Research, the Internet and Innovation: Ready or Not… AcademyHealth Summit on the Future of HSR Data and Methods June 1, 2009 Carol C. Diamond MD, MPH Managing.

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Presentation transcript:

Research, the Internet and Innovation: Ready or Not… AcademyHealth Summit on the Future of HSR Data and Methods June 1, 2009 Carol C. Diamond MD, MPH Managing Director, Markle Foundation Chair, Markle Connecting for Health

Four Points 1.This is a moment of both great urgency and tremendous opportunity for HSR 2.A learning health care system: better decisions by many (not better data for the few) 3.The future will be dependent on innovations that are distributed, networked and trusted 4.The internet is creating possibilities that can re- set relationships between researchers, providers, care givers and patients

1. Urgency and Opportunity Will we seize the moment?

Urgency! Rising health care costs represent the central fiscal challenge facing the country Peter Orszag, Director, CBO

Opportunity! -Explosion of data and data sources -New public sector investments -Availability of new tools, technology and relationships

2. The Ultimate Goal Better decisions for many; not more data for the few

IOM has created the vision a Learning Healthcare System Transformed by the availability and use of the best evidence for the collaborative health care choices of patient and provider; The process of discovery as a natural outgrowth of patient care; to ensure innovation, quality, safety, and value in health care.

IOM Roundtable on Evidence Based Medicine has clearly articulated the challenge… Health care under-performs on many dimensions –high cost –poor performance, –inconsistent delivery of evidence based –large variations in care delivered unrelated to outcomes and unexplained by burden of illness, etc. –large gaps in evidence –long time lags research –a chasm in applying results to clinical care and – a rate of innovation in devices, biologics and procedures that outpaces research on comparative effectiveness generally… –and on what works best for a particular individual (personalized medicine)

The ultimate goal is the use of information to improve decision-making Too often we let discussions about IT, data, standards, methods obscure our focus on the goal. Health services research is a tool Its ability to have impact on costs and outcomes depends on how it is used. But this goal remains elusiveso much of what we already know is not applied in a consistent manner

Real Transformation: Better decisions by many, not more data for the few It is tempting to focus our efforts on amassing data for better research But the thornier and more important question is how to truly improve decision-making – and what role the use of information plays in this process: Whose actions are you trying to impact? Real transformation occurs when very clinical encounter is an opportunity to provide the right care to the right patient A learning healthcare system is transformed by the availability and use of the best evidence for the collaborative health care choices of patient and provider

The Challenge Research is inherently challenging today because there is no controlled environment for assessing therapeutic options and the heterogeneity of patient characteristics (never, always and truth) This almost by definition requires thinking in terms of connectivity and networks rather than databases

3. Distributed, Networked and Trusted A paradigm shift

Americans recognize the upside… and the downside… Three-quarters of Americans are willing to share their personal information to help public officials look for disease outbreaks and research ways to improve the quality of health care if they have safeguards to protect their identity (Markle Survey 2006). Significant concern about privacy and security –85% say protecting confidentiality absolutely essential –FACCT survey: 91% very concerned (barrier for 1/4) –Strong desire to control who sees health information Fear of misuses –52% believe employer uses medical info to affect personnel or insurance benefits (CHCF Survey 2005) –85% believe if genetic test results known to insurers, would refuse policies or charge more (Genetics and Public Policy Center Survey 2007)

The Common Framework Core Privacy Principles Sound Network Design Accountability and Oversight The Common Framework Core Privacy Principles Sound Network Design Accountability and Oversight Consensus Policy Practices Consensus Technology Practices Common Framework for Networked Personal Health Information Markle Connecting for Health Common Framework for Health Information Exchange

Architecture for Privacy in a Networked Health Information Environment 1.Openness and Transparency 2.Purpose Specification and Minimization 3.Collection Limitation 4.Use Limitation 5.Individual Participation and Control 6.Data Integrity and Quality 7.Security Safeguards and Controls 8.Accountability and Oversight 9.Remedies

Research: The Way We Do it Today Most of the effort in trying to collect, clean and then silo data from a decentralized and fragmented system. Places a huge burden on data providers to submit the (same) information repeatedly to different repositories Creates separate repositories for each specific purpose at great cost in money and time Poorly adaptable and therefore success is elusive Creates privacy and security vulnerabilities Lacks connectivity, feedback, and broad USE for better decision-making Does not include the consumer (and often not the provider) as a key and active participant

Kenneth Buetow, National Cancer Institute The current world of biomedicine is best characterized as information islands Information dissemination uses methods recognizable to Gutenberg Presentation to AHIC July 29, de5.html

