Culver Stepping Down as CEO of Maine HIE

Sept. 21, 2017
Devore Culver, a well-known executive in health information exchange circles, is retiring from his position as CEO of Maine’s HIE, HealthInfoNet, after 11 years there. He will continue to serve as a senior consultant to the HIE.

Devore Culver, a well-known executive in health information exchange circles, is retiring from his position as CEO of Maine’s HIE, HealthInfoNet, after 11 years there. He will continue to serve as a senior consultant to the HIE.

“The board values Dev’s tremendous success in leading HealthInfoNet since its inception, building the organization from “a good idea” to a nonprofit seen as a national leader in the field of health information exchange,” said Board Chair David Howes, M.D., in a prepared statement. “This transition is focused on building upon the remarkable innovation and success that HealthInfoNet has achieved over the past 11 years.”

Shaun Alfreds, M.B.A., has been named acting CEO. He has served as chief operating officer since 2010. In that role he had direct oversight over the information and client services, finance and human resources. he also served as the principal investigator for all of HealthInfoNet’s major grant programs including the Regional Extension Center, the State Innovation Model Grant and the Robert Wood Johnson Data Across Sectors for Health program.

Alfreds maintains a faculty appointment in the Department of Family Medicine and Community Health at the University of Massachusetts Medical School and is a member of the Board of Strategic Advisors of the Health Delivery Institute at the Worcester Polytechnic Institute. Shaun also serves on multiple federal advisory committees dealing with interoperability. He received a Master’s degree in Business Administration from the University of Maine and is a Certified Professional in Health Information Technology.

In a May 2015 article, Healthcare Informatics’ Mark Hagland described a case study presentation Culver gave on predictive analytics:

“As Culver explained it, he and his colleagues at HealthInfoNet have been working with the leaders of a 112-bed community hospital in Maine who wanted to be able to predict events such as hospital admissions and readmissions, ED visits, and other important patient events. That hospital’s leaders recognized that ED visits and readmissions were leading to actual and de facto penalties coming from federal, state and private payers. The hospital’s leaders hoped to be able to avert such readmissions and ED visits through predicting such events in advance.

“The impact at this community hospital has been fascinating,” Culver told his audience. “They’re not in a lot of risk-based contracts; they’re doing it to focus on self-pay and Medicaid populations, because every time any one of those individuals visits them, it costs them money.”

What became clear was that, while “care managers tend to know who the high-risk people are, what they’re really interested in is those patients who are 40-percent or 50-percent probable, but are ‘moving’” from lower levels to higher levels, of risk for readmissions and ED visits. “Can you tell me who my top ten patients are who are in motion? We had to figure this out.” Culver and his colleagues began by analyzing which patients were at risk for 40 percent or greater risk for readmission, within the next three months, based on a six-month window of analysis.

Culver and his colleagues began by focusing on predicting which patients were at highest risk for readmission and ED visits. Over time, they’ve introduced disease-based predictions: which patients were at risk for developing type 2 diabetes, for having a heart a attack, for having a stroke, or for dying. As Culver noted, the community hospital client involved provides a great deal of palliative care, but was finding that they were initiating the provision of palliative care too late—thus the need to predict the probability of death.

The process has become more sophisticated over time, with Culver and his colleagues helping the hospital’s leaders to identify higher-than-expected inpatient lengths of stay, and to identify utilization trends and disease prevalence, as well as the psychosocial and socioeconomic factors that might be influencing outcomes for patients. The ability to help that hospital’s leaders combine clinical and claims data, Culver added, has been extremely helpful.

Sponsored Recommendations

Bridging the Health Plan/Provider Gap: Data-Driven Collaboration for a Value-Based Future

Download the findings report to understand the current perspective of provider and health plan leaders’ shift to value-based care—with a focus on the gaps holding them back and...

Exploring the future of healthcare with Advanced Practice Providers

Discover how Advanced Practice Providers are transforming healthcare: boosting efficiency, cutting wait times and enhancing patient care through strategic integration and digital...

Unlock Staff Capacity, Increase Safety and Reduce Operational Spend - Realizing ROI from AI enabled RTLS

Unlock staff capacity and enhance safety with AI-enabled RTLS! Join us on June 25th to learn how these systems can reduce operational spending and complexity, improving efficiency...

New Research: The State of Healthcare Cloud Security and Compliance Posture

Compliance & Security Debt Awareness Could Have Prevented Change Healthcare & Ascension Healthcare Breaches