The are focused on supporting their organization’s initiatives to drive analytics for population health management. Rightfully so, they are looking at the extreme demands on their IT departments, their lower margins and the magnitude of change occurring around them to make deliberate and specific steps toward managing their populations’ health. Many of these experiments are happening in very discrete and targeted ways, employing resources carefully, all of which makes a vast amount of sense in the current healthcare landscape. The danger of this approach, however, is a myopic view of population health by the stakeholders that fails to deliver true organizational impact.
Equally critical to husbanding resources appropriately with these new endeavors is the need to have an enterprise view
of how these strategies will play out over the whole network over time. A synchronized organizational strategy that involves all key stakeholders will guide resource decisions that will be critical in preventing future costly rework. A common aggregation of population health needs across stakeholders will often uncover the requirement to have a longitudinal view of patient data. This ensures common patient counts in the most basic of analytics, as well as more complex questions of exclusions, duplicative information and which measures matter the most to ensure compliance with quality, utilization and outcomes goals for the whole enterprise. Furthermore, the level of investment required for an organization to fully liberate the vast sums of useful data currently locked in provider facilities and data silos is a strategic choice better suited to serving multiple purposes to ensure that the investment reaps its potential economic value and supports enterprise-wide decisions.
Working with limited data sets in the short-term to quickly get an experiment up and running or focusing on meeting one Centers for Medicare & Medicaid Services (CMS) requirement must be in line with the long-term goal of having financial and operational metrics that are in sync, both for the clinician leveraging that data for his or her own practice as well as the CFO looking at the outcomes across a program, as an example. Neglecting to take time to sort through these universal data needs in the planning of a program can lead to frustration and a potential lack of trust in the data which will in turn severely challenge key stakeholder engagement.
It’s a simple idea that is much easier said than done in the real world.
A fully vetted strategy that is supported by partners with real-world experience on the cost/benefit choices to be made during these kinds of population health analytics efforts, will go a long way to set an organization on a track, break population health into manageable pieces, and ensure that the whole organization ultimately moves forward together. Without this alignment and focus, limited resources can be lost to isolated pet projects that fail to impact overall patient outcomes or the organization’s bottom line.
Manager, Solution Management