Populations are connected. There are no isolated pieces of information, but rich, connected domains. Any citizen can be related in any number of ways. Family ties. Lifestyle preferences. Hereditary predispositions. Medical conditions. Purchasing preferences. The strength and patterns of these relationships are the primary determinant of a populations overall health.
A citizen predisposed to lousy health is likely to have a better quality of life if part of a healthy population; and the inverse holds true (an untested, personal hypothesis!).
Collecting, aggregating and synthesizing information from millions of relationships is complex. Performing this on sub-populations is a task ill suited to traditional tools and approaches.
The emergence of Network Graph[^1] stores has been driven by Social Network Analysis (SNA) to solve problems in Public Health, Law Enforcement, Retailing, Economics and Social Sciences. Little attention has been focused on Population Health in a private, accountable health care context.
Challenged with managing the health of a population, could we conceive of all the necessary data points and store them in a tabular datastore like an Excel spreadsheet? Do all these data points exist in the EMR?
Does this challenge involve long chains of evolving relationships and patterns of interaction and determinants? Might these include contextual, non-clinical factors? These would seem to be essential considerations in an epidemiologic or risk analysis of a population.
The patient population is increasingly hetrogeneous. Increasing social and geographic mobility, fuels patient churn
The vendors circling hungrily above all health provider systems have yet to offer a credible Population Health Management solution (personal opinion!). Credibility would seem to come from any two of the following
- Domain thought leadership
- Advanced, breakthrough technology
- Quantitative track record of success
Clearly many millions of dollars have been invested in product and service development and this has convinced many health systems to place an investment bet on them. All involve considerable barriers to entry with few guarantees of ROI. These early customers are ‘fast followers’ of emerging trends and heralded as progressive leaders by vendors seeking out other followers.
While no clear solution has emerged, the Population Health mandate and Quality Measures continue closing in on us. The clock continues to tick on our window for informed discussion and decision making.
If no vendor steps forward with a compelling, credible, affordable solution to our problem, what do Clinical Intelligence Analysts do? And even if one does, how do we hedge our risk on them?
Plan & Prepare
As we plan, we are forced to consider our definition of “Population Health” (the knowledge domain) as this informs our “Management” strategy (tools, processes, targets).
Health System Administrators are legitimitly inclined towards a business-first definition focused on CMS Quality Outcome Measures.
A business-first definition would encourage optimization of our operating model, consistent with general high volume, low margin, service businesses. The evoluton of service industries suggest adoption of multi-class service models to accommodate population outliers (Hotels, Airlines, Banking, Automotive, Retail offer some inisght).
An alternative viable option is an academic, clinical, science or mission-first definition. This would seem to be a less obvious choice that would be a broader superset of the business-first definition.
Such a choice would encourage consideration of network and psychographic factors of the population. This would seem to be necessary to affect the behavior changes evidence suggests is needed for improvement in longer term health outcomes.
If a Health Systems chooses a definition broader than business-first, it will plan, prepare and prioritize differently. Subsequently, needs shift from near time reporting to forecasting, anticipating, reasoning and prediction. These are skills and competencies that will need to be developed across the continuum of care, irrespective of facility size.