mHealth Approaches to Engaging the Patient in Comparative Effectiveness Research Zubin J. Eapen, MD, MHS Faculty Director, Duke Clinical Research Institute Innovation Center

Care delivery Clinical Research

Data collected by providers in hospitals

Problem: Data collection platforms are siloed according to users and venues of care Provider Patient Hospital Home

Data collected by patients at home

Integrating data across users and venues of care

Admit for Heart Failure/Afib This is a depiction of the patient’s weight and BP over 90 days. Here, the patient had a noticeable rise of about 6-8 lbs over the course of January before being admitted for heart failure and afib. I thought this was interesting, as perhaps there could have been a preventive intervention. His BP stayed under good control throughout the study period.

Care delivery Clinical Research

ResearchKit capabilities Open framework for easy collection of data needed for medical research Participants can transmit valuable data to clinical researchers almost instantly through their personal digital devices

Revolutionary tool for pragmatic trials ResearchKit creates a new channel for study discovery and participant recruitment Local, national and global recruitment Disrupt the way large cohort studies are executed Cheaper to send every study participant an iOS device than the current standard surveys Integration with wearables to passively collect biometrics Larger sample size expands the diversity of participants in trials?

ResearchKit apps at launch The University of Rochester and Sage Bionetworks “Parkinson mPower” allows patients to track real-time changes in balance, gait, voice tremors and other symptoms. Mount Sinai’s Icahn School of Medicine “Asthma Health” encourages patient education, self-monitoring and behavioral changes, ultimately leading to better asthma symptom control, improved quality of life and less need for healthcare services. Massachusetts General Hospital GlucoSuccess helps to manage diabetes symptoms and study how personal habits affect glucose levels. Dana-Farber Cancer Institute, Penn Medicine, and UCLA’s Jonsson Comprehensive Cancer Center, Sage Bionetworks Program to track the daily impact of breast cancer. Stanford University MyHeart Counts, monitors daily activities, tracks behavior through surveys, and correlates that data with reported cardiovascular health

1st ResearchKit app to get international release 41,000 downloads domestically Now available to iOS users in Hong Kong and UK

Data collection for clinical trials

Study modules Consent Surveys Active Tasks

Informed consent Flexible framework Waivers & institution-specific customization Comprehension tests Electronic signature

Surveys Pre-built interface Flexible question and answer types Localization and language support

Active Tasks Active tasks invite users to perform activities under partially controlled conditions while iPhone sensors are used to collect data e.g. active task for analyzing gait and balance might asks the user to walk a short distance, while collecting accelerometer sample data on iPhone. Data collection capabilities of the HealthKit and CoreMotion APIs on iOS

Active Tasks

High frequency data acquisition

Pros Cons Scale Open source PRO collection Novel measures Missingness Selection bias Reporting bias Data normalization

ResearchKit Best Practices: Consent Consider including a cryptographic signature to protect the consent process. Consider the level of identity verification required to obtain a valid consent. Consider whether you can provide for prospective participants to ask additional questions once they have reviewed your consent material. If your study may recruit minors as participants, you must ensure that you are obtaining consent from the parent or guardian rather than from the minor. https://github.com/ResearchKit/ResearchKit/wiki/best-practices

ResearchKit Framework Best Practices: Participant Control Participants should have granular control over what data they choose to share with the study. If you intend to share the collected data with other researchers, participants must be able to control whether their data is included in this. Participants should be able to leave a research study at any time if they so choose. https://github.com/ResearchKit/ResearchKit/wiki/best-practices

ResearchKit Framework Best Practices: Privacy Participants should be told up front exactly what enrolling in the study would mean for them, what data they are contributing, and who may have access to the data. Having an explicit privacy policy is highly recommended for every app that collects personal data. It is also required for ResearchKit apps posted to the iOS App Store. Use touch ID or PIN access to control access to your app, if your app records or displays personal data. Do not use iCloud to store health information. https://github.com/ResearchKit/ResearchKit/wiki/best-practices

ResearchKit Framework Best Practices: Security Use the highest level of file protection possible for the given use case. Usually this should be NSFileProtectionComplete or NSFileProtectionCompleteUnlessOpen. This way, files stored by your app are encrypted automatically whenever the device is locked. Do not keep personal data for longer than necessary for your app to function. When transmitting data via networks that terminate SSL early, or when contemplating a store and forward mechanism of any kind for your research data, consider an extra cryptographic wrapper for the data to protect it end to end. For example, a Cryptographic Message Syntax (CMS) envelope, the same technology used in S/MIME, can be used to encrypt data before transmission. https://github.com/ResearchKit/ResearchKit/wiki/best-practices

ResearchKit Framework Best Practices: Software Development Give your ResearchKit tasks context by using instruction steps at the beginning of your task. This also allows for clean presentation of any requests for data access. If your tasks and questions are maintained in a database, have unique keys for them and propagate these through ResearchKit model objects like ORKStep and ORKOrderedTask and into ResearchKit results. The ResearchKit framework does not include a data management solution. The framework can be used with a data management solution of your choice. https://github.com/ResearchKit/ResearchKit/wiki/best-practices

The Backend Code: AppCore AppCore is a layer built on top of ResearchKit which forms the core of the five initial ResearchKit apps It includes some of the key features of those initial ResearchKit apps, including: Dashboard with progress graphs Data storage back end JSON serialization and deserialization Integration with Sage Bionetworks' Bridge service Over time, some of the features in AppCore may be migrated into ResearchKit. https://github.com/researchkit/AppCore

Duke ResearchKit 2015 roadmap Duke ResearchKit infrastructure deployed by Summer 2015 Duke University first ResearchKit app launched in Summer 2015 Prepare Duke guidelines for ResearchKit apps by Summer 2015 Scale backend infrastructure to support large number of ResearchKit apps (2015) Android version of ResearchKit (2015)