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Breaking Through the Social Determinants of Health Data Barriers
The global population health market is expected to reach $91.4 billion by 2026, up from just $21.4 billion in 2018. Those in the health care trenches understand that this is due primarily to the growing shift from fee-for-service reimbursement to value-based care. As providers and payers move deeper into population health and value-based case, one thing is clear—they need to be much more strategic in how they tackle social determinants of health (SDoH). They need to have a new look at broader industry partnerships and programs, as well as advanced technology solutions.
For the last two decades, stakeholders across the health care spectrum, including providers, payers, health care IT companies, public health agencies, community organizations, and more, have been rolling out services, programs, and funding to address the key social risk factors and social needs impacting patients’ lives. From hospital-sponsored food banks and transportation programs to payer housing initiatives, and big pharma programs that provide free prescriptions, the health care industry is stepping up its game to improve patients’ health and well-being.
Research shows that SDoH contribute 80% to 90% of a person’s health outcomes versus medical care. The health care industry is spending billions on solutions. According to a Health Affairs research article, 917 US hospitals alone spent $2.5 billion between 2017-2019 on SDoH programs.
Social Risk Factors Intersect With Population Health
Social risk factors and needs have a tremendous impact on population health, especially for patients with chronic conditions. Health care organizations must consider the leading SDoH risk factors when implementing population health initiatives and value-based care programs.
For example, a Kaiser Permanente national survey on social needs in America polled over 1000 US adults “demographically matched to represent the US population based on Census data,” finding that more than a quarter had “endured health risks stemming from unmet social needs.” Additionally, according to the research, those who reported an unmet social need in the previous year were “twice as likely to rate their health as fair or poor,” compared to those who did not experience an unmet social need.
How does this translate to managing population health and value-based care programs? Consider this, food insecurity, one of the most reported social needs, is more prevalent among those with certain chronic health conditions. For example, a journal review of current research on food insecurity and diabetes self-management found that when individuals with diabetes face challenges accessing sufficient food, they have greater difficulty making food choices aligned with their diabetes care program.
It is no coincidence then that the intensifying interest in SDoH has paralleled the growing interest among providers and payers in value-based care and population health, which ultimately work hand in hand to improve patient outcomes while lowering health care costs. Understanding and accounting for the impact of SDoH across these two areas is critical.
Managing SDoH data requires providers and payers to work together in new ways to develop a holistic care approach for patients and plan members that encompasses health and lifestyle, education, social services coordination and referrals, and population health initiatives. SDOH data is vital to providing the 360-degree view of individuals and specific populations that allows VBC and population health to succeed.
This SDoH data needs to be analyzed with external data sets that cover the 12 dimensions of Social Determinants as laid out by the CDC in its study. These comprise of data sets in the dimensions of: Economy, Employment, Education, Political, Environmental, Housing, Medical, Governmental, Public Health, Psychosocial, Behavioral, and Transport. Analysis of patient data along with these external datasets provide the insights that are needed to build out initiatives to address the SDoH issues at the local level.
Breaking Through SDoH Data Silos
Providers and payers know this, but they still struggle to fully harness SDoH data to manage patients’ and members’ health proactively. Technology and cultural barriers across an expansive array of SDoH stakeholders have traditionally impeded the flow of information, resulting in vast data silos. While patient information flowed more freely between providers, payers, and community organizations during COVID-19, data access problems continue to slow patient care coordination and referrals to key community services such as food, housing, and transportation.
There are technology challenges in securing and managing patient permission to share this data. For example, the underlying technology must have consent management capabilities that include an audit trail of disclosures to ensure patient-permissioned data sharing. Technology platforms must also support communication channels – such as mobile apps, secure text, audio, and video – that obtain and manage consent.
To resolve the barriers to preparing a patient Longitudinal Healthcare Record (LHR) and sharing it in a secure, permissioned, and scalable manner, five things are needed:
- Digitization of the unstructured datasets—just storing unstructured data as is (in the form of charts/notes, PDFs, video/audio, documents) and rendering them as is won’t solve the issue. It requires a proper Artificial Intelligence/Machine Learning application to digitize that data including the medical facts using something like Unified Medical Language System (UMLS). The data needs to be made searchable.
