By KIM BELLARD
I’ve been working in healthcare for over forty (!) years now, in one form or another, but it wasn’t until this past week that I heard of implementation science. Which, in a way, is sort of the problem healthcare has.
Granted, I’m not a doctor or other clinician, but everyone working in healthcare should be aware of, and thinking a lot about, “the scientific study of methods to promote the systematic uptake of research findings and other EBPs into routine practice, and, hence, to improve the quality and effectiveness of health services” (Bauer, et. al).
It took a JAMA article, by Rita Rubin, to alert me to this intriguing science: It Takes an Average of 17 Years for Evidence to Change Practice—the Burgeoning Field of Implementation Science Seeks to Speed Things Up.
It turns out that implementation science is nothing new. There has been a journal devoted to it (cleverly named Implementation Science) since 2006, along with the relatively newer Implementation Science Communications. Both focus on articles that illustrate “methods to promote the uptake of research findings into routine healthcare in clinical, organizational, or policy contexts.”
Brian Mittman, Ph.D., has stated that the aims of implementation science are:
- “To generate reliable strategies for improving health-related processes and outcomes and to facilitate the widespread adoption of these strategies.
- To produce insights and generalizable knowledge regarding implementation processes, barriers, facilitators, and strategies.
- To develop, test, and refine implementation theories and hypotheses, methods, and measures.”
Dr. Mittman distinguished it from quality improvement largely because QI focuses primarily on local problems, whereas “the goal of implementation science is to develop generalizable knowledge.”
Ms. Rubin’s headline highlights the problem healthcare has: it can take an alarmingly long time for empirical research findings to be incorporated into standard medical practice. There is some dispute about whether 17 years is actually true or not, but it is widely accepted that, whatever the actual number is, it is much too long. Even then, Ms. Rubin reminds us, it is further estimated that only 1 in 5 interventions make it to routine clinical care.
While your humble columnist eschewed forecasting for 2013, he has decided to reverse course and inaugurate the 2014 blogging season with a contrarian duodecimal exercise in futurism. Will this antidecimal augury align with the mysterious cosmic order and governing perfection? Let the readers be the judge in January 2015……
1. Obamacare will neither succeed or fail. This hugely complex law will have too many outcomes, statistics and analyses that will be subject to too much spin by both supporters and detractors. Like puppies clamoring for the mother’s attention, the loudest wins, but only in 15 minute media increments.
2. Inflation returns, with a vengeance: While we won’t know it until well into 2015 or 2016, 2014 will be the year that the sleeping giant of healthcare costs awakens. Millions of new insureds in an improving economy will finally get their pent-up pricey preference-sensitive health care needs fulfilled.
3. Duh, it’s the delays stupid: While low income Americans will appreciate having access to subsidized health insurance and Medicaid, the middle class’ unsubsidized sticker shock will threaten the fall 2014 elections. Caught between conflicting advice of insurance actuaries and political hacks, the White House’s regulatory choices will be obvious.
4. Commercial scientific misconduct: Unable to resist the allure of bonus payments (like this) or the branding that is dependent on the public release of quality outcomes, at least one large health entity will be caught committing “reporting fraud.”
5. Snowden blow-back: as the promise of big-data grows, fearful health care consumers will be even less inclined toward allowing access to their health information. Too bad they won’t be given a say.
6. Innovator’s Dilemma for health tech: solutions that are simple, transparent and modular will continue to make ‘from the bottom’ inroads into a tech industry that – like early data storage – is too complex, opaque and entangled.
7. Speaking of health tech, patient-monitoring solutions that offer more insight and less data will grab market share. Instead of a series of blood glucose results dumped into an electronic inbox, think algorithms that suggest insulin dose adjustments.