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Randomized Controlled Trials a nd Applied Informatics at Duke

Randomized Controlled Trials a nd Applied Informatics at Duke. Martha B. Adams, MD, MA May 2, 2011. RCTs and Informatics. Randomized Controlled Trials continue to be the backbone of clinical trials.

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Randomized Controlled Trials a nd Applied Informatics at Duke

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  1. Randomized Controlled Trials and Applied Informatics at Duke Martha B. Adams, MD, MA May 2, 2011

  2. RCTs and Informatics • Randomized Controlled Trials continue to be the backbone of clinical trials. • Informatics provides the integration of the people, information, and knowledge. Applied Informatics especially relates to the use of IT in clinical effectiveness.

  3. Smarter Healthcare Research at Duke

  4. Critical Care • Over 200,000 cases of Acute Lung Injury (ALI) occur in the U.S. each year, mortality ARDS 30-40% • Will it help to identify patients early? • A Lung Injury Prediction Score (LIPS) has been validated in a multicenter cohort study* • The goal is to ameliorate secondary injury and to facilitate enrollment into future ALI prevention trials *Gajic O et al. Early Identification of Patients at Risk for Acute Lung Injury. Am J RespCrit Care Med 2011;183:462-470.

  5. Critical Care • Background: The work resulted from the USCIITG-LIPS,(US Critical Illness and Injury Trials Group, the Lung Injury Prevention Study) demonstrating the multiple hit model of ALI, which led to the validation of CLIP, a checklist for Lung Injury Prevention (LIP).Multiple hit: aspiration, high tidal volume, sepsis, wrong antibiotics, high FiO2Mechanism: membrane injury and inflammationOnset of ALI: median 2 days

  6. Critical Care • Based on these epidemiologic results, learned that a Lung Injury Prevention Score (LIPS): >4 results in 10% higher risk of ARDS >20% results in 20% higher risk of ARDS • Proposing a clinical trial using an iPad app to score illness severity and randomize to Aspirin vsplacebo • Applied for UO1 grant to enroll across 14 institutions; multidisciplinary with ED, Anesthesia and Pulmonary Critical Care Principle Investigator: R Bartz, MD

  7. Critical Care Users see the Lung Injury Prevention Score and participants are randomized to Aspirin or placebo Principle Investigator: R Bartz, MD

  8. DISCERN – automate eligibility screening • We have been using DEDUCE which is a retrospective look into the DSR, now we are also using DISCERN to notify of potential enrollees for trials. • We did this by tapping into the messaging system, for example ADT (admission, discharge and transfer) • Metrics of success: volume of users, who’s using it and what for; is the use for new grants? How do we compare to other schools? The “Duke Integrated Subject Cohort Enrollment Research Network” Lead developer: Jeffrey Ferranti, MD

  9. The NCRI – scaling collaboration • National Cardiovascular Research Infrastructure • Recognizing clinical research in crisis • Clinical guidelines founded upon “expert consensus” • Disjoint operations, start and stop, start and stop • Only 10% of sites enroll 40% of patients • Fragmented data collection Funding support: ARRA, the GO initiative, NHLBI Award, $2.6M over 2 years. Principle Investigator is Robert A. Harrington, MD, Duke Cardiovascular Research Institute

  10. The NCRI – scaling collaboration • Mission to integrate existing resources to efficiently execute large projects • Site recruitment and education (CTNBP) • Randomization (DCRI) • Data collection (NCDR) • Data standards (CDISC, HL7) • Guideline development (ACC) • Proof of concept clinical trial – TREATT • TransRAdial Education, Training and Therapy

  11. The NCRI – scaling collaboration ncrinetwork.org

  12. Towards Smarter Healthcare

  13. Towards Smarter Healthcare

  14. Telegenetics • The Problem • Hereditary cancer risk effects approximately 25% of cancer patients. Genetic counseling is a standard of care particularly because it impacts Rx decisions. • N.C. has 15 counselors and they are clustered in tertiary care centers • Access is a health disparity issue • No studies have assessed cost effectiveness, patient satisfaction with validated surveys, in a RCT design Funded by the Susan G. Komen Foundation

  15. Telegenetics • The Method • Randomized, sample size 139 • Surveys to assess the visit and the counselor • Cost measures (travel time, mileage, counselor, labor, equipment) • Assessed other variables to understand the two groups, e.g., TM group older, less well educated, less likely to be employed, lower income, and less computer comfort

  16. Telegenetics

  17. Telegenetics • Included college student poster at NCCU Science DayFreeman Booker with Dean for Science and Technology

  18. Telegenetics – the results Conclusions Telemedicine costs less than half of in-person CGC Satisfaction is equivalent, and high, in both groups Next steps to test viability without research support Datta S, Buchanan A, Hollowell G, Beresford H,Marcom P, Adams M. Telemedicine vs in-person cancer genetic counseling: measuring satisfaction and conducting economic analysis. Accepted for publication: Comparative Effectiveness Research.

