Can Emergency Department Provider Notes Help Achieve More Dynamic

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Presentation transcript:

Can Emergency Department Provider Notes Help Achieve More Dynamic Clinical Decision Support? Informatics Insights for Clinical Documentation S03 Justin Rousseau Brigham and Women’s Hospital, Harvard Medical School Dell Medical School at the University of Texas at Austin Twitter: #AMIA2017

Disclosure Research was funded by National Library of Medicine grant #T15LM007092 No bearing on study design, data collection, analysis, or interpretation I and my spouse/partner have no other relevant relationships with commercial interests to disclose. AMIA 2017 | amia.org

Learning Objectives After participating in this session the learner should be better able to: Identify and assess unique sources of clinical data in the EHR to use to augment interaction with clinical decision support tools. Assess opportunities for the use of informatics tools to enhance the order entry process to deliver the right clinical decision support for the right person at the right time. AMIA 2017 | amia.org

Imaging Clinical Decision Support (CDS)  An application of health information technology to inform clinical decision- making at the point of care regarding the need for imaging or the optimal diagnostic study based on the best available evidence Khorasani R, et al. Ten commandments for effective clinical decision support for imaging: enabling evidence-based practice to improve quality and reduce waste. Am J Roentgenol. 2014 Oct 23;203(5):945–51. AMIA 2017 | amia.org

Order Requisition Computerized physician order entry system (CPOE) Ip IK, Khorasani R. Decision Support in Diagnostic Radiology. In: Evidence-Based Neuroimaging Diagnosis and Treatment. AMIA 2017 | amia.org

Imaging CDS – “Activation” AMIA 2017 | amia.org

Imaging CDS AMIA 2017 | amia.org

Cervical Spine CDS National Emergency X-Radiography Utilization Study (NEXUS) Assists clinicians in ruling out cervical spine injury Reduces unnecessary c-spine imaging Well validated and in clinical use CDS Displays when CT C-spine or 3 View X-ray C-spine AND Hx = Trauma Hoffman JR, et al. Selective cervical spine radiography in blunt trauma: methodology of the National Emergency X-Radiography Utilization Study (NEXUS). Ann Emerg Med 1998;32:461–9. Hoffman JR, et al. Validity of a Set of Clinical Criteria to Rule Out Injury to the Cervical Spine in Patients with Blunt Trauma. N Engl J Med 2000;343:94–9. AMIA 2017 | amia.org

Cervical Spine CDS National Emergency X-Radiography Utilization Study (NEXUS) C-spine radiography indicated if any of the clinical criteria are met Posterior midline c-spine tenderness Evidence of intoxication Decreased level of alertness Focal neurologic deficit Painful distracting injuries Hoffman JR, et al. Ann Emerg Med 1998;32:461–9. Hoffman JR, et al. N Engl J Med 2000;343:94–9. AMIA 2017 | amia.org

Identifying Gaps Areas for Improvement of CDS Impacts Timing of delivery Specificity Alert fatigue Sensitivity Missed opportunities Redundant data entry Incomplete, Inaccurate, or conflicting data Impacts Quality of care Secondary use of data Research and monitoring adherence to guidelines Bates DW. Ten Commandments for Effective Clinical Decision Support. JAMIA 2003;10:523–30. AMIA 2017 | amia.org

Patient Selection 85,916 of Emergency Department encounters over 18 months 3,155 encounters with chief complaint of Fall/Trauma/Bicycle Accident that did not alert trauma team 438 encounters with both fall/trauma/bicycle accident and c- spine imaging AMIA 2017 | amia.org

Methods Outcomes: Proportion of encounters with at least one c-spine-specific CDS rule attribute in clinical notes at time of imaging order Agreement between CDS attributes in clinical notes and data entered in CDS tool in the CPOE Manual review by two physicians (internal medicine attending and neurologist) of most recent of all note sections submitted prior to image ordering NEXUS Criteria NEXUS Exclusion Criteria Canadian C-spine CDS Rule Exclusion Criteria AMIA 2017 | amia.org

Results 438 Encounters with fall/trauma/bicycle accident where imaging of c-spine was performed At least one note section was complete in 42% (184/438) of encounters HPI (35%), A/P (11%), Attending note (8%), Head and Neck Exam, nml (8%), Neuro Exam, nml (7%), HEENT Comments (5%), Neuro Exam Comments (3%), Neuro ROS comment (1%), NEXUS CDS activated in 27% (117/438) 48% (56/117) had note sections submitted prior to image ordering AMIA 2017 | amia.org

CDS Attributes in encounters with notes prior to imaging AMIA 2017 | amia.org

Agreement between Notes and CDS Kappa Agreement <0 Less than chance 0.01-0.20 Slight 0.21-0.40 Fair 0.41-0.60 Moderate 0.61-0.80 Substantial 0.81-0.99 Almost perfect McNemar; p=0.23 Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic. Fam Med 2005;37:360–3. AMIA 2017 | amia.org

Conclusions Provider EHR documentation is an underutilized information resource that contains CDS attributes and exclusion criteria and is available in a significant percentage of encounters at the point of C-spine image ordering Harvesting CDS attributes and exclusion criteria from EHR notes when available may: Allow pre-population of CDS tools, reducing redundant data entry Allow suppression of CDS rules not applicable to the current patient, potentially reducing workflow interruption and alert fatigue CDS is not activated as often as expected There is only fair agreement of CDS rule attributes comparing notes to the CDS tool in the CPOE AMIA 2017 | amia.org

Future Work Evaluate the quality and quantity of clinical data documented in encounters that are less acute Evaluate performance of automated extraction of attributes using text mining or natural language processing AMIA 2017 | amia.org

Questions What of the following ten commandments for effective clinical decision support for imaging1 is most impacted by the identification of clinical decision support (CDS) criteria in clinical notes prior to image ordering? Respect the ordering provider’s workflow Evidence must be current Clinical recommendations must be brief, unambiguous, and actionable Imaging CDS must enable measurement of its impact 1. Khorasani R, Hentel K, Darer J, Langlotz C, Ip IK, Manaker S, et al. Ten commandments for effective clinical decision support for imaging: enabling evidence-based practice to improve quality and reduce waste. Am J Roentgenol. 2014 Oct 23;203(5):945–51. AMIA 2017 | amia.org

Answer Respect the ordering provider’s workflow Evidence must be current Clinical recommendations must be brief, unambiguous, and actionable Imaging CDS must enable measurement of its impact Explanation: Considering the ordering provider’s workflow includes considering every click of the provider and an effort to reduce or eliminate redundant data entry. Identifying CDS criteria in clinical notes prior to image ordering would provide the opportunity to prepopulate these criteria into CDS tools, reducing redundant data entry and reducing time spent by the provider interacting with the CDS tool. The most immediate impact of identifying CDS criteria in clinical notes is on the provider’s workflow. AMIA 2017 | amia.org

Questions Alert fatigue results from excess alerts or notifications that are not relevant to the current context of the situation. What is the most likely opportunity to reduce alert fatigue from interacting with Clinical Decision Support (CDS) tools for imaging? Identifying CDS criteria in providers notes to prepopulate into CDS tools Identifying inclusion criteria in the EHR to suggest CDS when applicable for an imaging study that has not been ordered Identifying exclusion criteria in the EHR to suppress CDS when not applicable for an imaging study that has been ordered Reconfigure the production rules to identify candidate cases to deliver imaging CDS AMIA 2017 | amia.org

Answer Identifying CDS criteria in providers notes to prepopulate into CDS tools Identifying inclusion criteria in the EHR to suggest CDS when applicable for an imaging study that has not been ordered Identifying exclusion criteria in the EHR to suppress CDS when not applicable for an imaging study that has been ordered Reconfigure the production rules to identify candidate cases to deliver imaging CDS Explanation: The goal to reduce alert fatigue would be to eliminate inappropriate exposure to a CDS tool. The most effective way to address this of the options above is to maximize the specificity of delivery of the tool by identifying exclusion criteria that are already known or present in the EHR in order to suppress CDS when it is not relevant to the patient context due to the presence of an exclusion criterion for the evidence supporting the CDS rule. Lin C-P, Payne TH, Nichol WP, Hoey PJ, Anderson CL, Gennari JH. Evaluating clinical decision support systems: monitoring CPOE order check override rates in the Department of Veterans Affairs’ Computerized Patient Record System. J Am Med Inform Assoc JAMIA. 2008 Oct;15(5):620–6. AMIA 2017 | amia.org

AMIA is the professional home for more than 5,400 informatics professionals, representing frontline clinicians, researchers, public health experts and educators who bring meaning to data, manage information and generate new knowledge across the research and healthcare enterprise. AMIA 2017 | amia.org

Thank you! Email me at: justin.rousseau@austin.utexas.edu Twitter: @JfrederickR