I’ve had the distinct privilege, as an AARP-sponsored scholar-in-residence at the National Center for Complex Health and Social Needs to continue evolving the ideas spurred by my DrPH dissertation research on innovating ways to replicate models of care for vulnerable populations that while more effective, are also more difficult to spread. Last week, Health Affairs Blog published a post that I wrote with colleagues from the Camden Coalition of Healthcare Providers on this subject. To give it a read click here. There are some exciting new approaches that we can take to this problem and a path to do so that can build a field of practical knowledge we need to transform our health care system for the better.
A couple weeks ago I took a great 2-day stats course on evaluating treatment effects using observational data that was offered by Statistical Horizons and taught by Dr. Stephen Vaisey, Professor of Sociology at Duke. Terrific stuff. Learned key concepts about new and better ways to do such analyses. One gem that my colleague, Tim Hediger, recommended and which resonated with the theme of the course was this YouTube video by Dr. Gary King at Harvard click here. It clearly lays out why, despite its buzz … propensity score matching is NOT the best way to match observational data prior to analyzing treatment effects.
Fellow geeks, enjoy!
An article in the May 2017 issue of Health Affairs, Bending The Spending Curve By Altering Care Delivery Patterns: The Role Of Care Management Within A Pioneer ACO by John Hsu and others from the Massachusetts General Hospital and Partners HealthCare in Boston, provides more evidence that care management interventions can meaningfully contribute to the performance of an ACO. Doing so, however, is neither fast nor easy.
Here are a few key takeaways (which parallel my own experience):
1. Target higher-risk populations with modifiable risk factors which your program is specifically designed to address
2. Stay constant to purpose … utilization (ER visits and hospitalizations) may even go up at first … but will, as participants are in the the care management program longer, progressively decline over time (most notably at 13+ months)
3. Sophisticated analytics and study designs are required to assess the impacts of such programs in ‘real-world’ implementations (i.e., without a randomized controlled trial)
4. Inability to serve the entire target population should not deter continued implementation – enroll as many as current resources permit and continue to work toward expanding capacity
The care management program described in the article shares some attributes with HQP’s Advanced Preventive Care model. One of the authors of the Health Affairs article was also an author on a 2014 issue brief for the Commonwealth Fund that identified HQP’s model as one of four (out of 18 successful models reviewed) having the highest quality evidence of effectiveness in managing populations with complex chronic disease. The details of a care management program’s design and implementation are critical to its success, with many varieties of “generic” care management have been found to be ineffective.
While not quick or easy, the path to improving population health – from both a health outcomes and cost perspective – is becoming clearer. The advantage will go to those with the know-how, relentless commitment to innovation, and constancy to purpose.
I had a great time participating in the amazing work of the Camden Coalition of Healthcare Providers (CCHP) at their March 18, 2014 Clinical Champion Leadership Workshop. The program is helping leaders of “hot-spotter” organizations of all shapes and sizes from around the country learn how to advocate for and advance the effectiveness of care models serving the most vulnerable populations. For more information about that experience and the Camden Coalition click here.
I also had the great privilege of delivering the Keynote Closing address to the Population Health Colloquium on March 19. It was a wonderful opportunity to tell the story of what my team at HQP has learned about designing models of effective advanced preventive care. The principles and disciplined approach to health care delivery system design we’ve uncovered addresses the gap between traditional public health and primary care. It could do much to improve our health system and the health of vulnerable populations. Learn how HQP applies design principles (person-centeredness, population-relevance, and reliability) and operational domains (standards, staff training, participant education, data management and decision support, and analytics) to create effective models of advanced preventive care. Here’s a video clip of my keynote, generously provided by the CCHP: