New Models of Evidence Generation and Cancer Care Delivery: Distance Medicine Technologies

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1 New Models of Evidence Generation and Cancer Care Delivery: Distance Medicine Technologies Susan K. Peterson, PhD, MPH National Cancer Policy Summit Institute of Medicine November 4, 2013

2 How distance medicine technology can collect evidence to inform cancer care Effectively engage patients outside of traditional clinic setting Increase efficiency in clinical trials New methods, types of data collection Monitor treatment adherence, symptoms, side effects, toxicities Patient reported outcomes (PROs), health states Generate data not typically collected and identify trends relevant to prevention and survivorship Ex: Tobacco use, physical activity, diet, gene-environment interactions Inform CER, rapid learning systems

3 Data Supporting Distance Medicine Technology in Cancer Care Psychological distress, adverse events, side effects may affect treatment adherence SupportScreen identification of patient distress via automated system Autonotification of appropriate providers when PRO reach threshold levels Severe pain MD Nausea Nurse Distress Psychologist Loscalzo, 2010

4 Data Supporting Distance Medicine Technology in Cancer Care STAR - online platform for PROs based on CTCAE toxicity monitoring criteria Well-accepted by lung cancer patients undergoing therapy and providers, incorporated into clinic discussions Added value of patient data for clinic visit Altered patient management PROs added complementary data on daily health status during therapy Basch, 2007, 2007

5 Data Supporting Distance Medicine Technology in Cancer Care CYCORE: Home-based sensor technology combined with a novel cyber-infrastructure for the early identification of dehydration risk in patients undergoing radiation treatment for head and neck cancers. 60% of patients had at least one dehydration risk-related event that was clinically actionable. PROs correlated: nausea, vomiting, swallowing difficulty Patients rated their ease, self-efficacy, and satisfaction with CYCORE as extremely favorable; minimal concerns regarding data privacy issues. Clinicians indicated a high degree of satisfaction with using CYCORE to monitor their patients remotely during radiation therapy. Peterson, et al., JNCI Monographs, in press

6 CYCORE Framework Home Health Hub Home Health Hub Patient self-reported outcomes (EMA) Patient Symptoms Activity Diet Data Integration Interface Electronic Medical Records Research Databases Data Integration Interface Researchers Clinicians Define Algorithms Run Comparative Studies Perform Observations CYCORE Data Mining Analytic Methods Infrastructure Management Policies Patient-centered outcomes Quality of life Clinical decision-making

7 Data Supporting Distance Medicine Technology in Cancer Care Post-surgical lung cancer patients randomized to remote symptom monitoring via interactive voice response (IVR) + clinician notification for moderate/severe symptoms VS usual care IVR group experienced decrease + more rapid decline in symptom threshold events Clinicians responded to 84% of alerts Patients and clinicians reported equally high satisfaction IVR and post-op symptom control Cleeland, JCO, 2013

8 Challenges and Opportunities for Patientfocused Distance Medicine Technologies in Cancer IT infrastructure needed to capture data throughout cancer continuum: Support longitudinal, continuous data collection Computer adaptive technology for patient and provider reporting and feedback Proprietary applications do not lend well to wide applicability, use Private-academic partnerships Data privacy, HIPAA

9 Challenges and Opportunities for Patientfocused Distance Medicine Technologies in Cancer Barriers to acceptability Limited evidence on clinical utility of measures and data Limited guidance on incorporating and using measures in clinical workflow and decisionmaking Need for standardized IT-enabled applications Individual level variables: Culture, language, literacy, technology preferences, and access

10 Challenges and Opportunities for Patientfocused Distance Medicine Technologies in Cancer Sustainability Funding, reimbursement, incentives Benefits and outcomes to be determined and balanced What role do distance medicine data have in EHR, and how to integrate those data into EHR

11 Challenges and Opportunities for Patientfocused Distance Medicine Technologies in Cancer Need to expand evidence base for patient-centered IT applications Under what circumstances are they most appropriate, for which patients and conditions? Evaluate use in diverse care settings Opportunities and constraints in accelerating use and implementation Funding for basic and applied research

12 Challenges and Opportunities for Patientfocused Distance Medicine Technologies in Cancer Need for a systems-based approach that enables personalized decision support Assess and interpret data on health status, behavioral and psychosocial outcomes Context-driven, meaningful interpretation of data, with alert and feedback prioritization Integration and analysis of data from multiple sources (patients, EHR)

13 Policy Issues New Models of Evidence Generation and Cancer Care Delivery: Distance-Medicine Technology Facilitate the utilization and evaluation of distance medicine and ehealth technologies in oncology research and care Emphasize systems that: 1) enable optimal patient self-management; 2) readily provide clinicians with actionable data that can help inform patient care; and, 3) identify research opportunities through emerging trends over time Expand the evidence base regarding the impact of these technologies for improving cancer care, clinical trials, patient engagement and quality of life Enable the adoption of consumer-engaged systems that facilitate the intake and sharing of information, and also promote changes in patients health behaviors Capitalize on synergies between patients, health care providers and technologies to foster information exchange, facilitate decision-making, and enable health behavior change Improve health care providers and patients access to distancemedicine and ehealth technologies Consider needs of specific populations (e.g., health disparities, connectivity, health literacy, cost) Address barriers to access, such as those related to technology (e.g., data interoperability, large-scale data aggregation capabilities) and cost (e.g., reimbursement, added value and cost-effectiveness)