- Amalgamation of the unstructured data with structured data into the ontologies so that proper categorization (and sub-categorization[s]) can be done. If this is not done, we are not really solving the problem.
- An Enterprise Master Patient Index (EMPI) solution that ties all these together properly with a very high accuracy.
- APIs that allow for ease of access in a secure manner to help with interoperability, and
- A platform that can disseminate information in real time, with 100% accuracy and on a permissioned basis so that entire the LHR or portions of the LHR (records/sub-records or even just attributes) can be shared with only the entities that need to see it.
The above datasets can come from a multitude of data silos. The integration and convergence of AI, Internet of Things (IoT), and distributed ledgers is key—where the output of intelligence gleaned from volumes of data processing is delivered to the members of the distributed network in real time, based on smart contract rules defined on the ledger, hence leading to decentralized intelligence networks.
Program Administration
One way to slash through these barriers and/or challenges is by putting SDoH at the center of value-based care and population health initiatives through a program of Value-Based Benefits Administration (VBBA). A platform for VBBA operationalizes value-based benefit design while aligning in-home and community based services with physician office and hospital-based services. This programmatic approach integrates the flow of information between traditional health care providers, payers, social services, and community-based organizations.
VBBA aligns the distinctive but complementary functions of value-based payments and chronic care programs with the sharing and communication of SDoH data. This coordination is key to achieving VBC and population health goals. In this context, providers and payers have a comprehensive view of the individual inclusive of the necessary capabilities to most impact their health and everyday lives.
A VBBA platform facilitates a more holistic patient view by accessing and aggregating data from all of the different patient data sets into a patient specific LHR, applying natural language processing for digitization of unstructured and semi-structured data, and supporting language translation for non-English speaking populations.
To illustrate the unique challenges in play and the power that comes from solving them, consider a simple example of a diabetic patient with no access to transportation and wheelchair accommodation requirements who would benefit greatly from an office visit with his provider. Identifying these patient attributes is something that is done today via multiple, often redundant patient touch points—ie, provider assessments, health advocate/social services screenings, payer care management programming surveys, etc. However, leveraging the collective attributes inside of the various disparate workflows does not occur because the information remains siloed within the various provider VBC systems in play, and the consent provided by the patient does not span all the interactions.
The resulting patient experience is frustrating and loaded with redundancy, with the patient being forced to provide his own advocacy to connect the dots. The caregiver experiences are no less maddening—they are left to resolve the transportation challenge via multiple, separate manual outreaches to the patient and the transportation providers having nowhere to capture the success or failure loop that occurs from providing the transportation. Thus, with each future visit, both the patient and their caregivers are doomed to repeat the same experience due to the data sharing limitations.
As an alternative, by leveraging a VBBA approach, the transportation gap identified by the social services patient encounter along with the captured patient consent is immediately shared with both the payer and provider care teams for use in future scheduling. Already being aware of the transportation gap and with patient consent passed to them, in the same interaction used to schedule the office visit, the provider also schedules the required transportation. The success and/or failure loop for the transportation is returned to the provider, along with the captured consent, and is immediately shared with the payer and social services care teams advocating for the patient. This process helps informs all future scheduling with the existence of a preferred transportation provider.
This unique data solution not only improves patient care coordination, but also offers context and information for health care organizations and practitioners to reimburse or incentivize community-based service providers. At the same time, patients receive a more personalized health care experience and access to vital resources when they need them most. In the end, VBBA offers an innovative and efficient solution for health care ecosystem stakeholders, delivers improved patient outcomes, and generates cost savings.
Disclaimer: The views and opinions expressed are those of the author(s) and do not necessarily reflect the official policy or position of the Population Health Learning Network or HMP Global, their employees, and affiliates. Any content provided by our bloggers or authors are of their opinion and are not intended to malign any religion, ethnic group, club, association, organization, company, individual, or anyone or anything.
