Peer-Reviewed Research

Evidence has been published after external peer-review. Findings are generalizable but may have limitations.

  • AHIMA logo

    Ostrovsky A, O’Connor L, Marshal O, et al. Predicting 30-120 day readmission risk among Medicare FFS patients using non-medical workers and mobile technology. Perspectives in Health Information Management. January 2016.
    Link to Study

  • Avalere logo

    Munevar D, Drozd E, & Ostrovsky A. Correlation between Medicare A spending and hospitalization risk score using mobile technology. Avalere Independent Analysis. 2015.
    Download Report

  • Blue Cross Foundation of Michigan logo

    Call to Reduce Hospitalizations Using Phone Assessments to Predict & Avoid Hospitalizations For MI Choice Participants
    Download Report

  • AHRQ logo

    AHRQ. Service Delivery Innovation: Community-Based Health Coaches and Care Coordinators Reduce Readmissions Using Information Technology To Identify and Support At-Risk Medicare Patients After Discharge. Rockville, MD. 2014.
    View Study

  • AHRQ logo

    AHRQ: AHRQ’s Care Coordination Work Leads to Better Outcomes, Lower Costs for Massachusetts Agency on Aging. Impact Case Study. Rockville, MD. Sept 2014.
    View Study

  • Leading Age: CAST logo

    Leading Age: Center for Aging Services Technologies. Telehealth and Remote Patient Monitoring for Long-Term and Post-Acute Care: A Primer and Provider Selection Guide 2015

  • Annals of Long Term Care logo

    Ostrovsky A, Cisneros A, & Morgan A. Are long-term supports and services a logical next step in the evolution of bundled payments? Annals of Long-term Care. Nov 2015.

Emerging Evidence

Quality improvement data, presentation at academic conference requiring peer-review, or case studies. Findings require more research to be generalizable.

  • HCBS logo

    Parsons C & O’Connor L. Medicare claims demonstrating up to 20% reduction in 30-day readmissions after introduction of mobile technology. Healthy Aging Summit. 2015.

  • New England Quality Innovation Network logo

    Ostrovsky A. Using community (big) data to drive quality improvement. New England Quality Improvement Organization Educational Webinar. 2015.
    Download Presentation

  • Robert Wood Johnson Foundation logo

    Care Transitions Programs: Creating a Behavioral Health Intervention. The Robert Wood Johnson Foundation.
    View Report

Current Research

Research initiatives currently underway. No findings to report yet.

  • University of Maryland logo

    Dr. Charlene Quinn. Clustered randomized controlled trial comparing standard care coordination vs care coordination with a predictive analytics technology in a Medicaid-funded LTSS population. (Funded)

  • NORC at the University of Chicago logo

    Dr. Kennon Copeland. Retrospective comparison of 3 communities in MD, MA, and WA: Impact of a community-based care transition program using predictive analytics on Medicare A utilization

  • Human Services Research Institute logo

    Dr. Alexi Bonardi. Prospective evaluation of HCBS providers using predictive analytics technology on National Core Indicators.

  • Leading Age logo

    Dr. Robyn Stone. Clustered randomized controlled trial comparing impact of standard housing resource specialists to resource specialists using a predictive analytics technology on ED utilization in an aging population living in publicly subsidized housing.

  • SIEW Healchare NW logo

    Dr. Si-Chi Chin. Randomized Controlled Trial of Connected Care Technology and Home Care Aides.

Become A Research Partner

Evidence-based practice is just good business. We highly value research partnerships and welcome investigator-initiated proposals. Please contact with a brief statement of your interest.