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Data analytics platforms help providers find patterns pertaining to the social
determinants of health in their patient populations.
With knowledge of these patterns, providers can decipher why outcomes may differ
among patients who received the same care.
Benefits include improved care management and care coordination for patients
and better allocation of resources at the practice level.
providers take on more risk for managing the health of patient populations,
many hope to gain an edge by applying data analytics to the social determinants
of health. They recognize that social factors such as lack of housing, food
insecurity and domestic violence can determine the success of a patient’s treatment
and whether the organization wins or loses in a risk-sharing contract.
providers use sophisticated analytics programs with natural language processing
algorithms that can “read” through the unstructured data in an electronic
health record (EHR) to extract terms or concepts related to social determinants
of health, says Douglas Fridsma, MD, PhD, president and CEO of the American
Medical Informatics Association (AMIA).
common strategy is to “link” social determinants to patients through techniques
like geocoding, which associates socioeconomic factors (e.g., average income,
average housing prices, access to transportation and grocery stores) with specific
ZIP codes. Providers can then merge neighborhood data with EHR data and public
data sets to create a multidimensional view of a patient, Fridsma says.
lot of data analytics is about pattern matching: trying to find patterns in the
data to identify patients at risk of having a bad outcome and patients who have
had a good outcome to understand the process of care that potentially led to
that outcome,” Fridsma says. “If people got the same care, adding in social
determinants often can give you a better sense of what makes those two groups
of patients different.”
Providence St. Joseph Health, leaders are using analytics to identify social
conditions that impact patients’ care, access to care and overall health status,
says Rhonda Medows, MD (pictured at right), president
of population health management. Leaders have found that the four social
factors most likely to correlate to a future medical event are:
part of this strategy, leaders leverage patient-level EHR data as well as
public-health mortality and morbidity data and screening and prevention data. These
sources feed into an integrated data platform that was launched in October
2017. The platform also incorporates “hot spot” analysis to identify specific ZIP
codes where factors like employment rates, education levels, income and access
to food and mental health centers can contribute to poor health outcomes.
far, leaders at Providence St. Joseph Health have focused their analysis on
Medicaid patients and dual-eligibles who are high-utilizers and have certain
clinical factors, such as active substance abuse, a mental health diagnosis or
multiple chronic conditions.
patients with high social needs have a primary care “home,” a specially trained
care coordinator in the physician practice will follow up with the patient and
set up referrals to community partners that can address some of the social
issues. If the patient does not have a primary care home, a centralized care
manager will reach out to address the individual’s healthcare and social needs
and connect her or him with primary care.
and her team plan to compare results from using the analytics platform to the
traditional method of using claims data and some clinical and social data to
identify patients in need of care management. The comparison will look at how
well each approach reduces unwanted utilization, such as avoidable emergency
department visits and readmissions, and the associated costs.
believes the analytics platform can identify the impact of social determinants
of health more accurately compared with more-traditional care management
approaches. “We will identify more people in need, intervene earlier, and
partner with our community and social service agencies well in advance and
address issues that usually impede or impair their ability to get care,” she
addition to improving patients’ care management and care coordination, utilizing
analytics should help leaders better allocate resources at the practice level.
“If a practice has a lot of patients with diabetes, maybe we can have stronger a
partnership with a food bank that can provide more nutritional food or a
transportation service that can help patients get to their appointment for nutrition
counseling,” Medows says.
organizations such as Providence St. Joseph Health are using their own analytics
tools to identify social determinants of health, others may choose to work with
a vendor. In such cases, Fridsma recommends inquiring about the specific data
sets used in the platform to ensure the age and sex distribution, socioeconomic
mix and other attributes closely match the provider’s own population. If the
populations are not well matched, the analytics platform could create incorrect
associations or miss subtler associations, he says.
also should have a clear understanding of the specific data standards and
definitions used. “Black boxes are hard to describe, and they are hard to
trust,” he says. “Transparency and explainability are important so that you
know the algorithms are doing the right thing.”
more examples of how hospitals are using analytics to address social
determinants of health, see:
How artificial intelligence could help uncover social determinants of health
Testing a model for better coordination of care in the community
Laura Ramos Hegwer is a freelance writer and editor
based in Lake Bluff, Ill.
Interviewed for this article: Douglas Fridsma, MD, PhD, FACP, FACMI,
president and CEO, American Medical Informatics Association (AMIA), Bethesda,
president of population health management, Providence St. Joseph Health,
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Faced with a rising tide of bad debt, a large Southeastern healthcare system was seeing a sharp decline in net patient revenues. The need to improve collections was dire. By integrating critical tools and processes, the health system was able to increase online payments and improve its financial position. Taking a holistic approach increased overall collection yield by 10% while costs came down because the number of statements sent to patients fell by 10%, which equated to a $1.3M annualized improvement in patient cash over a six-month period. This case study explains how.
ICD-10: Managing Performance
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Yuma Regional Medical Center case study
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