4 Ways to Use Social Determinants Data in HealthcareReading time: 5 minutes
Social Determinants of Health (SDOH) are factors outside of medical treatment that influence a person’s wellbeing. These are typically economic, geographic, and behavioral factors, and they can be unique to an individual or shared among populations. SDOH data makes it possible to gather a complete, holistic view of each patient.
SDOH data is increasingly being seen as a critical part of comprehensive treatment. But just collecting and reviewing this data isn’t enough to lead to actionable insights.
The wide and varied sources of SDOH data make organizing and cleaning it a top priority. Next, predictive modeling will ensure you’re getting the maximum insights out of the data. Finally, making the data and modeling results accessible to colleagues and stakeholders inside and outside your organization is critical to putting it to use.
In this post, you’ll find suggestions on how to gather SDOH data and ethical guideposts on how to put it to its best use.
Examples of Social Determinants of Health
- Financial Stability
- Access to transportation
- Educational Opportunities
- Neighborhood and Physical Environment
- Community and Social Structure
Resources for Social Determinant Data:
The first step in putting SDOH data to use is collecting it. Here are several resources for commonly used SDOH data points:
- The US Census for generalized, location-based data to cross-reference
- The CDC’s list of Social Determinant data tools
- The Robert Wood Johnson Foundation’s resources for gathering SDOH data
- The Institute for Health Metrics and Evaluation’s SDOH visualizations
- The National Association of County Health Officials’ SDOH resource list
It’s also recommended that you contact your local municipality, as they may have data specific to your city or town.
With access to the right data, let’s explore how to integrate the data with analytics to incorporate it into an overall health plan.
Ethical Use of Social Determinants Data
The eHealth Initiative released a paper developed from the findings of a panel of health experts on the impact of Social Determinant data on health, explaining how to use this data to improve health outcomes for patients while maintaining and respecting privacy.
Below are four ways the Initiative recommends using SDOH data, along with tips on how a data analytics platform can help complete these objectives:
1. Identify Gaps in Community Resources
Issues like lack of access to transportation, healthy food, or education are a concern in many communities. SDOH data from the sources mentioned above, along with municipal data and records from community organizations, can map out what resources do and don’t exist in a community, allowing organizations to take initiatives to plug any gaps. By tapping into SDOH data, you can identify what services the community needs but lacks, and what exists but is underutilized.
Organizing this vast amount of data is paramount to making it actionable. National, municipal, and organizational data is collected in different formats and to varying degrees of comprehensiveness. It takes a great deal of work to collate and append data manually, particularly if some of it is stored in a spreadsheet, some in a database, and some in a Word document. It’s also important to clean the data, replacing null values and standardizing formats.
A data prep solution makes this process much more straightforward by removing much of the manual labor from the process. It creates a replicable process and never alters source data, so when you need to integrate data from an additional source, you can drag and drop the new data into the existing saved process.
2. Assess the Impact of Interventions and Services
Tracking the success of initiatives is the only way of verifying if they’re succeeding, on both a macro and micro scale.
According to the eHealth Initiative report, “Stakeholders should measure and monitor SDOH interventions and their correlations to better health outcomes, specifically whether the intervention positively impacts the SDOH needs and their related health outcomes.”
Sharing this data with stakeholders, both within your organization and with outsider partner organizations, is critical to making use of the information. With a cloud-based data sharing solution, anyone in your organization can access the exact, up-to-date data they need in the form they prefer. They can then download and share reports with partnering organizations to keep everyone abreast of developments.
3. Forecast Outcomes to Develop Health Interventions
Analyzing the impact of initiatives is critical, as mentioned above, but predictive analytics allows you to take this information a step further and forecast future outcomes based on health histories and Social Determinants.
That same eHealth Initiative paper states: “By leveraging their SDOH data, a healthcare stakeholder may be able to predict if an individual is at an increased risk of a certain adverse health outcome, such as being readmitted to the hospital or not adhering to a medication regimen.”
With SDOH data on-hand, caregivers can use predictive modeling to forecast future outcomes for patients based on commonalities they share with past patients. Predictive modeling can flag patients who may need interventions like help with transportation to make it to scheduled appointments.
4. Use Analytics to Match Patients with Health Services and Customize Care
Based on an individual’s health profile and significant Social Determinants, predictive analytics can determine what health problems a patient is at risk of developing. This information can be used to make suggestions to patients about services they may want to take advantage of, whether it’s health and nutrition counseling or mental health instruction.
Perhaps due to age and a pre-existing injury, there’s an 85% likelihood that a patient will need in-home service or medication delivery. Predictive analytics identifies these trends and makes them available to you. You can then bring these suggestions into a conversation with the new patient or client to help guide their decision-making about the future.
Ultimately, the decision is up to the individual patient and his or her caregivers. However, the insight provided by predictive modeling makes the decision a more informed one. A predictive model can highlight treatment options that a patient or caregiver may not have thought of on their own.
Social Determinants of Health provide a broadened perspective into the behaviors and communities of patients and clients. This more comprehensive understanding allows caseworkers and healthcare professionals to make informed, targeted decisions alongside the individuals they help.
Using the right data analytics platform, you can organize data from several sources, even if it’s stored in a variety of formats. You can then use that data to create predictive models to guide decision-making and provide patients with data-backed predictions about their health outcomes. Finally, you can share data and predictions with colleagues and partnering organizations to enable collaborative care.
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