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As we enter the New Year, there will be a push by the healthcare industry to use artificial intelligence and the social determinants of health data in order to improve clinical decision-making

Following a booming, milestone year, in 2021, many were ready for a fresh start. Some things, in healthcare, however, will remain the same: specifically, the importance of artificial intelligence and the social determinants of health data

During the entire pandemic, organizations used AI and data analytics tools to track the spread of disease and assess risk to patients. A crisis spurred academic institutions, health systems, and providers to develop and improve their AI and machine learning capabilities, setting the stage for even more advanced technologies in 2021.

The payers, pharmacies, and pharmaceutical companies are beginning to join providers in recognizing that social determinants of health (SDOH) have a major impact on patient adherence and clinical outcomes. At this time, health care organizations are faced with the challenge of finding ways to analyze and use this data to help patients.

Let’s Look In-Depth Below

Researchers so far in the New Year have used AI to predict the likelihood of prostate cancer recurrence, assess tumor genetics, and analyze patient brain scans. 

As the year progresses, the industry is likely to use data analysis tools to improve day-to-day operations, as well as visibility, to keep up with the demand for virtual care.

In 2021, social determinants of health data will also play an important role in the healthcare industry. Even though this information tends to be difficult to access and share, COVID-19 has made social determinants data a critical asset for organizations seeking to target interventions and stay ahead of poor outcomes.

The Impact Of Social Determinants of Health 

Most cases, social determinants of health are the conditions where patients live, learn, work and play. Moreover key elements of social determinants of health include employment, education, crime and imprisonment, healthcare access, food insecurity and pollution. 

The data sets of social determinants of health are large and complex which normally includes the census data, ICD-10 Z codes and consumer behavior data.

Looking at and predicting which social determinants make patients most likely to be at risk as a result, it can help health care organizations intervene effectively to improve outcomes for individual patients.

In 2021, a trend will continue to rise between healthcare systems and community organizations. Their collaborations became more widespread day by day.

Moreover, there are lots of social determinants of health that will have a serious impact on a patient’s wellness. Let’s take an example;

Transportation

Having transportation has an effect on a patient’s well-being because it directly affects whether or not the patient can access his or her health care. At times when patients have transportation barriers, they are less likely to attend a wellness visit, a doctor’s appointment for chronic conditions, or follow-up care.

Income

Income is a widely accepted social determinant of health because it has a dominant influence on several other social determinants of health. As, income can impact 

• Educational attainment 
• Healthcare affordability, payer status
• Housing status 
• Access to nutritious food

And numerous other domains. However, it is challenging for patients to achieve wellness because of facing limitations in social determinants of health. 

How AI Delivers Value From Social Determinants of Health Data?

It is possible for the AI to unlock value in SDOH data. This can identify patients who are struggling with SDOH-related health problems. The AI can then adapt targeted measures to help these patients better manage their health by making the most efficient use of resources in the process.

In a recent study published in the American Journal of Managed care have found that AI can perfectly predicted inpatient and emergency department use using only publicly available SDOH data such as sex, age, race, and address. In addition, this study showed that local air quality and income were more important predictors of health than age, gender, or ethnicity.

Difficult To Access SDOH Data?

Having access to SDOH data isn’t easy – you also need a team that understands the unique complexity of healthcare data.

At MED-MILES LLC, our primary goal is to use artificial intelligence to drive positive health outcomes because our programs take care gaps, compliance and quality measures into account with payers. 

So don’t be left behind just give us a call at +1 888-598-9181