Technology should enable researchers, practitioners, and public health officials to share data across networks, while protecting patient privacy. C Diamond, F Mostashari, C Shirky. Data Aggregation and Sharing for Population Health: Exploring a New Paradigm, Health Affairs 28(2): A New Paradigm for Data Aggregation and Sharing for Population Health

DiSTRIBuTE for Flu Surveillance Uses summarized counts of influenza-like-illness (ILI) syndrome reported by age group from existing syndromic surveillance systems. The data is visualized and used to provide public health practitioners with age-specific weekly trends in influenza morbidity. The DiSTRIBuTE approach changes the traditional surveillance paradigm from central data collection and analysis to one of distributed data collection and analysis with central monitoring of summary information. By limiting the data request to the information that is truly the minimum required (summarized counts), the system has retained the ability to demonstrate meaningful flu trending data quickly and cost effectively.

DiSTRIBuTE

The 21 st century Health care environment Increasingly distributed needs for sharing and accessing information about what works best Increasingly sophisticated nodes capable of analytics Seeing research as occurring in a connected environment, not a database Clinicians as researchers and researchers as clinicians Embracing consumers as key producers, users and potentially managers of clinical data and partners in the research process A networked and distributed approach to information sharing and evidence creation Tolerance for incremental progress

4. The Internet and Innovation Creating New Relationships and New Possibilities

A networked society has already begun to change traditional research paradigms…

The average individuals health-care record, including digital x-rays and scan information, contains as many bits of data as 12 million novels. Source: The Exploding Digital Universe, Wall Street Journal, May 18, 2009 The number of physicians turning to Wikipedia for medical information has doubled in the past year alone. Nearly 50% of US physicians going online for professional purposes are visiting Wikipedia for health and medical information, especially condition information. Source: Docs Look to Wikipedia for Condition Info: Manhattan Research, Medical Marketing & Media, April 21, 2009 Before the swine flu outbreak, a Centers for Disease Control and Prevention Twitter page launched in January and devoted to emergency preparedness had about 10,000 followers. By May 21, that number had jumped to more than 182,000. Source: Health Data Proves Contagious On Social Media, Dow Jones Newswire, May 27, % of Physicians in the US say the Internet is essential to their professional practice. Source: Manhattan Research, "Taking the Pulse," "Taking the Pulse Europe" and "Taking the Pulse Asia " Forty percent of online users connected with other individuals on the Internet or via a cell phone regarding health and wellness issues in the past year. Source: Do Online Users Create and Consumer Health Content Using One-to-One and Social Media?, iHealthbeat, Sept. 20, 2008

Innovation and the Internet Dramatic new models that: Embrace many distributed data sources and users Do not require the need to anticipate the question before data is collected Are not limited to geographic boundaries Real-time and real-world Do not begin by collecting personally identifiable data to add value Are based on trust and value to the end users

INDIVIDUALS New models are changing the way people think about research

the first real-time, real-world, open and non-blinded, patient-driven trial.

We believe that the Internet can democratize patient data and accelerate research like never before PatientsLikeMe was built to… accelerate the transfer of knowledge about what works and what does not. Today, PatientsLikeMe has data on the progression and history of more than 1600 ALS patients - twice the number in the largest ALS trial in history. Even before the trial results were published, 50 patients worldwide who had elected to start taking lithium, in collaboration with their doctors, have been tracking their progression and blood levels on PatientslikeMe. This is more than twice the number of patients participating in the trial itself! We have data on historical forced vital capacity, the ALS Functional Rating scale, and a full symptom battery for most of the patients who have started, as well as for all the other non-lithium users in our system.PatientsLikeMe (from

Users join 23andMe & add their genetic data to the community. People add information about their health through quick online surveys. Users can see how their data compares to others. The collective data offers a pool for ongoing research. 23andMe

DOCTORS New models are changing the way people think about research

A social network for physicians Physicians ask questions and challenge or corroborate each others opinions Physicians can apply the collective knowledge (responses to research questions) to help improve outcomes. sermo

PUBLIC HEALTH New models are changing the way people think about research

A unified and comprehensive view of the current global state of infectious diseases. Mashup of: news sources disease reporting tools official health organizations HealthMap [Global Disease Alert Map]

Increases access to high value, machine readable datasets from the Executive Branch of the Federal Government. Efforts growing to provide easy access and understanding for the public (e.g, Apps for America) from the raw data. data.gov

Tremendous opportunity to dramatically transform health services research if… We are clear about the ultimate goal Embrace innovation that may reset thinking about the required methods/ paradigm for health services research Demonstrate the power of networks and networked analysis for population health Foster trust among the public that both the goals of health services research are in the public interest, and there are privacy frameworks in place to help ensure their information is protected while shared in these research efforts