There is a lot of focus on how the social determinants of health data—strongly linked to patient outcomes—are used in real-world healthcare scenarios with many researchers focusing on the lack of standardization and the barriers it presents to health fairness.
Because it was not clear whether SDOH data is routinely collected and would facilitate exchange if captured in a structured format, the Office of the National Coordinator for Healthcare Information Technology used nationally representative survey data from the American Hospital Association’s 2022 Information Technology Supplement to gain insights about otherwise. Federal acute care hospitals collect and receive data about patients’ health-related social needs and how the data is used, according to the instructions Last month of ONC.
The agency found that 83% of acute care hospitals in the United States collect at least some SDOH, while 54% do so routinely. It also found that the top three uses of SDOH data are to inform clinical decision-making, discharge planning and making referrals.
While ONC focuses on measuring providers’ use of screening tools to identify opportunities to “increase the use of certified and standardized screening tools that align with CMS guidelines,” using artificial intelligence and natural language processing to incorporate SDOH information—as well as mental health and cultural factors—can help improve recovery after acute, according to new research from the NorthShore Department of Cardiology and Laguna Health.
Their research looked at how patients with cardiovascular disease admitted to hospital under a café management program that uses SDOH data but also takes into account the “life context” to benefit from behavioral and emotional support improve patient outcomes in the first 30 days after discharge. from the hospital.
the Research reportpublished in Journal of Health Care Management The July/August edition found significant cost savings among those patients who received additional support — $1.1 million versus $2.0 million — and a significantly lower average cost per readmitted patient — $44,052 versus $91,278.
Speak with Dr. Mark Lambert, MD, vice chair of cardiology at Northshore Healthcare Information Technology News on how addressing the life context—considerations beyond the patient’s SDOH—helped reduce total readmission costs among study participants.
Q: While screening can help healthcare organizations understand a patient’s health social needs, the effective use of the data collected was a challenge. How does focusing on the “context of life” improve the provider’s understanding of the emotional, behavioral, and social factors affecting patient health and ultimately improve utilization?
a. The life context allows the provider to understand the unique circumstances of each patient, which includes their social, financial, behavioral, and medical context.
These factors are often barriers to patient recovery that go undetected during hospitalization, in the discharge process, or at the brief follow-up visit with a physician.
s. How was the behavioral and emotional support tailored to the needs of the individual patient in the study?
a. When the patient engaged with a Laguna trainer, an assessment of their behavioral and emotional needs was performed and barriers to recovery were identified. From there, strategies have been used to overcome barriers or to provide professional guidance if needed to deal with each patient’s unique situation.
Q: The study indicates that the intervention is replicable. How will technology help scale this approach?
a. The intervention is aided by technology to alert coaches to their identification of barriers to recovery. Conversations are transcribed in real time using natural language processing, and artificial intelligence analyzes the conversation in real time.
When certain words are identified by the AI during a conversation as potential barriers to recovery, the coach can be alerted and prompted to follow up on the subject during the conversation. This will result in a checklist of barriers that the coach and patient will identify, working together on solutions.
Q: How does AI help improve the effectiveness of virtual care management platforms?
a. AI allows for consistency when an intervention is scaled up to a large number of trainers with a wide range of training and experience.
The software used by the Laguna intervention can be used to train the trainers, document the conversations and findings of the trainers, and facilitate the effectiveness of the interventions.
s. Other than testing interventions to improve the hospital-to-home transition, what are some other areas of care delivery that could benefit from individualized care provision using virtual platforms?
A: The intervention could have a wide range of applications, including chronic care management of diseases such as congestive heart failure, chronic pain, diabetes, chronic lung disease, etc.
Andrea Fox is Senior Editor, Healthcare News for IT.
Email: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.