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The Evolution of SDOH and Health Data Exchange

health data exchange
Senior Director, Market Planning

I recently provided my perspective as a healthcare solution provider to Healthcare Innovation on the topic of what the current landscape of Social Determinants of Health and health data exchange is and where I see it heading. Here are my thoughts on the questions they presented.

What does the landscape look like around the collection, storage, sharing and use of data around the social determinants of health (SDOH)?

What we’ve seen in our consulting ser­vices is the leveraging of aggregate sources of information (e.g., census data) or indi­vidual reports of challenges (survey data) as data sources today. Those types of data vary widely, as does the sensitivity around storage, sharing and use of those data points. Z codes have included categories capturing several areas for years but have been minimally used.

Recently, focus under USCDI v2 recommendations could drive increased utilization of these encoun­ter codes at the point of care, which would increase consistency of capture, thus improving utilization.

What are the biggest challenges right now in terms of systematizing data collection and analysis around data?

health data exchange

Resources are limited, and organizations expend significant resource time to implement data collection methods, often surveys, at the point of care to assess social determinants for patients. These can be incomplete, sensitive to bias and stagnant in time. For example, patients may have hesitation in admitting openly to challenges with housing or may not consider themselves unhoused because they have a place to stay at that time, yielding an incomplete picture of the risks.

Healthcare organizations typically only capture survey responses at a visit, meaning they will always represent a single point in time and leave blind spots for patients that haven’t had a visit or who didn’t have time to complete it at their visit. In addition, organizations are challenged to systematically leverage that data in patient care planning. Data entry and standardiza­tion are required to support analysis. Analytics and informatics teams are often overwhelmed with more requests than they can address, and analysis of topics that are tied to reimburse­ment or compliance will often take precedence when resources are limited.

Where are the pioneering patient care organization leaders making the most headway in figuring out how to systematize data, including work around data hygiene, data cleansing, vocabulary and terminology systematization and analytics?

Organizations with a specific focus and con­crete plan tend to make the most headway on implementing programs and leverag­ing data in a systematic way. That can take the shape of focusing on a specific set of barriers to impact (e.g., transportation, medication adherence) or limiting programs to a specific patient population. Addressing a finite set of challenges enables organizations to develop programs that can be executed, implemented and standardized. It is critical to create programs that address workflow concerns to allow for scaling and expansion down the road.

Given the need for ROI, how can Healthcare organizations equip themselves to measure the impacts and outcomes of initiatives?

To evolve programs from special projects to business as usual, organizations must focus on program evaluation. While evaluation can take several shapes, success­ful evaluation will come with consistent features: active planning for evaluation at the time of program creation; leveraging multiple data types and sources to assess a more complete picture; taking a broad view of success to include patients, the organiza­tion, operational impacts and outcomes; and having patience.

health data exchange

Organizations that take a very narrow focus, specifically looking to define success based on percent lift in a predictive model or specific treatment outcomes, are at risk of missing other positive impacts. Patient satisfaction and progression across stages of behavior change are measures that indicate positive momentum toward more measur­able changes in outcomes.

Organizational metrics like increase in successful contacts with a patient, increases in referrals and resource utilization, can be leading indica­tors of future success. What is important to remember in all cases is consideration of both near-term and long-term goals through vari­ous lenses for a broad view of success.

What will the landscape around all this be like in a few years?

The landscape will be impacted by two fac­tors and the associated incentives:

  1. How successful organizations can implement and standardize programs.
  2. The continuity of policy/legislative focus on, including consistent use of Z codes to classify barriers on medical claims and within EHR systems.

Organizations today are interested in considering and evaluating more so than necessitating programs. As an industry, we must continue to prioritize the development and execution of programs for better patient outcomes with favorable fiscal impact. To explore further, register for our Nov. 18th webinar, “Social Determinants of Health and Health Data Exchange.

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