Toward Better Meds-to-Beds Programs

May 16, 2017

Article

Technology is creating a system to identify patients in need of medication help at discharge.

New technology could help pharmacists identify patients at high risk for nonadherence before they leave the hospital.

Nonadherence, particularly immediately after discharge, continues to be an obstacle for the health-care system and has been linked to higher readmission rates, greater costs, and worse health outcomes.

However, by using new technology and intervention strategies, health systems can partner with on-site ambulatory care pharmacies to improve the success of meds-to-beds programs and plan specific targeted interventions that are focused on those patients who need it most.

On-site ambulatory care pharmacists often have the skills and resources necessary to help position high-risk patients for success after discharge, but in many cases these pharmacists may not be used to their fullest ability.
“[Health systems] have a tremendous resource of having a pharmacy on campus and yet, in many ways, this resource really isn’t being leveraged as a hub for med adherence,” says Neil Smiley, CEO of Loopback Analytics, a software service platform.

To help target patient interventions, Loopback Analytics uses data analytics to identify patients who are at high-risk for an adverse outcome. These data integrate hospital electronic medical records, information from prior hospitalization, discharge medications, and patient fills. They can then be used by pharmacists to identify patients within a hospital who may benefit most from extra attention or interventions before they are sent home.

“You’ve got an opportunity now to engage with them and set them on the right course before they transition to their next care setting, wherever that might be,” Smiley says.

On-site pharmacies typically don’t have the resources to provide extra counseling and support for every patient, but by targeting those who are at the greatest risk for nonadherence or other concerns, pharmacies can use their resources in the most effective manner.

“Doing a meds-to-beds program, you’ve got a limited number of resources-obviously, they cost money. If you have a pharmacy tech who is rounding at bedside-if you use that resource indiscriminately, then you are not really going to be getting to the patients who are most in need,” Smiley says.

Reducing readmissions

Pharmacies that have used this more-targeted approach in their meds-to-beds program are already starting to see success.

The University of Tennessee Medical Center started a pilot program using the technology in mid-September as a strategy to improve their concierge service or bedside delivery program.

Prior to the pilot, the medical center had a concierge program, but they weren’t identifying specific individuals and were relying on nurse referrals or patient knowledge of the program to foster participation.

“We weren’t getting any huge buy-in and we weren’t really targeting anybody,” says Troy Rebert, DPh, Assistant Director of Pharmacy for the University of Tennessee Medical Center.

Up next: How the program helped patients

With the help of Loopback Analytics, they were able to identify high-risk patients who could benefit most from more personalized attention from a pharmacist. Once the patient was identified, a pharmacist reached out to the patient during a hospital stay to see whether he or she wanted to participate in the program.

“If they are interested, we’ll put them in the program, talk to them a little bit more about their medicines at that time. When they discharge, the prescriptions are sent down to us by our staff. We have a pharmacist, again, deliver the meds to patient [and] counsel,” Rebert says.

Typically, the team also tries to do a follow-up call with patients after discharge to check on their progress and help address any problems or concerns a patient may have.

During the patient education and counseling session, the pharmacist also asks patients about their copays or how they plan to pay for the medication so they are able to address any financial obstacles to care.

“There’s a lot of patients who probably would go home and maybe not mention to somebody that they can’t afford their medications. So we know that upfront,” Rebert says.

Using Loopback Analytics also helped the pharmacy strategically use their resources to help those in greatest need. Due to the size of the hospital, Rebert says it’s not possible to have a pharmacist spend additional time with every patient.

The information helps the pharmacist limit the extra attention to those patients who are very sick, have risk factors that make their readmission more likely, or who are less likely to fill their prescriptions. ”We can get a few more touch points on them with pharmacists and really hammer home the concept and the idea that if you not taking your medicine you are going to come back,” he says.

Since the program began, the medical center has seen a fairly significant reduction in readmission rates. “It has had a tremendous effect so far,” Rebert says.

Kim Mason, PharmD, Director of Pharmacy for University of Tennessee Medical Center, says the program also has been very well received by patients. According to her, the program has a very high rate of reuse by patients.
“The hospital at large has tried other predictive analytic tools that frankly weren’t as successful, particularly for targeting medication risk points. So we’ve been glad to have the tool to do that,” she says.

Smiley says Loopback Analytics can also improve an ambulatory care center’s profitability, since many of these patients typically have complex medication regimens that are usually more profitable for the pharmacy.

“They can not only be more effective with the resources, but they can run a more profitable program,” he says.
A common misconception for ambulatory care pharmacies, he says, is the idea that increasing volume will also increase profitability. However that isn’t the case. “If you are serving unprofitable patients you can’t make enough on volume,” he says.

Community component

Loopback Analytics offers on-site pharmacies a strategy to help patients have their medications in hand before they leave the hospital. But the help to a patient doesn’t end there.

“Part of what we do is to help ensure that there is a good coordination between that first fill that happens in the on-site pharmacy and the refill part [that] is then picked up by a retail partner out in the community,” Smiley says.

For high-risk patients, or patients who aren’t able to afford their medications, there’s a need for post-discharge care coordination so that patients can avoid readmission.

“One of the other things that our company does is support post-discharge follow-up calls in an automated way using this same kind of risk stratification approach,” Smiley says.