Posts Tagged ‘Health information technology’

Harnessing the Power of Health IT in a New Era of Translational Research

March 8, 2010

In the final years of the 20th century and the first decade of the 21st century, tremendous progress has been made toward bridging a recognized chasm between science and the real world, and specifically in medicine, between biomedical research and its application in healthcare.  Three identified “blocks” to translation have impeded the use of research findings to better the lot of our patients: T1, the translation of laboratory findings to clinical care, T2, the application of best evidence identified during T2 to everyday clinical care; and T3, wider generalization of research findings to improve the health of the community and, more broadly, the public.  The recent deluge of funding for comparative effectiveness research (CER) represents, in large part, an attempt to conquer T2 and T3.  T1, however, persists and presents a fundamental impediment to personalized medicine.

To overcome T1, and transfer T1 knowledge to T2, will require true integration of the clinical and research spheres – an integration that necessitates bidirectional information flow from the patient and physician in the clinic to the research scientist and back again, in an iterative cycle of hypothesis, question, answer, and testing of that answer in the real world setting.  To support this sort of information exchange, we will need: new coordinated health information technology (HIT) systems that span former “silos” in the biomedical community, and that can collect and manage large volumes of disparate and heterogeneous data; culture change that engages clinicians and researchers in a common mission of inquiry to improve care; communication channels that fuel hypothesis generation, and that support the translation of research findings into change in clinical practice, and; decision support mechanisms that help clinicians leverage the power of large-scale aggregated data to improve care for the individual patient.  In short, we need a new model of care, one that harnesses the potential of HIT and integrated clinical/research data to dismantle the T1 block. The purpose, fundamentally, of such a model will be to enable personalized medicine.

In advancing “rapid learning healthcare,” the Institute of Medicine has spearheaded the development of a new healthcare paradigm in which personalized medicine could become a reality.  Efforts are underway to develop this paradigm and its prerequisites.  As one such example, the Cancer Biomedical Informatics Grid (caBIG®) championed by the National Cancer Institute has tackled the development of an infrastructure promoting large-scale data interoperability spanning the data type boundaries from the basic sciences to clinical care and the patient report.  As we seek to match novel therapeutics and trials to patients, and to personalize care using individually relevant information, critical steps will be: (1) providing access to data, (2) generating data, and (3) making sense of the data.  Making sense of data needs to be facilitated at the levels of basic science (to guide translation of in silico research results into clinical practice change and further discovery), the population (to allow CER to guide health services decisions and policy), and the individual patient (to enable personalized medicine).  New data generated in any of these steps should be reinvested in the system to iteratively update the knowledge base.

The caBIG® experience has taught us that just having access to better HIT does not, in itself, advance personalized medicine.  Though a powerful tool, HIT alone is not enough to bulldoze the translation blocks.  Why?  Because healthcare is not a purely technical matter; rather, it is a human system, fundamentally dependent upon human understanding, acceptance, and behavior.  All of these must change in order to transform information flow through HIT, implement a new data-driven model of healthcare, and thus realize the vision of personalized medicine.  The individual stakeholders in medicine need to be aligned behind the new vision – through incentives to participation that speak to each one.  First, the new model needs to be structured, and to function, so that the HIT makes sense to real human beings using the system (clinicians, staff, patients, administrators, clinical researchers, basic scientists); HIT must represent “value added” to the existing system from the perspective of each stakeholder.  Second, interoperable data must be generated, so that the system has “grist for the mill” of inquiry; we have to start somewhere and someone needs to be encouraged to put their first big toe in the water — there is nothing like a “big story” to bring along the naysayers.  Third, to build confidence in the approach, we must make sure that privacy, confidentiality and the sanctity of personal health information are preserved. And fourth, novel ways to make sense of ever-growing databanks need to be developed; these methods may include new approaches for visualization, decision support systems, Bayesian and other branched analytic approaches, CER, and in silico research.  Current efforts focus on generating interoperable data (the middle step), but neglect to create systems that make sense of the data and promote its use, or that provide a structure and an engine to produce the data.

Finally, and, in my mind, most importantly, a critical next step is to define a reorganization of medicine at the point of care.  The new model must fully utilize available data and linked datasets, and must help clinicians understand the data and apply it in tailoring care to their individual patients.  If it makes sense to them, clinicians and patients will drive this.  In the background, interdigitated with the growing body of clinical experiences captured in linked clinical/research databases, will be the robust evidence base comprising published results of basic science, clinical research, and translational studies.  The resulting combination creates a system in which each patient’s care is guided by personal history and characteristics, the experiences of similar patients included in local and massive national longitudinal datasets, and the historical evidence base constituting an up-to-date state of the science.  Our challenge, today, is to develop this system beginning at the point of care, with the patient.

