10 May Home Health Care and Predictive Modeling: Reducing Unplanned Rehospitalizations
[row][col sm_width=”10″ sm_offset=”1″]Accountable Care News (column by Tessie Ganzsarto and Dan Hogan)
Home health care is changing. A galaxy of powerful new technologies is redefining the home care experience for patients, providers, and families alike. Home care agencies must strive to put this new technology to meaningful use. Data and analytics are not just immovable numbers and statistics on a page – they hold the key to reducing patient hospital readmissions, improving patient outcomes, and crossing the threshold into a higher quality of care. Across the health care sector, the sweeping changes of a new era of Federal mandates for improved patient outcomes, reduced reimbursements, and shared risk are forcing hospital systems and home care agencies to build stronger partnerships in ACO and ACO-like models and in initiatives specific to reducing unwarranted readmissions.[/col][/row]
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With the imminent retirement of the Baby Boomers over the next 15 years, the number of patients needing home health services will grow at an exponential rate. And because these patients will be Baby Boomers – defined by their expectations of aging with amenities – they will demand and expect to be cared for in their homes instead of a nursing facility. Home health care services are patient-centered, after all. It is natural for a patient to prefer to be in his or her own home, where care can be personalized and consistently monitored.
The tech firm Medalogix, a Nashville-based company, emerged from the idea that homebound patients would benefit from a more in-depth analysis of the risks associated with their conditions and medications, and that home care agencies – when armed with that information – would be better able to remediate that risk. A litany of studies has shown that patient outcomes are far better at home than anywhere else for a variety of clinical conditions.