Informatics and Social Work Intersect Under Value-Based Care

a young female medical professional with an elderly woman in a wheel chair

The cold rationality of big data and the intuitive, people-centric field of social work may seem to come from opposite ends of the campus, or opposite sides of the brain.

However, the two prove to be simpatico partners in the development and implementation of value-based care. It’s a combination that looks to be getting a lot of use in the coming years – nearly 40% of employers plan to incorporate some element of value-based care in their employees’ health plans this year, according to the National Business Group on Health.

The value-based system rewards physicians for results and is replacing the fee-for-service model, in which providers are paid for each visit and service provided. Some blame this in part for the high cost of health care in the U.S. compared to other countries.

Data in Value-Based Care

It’s easy to see the role data will play in value-based care. Providers are incentivized to know as much about a patient’s medical history as possible.

“How do we keep people out of the hospital? How do we keep them at home? How do we make sure healthy patients stay healthy so we can maximize our resources when we have to care for the people who are sick” asked Dr. Michael Blackman, Chief Medical Officer at McKesson Enterprise Information Solutions, in an article from Health IT Analytics.

“The only way to do that is to get data in real-time – or as close to real-time as you possibly can,” he continued.  “And in order to do that, you have to take advantage of every interaction with the patient.”

The more data providers have on patients, the better able they are to anticipate issues before they arise. The better able clinicians are to anticipate issues, the shorter the patient’s stay is likely to be. Also, the likelihood of returning to the hospital is reduced. And overall, the value of a value-based care transaction increases.

The Human Aspect

Data, however, can’t do it alone. “ The best analytics and clinical care plan in the world will fall short of improving outcomes and lowering costs if the individual in need lacks the social and environmental resources necessary to follow through,” wrote Dr. Jamo Rubin in an article on the Oliver Wyman Health website.

Rubin points out that “non-clinical factors” such as income, location and level of education often have more to do with a patient’s outcome than his or her clinical care. Often times, this is referred to as Social Determinants of Health (SDoH).

This is where social work comes into the equation. Are there language or learning barriers that prevent the patient from understanding aftercare instructions? Does the patient live in a secure and safe environment? Can the patient afford medications? Does the patient have access to transportation for follow-up visits?

“Developing individualized care plans helps prevent readmissions and unnecessary visits to the emergency department during that vulnerable transition period,” Rubin wrote. “When providers stay connected with patients, their community, and their support systems, they help minimize these barriers to full recovery.”

In support of these efforts, social workers are becoming more involved in the integration of IT into the care plan for patients once they leave the hospital. According to an article from Social Work Today, an increasing number of social workers are “delving into the technical administration aspects [of care], either by contributing to projects in a consulting capacity or by working directly for population health management solution providers, where they are helping shape the development of applications and tools.”

This is important because outside of the hospital, social workers can create relationships with patients similar to what a nurse might experience inside the hospital. In doing so, these workers can create opportunities for engagement with patients that benefit both healthcare and technology companies. They can play important roles in the creation of risk assessments, program evaluations and identifying the right types of questions to ask patients in order to fuel more accurate baseline assumptions used in the development of healthcare tech.

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