  19. Behavioral Health Interventions • Chronic illnesses contribute to the majority of U.S. health expenditures • There’s proven value in tailoring interventions to patients’ needs • General Medicine HSR&D research led by Hayden Bosworth, PhD has demonstrated success with multiple health behaviors combined with intensification of pharmacotherapy and including the provider

  20. Risk Reduction Using Telemedicine • Background • Risk factor modification improves patient outcomes yet often is not achieved because of poor prioritization and failure to change behaviors • Hypothesis • A telemedicine intervention with tailored patient education could improve risk factors • Method • To enroll 450 patients post-MI with hypertension • Measure BP, LDL cholesterol, A1c, weight, BP, adherance at 12 months

  21. Risk Reduction Using Telemedicine • A 3-arm, randomized trial with eligible patients to: • Usual care • Home BP monitor + nurse tailored education by phoneand enrolled in HealthVault • Home BP monitor + tailored web based education and enrolled in HealthVault • Sponsored by the American Heart Association • Besides HealthVault, includes the Heart360 platform • A disease monitoring tool, not a medical record

  22. Risk Reduction Using Telemedicine • Nurse intervention Shah B, Adams M, Peterson E, Powers B, Oddone E, Royal K, McCant F, Grambow S, Linquist J, Bosworth H. Secondary Prevention Risk Interventions Via Telemedicine and Tailored Patient Education (SPRITE): A Randomized Trial to Improve Postmyocardial Infarction Management. Circulation: Cardiovascular Quality and Outcomes 2011; 4: 235-242.

  23. Patients Reporting Outcomes (PRO) • A quality healthcare metric • Patients reporting symptoms, performance status, satisfaction with care, and quality of life (QOL) • e/Tablets pre-programmed with the PACE system Abernethy AP, Ahmad A, Zafar Y, Wheeler JL, Reese JB, Lyerly K. Electronic Patient-Reported Data Capture as a Foundation of Rapid Learniing Cancer Care. Medical Care 2010;48:S32-S38.

  24. Used by permission from AP Abernethy, MD

  25. e/Tablet Results • Easy to use, navigate, and read • Patients satisfied with e/Tablets, and would recommend them to other patients. • Help patients recall symptoms to report. • ePRO system can be used to collect research-quality data using common, validated instruments in an academic oncology clinic. Used by permission from AP Abernethy, MD

  26. Roll-out of the eTablet system and Patient Care Monitor (PCM) tool into usual practice in the Duke oncology clinics starting with the GU Oncology clinic in 8/09 with serial roll out to Thoracic Oncology in 11/09, Breast Oncology in 5/10, and GI Oncology sequentially. Other clinics will follow. Used by permission from AP Abernethy, MD

  27. We are currently averaging 1300-1400 PCM surveys being completed per month, with approximately 300-350 new patients using the system per month. Used by permission from AP Abernethy, MD

  28. Used by permission from AP Abernethy, MD

  29. Oncology Data Mart Common across all disease groups (80%) Disease Specific (20%) Data transferred and feeding into a variety of databases and reports Basic & Population Research Tumor Registry NCCN Databases Clinical Trials Clinical Care Quality Used by permission from AP Abernethy, MD

  30. Did you see this in the WSJ? • “ALS Study Shows Social Media’s Value as Research Tool” • An example of patient reported outcomes with patients themselves taking charge! Findings released online April 24, 2011 in Nature Biotechnology • Social-networks do have potential in clinical research • Speedy to launch, costs avoided, recruitment easy, and results transparent in open access publishing

  31. Future challenges and plans for us in CRI • Regulatory • Budget planning to include informatics • Data management (already NSF requirement) • More cultural and behavioral intervention studies • Expansion of the global outreach • Increase in the demand for informatics experts

  32. Thank you! • Appreciated contributions from Duke colleagues: • Raquel Bartz, MD, Anesthesiology and Critical Care • Robert Harrington, MD and David Kong, MDDuke Cardiovascular Research Institute • Amy Abernethy, MD, Medical Oncology • To find me: • @CallingFC on Twitter • @mbadams also on Twitter • www.dukehealth.org • martha.adams@duke.edu

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