HDG #005: Data outside your four walls is the key to health equity
Read time: 10 minutes
Today I'm going to share 3 ways you can start adding new data to your old repertoire using my "data outside your four walls" concept. It will transform how you do program design, identify initiatives, and conduct analyses—especially in health equity.
Unfortunately, we see a general lack of awareness of what data exists and where. This is a missed opportunity and low-hanging fruit with all of the new data sources being published and attention on community.
Things happening "outside your four walls" play a major role in the future of health and community wellbeing.
By now, we have mostly all heard that external determinants can account for up to 80-90% of addressable contributors to adverse outcomes in health, education, opportunity, etc.
But the current state of decision-making is in a vacuum that only tends to examine internal source data, mostly due to:
the newness of the concept (health equity and external datasets),
gaps in knowing how to use/manipulate/analyze that data or where to start looking,
the lack of resources and/or skillsets available within healthcare organizations (whether that be due to time constraints or technical constraints),
the complexity of blending the data together to create information,
"last mile" challenges turning raw data into information and decisions that impact organizational performance improvement,
and decision-making based on "gut" feelings or anecdotal information received from the boots on the ground.
What do I mean by "outside your four walls?"
You may have access to data that occurred “within your four walls” from your source systems, program data, or internal organization. This could be things like EMR/clinical data, patient-specific data, patient-specific SDOH, visit history, health plan claims + utilization data, medical history, and referrals, etc.
But did you know that there is a wealth of information (data) that exists “outside of your four walls” that you could also use to help identify where these barriers exist so that you can support the development of new strategies with more precision? Or facilitate meaningful and data-driven conversations with patients/providers/payers/and other funding agencies?
This could be anything that happens outside of your organization but contributes to or informs the health/behaviors/decisions/outcomes of things that do affect your stakeholders. This could be data such as the location of and distance to resources, disease prevalence, population health data & quality gaps, community vulnerabilities and social determinants, location-specific natural disaster/sociocultural/community hazards, digital health data, external benchmark data to answer how do I compare to peers?, longitudinal health information exchange (HIE), and so much more.
This kind of data can illuminate your blind spots and should be in tandem with your internal data to support new performance improvement or case management initiatives, payer contracting, and funding requests, or to better address gaps in the communities you serve.
Here are 3 ways you can start thinking about this tomorrow:
1: DEVELOPING A PRECISION STRATEGY
Where does the data say that should I focus my limited resources? What interventions will really make a measurable impact vs. throwing darts or acting based on anecdotes? How can we quantify the likely outcome of launching a new program, based on what we know about the community or population?
2: CONTRACTING + FUNDING
What initiatives would payers consider for value-based? How can I use this data to support more funding based on our patients' unique risks and challenges to treat? What types of chronic or community conditions are most aligned and represent the biggest opportunity to move the needle?
3: UNDERSTANDING HEALTH & COMMUNITY EQUITY
How can we use the data to identify exactly where people and patients are “falling through the cracks” or disproportionately impacted by new programs, policies, or new technologies (like virtual care)? Does this tend to occur in certain "hot spots" more than others? How do the interplay of data/risk factors present in unique ways that we can address?
Here are some open-source starter sets that can be used to help answer some of these questions:
American Community Survey (ACS)
Has data about regions and the people living within them and you can drill down beyond just a county which is imperative. This data is widely used but has some limitations related to sampling and frequency.
Use this to understand what the makeup of the community looks like as a whole, compare it to your makeup, identify trends and characteristics of the people you serve, and identify how much of certain populations you are actually seeing "within your four walls."
Centers for Disease Control and Prevention (CDC) Places
Focused on "small areas" and specifically health-related measures. Can go to tract-level, but no layering or combinatorial views. They do have a straightforward interactive map, though.
Hospital quality and cost comparisons, Medicare utilization trends, services and charges billed by providers for professional (PUF), inpatient (Medpar), etc. Use this for benchmarking, such as: comparing your % of regional utilization for Medicare patients across all settings (IP, OP, Professional, Rehab, etc.) down to the CPT- and provider-level. Identify how often providers do certain types of procedures, and what their case mix looks like. Identify trends/changes in coding and billing for certain services among Medicare, like telehealth.
AHRQ Healthcare Cost and Utilization Project (HCUP) Data
Similar uses as above, but goes down to certain diseases and acute events. HCUP is the Nation's most comprehensive source of hospital care data, including information on inpatient stays, ambulatory surgery, and services visits, and emergency department encounters.
Provider demographics, name, location, specialty, licensure, and other information. This can also be used to map providers, even those who might not be in your network. This can be used to understand access to care, and compare how often providers are seeing Medicare/Medicaid patients and for what. They even offer this in a full download and API format.
Medicare/Medicaid Enrollment, and/or your local state agencies’ health and human services or department of health:
This may vary by state, but state sites tend to offer data about disease prevalence, indicators of health and social status, COVID and vaccination information, births/deaths/vital records, and outcomes by region for certain health outcomes like screenings. You can also find information about what kind of community or health equity programs are deployed, and they may have lists of community service providers that are of value.
This is just barely scratching the surface of the type of data that exists in the public domain that can be used to augment your work. And this doesn’t even start to touch on datasets for purchase. In future newsletters, I will drill down into more specifics about certain datasets and their uses, but for now, I wanted to introduce the concept.
If you want to learn more about this, check out the webinar I did for AMN's Nursing Leadership group here: Looking at Data “Outside of Your Four Walls” to Advance Health Equity.
Your 1 actionable idea for the week:
When you're starting a new analysis or a new strategy, keep this "data outside your four walls" concept in mind and try to pull in at least 1 new source of external data to round out your insights or gut-check your assumption:
Ask yourself:
What data do I NOT have reflected in this analysis that would help me tell a fuller, more complete, different, new, or wider story?
What angles am I missing?
What (or who) does my data or assumptions NOT include here (the negative space) that I need to learn more about?
What is going on outside my four walls that could impact or bias this?
What would you add? Hit reply and let me know your thoughts.
See you next week!
-Stefany
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