Transforming Research Beyond 2010 – The New Role for the Patient in Data Sharing and Research

January 25, 2010

As the 20th century came to a close, the first human genome sequence was being finalized. This was hailed as a landmark achievement in biology – a molecular moon landing. And much of its success was owed to a new approach to doing large-scale science. Called the “Bermuda Principles,” researchers switched from research silos and data hoarding to freely available and immediate publication of basic research across the scientific community. Perhaps we were a bit optimistic about how quickly we could translate knowledge from the human genome project into actual cures, but the project demonstrated the overwhelming value of data sharing and access.

This transformation for open access to research data is still occurring and is gaining momentum within the patient and advocacy communities.  Patient knowledge in this area is evidenced by the Congressional passage of the Genetic Information Non-Discrimination Act in 2008 and the recent introduction of the Federal Research Public Access Act. Both patient communities and policymakers are realizing the value of molecular research and understand that the value multiplies when shared among the medical research community, provided patient privacy and security protections are in place.

In the upcoming years, the role of the patient in research will continue to expand and be critical to realizing the promise of personalized medicine.  The Obama Administration has set a goal to have an electronic medical record for every American by 2014.  The HITECH Act, part of the Recovery Act, which will help pay for adoption of electronic medical records, also ensures that the patient has control of his or her medical data and where the data go. This 2014 timeframe coalesces nicely with our expectation to have low-cost individual genome sequencing, commonly referred to as the thousand dollar genome, in the same time frame– an achievement that would allow every patient to have their genome annotated as a part of their personal electronic health record.

With the convergence of electronic technologies and molecular profiles, patients will begin to drive the transformation of the research environment and break down the walls of research silos. Patients, not scientists, will begin to control who has access to this medical information and how they can use it. Through a more patient-centered healthcare model, patients will play active roles in research by allowing their anonymized health information to populate knowledge environments for researchers. This will create a real-time medical effectiveness data environment and catapult a learning healthcare system. But the information will flow both ways. Through this information exchange, medical researchers will be able to design targeted clinical trials and recruit patients to these trials by searching for specific molecular genotypes. Such information will then flow back to the patient and his or her doctor, outlining opportunities to participate in these trials.

This new world of research will certainly raise policy issues that will need to be addressed, such as patient control, drug approval, and reimbursement for targeted therapeutics.  But there will also be issues in the private sector regarding business models for personalized medicine and issues within the academic setting regarding publication, access to data, and career advancement in a world of real-time data dissemination.  There will also be voices who will oppose this new approach to science, but momentum is gaining and transformation is occurring.  The leaders in the field will be those that recognize and plan for the transformation, understanding that the patient is not a bystander in research, but an active participant.

By Adam Clark, Director of Research and Policy, LIVESTRONG

Are We There Yet? Casting a Vision for the Future of Personalized Medicine

January 15, 2010

As part of their first issue of the new year, Nature ran a series of commentaries entitled 2020 Visions from leaders throughout the industry offering their predictions for what lies ahead in the coming decade. In his commentary on the future of personalized medicine, David Goldstein of Duke University recognized the following challenge, “Over the next decade millions of people could have their genomes sequenced. Many will be given an indication of the risks they face. Serious consideration about how to handle the practical and ethical implications of such predictive power should begin now.”

Dr. Goldstein’s admonition to consider the ramifications of personalized medicine for consumers is well warranted. Consumers have become increasingly informed and engaged in their health care, and the proper implementation of personalized medicine must include recognizing the impact this is already having on clinical care. There are also other significant challenges and opportunities that many are working vigorously to address, and will require additional effort in the coming months and years. To name a few:

  • To what degree will personalized medicine be addressed in the final version of the health reform bill?
  • Is personalized medicine ready to be adopted into clinical practice, or is there need for a greater scientific evidence-base? If so, what does that look like?
  • Will federal incentives for the adoption of electronic medical records enhance the practice of personalized medicine, or impede its progress through implementation that is not aligned with personalized medicine?
  • Are the efforts from biotech and pharmaceutical companies to augment their drug development pipelines with tailored therapeutics (and companion diagnostics) sufficient, or are we still relying too heavily on traditional drug development models?

In the coming weeks, this blog will feature commentaries from those involved in advancing personalized medicine and offer perspectives on what lies ahead. I invite you to share your predictions and expectations for the coming year and beyond. Many have recognized the potential of personalized medicine, but what must take place on the scientific, regulatory, political, or clinical levels to make personalized medicine a reality? I look forward to hearing your thoughts!

A Holiday Reading List from The Age of Personalized Medicine Blog

December 23, 2009

As we head into the final weeks of 2009, I wanted to share some recent articles and reports that you might want to read between glasses of eggnog and gatherings with family and friends. As the year draws to a close, these articles point to the tremendous opportunities that are ahead for personalized medicine, as well as the challenges in policy, business, and health care practice .

