EHR4CR ENABLING PROACTIVE RESEARCH

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1 EHR4CR ENABLING PROACTIVE RESEARCH Neelam Patel Neelam Consulting Electronic Health Records for Clinical Research 76

2 Why change how I currently operate? To more visible to the clinical trial community (and, in the future, patients) To accelerate patient recruitment processes To streamline processes, stop redundant data entry To derive greater value from EHR data A manual process misses 27% of suitable candidates compared with electronic searching 1 50% of today s clinical trials fail to achieve the target recruitment rate 2 The percentage of studies that complete enrolment on time: 18% in Europe, 7% in the US 3 Investigational sites estimate that over 70% of data are duplicated between EHR and clinical trial systems 4 1. CSC Use of Real Life Data for Clinical Research and Personalised Medicine Webinar; November Tufts State of the Clinical Trials Industry: A Sourcebook of Charts and Statistics, Center Watch, EDC Site Survey: Investigational Site Perspectives on Clinical Trial Information Systems, eclinical Forum Available at: (accessed December 1, 2011) 5. Beasley, Recruiting 2008 Each day a drug is delayed from market, sponsors lose up to $8m 5 Electronic Health Records for Clinical Research 77

3 The burden of running a clinical trial has increased Protocol design Trials have become increasingly complicated More endpoints to observe as science has expanded knowledge about how to measure safety and effectiveness Patient recruitment Larger on average and require more participants. Recruitment has become more difficult and expensive Data capture and exchange More data collected, more routine more work THE GROWING COMPLEXITY OF CLINICAL TRIALS Unique Procedures per Trial (median) Total Procedures per Trial (median) Clinical trial Staff Work Burden (measures in work-effort units) % Change % % % Length of Clinical Trial (days) % Clinical Trial Participant Enrolment Rate Clinical Trial Participant Retention Rate 75% 59% -21% 69% 48% -30% Source: PhRMA Report 2010 Electronic Health Records for Clinical Research 78

4 The clinical trial journey today is fragmented with many hurdles TRIAL DESIGN Protocol design Early feasibility Site input Country and early site selection Key data for Pharma: Previous trial performance in this area Available patients with inclusion/exclusion criteria listed Ability to access patients through referrals or other means Evidence of good quality and operations Data for Hospitals: Number of Eligible and accessible patients Knowledge of previous trial performance FEASIBILITY/SITE SELECTION PATIENT RECRUITMENT Patient recruitment / screening Consent Randomisation TRIAL EXECUTION First patient, first visit Visits/follow-up Safety Reporting Data management Last patient enter treatment End of study REPORTING Data lock End of study report Study publication Study outcome Key data for Pharma: Country standard of care for disease area Ethics and local regulatory knowledge Previous trial performance in this area Operational/scientific expertise if area is new Detailed feasibility Site selection Contracting Site training Key data for Pharma: Screening/recruitment rate Numbers of screening dropouts Numbers of patients randomised Data for Hospitals: Upcoming studies that may fit Hospital patient population and expertise Data for Hospitals: Identification of eligible patients coming through clinic & elsewhere Numbers that have consented & randomised Electronic Health Records for Clinical Research 79

5 Detailed Feasibility hospital perspective If your hospital is approached to take part in a clinical trial An investigator completes questionnaire or meets team to assess interest and potential pool of eligible patients More robust patient numbers, recruitment plan and operational capability then assessed Consults clinical database Reviews spreadsheet of patients Consults research coordinator to look through manual records of last clinic Calls to referral centres/patient groups to identify further patients and agree mechanism of referral? Estimates based on patient knowledge Based on these estimates, this trial has a 50% chance of achieving achieving the target recruitment rate Patient number agreed Payment agreed Contract drawn up Electronic Health Records for Clinical Research 80

6 Identifying an eligible patient an example Hospital database - EHR Clinical researcher Multidisciplinary team sees Patient record patient & classifies tumour CONSENT FORM PATIENT FILES Clinician may note down this patient as one that could be suitable in study they recall Written and filed Clinician may remember to alert investigator or research nurse about a potential patient that was reviewed at this clinic Manually identifies patients against inclusion/exclusion criteria Investigator validates information and consents patient during first visit Electronic Health Records for Clinical Research 81

7 Access to health records speeds up protocol design and patient recruitment PATIENTS PROTECTED BY LEGAL AND PRIVACY PROTECTION STANDARDS & REGULATIONS EHR becomes patient data repository to streamline clinical trials Evaluate patient populations in study set up Query EHR database to establish number of potential candidates Improve and validate study designs Accelerate patient identification and recruitment Query EHR database to select sites and identify and recruit patients Implement study screening parameters into patient registration and scheduling Researchers obtain key health information before patients arrive for a screening visit (after consent) Electronic Health Records for Clinical Research 82

8 A streamlined process for protocol feasibility De-identified data for Clinical Research Disease & diagnosis Demographics Treatment regime Co-morbidities Clinician interrogates EHR data (EHR4CR platform) to accurately assess hospital patient population Accurate patient numbers Clinician uses information to proactively approach clinical trial sponsors Sponsor uses inclusion/exclusion criteria to search EHR4CR database and identify eligible patient population Clinician uses this information to better design study protocols for academic research Payments and contracts based on realistic patient targets Higher probability of reaching recruitment target Revenue stream more predictable 1. Drug Information Journal, Vol 45, Industry Standard Research, 2010 Electronic Health Records for Clinical Research 83

9 could result in a much simpler clinical trial journey TRIAL EXECUTION TRIAL DESIGN Feasibility Protocol design Site input Country and early site selection FEASIBILITY/ SITE SELECTION Site selection Contracting Site training PATIENT RECRUITMENT Patient recruitment/ screening Consent Randomisation First patient, first visit Visits/follow-up Safety Reporting Data management Last patient enter treatment End of study REPORTING Data lock End of study report Study publication Study outcome Key data for Pharma & Hospitals: Access to real eligible patient numbers Country standard of care for disease area Ethics and local regulatory knowledge Previous trial performance in this area Operational/scientific expertise if area is new Upcoming studies that may fit patient population Ability to access wider patient numbers through EHR Move from reactive to proactive partnership Key data for Pharma: Screening/recruitment rate Numbers of screening dropouts Numbers of patients randomised Data for Hospitals: Identification of eligible patients coming through clinic & elsewhere Numbers that have consented & randomised Contracting and Payment accurate and to plan Electronic Health Records for Clinical Research 84

10 Proactive partnership in conducting clinical research With research and healthcare systems siting on the same spine and conforming to the same data exchange standards, the re-use of EHR information is possible on a large and scalable way across: organisations regions and countries Clinical researcher De-identified research data Physician/ Investigator Patient health records Electronic Health Records for Clinical Research 85

11 Creating value for hospitals Better patient care Improved route to inclusion in clinical trials. Enhances treatment options, giving patients access to trial drugs and care pathways with no cost to the Trust Improved clinical research Improved efficiencies and interconnectivity with other hospitals facilitates, streamlines and enriches clinical research Enhanced reputation Greater visibility of hospital/clinicians in scientific community. Improved ability to participate in/conduct clinical trials Income stream Better placed to generate income from clinical research. At a time of squeezed budgets, income from research can help drive innovation and efficiency with better outcomes for patients Better quality EHR data Improved monitoring, performance benchmarking, reporting and management (e.g. reimbursement coding) Drives optimisation of patient care and improved efficiencies Electronic Health Records for Clinical Research 86