Division of Population Health Sciences Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in Éirinn Aspects of the TRANSFoRm Project - HIQA, Dublin - 7 th July 2011 Derek Corrigan 1, Christian Ohmann 2, Borislav D. Dimitrov 1, Tom Fahey 1 1 – RCSI, Ireland 2 - University of Dusseldorf, Germany

Division of Population Health Sciences Overview General overview and context for the TRANSFoRm project Part A - Overview of TRANSFoRm work being done by RCSI Part B – Core Services - Description of framework proposed to implement security and privacy in TRANSFoRm

Division of Population Health Sciences The TRANSFoRm Project “Translational Research and Patient Safety in Europe” – 5 Year FP7 EU funded research project – 1st year review complete - Antwerp 17 International collaborating bodies including the HRB Centre for Primary Care Research (RCSI) RCSI leading Work Package 4 – “Decision Rules and Evidence”

The TRANSFoRm Consortium

Division of Population Health Sciences TRANSFoRm Goals The underlying concept of TRANSFoRm is to develop a ‘rapid learning healthcare system’ driven by advanced computational infrastructure that can improve both patient safety and the conduct and volume of clinical research in Europe Research trials are slow, manually intensive and costly Huge potential in electronic sources of aggregated primary care data – e.g. GPRD in UK, Nivel in Netherlands, national disease registries Bridging clinical research and primary care practice – dissemination of timely evidence based care

Division of Population Health Sciences The TRANSFoRm Project SAFER CLINICAL PRACTICE MORE RESEARCH EVIDENCE TRANSFoRm -INTEGRATION -INTEROPERABILITY -SERVICES KNOWLEDGE TRANSLATION EPIDEMIOLOGICAL STUDIES AND RCTS

Division of Population Health Sciences The TRANSFoRm Project 3 sets of clinical use cases defined for implementing and validating TRANSFoRm approach: –Research use cases – electronic research trials Genotype/Phenotype study in type II diabetes Randomised control trial (RCT) in gastro-oesophageal reflux disease (GORD) –Patient safety use cases – clinical decision support Chest pain, abdominal pain, dyspnoea (shortness of breath)

Division of Population Health Sciences The TRANSFoRm Project PART A – RCSI work

Division of Population Health Sciences The TRANSFoRm Project – My Background Worked as a software developer for many years! Completed Masters in Health Informatics with TCD in 2010 Joined HRB Centre for Primary Care Research in 2010 to work on the TRANSFoRm project Work package lead for WP4 – decision rules and evidence

Division of Population Health Sciences User requirements Development and Evaluation WP7 SYSTEMS AND SERVICES FOR DATA INTEGRATION WP 1 RESEARCH USE CASES WP 2 PATIENT SAFETY USE CASE ICT WP8 DEMONSTRATION INDUSTRY CONTRACT RESEARCH ORG ACADEMIA WP9 DISSEMINATION WEBSITE PUBLICATION WORKSHOPS PROTOTYPES COLLABORATION INFRASTRUCTURE TECHNOLOGY PLATFORMS WP10 MANAGEMENT

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 Decision Support 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 An Example – CRB 65 Rule – Pneumonia Mortality 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 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 GP case 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

RCSI work to date – key elements

RCSI work to date – clinical evidence models

RCSI work to date – ontology development

Division of Population Health Sciences The TRANSFoRm Project PART B –Core services

Division of Population Health Sciences Common core services for TRANSFoRm Confidentiality and privacy framework Vocabulary services – how to manage different vocabulary schemes – e.g. SNOMED, ICPC2 Provenance service – not just the “who” and “when” but the “why” – more than audit Security model – Stephen Farrell (TCD)

Division of Population Health Sciences Vocabulary services umls SNOMED- CT ReadICPC2ICD9ICD10 vocabulary service

Division of Population Health Sciences Confidentiality and Privacy Confidentiality and privacy are huge challenges for TRANSFoRm Work done by Professor Christian Ohmann (WP3) and his group from the University of Dusseldorf to: review the regulatory context for electronic clinical research systems review the confidentiality and privacy context around EU legislation as applicable to TRANSFoRm describe formal concepts abstracted from these contexts that can be used to describe a privacy and confidentiality framework suitable for TRANSFoRm

