The analytics elephant is sitting in the waiting room
Whether you are an ambulatory practice, an urgent care center, a hospital, an insurer, an integrated delivery system, an accountable care organization, a health information exchange, a provider hospital organization, or whatever healthcare delivery or administration acronym we have managed to dream up now; you share a very common trait with all of your other healthcare brethren. You have an analytics elephant sitting just outside your office!
There is an old joke that poses the question, “How do you eat an elephant?” The punch line is, “One bite at a time!” I will give you a moment to pause in reflection and perhaps chuckle quietly to yourself! This piece of humor is truly applicable to analytics in healthcare; there is indeed an elephant out there that each of us needs to consume.
Before we even think of how we are going to ingest this pachyderm; let us look more closely at our dinnertime “catch of the day.” Our elephant’s anatomy is made up of four components. First, we have a multitude of data sources, of varying quality, and scattered across what seems like an endless series of disparate silos. The beast has multiple categories of measurement; including clinical quality, administrative cost, financial, and operation key performance indicators. For each of the categories, there exist a set of measure families that have been generated by national standards bodies or that have been created to suit regional initiatives. Finally, our pachyderm supports an entire community of would-be information consumers.
If we are to eat the analytics elephant one bite at a time; we wish to assure that the entire healthcare village gets fed well. This goal mandates that every anatomical portion of the analytics elephant must be addressed. The first challenge is to find all of the data that make up the core of the elephant. This information is nestled in multiple disparate sources and will require serious heavy lifting to extract. Since the village is best fed from a common pachyderm; we wish to place all of our data in a single community data foundation. Once we normalize and cleanse this data, it is fair to say that we now have a single version of the truth across the 360-degree continuum of healthcare.
Different consumers of the elephant will have varying tastes as to what part of the beast they prefer to ingest. For this reason we need to acknowledge that providers, payers, quality organizations, government, and all of the other guests at the banquet will each request a different cut of the meat. Our elephant must satisfy the palate with analytics that addresses quality, cost, finance, operations, utilization, and access of care. There will also be those consumers who will come back for seconds; more than likely having a change in taste along the way! Answers always beget new questions, right?
In order to assure that everyone requesting a certain cut of the elephant gets the same quality and portion; it is critical to harmonize our measures. The entire village needs to be eating off the same platter; that is to say, nationally accepted standards must be used and the determination of how the measure is calculated must remain constant. These measures must meet the specific needs of a group, with enough flexibility to be customized.
Finally, we need a way to share our analytics elephant bounty with the entire village. We can cook the beast to perfection; but it serves dubious purpose if there is no serving platter to bring it from hearth to table. In any analytics effort there are three principal measures of success; (1) did we identify gaps or places for improvement, (2) can we surface the opportunity to the right person, and (3) can that person take action based upon this knowledge? If you cannot surface and share what you have learned from the analytics elephant; better to have ordered delivery pizza!
Assuming you can access all of your data, measure each piece, utilize the correct measures, identify gaps, and act upon what you have surfaced; the entirety of the analytics elephant can become too much to consume, even for a large and prosperous village. If you try to address everything from everywhere for everyone, you will simply choke your analytics initiative. The answer is that we must all eat the elephant one bite at a time. For our case of the elephant, these bite-size pieces are:
- Limit the initial number of data sources – Select several sources that perhaps use a common EHR/HIS system, or a common protocol. These sources should be prequalified with respect to the quality of their data
- Limit the measure domains (categories) that you will examine – Do not try to meet the needs of providers, payers, quality organizations, and government simultaneously. Restrain yourself to just one of these domains initially.
- Limit the measure families for initial implementation – You will simply not be able to handle the volume of information that comes from a solid analytics platform. Select a population subset such as diabetics, opt for actionable measures such as A1c percentage reduction, and focus on identifying gaps and taking action.
- Limit the number of consumers for analytics – This is most easily accomplished by data-marting results back out to the data sources originally used. In this way, immediate benefit can be shown and trust of the results reported will occur.
Most healthcare organizations are in no position to build an analytics solution. Third party vendors abound in the marketplace. Two types are worthy of closer examination. The first is driven through a consulting model, loaded with front end services, and eventually delivering a customized analytics solution. This is usually an extremely large elephant, that tends to be very expensive, takes forever to cook, and is served in its entirety. The second vendor type delivers a product that is integrated to data sources, preloaded with measure sets, and is accelerated through services. This elephant is still very large, but it is cooked and served in bite-size pieces, making it less expensive and easier to digest.
As you move forward with identifying your partner for analytics, ask yourself a very important question. “Does this vendor understand the elephant in my room?” If the answer is yes, then there is only one more question to ask. “Will my organization be forced to choke on the entire elephant, or will my vendor help me eat it one piece at a time?”
Learn more about how to predict hospital readmission using artificial intelligence.Tags: Healthcare, Intelligence