Role of Technology in determining SDOH
Efforts to improve health in the U.S. have traditionally looked to the health care system as the key driver of health and health outcomes. However, there has been increased recognition that improving health and achieving health equity will require broader approaches that address Social Determinants of Health (SDOH) that influence individuals' health.
What are social determinants of health?
Social determinants of health (SDOH) are the social and economic circumstances of an individual that affect a wide range of health. These circumstances are where people are born, grow, live, work, age as well as access to healthcare
Social Determinants of Health (SDOH) was a new concept a few years ago but today, healthcare payers and providers are taking initiatives to incorporate SDOH factors to predict the impact on an individual’s health. There are five factors that contribute to a person's state of health:
- Biology and genetics such as sex and age
- Individual behaviour such as alcohol use, smoking, drug use, and unprotected sex
- Social environment such as gender, unemployment and job insecurity, discrimination factors
- Physical environment that includes work life conditions, Housing, basic amenities
- Health services such as access to healthcare and having or not having health insurance
In fact, researchers at Massachusetts Medical Society have estimated that your overall health is determined by individual behaviour (40%), genetics (30%), social circumstance (15%), environmental factors (5%), and healthcare (10%)
Importance of SDOH
Payers and providers can definitely benefit from a comprehensive health record that integrates SDOH information to connect patients with community resources that address unmet social needs. Healthcare organizations understand that SDOH factors can improve minimize medical costs. By having SDOH information accessible at the place of care, doctors and other healthcare professionals have a comprehensive view of the patient, enabling them to approach care holistically and deliver the best care possible.
Challenges in Identifying and Integrating SDOH
Data Collection and Sharing
A lack of standardization in data collection and sharing has significantly impacted organizations’ ability to address the SDOH.
Finding the Time and Tools to Address SDOH Data
Although providers recognize the important role social determinants play in overall health, many still lack the time and resources necessary to adequately address their patients’ social needs.
Unfortunately, healthcare ecosystem even today operates in silos, with interoperability a current challenge. A lack of industry standards makes it difficult to collect and share this essential information between payers, providers, members/patients, and community resources which are capable to address social factors directly. Hence, the efforts are ineffective to capture and integrate SDOH data across the healthcare ecosystem. A 2019 Dartmouth study showed that only 24% of hospitals and 16% of physician practices in the U.S. reported screening for SDOH factors like food insecurity, housing instability, interpersonal violence, transportation needs, and utility needs.
Unlocking the Value of SDOH with Technology
Technology can make it possible to collect and synthesize data from different sources and in different forms (structured and unstructured).
SDOH broken down into three distinct stages: identification, integration and application. Identification comes first, as care teams need to pinpoint the specific SDOH factors that are relevant to a given case.
Next comes integration.A big chunk of the industry is still trying to figure out how to best utilize social determinants, and many organizations are developing libraries of responses to those factors. There have also been grants issued by the Centers for Medicare and Medicaid Services and other agencies to help shepherd these factors into quality formulas. The goal is to integrate those into the health system so providers can understand the risk involved and the impact of all of these different SDOH factors.
Then comes application,and where AI is concerned, that's where the rubber truly meets the road.
Artificial Intelligence (AI)
In the new year, the healthcare industry will leverage artificial intelligence and social determinants of health data to enhance clinical decision-making.
SDOH(unstructured) data can be captured and integrated into longitudinal health records for individual patients. Digitization of the unstructured data sets using Artificial Intelligence (AI) algorithms can provide a wealth of information for enhancing the longitudinal health record of the patients. AI can be used to detect SDOH factors in EMRs, which can then notify providers and care managers in real time. Machine learning will be one of the most important technologies for success. Machine learning (ML) can then be applied to build models for patient medical and social risk scores, cost prediction, and patient behaviour.
These new methods to detect SDOH, leverage the unstructured data that is already present within a patient’s electronic health record as an input to a machine learning model that analyzes and predicts the likelihood the patient is at risk for a SDOH.
Natural Language processing (NLP)
Natural Language processing (NLP), where machines process human-generated data, like text or speech, is quickly processed to machine-generated data. It is reported that NLP in the healthcare and life sciences sectors is expected to grow to $3.7 billion by 2025, increasing 20.5% annually. Second, roughly 80% of healthcare data is unstructured. Now, advances in NLP and its integration into healthcare is providing a way to translate human language into actionable data. Healthcare organizations can use Natural Language Processing (NLP), multilingual support and translation service capabilities, to digitize this unstructured data. NLP is becoming an integral and transformative element in many EHR systems and it is forecasted to grow exponentially in the near future. Unstructured SDOH data such as handwritten notes, documents, free form text, images and audio and video recordings must be digitized and structured for use in applied analytics to provide valuable decision-making insights to healthcare professionals and other authorized care team stakeholders.
Distributed Ledger Technology (DLT)
Distributed Ledger Technology (DLT) is a protocol that enables the secure functioning of a decentralized digital database. Distributed networks eliminate the need for a central authority to keep a check against manipulation. One way to ensure authorized disclosure and use of SDOH and other healthcare data is to leverage distributed ledger technology (DLT) for secure and permissioned sharing in near real-time, and at a granular level. This approach ensures the reliability of the data and its source(s), providing the transparency necessary for decision-making. It also ensures that the concerned parties are seeing the same data without any need for reconciliation.
Remote patient monitoring Provides Actionable Insights
The most important currently available technology is mobile. Once patients do participate, providers can start to glean more information about patients. Face-to-face interactions via remote patient monitoring (RPM) don’t only involve faces. RPM allows care to focus on factors that may negatively affect a person’s health that are not controlled inside the hospital. Through phone and video conferences, doctors gain perspective on a patient’s life and step in when needed. Also, virtual care allows doctors to see every aspect of a patient’s home setting, which can help assess health issues that a patient might not otherwise reveal.The most important currently available technology is mobile. Once patients do participate, providers can start to glean more information about patients. Face-to-face interactions via remote patient monitoring (RPM) don’t only involve faces. RPM allows care to focus on factors that may negatively affect a person’s health that are not controlled inside the hospital. Through phone and video conferences, doctors gain perspective on a patient’s life and step in when needed. Also, virtual care allows doctors to see every aspect of a patient’s home setting, which can help assess health issues that a patient might not otherwise reveal.
Just as different data systems need a way to communicate with each other, different SDOH stakeholders must be able to securely exchange information. A next-generation integration engine that provides end-to-end secure communication capabilities for B2B and B2C using protocols like Email, SMS, MMS with extensions to widely used instant messaging software can eliminate communication barriers among health plans, hospitals, clinics, social service agencies, and patients.
Identifying and implementing social determinants of health (SDOH) data into the EHR is critical to finding answers to a state’s most significant issues. Though we have datasets available to us through the federal government or through local organizations and local community groups, that data is often not brought into the EHR system. HIEs are accepting the challenge of integrating SDOH. Many
healthcare institutes partnering with these HIE’s to add behavioural health data such as SDOH into HIE’s and then into EHRs.
KPi-Tech Services has interface engineers and architects with profound experience in Healthcare IT Services. We can help HIEs, Healthcare organizations and providers to build highly customizable integration solutions to bring SDOH into the EHRs