Division of Population Health Sciences Regulatory context Background: currently no recognized (industry) standard for specific CDMS (clinical trial data management system) requirements available lack of European guidance in the field of software and electronic records use of electronic source data is becoming increasingly prevalent, current regulatory framework still focused on paper documents

Division of Population Health Sciences Confidentiality and data privacy - EU legislative context Background: divergent implementation of EU Directive 95/46/EC in the member states access to health data in the EU hampered by fragmented legal framework, inconsistency in interpretation of regulations and variable guidance existing frameworks largely limited in scope, target and application areas different need for TRANSFoRm

Division of Population Health Sciences Confidentiality and data privacy framework – development methodology Methods: exploration of legal requirements and access policies extraction of privacy principles (non-formal) definition of core formal concepts - zones/subzones, privacy filters and data linkers, actors and roles development of a formal description of the framework based on structural analysis/data flow diagrams application of the formal description to research scenarios and TRANSFoRm clinical use cases

Division of Population Health Sciences Confidentiality and data privacy framework – key concepts Zones  represent 3 clinical areas of low, medium and high identifiability of patient data (risk-gradient)  similar with respect to clinical purpose, policies and regulations Subzones  comparable and can be used for the same or very similar purpose and with similar applicable legislative regulations Data linkers  allowing connection within or between zones/subzones  manages mapping data between different sources  performed by one-way coding or two-way coding Privacy filters  tools for anonymization, pseudonymization, coding, data aggregation using Privacy Enhancing Techniques (PET) Results: Formal description of the framework

Division of Population Health Sciences Confidentiality and data privacy framework Research zone Non-care zoneCare zone Subzone Research data directly identifiable data (e.g. EHR) pseudonymous data (e.g. cohort study, clinical trial DB, primary care DB) (coded) anonymous data (data needed for research project)

Division of Population Health Sciences Confidentiality and data privacy framework Data bases in the non-care zone (example Netherlands): health care insurers data base about medical consumption (directly identifiable by insurer) LINH (Netherlands Information Network of General Practice) (coded indirectly identifiable) National cancer registry (indirectly identifiable) death registry at the Statistic Netherlands (directly identifiable by Statistic Netherlands)

Confidentiality and data privacy framework Results: Notation for data transfer, functions and actions

Division of Population Health Sciences Confidentiality and data privacy framework - use case development Results: Subcases represented in the framework counts of patients with a defined pattern find patients for clinical research select patients for research question extract information of selected patients linkage of data

Division of Population Health Sciences Confidentiality and data privacy framework – use case example Results: Subcase 2 – Find patients for clinical research

Division of Population Health Sciences Confidentiality and data privacy framework Results: Subcase 2 – Find patients for clinical research (different options) 1. identification of trial patients by treatment physician within treatment context 2. identification of trial patients by extra staff acting for the treating physician 3. identification of trial patients in non-care databases (e.g. research database, register) 4. identification of trial patients in care or non-care database with the possibility to identify patients by the researcher

Division of Population Health Sciences Confidentiality and data privacy framework Results: Subcase 2.1 – Find patients for clinical research

Confidentiality and data privacy framework Results: Subcase 2 - Find patients for clinical research 1: by treating physician in care-zone 3: in non-care database

Confidentiality and data privacy framework Results: Subcase 5 – Linkage of databases Linkage of database in the care zone with database in the non-care zone. Researcher is provided with pseudonymized (or coded) anonymous data or fully anonymized data according to research question and authorisation

Confidentiality and data privacy framework Research scenario for use case GORD association between PPI consuming and the incidence of adenocarcinoma Two databases in the same subzone of the non-care zone (e.g. cancer registry, civic registry) are linked by Trusted Third Party (TTP). This data base linked by new TTP with primary health care research database after passing a privacy filter

Division of Population Health Sciences To summarise Ambitious project with substantial Irish involvement Privacy Framework provides conceptual language to define and discuss the issues specific to e-research using consistent terms Conceptualisation of TRANSFoRm now moving into development and implementation Technical challenges and solutions will now be the focus Confidentiality and Privacy Framework was well received by EU review panel and encouraged dissemination of its contents

Division of Population Health Sciences Thank You Discuss!