and tabular family history, provider recommendation report and patient summary report) for 4 pilot conditions: breast cancer, ovarian cancer, colon cancer, and thrombosis. All adult English-speaking, non-adopted, patients scheduled for well-visits are invited to complete the family health system prior to their appointment. Decision support documents are entered into the medical record and available to provider's prior to the appointment. In order to optimize integration, components were piloted by stakeholders prior to and during implementation. Primary outcomes are change in appropriate testing for hereditary thrombophilia and screening for breast cancer, colon cancer, and ovarian cancer one year after study enrollment. Secondary outcomes include implementation measures related to the benefits and burdens of the family health system and its impact on clinic workflow, patients' risk perception, and intention to change health related behaviors. Outcomes are assessed through chart review, patient surveys at baseline and follow-up, and provider surveys. Clinical validity of the decision support is calculated by comparing its recommendations to those made by a genetic counselor reviewing the same pedigree; and clinical utility is demonstrated through reclassification rates and changes in appropriate screening (the primary outcome).DiscussionThis study integrates a computerized family health history system within the context of a routine well-visit appointment to overcome many of the existing barriers to collection and use of family history information by primary care providers. Results of the implementation process, its acceptability to patients and providers, modifications necessary to optimize the system, and impact on clinical care can serve to guide future implementation projects for both family history and other tools of personalized medicine, such as health risk assessments.

Project description:BACKGROUND:The overuse of cranial computed tomography (CT) to diagnose potential traumatic brain injuries (TBIs) exposes children with minor blunt head trauma to unnecessary ionizing radiation. The Pediatric Emergency Care Applied Research Network and the Clinical Research on Emergency Services and Treatments Network implemented TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) to decrease use of CTs in children with minor blunt head trauma. OBJECTIVE:This article aims to facilitate implementation and dissemination of a CDS alert into emergency departments around the country. METHODS:We evaluated the EHR CT CDS tool through a mixed-methods analysis of 38 audio-recorded interviews with health care stakeholders and quantitative data sources, using the Reach, Efficacy, Adoption, Implementation, and Maintenance framework. RESULTS:Reach -: The demographics of participants enrolled in the clinical trial were consistent with national estimates of TBI prevalence. Efficacy-There was a variable and modest reduction in CT rates for the 8,067 children with minor head trauma whose clinicians received CDS. Adoption -: The EHR CT CDS tool was well matched with the organizational mission, values, and priorities of the implementation sites. Implementation- The most important predisposing factors for successful implementation were the presence of an approachable clinical champion at each site and belief that the tool was a relevant, reusable knowledge asset. Enabling factors included an effective integration within the clinical workflow, organizational investment in user training, and ease of use. Maintenance -: Reinforcing factors for the EHR CT CDS tool included a close fit with the institutional culture, belief that it was useful for providers and families, and a good educational and informational tool. As such, the EHR CT CDS tool was maintained in clinical practice long after study completion. CONCLUSION:Data from this mixed-methods study complement findings from the efficacy trial and provide critical components for consideration prior to integration and subsequent dissemination of the EHR CT CDS tool. TRIAL REGISTRATION:NCT01453621, Registered September 27, 2011.

Project description:BackgroundThe Canadian Computed Tomography (CT) Head Rule, a clinical decision rule designed to safely reduce imaging in minor head injury, has been rigorously validated and implemented, and yet expected decreases in CT were unsuccessful. Recent work has identified empathic care as a key component in decreasing CT overuse. Health information technology can hinder the clinician-patient relationship. Patient-centered decision tools to support the clinician-patient relationship are needed to promote evidence-based decisions.ObjectiveOur objective is to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns.MethodsUser-centered design with practice-based and participatory decision aid development was used to design, develop, and evaluate patient-centered decision support regarding CT use in minor head injury in the emergency department. User experience and user interface (UX/UI) development involved successive iterations with incremental refinement in 4 phases: (1) initial prototype development, (2) usability assessment, (3) field testing, and (4) beta testing. This qualitative approach involved input from patients, emergency care clinicians, health services researchers, designers, and clinical informaticists at every stage.ResultsThe Concussion or Brain Bleed app is the product of 16 successive iterative revisions in accordance with UX/UI industry design standards. This useful and usable final product integrates clinical decision support with a patient decision aid. It promotes shared use by emergency clinicians and patients at the point of care within the emergency department context. This tablet computer app facilitates evidence-based conversations regarding CT in minor head injury. It is adaptable to individual clinician practice styles. The resultant tool includes a patient injury evaluator based on the Canadian CT Head Rule and provides patient specific risks using pictographs with natural frequencies and cues for discussion about patient concerns.ConclusionsThis tool was designed to align evidence-based practices about CT in minor head injury patients. It establishes trust, empowers active participation, and addresses patient concerns and uncertainty about their condition. We hypothesize that, when implemented, the Concussion or Brain Bleed app will support-not hinder-the clinician-patient relationship, safely reduce CT use, and improve the patient experience of care.

Dataset Information

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

Publications

Development, Evaluation and Implementation of Chief Complaint Groupings to Activate Data Collection: A Multi-Center Study of Clinical Decision Support for Children with Head Trauma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets