In today's competitive environment, when profit margins are razor thin, providers are well aware of the old sales training adage that it is easier to keep a customer than to win a new one. The expense, however, of keeping in touch with every discharged patient is prohibitive, when all that is really necessary from a marketing and census building point of view is to keep in touch with those discharged patients who will one day need in-home services again. But how does one know which patients those are?
When a Medicare patient meets treatment goals and is discharged from home healthcare, that patient may never been seen again or he or she may return for another episode of care one day in the future. Providers of healthcare at home services would like to keep in touch with the patients who might need their services again, both to keep a casual eye on their progress after discharge and to remain top-of-mind when the time comes. The problem is that they never know who will return and who will not. That may no longer be a serious dilemma, thanks to a new way of using an existing data analysis system.
Until now, the answer has been that there is no way to know. A provider's choices were to bear the expense of calling every discharged patient periodically or just sit back and hope that they will remember your name if and when they need you again. What has changed is a new way of looking at data, the data already in home health EMR software.
Dan Hogan had the problem presented to him by users of his data analysis system, Medalogix. "Several of our customers explained to us that readmissions are an important issue, as it pertains to patients moving from our care to hospitals," the CEO told HCTR. "'We know that our patients may use several home health episodes,' they would tell us, 'but, if those episodes are not contiguous, they may not remember us.' So we began to think about using our data analytics tool in a new way."
Previously, Medalogix products, Touch and Bridge, had been used to analyze years of OASIS data to identify patients at risk of hospital readmission or pinpoint when the time has come to move a patient from home healthcare to hospice. "By pointing the system's functions toward a new way of looking at the same data," he continued," we were able to determine the signs common to patients who come back to home healthcare after discharge. "We were identifying what we call 'elevated probability,'" he said.
"The new product, to be known as Nurture, was released after two years of thinking about how to help clients scale both programs," Hogan continued. "We went out into field in the fourth quarter of last year and let clients test the tool. We took the templates of our other two tools to risk stratify patients who have returned to home care in the past. Now with the ability to see that predictive analysis, which it turns out is quite accurate, clients can dedicate post-discharge contact efforts to a smaller subset of patients. Instead of reaching out to everybody, they can target the top 25% to 30% most likely to need them again.
Citing some encouraging early results, Hogan explained that the new product's goal is to maximize "patient continuity." A provider that serves patients in Texas and Oklahoma ran a pilot in five of its branches. This customer told Medalogix that they had an existing program of post-discharge contact and it was running well. "We came in with Nurture," Hogan remembers, "and they generated 16 new admissions in the first three weeks, simply by calling the top 25% of patients discharged in last 45 days, dramatically improving their recapture rate."
Predictive analytics of this type may be in the "nice-to-have" category this year but Hogan believes that it will be a critical differentiator once Medicare's readmission penalties expand from hospitals to post-acute providers in two to three years. Nurture is available now and will be priced at $3 per patient per month, a price that will decrease as volume increases.
©2015 by Rowan Consulting Associates, Inc., Colorado Springs, CO. All rights reserved. This article originally appeared in Tim Rowan's Home Care Technology Report. homecaretechreport.com One copy may be printed for personal use; further reproduction by permission only. firstname.lastname@example.org