With so much focus being shifted to post-hospitalization care coordination, who’s the most effective provider to lead that coordination? And how do provider organizations make sure the best protocols are being employed? Perhaps it’s not providers at all who should be following up with patients. Instead, wouldn’t it be far more efficient to deploy the scores of already existing home care workers, or other nonclinical care teams?
Care at Hand, a Boston-based startup, is focused on just that, deploying care teams for such coordination. But it’s not just providing home care, it’s using technology and data to determine which patient’s are most at risk for readmission and then intervening with the appropriate response and whether the patient warrants a visit from a nurse or from a nonclinical worker.
“The real setting of health is in the home and the community,” Care at Hand co-founder and CEO Dr. Andrey Ostrovsky said. The thrust of Care at Hand, which was incubated by Rock Health, is relatively straightforward but nevertheless elusive in healthcare.
“What if we digitized this hunch of the community health worker, combined with an empathetic, nonclinical care worker with the supervision of a clinical person?” Ostrovsky said.
If the community health worker knew what to look for in determining who’s the most vulnerable for readmission, that would go a long way in curbing costs in what Ostrovsky called “a blind spot” in the healthcare system. That’s where the data and mobile technology come in.
In a pilot project with four hospitals in Merrimack Valley in Massachusetts, the nonclinical health coach visited with the patient before they were actually discharged. Using mobile tablets, trained health coaches then visit recently discharged patients, typically elderly and on Medicare. Those determined to be medium-to-high risk for readmission receive a home visit within 48 hours and a weekly phone call.
During each interaction, the coach used the tablet-based application, which is pre-loaded with suggested questions, written in lay person language, based on the patient’s diagnosis. If the answers indicate a decline in health status, the system sends a real-time alert to a nurse care coordinator who uses a different part of the system to help the patient and coach address the issue within 24 hours.
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A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
The challenge, Ostrovsky said, was determining how to come up with with accurate metrics and standards for the questions asked by the community health worker.
“Our technology is community health workers – how accurate can they be in predicting hospital readmissions? There was so much variability in having nonclinical workers do this,” he said. “We couldn’t parse out signals from noise. It literally took thousands of surveys. We actually had to make it clinically relevant. We had to make sure that what we’re proposing is 15 nonclinical questions that should be paid attention to.”
Using existing data and published materials on best practices, Care at Hand incorporated that into software that helped devise the questions.
The software deployed by Care at Hand, for example, will prompt a health coach to ask a patient with congestive heart failure about weight gain or shortness of breath – both potentially key indicators of readmission.
“Algorithms are able to anticipate what will likely be the reason they’ll go to the hospital,” Ostrovsky said.
Care at Hand is already working with several hospitals, and payers are increasingly interested, Ostrovsky said. Skilled nursing facilities and home care agencies would be a natural fit, too.
Earlier this year, it raised $875,000 and has raised a total of $1.4 million to date.
In it’s pilot project with the Massachusetts hospitals, the results were telling: 30-day readmissions were reduced by nearly 40 percent among high-risk patients with a health coach compared to patients with coaches who didn’t used Care at Hand software.
That generated savings on average of $109 per patient per month – with gross savings of $600,000 and net savings of about $370,000 over a six-month period involving 561 patients.
“The problem is there hasn’t been evidence that community workers can be effective,” Ostrovsky said. “Now that’s changing.”
