I was at two different meetings last week at the NIH in Bethesda, MD, both of which were related to the fostering of clinical research networks. The first meeting, called "Clinical Research Networks: Building the Foundation for Health Care Transformation", was the culmination of the NIH Roadmap "Re-Engineering the Clinical Research Enterprise" program, in which a dozen academic health centers and other research institutions fulfilled contracts to do research and develop tools and techniques for the creation, care and feeding of clinical research networks.
The network concept was defined broadly to include disease-focused networks, practice-based research networks (PBRNs), transplant donor/recipient networks, and others. There were keynote speakers from the NIH leadership, but the bulk of the meeting consisted of panels composed of principal investigators discussing the lessons learned in the fulfillment of their contractual obligations. While each contract produced some sort of intellectual property, but the lessons learned were the primary goal of the program, and the lessons were rich and diverse.
The second meeting, "Accelerating the Dissemination and Translation of Clinical Research into Practice", was a closely related follow-on open to a much broader audience. It was more of a mix of speakers and panels, and covered a lot more ground. It included a speaker on the translation of knowledge into practice in an agricultural extension program, an admirable (and rare) attempt on the part of the medical research community to learn from unrelated disciplines with similar problems. There were representatives of many stakeholder communities within the realm of translational research, from high-ranking executives of funding agencies to physicians in private practice.
The theme of both meetings was the need to accelerate translation of research into practice. There is broad consensus on the need to move to a translational research paradigm. There have thus far been two types of translation in common biomedical parlance: Type 1 (T1) translation, translating basic science discoveries into cutting-edge therapeutics; and Type 2 (T2) translation, translating cutting-edge therapeutics into mainstream primary care. There is talk of the need for a third translational layer (T3), bringing evidence-based medical knowledge into everyday life at home, at work, and in the community at large.
Two themes emerged that I think define the current state of clinical research informatics, and in fact biomedical informatics in general. The first theme is the precedence of cultural and political barriers to adoption over technical challenges. The second theme is patient empowerment, the shift toward patient ownership of and responsibility for their electronic health records.
Politics Trumps Technology
Make no mistake: in terms of obstacles to progress in biomedical research informatics, and in particular such distributed operations as multi-site clinical trials and practice-based research networks, the technological challenges are formidable. Nonetheless, technology was anecdotally noted by several speakers at last week's events as constituting 10% to 20% of the picture.
By and large, the political and cultural barriers are not a matter of malfeasance. Some of the political challenges do involve a certain level of villainy, particularly in the defense of disciplinary and organizational silos and personal turf. The vast majority of political and cultural barriers I've encountered stem from problems among those eloquently stated by Jonathan Grudin in his paper from the early 1990's entitled "Groupware and Social Dynamics: Eight Challenges for Developers". These include disparities of work and benefit; critical mass and Prisoner's Dilemma problems; disruption of social processes; failure to account for necessary exceptions to standard operating procedures; unobtrusive accessibility in normal workflows; difficulty of evaluation and justification; failures of intuition; and unanticipated complexities in system deployments. I can't go into all of these here, but let's look at a few that characterize different major problem areas.
Disparities of work and benefit
Disparities of work and benefit arise when complex systems require effort on the part of individuals and groups who receive no direct, immediate benefit in return. One example from my own domain is the need to acquire research data at the point of care. If there is an Electronic Data Capture (EDC) system for such data acquisition, it is unlikely to be the same system in which clinical care and operations data are entered. Dual data entry imposes a burden on the clinical staff for which they receive no additional compensation or other ancillary benefit.
We encountered this problem in an effort to automate EDC for a study conducted through primary-care provider (PCP) practices that are members of a PBRN. The idea of a direct login to an EDC system to capture data during patient encounters was a non-starter.
Disruption of social processes
Aside from the work/benefit disparities, many physicians view data entry as a demeaning activity, especially he or she is over forty or so. Such physicians capture data in handwritten notes or oral dictation. In clinical research, tracking custody and transformation of data from the original source of truth is a requirement, and the source documents must be retained in the original or a facsimile form (e.g., scanned image of a paper form). In such a situation, either the clinician must be convinced to let go of the social norm, or an additional burden is imposed on the research staff and IT systems.
Our solution was two-pronged. First, the research data set consisted almost entirely of data points of significant value to the provider-patient relationship; some were captured at the clinic, but others were captured elsewhere and transmitted to the clinician from the patient's hospital and a telephone- and Web-based depression surveillance program. The additional effort involved in data capture during patient encounters was offset by its immediate usefulness in patient care, and the automated transmission of additional information from outside sources provided a benefit that could not easily be obtained in any other way.
Second, we were able to piggy-back study recruitment and EDC onto a prompt and reminder system, Cielo Clinic, which produces a problem summary sheet that is bi-directional, used both for data presentation and capture. Cielo Clinic began life as ClinfoTracker, a product originally developed by family physicians within our Health System for internal use that has been spun out commercially after extensive internal testing and refinement in real-world clinical environments. [Disclosure: I do some consulting for Cielo Medsolutions, so be aware of my potential bias.]
Adopting Cielo Clinic involved some effort on the part of clinicians and support staff in the PCP offices, but its added value manifested in immediate benefits: aside from the obvious beneficial effect on patient care, Cielo Clinic alerted the clinician to the need for evidence-based billable procedures that might otherwise have been overlooked, thus providing a positive effect on practices' bottom line. This financial incentive is difficult to quantify prospectively, but the technology transfer to Cielo put the burden of proof on people with a vested interest in finding believable quantitative revenue increase estimates. Primary care is not a hugely lucrative venture in most cases, so this incentive is more significant than we may wish it were.
Data capture could be either direct EDC or paper form-based, but because the hard-copy Cielo Clinic Problem Summary List is capturing clinical care information, offices with paper-based charts would retain it anyway, eliminating extra effort in tracking the original source of truth. Likewise, the secondary data entry involved in maintaining the problem summary list has both near- and long-term clinical benefit, given the focus on capturing research data that is durectly relevant to patient care.
The second sea change, the shift to a consumer-centric healthcare system, is closely related to the structural contradictions that are threatening to tear the US health care system apart. The US healthcare system is costlier by far, by any measure, than its equivalent in any other developed nation. The quality of care, defined in terms of outcomes on a statistical basis, is among the lowest among these same nations, again by almost any measure. The US healthcare picture is characterized by dramatic breakthroughs at the cutting edge of medicine and mediocrity throughout the day-to-day operations of most points of care in the system.
In an odd sort of way, the pressure from the payer side to contain costs synergizes with the healthcare consumer's desire for quality care. Patients want all the necessary tests, and only the necessary tests, to diagnose and determine the appropriate therapy for their conditions. With the wealth of information available via commercial online search engines, patients and their loved ones come to the physician-patient relationship more informed than ever before - in many cases where a rare disease is involved, more informed than the physician. Patients frequently come into the exam room with Web page printouts and a host of questions and ideas that challenge the paradigm of the physician as the expert and the patient as a passive recipient of diagnoses, prescriptions, and advice.
Dimensions of Trust
At present, "more informed" does not necessarily entail "better informed". But to be fair to the search engines, without contextual knowledge they are flying blind when attempting to divine the meaning of seekers' often brief and sometimes cryptic queries. An online EMR, such as those now being deployed by Google Health and Microsoft HealthVault, could be a big step toward provision of the necessary context.
Trust is the big issue here, and trust is multi-dimensional. Will consumers learn to trust massive online repositories to take custody of their health records? Will Google, Microsoft, and the others who will be competing in this space prove worthy of consumers' trust? And finally, will online search produce information consumers should trust? The jury is still out on all of these.