Social determinants of health account for 80% of health outcomes. From here on, it becomes significant to assess the overall impact of ‘social factors’ on population health and outcome measures. Since reducing cost and utilization is the primary goal of healthcare, it warrants a deeper understanding of factors directly or indirectly affecting patient’s health.
In the current care ecosystem, taking precautionary measures is better than curing disease. But more often than not, the efficiency in these processes can be questionable. Delivering care to any patient population should start by understanding each patient individually. One of the best practices is to understand the patient’s medical history alongwith the environment surrounding him. Whether the patient is a smoker? Does he have any unhealthy habits? Is his environment hygienic? Point being, there are a whole lot of markers that can paint a picture for the care community to treat the patient in the most suitable manner.
The social determinants of health (SDOH) have proven to correlate with health outcomes and risk factors. And there is already an abundance of data, then how can one leverage it? Even if we focused on just the most basic SDOH like community life, unhealthy habits, neighborhood, socio-economic environment, and education, that would still be a lot of data.
What would be the roadmap from this data to better care outcomes?
Is it a promise or a hype?
Many chose to ignore SDOH, some adopted it, but who has succeeded so far?
A careful examination of the graph given below shows the effect of an additional four years of education on individuals. The use of education as an indicator of health behaviour seems to have had a positive impact on the sample population. The data clearly demonstrates that the health risk of individuals who had more education considerably went down, than the ones who went without the extra four years of education.
Source: Robert Wood Johnson Foundation
SDOH materializes its promise in the form of these interventions which should be of interest to health care policymakers and practitioners seeking to leverage social services to improve health or reduce costs. Timely interventions in the areas of housing, income support, nutritional support, and care coordination and community outreach through community health workers (CHWs) have had a positive impact on population health.
Given the new entrance of such data in the healthcare realm, people have been slow to adopt it fully. However, SDOH has demonstrated immense promise in terms of population health and outcomes measures. It would be safe to conclude that SDOH is less hype and more value.
Impact on population health:
Call it social determinants or social factors, but in the interest of “public health,” “population health,” and “health promotion”, the most vital factor is the inclusion of social determinants data in population health management. The need for integrating SDOH into the population health workflow has become pertinent as the healthcare system’s responsibility expands beyond the clinic walls and into the community.
The most significant aspect of improving population health is identifying and stratifying high-risk patients. Including people’s social determinants data will make the analysis more accurate and the reports more comprehensive. Moreover, developing personalized care plans helps reduce readmissions rate and visits to the emergency departments.
In the case of economically and socially disadvantaged population it has been observed that assigning them community resources has been more effective and efficient than a visit to the hospital.
Take, for example, an elderly woman who returned home following a heart attack. Her physical therapist discovered during a home visit that the woman had no food and no family members or friends to bring her food. What she needed was community resources to ensure food security. Once alerted by the therapist, the woman started getting regular meals and her chances of recovery increased considerably thereby, avoiding a readmission in future.
Thus, it is only when providers stay connected with patients, their community, and their support systems, they help them stay healthy in a vulnerable environment.
Turning SDOH data into actionable insights:
Working with SDOH data requires a more drilled-down approach and the use of predictive analytics to accurately measure the at-risk population and to advance preventive care methods in an ecosystem.
In order to drive outcome insights, it is important to identify the unique identities of patients. Analyzing the risk score of patients using SDOH as well as utilization data can increase the accuracy of the result. Drilling down to census and zip level to understand vulnerability of population should be the first step. After that, working on a care plan would be a better idea than to just deliver care as there is a high possibility that a patient would fall sick again on account of his/her poor environmental conditions.
Best practice to leverage SDOH
Taking into consideration the shortcomings of the current approaches for risk analysis, Innovaccer’s Data platform seeks to apply key best practices for the successful integration of SDOH with other data. Some of the key features include:
Innovaccer’s key offerings for Social Determinants of Health
Innovaccer’s healthcare data platform is built with the aim to improve healthcare efficiency. The platform analyzes which social determinant of health impacts patients and drills down to every measure at national, state, and county level and strives to paint a clearer picture for care teams. It brings together county-level data for every social determinant of health and puts it together to help providers figure the impact of various SDOH and track the performance of each county, against the national and state average.
The road ahead
When 80% of the health outcomes are dependent on SDOH, we need to make the most of it. Maybe we can revolutionize the care continuum with the power of SDOH data. What if an individual needs a community care instead of hospital admission? What if we can predict the outliers by transforming raw utilization and SDOH data into a predictive model?
The era in which we are, we definitely do not have to cure diseases. That was the traditional practice, today we need to predict and prevent. The modern triple aim of healthcare needs modern steps and technology to be accomplished. Being smart and staying ahead should be the norm of the 21st century. We have the the right technology, we just need to apply it at the right place and at the right time.
To learn how you can leverage SDOH data to advance the goal of population health, get a demo.
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