Reporting Framework for Value Based Care
Learn how a provider's relative performance, or 'value', can be evaluated through three key components in an equation: quality, efficiency, and cost.
The Patient-Centered Medical Home (PCMH) model emerged in response to the recognized need for more systematic and evidence-based approaches to ensuring access to, and coordinating care for, an entire population. Within that framework an additional focus has developed that recognizes the specific needs of members with chronic and complex conditions. In order to respond to that population, additional models have emerged that focus on proactive identification of chronically ill members using claims-based predictive model scoring as well as clinically based referrals and information. These models are often referred to as Ambulatory Intensive Care Unit (AICU) or Intensive Outpatient Care Program (IOCP).
The AICU and IOCP models, now in pilot testing and operation in a number of sites and with different Milliman clients, have the following core design characteristics:
There are a number of good articles written about these initiatives including “Enhancing Quality of Primary Care Using an Ambulatory ICU to Achieve a Patient-Centered Medical Home” Lewis, Hoyt and Kakoza, Journal of Primary Care & Community Health May 27, 2011 and “American Medical Home Runs” Arnold Milstein and Elizabeth Gilbertson, Health Affairs, 28, no. 5 (2009) pages 1317-1326”. These and other articles provide good information on the results of these programs.
Most of these models involve hiring clinic-based case managers or imbedding health plan case managers in clinical sites. Working with the clinical teams and health plans involved in these projects has provided a number of insights into using risk-scoring information in supporting the needs of case managers in these new models.
These observations include the following.
Additional analysis of risk scores can be used to identify a more manageable list of candidates for care management. In the example below a client distribution analysis showed the number of members by risk score level both concurrently and prospectively for members with a score greater than one. This analysis helped identify patterns and clusters of members by risk score range. Further analysis isolated a smaller population (approximately 7% of the total) with concurrent and prospective scores that remained level or increased. This allowed the management team to focus on new candidates more quickly.
Client Example - Using Population Risk Score Distributions to Identify Care Management Candidates
The AICU and IOCP models, viewed as specialized programs designed to support the needs of chronically ill members, may in fact be good blueprints for all care management programs. The concept of integrating payer and provider data and expertise more directly can be rewarding for care management teams and beneficial to members.Claims analysis and risk scoring tools can be key tools in identifying opportunities and targeting interventions in these models.