Tom Burton of Health Catalyst offered a model to address this challenge by looking at what is motivating an organization to change and how quickly. The first dimension (the x-axis) is Motivation, where some organizations are motivated toward population health in financial and operational ways, and others are motivated clinically. The second dimension (the y-axis) is Timeframe, with some organizations thinking long-term and others short-term. These dimensions create the following four quadrants of population health efforts:
1. Long-term financial/operational 3. Long-term model of care
2. Short-term financial/operational 4. Short-term model of care
Organizations in each quadrant are working on different programs to achieve different incentives, but the group agreed that success in the long-term strategies requires success in the short-term tactics, i.e., working in multiple quadrants simultaneously.
Julia Swanson said, “Sometimes we think we have to do it all. We can move everything an inch, but we need to take some key areas, focus efforts and resources on those, build organizational capabilities and then move on. We need to make sure that we do not spread improvement like peanut butter.”
Dr. John Pirolo said Ascension “is spending a lot of time in the two upper quadrants (Figure 2) on strategy, and lots of time in the two lower quadrants tactically, working to gain enterprise momentum moving toward getting into the top two quadrants.” Christine Watts, The University of Chicago Medicine, said that “what we struggle with is knowing how fast we should go, how to get people on board, and how the long-term strategies should translate into short-term efforts.”
With one foot in the fee-for-service world and the other in value-based payments, it’s difficult to know what kind of message to send providers to get them aligned. These observations led right to the point being made, that healthcare organizations have to accept the challenge of working in all four quadrants at the same time.
Required Capabilities for Improvement
Efforts at improvement require the synergy of multiple processes and systems, not just technology. Three core capabilities are needed for clinical, cost and experience outcomes improvement:
1. Best Practice—what the system should be doing;
2. Analytics—how we measure and predict how the organization is doing;
3. Adoption—how to change and what pace of change can be tolerated.
Systematic outcomes improvements are possible when all three of these capabilities are in play, but they can be scaled only when the psychology of outcomes improvement is embedded within the leadership, culture and governance of the organization and when everyone is financially aligned.
The Need for Governance
The need for governance of data and data-related initiatives was a critical issue raised by the group. When participants were asked about the most prevalent symptoms of less-effective governance within their organizations, three issues echoed:
1. The inability to say ‘no’ to lower priority projects;
2. The light efforts in many areas with no deep efforts on the critical few; and
3. The lack of initiatives spreading across the organization.
Eric Yablonka, at The University of Chicago Medicine, said, “We have many important priorities and everyone with an enterprise view sees all those priorities, so there are challenges around allocation.”
Tom Burton suggested that well-designed governance significantly helps with optimally allocating scarce resources and increasing the breadth and depth of improvements. He outlined four core principles of effective outcomes governance:
Principle #1: Starting at the top, engage all stakeholders around a common vision.
Principle #2: Have a common understanding of organizational needs, capabilities and readiness.
Principle #3: Use a consistent improvement methodology, align incentives and balance polarities.
Principle #4: Focus: Practice disciplined decision-making to prioritize, fund, organize and sustain improvements.
The Need for Data Integration
The topic of data integration is a hot one and a handful of subtopics garnered the most attention. For example, among payers, providers and patients, who owns data? Data sharing carries the burdens of confidentiality, legal liability, relevance and difficulty of sharing. The storing, sharing and analysis of data is the bedrock of population health. Inpatient and outpatient episodes of care among entire patient populations generate an abundance of data, yet it all exists in silos and the multitude of data sources aren’t integrated.
Hospital systems come at this challenge in many different ways and participants shared their architecture and tactical approaches. The encyclopedia of technology and analytics providers was represented, including the major EHRs (Epic, Cerner, McKesson, Allscripts), data warehouses, analytics platforms, and population health management tools (Hadoop, Health Catalyst, HealtheIntent, Optum One, Caradigm).
Miriam Morales said that Memorial Hermann “just started with HealtheIntent, so we are getting a lot of different data into that system. We are in the beginning stages of outlining how these data will integrate with existing systems, data governance, and how to leverage data across the system.”
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