1) ObamaCare Threatens Personalized Medicine, Forbes – Dec 21, 2009 

Gregory Conko of the Competitive Enterprise Institute and Henry I. Miller, a physician and a fellow at Stanford University’s Hoover Institution, wrote a compelling op-ed this week on a topic we have discussed prominently at this blog – the need to align priorities for health care reform, particularly comparative effectiveness research, and personalized medicine. Conko and Miller point to the importance of taking into account the effects of a medicine on sub-populations and how the value of medicine (in terms of diversifying treatment indications) can increase over time. An approach to CER that lacks emphasis on such important advances may stunt the growth of personalized medicine. 

As Tony Coelho pointed out at this blog last week, the language in the Senate version of the health care bill does provide for an approach to CER that embraces patient differences and focuses on providing information that will enable patients and providers to make more-informed decisions. We’ll be standing by on Christmas Eve to see if this is what we get! 

2) Welcome to the Era of Personalized Medicine, Huffington Post – Dec 22, 2009 

In this article, WIRED Editor Thomas Goetz suggests that the era of personalized medicine is not only about advances in pharmacogenomics, but also about how advances in bioinformatics and consumer-oriented tools are generating huge amounts of data that can inform a more personalized approach to care. Goetz contends, “Personalized medicine isn’t something that happens to us; it’s something that we have to choose to engage in.” With such an engaged patient population emerging, health care providers also need to consider how interactions will change with patients bringing self-generated records and research into discussions about their health care.  

I look forward to seeing Goetz’s book The Decision Tree: Taking Control of Your Health in the New Era of Personalized Medicine in February. You can also check out the Decision Tree blog to hear more of his thoughts on predictive medicine and the future of health care. 

3) Personalized Medicine Market To Grow 11% Annually, Pharmaceutical Executive – Dec 15, 2009 

Earlier this month, PricewaterhouseCoopers released The new science of personalized medicine: Translating the promise into practice, highlighting how the “disruptive innovation” of personalized medicine is creating opportunities and challenges for traditional health care practice. In case you won’t have a chance to read the 50-page report, this article from Pharm Exec gives a great summary of its salient conclusions. Echoing Goetz’s suggestion that personalized medicine encompasses consumer-oriented products and services, the report contends that a growing emphasis on prevention and wellness is paving the way for advances in personalized medicine.

Personalized Medicine and Health Care Reform: Looking Back, Looking Ahead

December 18, 2009

Will health care reform support personalized medicine?  In my mind, that depends on two important factors: 1) the extent to which health care reform is truly patient-centered (does it make room for patient differences, room for patient voices, and time for patient care?) and, 2) the extent to which it is innovation-friendly.

I’m focusing on the first topic in this post.  Earlier posts have rightly focused on comparative effectiveness research as one key provision.  If CER is structured correctly, it can help inform patients about optimal medical and health care options based on our differing needs.  These differences come from a number of factors, including different clinical conditions we may have, differences in our preferences and the way we view risk/benefit trade-offs, cultural differences, and certainly molecular differences.  CER structured to recognize, and respect, these differences can only accelerate the move to personalized care.  Yet it remains unclear if this is the kind of CER we’ll get.  I think only the Senate bill’s CER language gets us close to this goal, by fully including patients and providers in the process, fully embracing patient differences, and focusing the program on results communications and not national policy recommendations. 

CER is one of several aspects of health care reform that will have an impact on patient-centeredness and personalized medicine.  Just as important are provisions that will apply the scientific evidence to policy decisions.  This includes proposals to establish an independent Medicare advisory board, define physician “best practices” and performance standards, and establish standards for use of health information technology.   

These types of policies, when deployed as cost-control levers, could be one of the single biggest factors influencing the future of personalized medicine.  Payment policy measures designed to control costs and expand access—but that fail to encourage continued development and adoption of personalized medicine—could substantially delay or diminish opportunities for meaningful, measurable improvements in health care value and quality.

That’s because cost containment proposals that impose access restrictions based on average, population-wide study results risk ignoring the different needs of individual patients and discouraging adoption of personalized tests and therapies based on these differences.  For example, “pay for performance” programs focused on short-term provider efficiency could discourage physicians from using gene-based tests and targeted therapies to optimize care for the individual.  As a patient with epilepsy myself, I take a very personal interest in how these policies get developed and applied.  

This nexus of CER and policy levers was highlighted earlier this year in an NPR commentary from Anne Brewster, an internist and instructor at Harvard Medical School.  “Physicians may agree with the end goal, but many of us worry about the methods and unintended consequences.  Comparative effectiveness research sounds sensible.  Of course we need more studies to define best practices.  But I find myself afraid that the results will be used by policy makers, hospital administrators, and lawyers to further limit my autonomy by setting hard and fast rules about what is “right”.  Clinical situations are always nuanced, never black and white.  Perhaps it is semantic, but I want to feel that CER will empower rather than constrain me.” 

Enacting, and implementing, health care policies that support patient-centered care and the science of personalized medicine won’t be easy; but it is absolutely essential.  Let’s work together to make it happen.

By Tony Coelho, Chairperson, Partnership for Improved Patient Care

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