Panel Presentation

(T7-01) Financial Flow Analysis Through the Cost Acuity Pyramid Uncovers Opportunities for Cost Savings by Telehealth

Monday, April 24
1:30 PM - 2:30 PM
Location: W331 A

It has been well documented ([1], [2]) that about half of overall CMS reimbursement is targeted to caring for a small handful of the sickest patients in the healthcare systems. However, it is less known what these patients look like prior to ‘rising to the top’ of the cost pyramid, and how we can prevent patients from getting there.
The primary objectives of a longitudinal retrospective study conducted by Partners Connected Health and Philips Research/Lifeline were:
- to evaluate healthcare utilization and expenditure on patients of Partners Healthcare at Home that have been using the Philips Lifeline service;
- to analyze patients transitions and their cost flow throughout the top-, middle- and bottom-segments of the cost acuity pyramids in the period 2011-2015.

We identified 3,335 patients with in-/out-patient encounters in 5 Partners Healthcare System (PHS)-affiliated hospitals through cross-reference of Partners Healthcare at Home and Philips Lifeline (PHH-PLL) data. Patient’s demographics, healthcare utilization, and expenditure for fiscal years FY11-FY15 were extracted from the Partners Healthcare’s Enterprise Data Warehouse. A multivariate analysis of inpatient/ outpatient encounter versus healthcare cost of all PHH-PLL patients was performed. Clinical outcomes (hospitalizations) and financial outcomes (healthcare expenditure) were assessed by linear regression models. PHH-PLL specific cost acuity pyramids for the fiscal years FY11-FY15 were built and compared to the CMS reference cost acuity pyramid. The flow of the PHH-PLL patients and their cost throughout the top-, middle- and bottom-segments of the cost acuity pyramids were modeled by Markov chains.

Multivariate analysis shows that inpatient admissions account for only 4% of overall encounters but contribute to 67% of overall total costs. The majority (80%) of inpatient admissions have ED charges. We observed increasing trends in total cost, average cost per patient and per encounter through FY11-FY15 that are higher than the CMS projected yearly increase of 6% [3]. Patients in the top- (5%), middle- (6-50%) and bottom- (51-100%) segments of the cost acuity pyramid account for 40%, 55% and 5% of the total healthcare expenditure, respectively, and these percentages stay stable across the FY11-FY15. Financial flow analyses shows that 22% of patients move down the cost acuity pyramid yearly and their cost decreases 86% in contrast to 18% of patients that move up with a cost increase of 682%. The remaining 60% of the patients stay in the same segment for two consecutive years but their cost increases 18%.

In addition to intensive care programs targeted at patients in the top-segment, this study shows the need for monitoring elderly patients in the middle-segment before they become high-cost, and tailor interventions to those who can benefit the most from them, using simple and inexpensive connected telehealth tools. Thereby, providing opportunities for both cost savings and high quality care.

Allison Orenstein

Product Manager
Philips Home Monitoring

Allison Orenstein is leading the ongoing development and market introduction of the Philips CareSage predictive analytics solutions. CareSage collects and analyzes data from multiple sources, including the industry-leading Philips Lifeline senior wearable. The first available CareSage product alerts clinicians when patients are identified at risk of hospital transport in the next 30 days, allowing physicians to intervene early and help reduce costs and admissions. Allison has more than 20 years’ experience working with healthcare information technology solutions. She earned an MBA from Santa Clara University and her BS from Northwestern University.


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Mariana Simons

Senior Data Scientist
Philips Research

Mariana Simons is a Senior Data Scientist at the Chronic Disease Management Department of Philips Research. She holds a PhD in Numerical Methods and Algorithms from the University of Nijmegen in the Netherlands. She also completed “with distinction” the Data Science Specialization at the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health. Her passion about innovation resulted in more than 50 patent applications as an author.


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Stephen Agboola

Associate Director, Research & Analytics Instructor, Havard Medical School
Partners Connected Health

Dr. Stephen Agboola is the Associate Director for Research and Analytics at Partners Connected Health and an Instructor at Harvard Medical School. In this role, he directs the evaluation and dissemination of connected health solutions, as well as leads data analytic efforts which include data mining, predictive modeling, and development and validation of algorithms. His research is focused on optimizing health outcomes by finding novel strategies to facilitate home monitoring, patient self-management as well as improving the efficiency of clinical workflows. He is also interested in finding innovative strategies to enhance the relevance and implementation of connected health interventions in real world settings.


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(T7-01) Financial Flow Analysis Through the Cost Acuity Pyramid Uncovers Opportunities for Cost Savings by Telehealth

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