Division of Population Health Sciences Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in Éirinn Patient Safety and Clinical Prediction Rules Derek Corrigan, Borislav D. Dimitrov, Tom Fahey

Division of Population Health Sciences Overview Previously seen examples of electronic CPR repositories incorporating decision support in ICT systems (CDSS) Take a step further - demonstrate how clinical research can also be incorporated into such CPR based systems to turn them into a true “self-learning” CPR based system Overview of the TRANSFoRm project Discuss how this addresses patient safety issues

Division of Population Health Sciences The TRANSFoRm Project “Translational Research and Patient Safety in Europe” 5 Year EU funded research project – just started 17 Participant bodies including the HRB Centre Leading Work Package 4 – “Decision Rules and Evidence” Bridge clinical research and primary care practice – will involve validation in Irish GP sites

Division of Population Health Sciences The TRANSFoRm Project

Division of Population Health Sciences 1 CPR Repository Clinical Prediction Rules Service TRANSFoRm Services 5 CPR Data Mining and Analysis 3 Research Study Designer 2 Distributed GP EHRs With CDSS CPR Analysis & Extraction Tool CP Classifier CP Rules Manager Study Criteria Design Find Eligible Patient ( 4 Research Study Management Recruit Eligible Patient Study Data Management

Division of Population Health Sciences TRANSFoRm Work Packages

Division of Population Health Sciences An Example – CRB 65 Rule - Pneumonia Confusion, Respiratory Rate >= 30 /min, BP : SBP< 90 mm Hg or DSP <= 60 mm Hg, Age >= 65 years 0 1 OR 23 OR 4 Mortality Low Mortality Intermediate Mortality High Likely Home Treatment Likely Hospital referral and assessment Urgent Hospital CRB Score Rule Criteria Risk Decision

Division of Population Health Sciences Define Study Eligibility Criteria – Electronic Primary Care Research Network (Epcrn)

Division of Population Health Sciences Gather Study Data - Case Report Forms -ePCRN

Division of Population Health Sciences Analyse CPR usage and Epidemiological study data Huge potential evidence base in EHRs in primary care May be used to amend an existing rule i.e. the inclusion of additional symptoms/signs identified by data analysis as potential diagnostic cues. E.g. In the case of CRB 65, add Urea> 7 mmol/l. to rule criteria May be used to create new CPR’s based on new diagnostic cue combinations Evidence base becomes “self-learning” and adds or improves the list of CPR’s used to suggest potential diagnoses to a GP

Division of Population Health Sciences How can this improve Patient Safety? Diagnostic error is the major threat to patient safety in the context of the primary care setting TRANSFoRm uses CPRs to broaden the evidence base considered by GPs to support inclusion / exclusion of diagnostic hypotheses for any particular case – not just previous patient history By implication, decreasing the possibility of diagnostic error will improve patient safety Bridges the gap between implementing evidence based care research in the primary care setting

Division of Population Health Sciences TRANSFoRm Challenges Clinical validation and quality of CPR’s is essential to have user confidence Data Provenance – Patient Safety includes managing how that data is used in ICT systems. Requires complete audit and security functions

Division of Population Health Sciences TRANSFoRm Challenges Clinical consultation using ICT will change GP workflow – not a trivial issue – needs to be tightly integrated and not interrupt workflow Integration with different types of EHR’s - ICT must be based on open standards to support both: –system interoperability e.g. HL7, OpenEHR –semantic interoperability e.g. SNOMED CT

Division of Population Health Sciences In Conclusion “Improvements in safety performance have the potential to benefit both patients and providers and to align their interests” - RAND Report – Greenberg, 2010 ICT systems based on: –electronic CPR repositories –integrated with EHR to provide CDSS –integrated with clinical research – “self learning” CPRs –reduce possibility of diagnostic error –improve patient safety