Why hasn't big data transformed healthcare?
Big data analytics are hot. And they are hot in healthcare. Conferences in 2014 include Healthcare Analytics Symposium, Predictive Analytics World Healthcare, Big Data & Analytics in Healthcare Summit, Healthcare Business Intelligence Forum... but are they relevant in nursing units and ORs?
I don't know of many charge nurses attending those conferences. Caregivers are focused on patients. Talk of technology in the hospital is more of its limitations than of transformations: the bed board doesn't talk to the EVS system, the OR schedule doesn't consider PACU capacity, it's "unclear" when the discharged patient has actually left the room...
How to sort the promise from the hype?
The promise of advanced analytics is the promise of GPS and point-to-point navigation. The promise is to deliver what "dashboards" do not in the same way that GPS delivers something maps do not. The promise is to create value now just as GPS did. How do I get to the airport now? What about traffic and construction?
- Advanced Analytics vs. Dashboards. Consider the difference between GPS and the "dashboards" most hospital software systems provide. Point-to-point navigation doesn't summarize the variation in your drive-time to work this month, or highlight what could have been done better yesterday. That type of analysis can be important... but that data is available in spades now, just like maps. Point-to-point navigation is different: it's about now and it's proscriptive.
- Decision Support Now. The promise of advanced analytics in healthcare is to improve decisions now. In which beds should we place these pending ED admissions, now? When should we schedule these two surgeries, now? How should we adjust tomorrow's staffing schedule, now? Which inpatients are at highest risk of readmission and merit additional consideration, now? How do I get to the airport, now?
- Predictive Decision Support. The promise of advanced analytics is to shape decisions now by anticipating what's likely to happen soon. In which beds should we place these pending ED and OR admissions, now, based on current patient needs and likely patient needs tomorrow? How do I best get to the airport now based on traffic that's likely to occur during my drive?
The potential impact of such analytics is big: less empty bed time, fewer internal transfers, less congestion in ICUs, better staffing, more focus on high-risk situations, more balancing of utilization... Together these can help to reduce patient safety risk, length-of-stay, patient waiting and costs.
So why hasn't this transformation occurred?
Change is a funny thing. It's happening all the time and yet can seem painfully slow. This is true with healthcare analytic applications. They're happening slowly but when we look back in a few years we'll see how much changed. To reach the tipping point providers and technology firms will have to overcome three obstacles:
- Complexity. Does anyone doubt that healthcare processes are more complex than other industries? The algorithms, preference hierarchies and sensing technology "underneath" the analytic must accommodate this complexity and the complexity of relevant data sources. Not easy.
- Nuance. Great analytics present information simply. This is tough to do. How many engineers understand well how a charge nurse needs to receive a prompt? Not many. Technology firms will have to sort this out.
- Scale. Healthcare operations are local. Every provider's process and data are different... even at two hospitals in the same healthcare system. This makes it difficult to "mass produce" analytics. That matters because the cost of building a "predictive placement analytic application" (or whatever) is not trivial. Until we figure out how to repurpose and reuse across disparate providers high-end analytics may be too expensive for broad adoption.
There is so much potential for analytics to transform healthcare. Much still needs to be done for the complete transform to become a reality. But, rest assured, progress is being made. In my next post, we'll take a sneak peek at hospital operations of the future, and how the promise of analytics is beginning to be delivered.