If you saw the title of this blog post and thought you were going to read a high-level health policy discussion about rapid learning healthcare systems and cancer care you would have been...wrong. I feel particularly unqualified for that discourse. In fact, when I first heard the expression not that many months ago, I admit that I thought it was more grandiose, implausible policy-speak mumbo jumbo from the inside-the-Beltway crowd without much of a basis in the reality of modern medical practice. But I have to admit that, as I have read a little more and thought about this, I am starting to get it. In the simplest terms, a rapid learning healthcare system is best thought of as a model, or perhaps it is a movement, whereby there are seamless transitions between the knowledge gained from the care of the individual patient, the data obtained from basic science research and clinical trials, and observations from studies of population health, all blended into an iterative process that constantly feeds back on itself to improve and transform care delivery. Perhaps it is more clearly stated in this excellent review from JCO last year by Sharon Murphy from IOM et al, particularly Figure 1:
In a patient-centered system of rapid-learning health care, patient-level data are aggregated to achieve population-based change, and results are applied to care of individual patients to achieve meaningful patient-level practice change.
The IOM has published on this concept since at least 2007, and they also held a workshop in 2009 where they describe rapid learning systems in cancer care. The cornerstone of all rapid learning systems is health information technology. Clinical data must be collected real time, in structured elements, using standards-based systems, and fed back into this loop in seamless fashion.
This concept was brought home to me recently when I interviewed Amy Abernethy and Ethan Basch for the Journal of Oncology Practice podcast this month on the topic of collecting patient-reported symptoms in routine clinical care. (You can listen to the podcast here or download it on iTunes; the link to their original JOP commentary is here). Basically, Dr. Abernethy was describing for me how at Duke her group is already trying to use the concepts of rapid learning when their patients fill out standardized symptom assessment questionnaires at each visit and their self-reports are automatically triaged into tiered interventions. Her comments on this part are in the last third of the podcast and are worth a listen.
My other observation is that this is the way care should be practiced. As individual clinicians and for those among us who are leaders in this area, we need to keep asking ourselves, why isn't it done this way all the time? Why should we continue to tolerate unacceptably long delays between clinical discovery and application or even between the recognition of clinical events in individual patients in our practices and change in management? It's what the public expects, it's what payers are starting to demand, and more importantly it's what our patients deserve. Of course, no one reading this is naive to all of the current systems barriers preventing rapid learning and real time feedback of data. And health IT as it exists in 2011 -- with all of its vendor-centric, non-interoperable, and bewildering variations -- is hardly a panacea. Figuring out the privacy and security issues is huge. But I think I am now starting to understand that the health policy geek-speak wordsmiths probably got this one right.
The ideas and opinions expressed on the ASCO Connection Blogs do not necessarily reflect those of ASCO. None of the information posted on ASCOconnection.org is intended as medical, legal, or business advice, or advice about reimbursement for health care services. The mention of any product, service, company, therapy or physician practice on ASCOconnection.org does not constitute an endorsement of any kind by ASCO. ASCO assumes no responsibility for any injury or damage to persons or property arising out of or related to any use of the material contained in, posted on, or linked to this site, or any errors or omissions.
Recent posts