Heart Disease Mortality Data-Guided Donation
- Laila Al Afnan
- May 16
- 6 min read
Big Picture Goal:
Reduce ischemic heart disease mortality rates in the U.S.
Project Objective: A Data-Guided Donation
By the end of the 15-week project, donate to one or more non-profit organizations serving priority counties within the United States and that run evidence-based programs to reduce heart disease mortality rates or an intermediate outcome, like preventing heart disease.
Learning Objective:
This project was completed as part of a 15-week training program where the learning objective was to practice the 7 core data skills: querying, entering, cleaning, enhancing, analyzing, visualizing, and humanizing data.
5 Steps
Overview: A team of Community Data Interns at BroadStreet Institute reviewed data on heart disease mortality rates in the U.S. from February to May 2026 and created a funding proposal for non-profit organizations implementing evidence-based strategies.
Step 1. Review heart disease data to create a list of 📍priority counties by state
Step 2. Teams prioritize one 📍county
Step 3. Review of evidence-based interventions in the scientific literature
Step 4. Identify non-profit organizations introducing evidence-based solutions in key regions.
Step 5. Review and donate to selected non-profit organizations
Inputs:
💰 Money: $750 to donate
⏰ Time: 15 weeks (February to May 2026)
👥 Team: 60 people (16 leaders, 44 team members)
🧰 Inventory:
🧰 Data Tools: Google Sheets, DataWrapper, Flourish
📊 Data Source: CDC WONDER Underlying Cause of Death (CDC WONDER, 2026)
Indicator Definitions:
Heart disease death defined as ICD-10 Code: I20-I25, "Ischemic heart diseases"
Mortality rate for heart disease: Crude mortality was calculated from overall number of heart disease deaths for every 100,000 people, 2018-2023.
Methods.
Nine teams, each composed of 4-6 members, used CDC WONDER mortality data (CDC WONDER, 2018-2023) to explore heart disease mortality rates across U.S. states. Each team identified a specific county as a 📍priority, reviewed scientific literature for evidence-based interventions, and then localized non-profit organizations tackling heart disease mortality rates in the county.
Step 1. Create a List of 📍Priority Counties by State
Objective: Each team shortlists counties of interest in assigned states.
To begin the process, the 50 U.S. states were assigned to the teams and team members. Each team received at least one state with a county that was known to be ranked among the top 10 in mortality rates in the U.S. Some team members were assigned to the same state. Each team member explored county-level crude mortality rates (deaths per 100,000 people, ICD-10 code range I20-I25) in the assigned state and selected one county to propose. Team members selected a county for further analysis: Either the county with the highest overall mortality rate (CDC WONDER, 2018 - 2023) within their assigned state or the county with the highest number of deaths.
Step 2. Teams prioritize one 📍county
Objective: Each team prioritized one county from the shortlist of counties proposed by team members from Step 1.
Each team refined its county proposals after exploring overall crude mortality estimates for 2018-2023, gender disparities, and population figures. Teams selected one county based on the following criteria: the highest mortality rate (2018-2023), the largest gender mortality disparity, or the largest number of deaths (i.e. areas with a high population).
Limitations and caveats of Steps 1 and 2:
Missing data. States that were missing from consideration: Arizona, Connecticut, Delaware, District of Columbia, Georgia, Hawaii, Idaho, Illinois, Indiana, Kentucky, Minnesota, Nevada, New Hampshire, New Jersey, North Carolina, Pennsylvania, Rhode Island, South Dakota.
States and counties may be excluded from the decision process if team members did not propose a key county for a state or if a state was not assigned to anyone. Some states were reviewed by more than one team member.
Data-guided, value-based decision-making was followed. This means that each team member could propose a county with some flexibility on how the final county was decided. Because teams had discretion which counties were prioritized, it is possible that counties with the highest mortality rates were not chosen.
Step 3. Review of evidence-based interventions in the scientific literature
Objective: Identify evidence-based interventions, including policies and programs, for reducing heart disease mortality or an intermediate outcome such as preventing heart disease.
Team members searched PubMed, Cochrane, and the U.S. Preventive Services Task Force (USPSTF) to identify evidence-based interventions that reduce mortality or address intermediate outcomes, such as heart disease risk factors. They focused on the highest level of evidence, namely systematic reviews and meta-analyses. USPSTF recommendations that were ranked as A or B were considered.
Limitations and caveats of Step 3:
Evidence-based interventions published in other databases may not have been considered.
Step 4. Identify non-profit organizations doing evidence-based solutions in key regions.
Objective: Each team locates non-profit organizations that are actively running evidence-based programs serving the population of their 📍prioritized county.
Every team explored 1 county. In total, eight counties were searched for non-profit organizations implementing evidence-based programs or promoting evidence-based policies to reduce heart disease mortality or incidence.
At least one organization was found in each of the eight counties. The identified organizations and programs were cross-checked by team members to determine whether they aligned with a decision matrix (see table "Decision Matrix"). The decision matrix was created by the BroadStreet Institute Steering Committee.
Limitations and caveats of Step 4:
Certain non-profit organizations working on evidence-based interventions may not have been considered if team members did not locate them on the internet using a search engine.
Decision Matrix | |
|---|---|
Criteria # | BroadStreet criteria for donation eligibility |
Criteria 1. Initial screening criteria | Organizations are running programs in key places. Note: "Key places" are counties where there are opportunities to reduce mortality (i.e. mortality rates are high, the number of deaths are high, disparities are high, etc.). |
Criteria 2. Initial screening criteria | The program(s) being run by the organization within that key place are evidence-based solutions for reducing heart disease mortality (or an intermediate outcome). |
Criteria 3. Initial screening criteria | Organizations are non-profits 501(c)3 to which we could donate (i.e. not a government agency). Note: Non-profit are still eligible if they receive government funding. |
Criteria 4. | A donation, if given, could be reasonably assumed to be going to: (1) The 📍key county and (2) The program of interest (i.e. the money would not go to another program or place). |
Criteria 5. optional | Organizations are at least 1 year old and have filed IRS 990s for 501(c)3. |
Criteria 6. optional | Organizations have an annual report in which we could see the number of people served. |
Criteria 7. | Is the organization free from obvious red flags or causes of concern? |
Project Outcomes
Key Counties. The eight counties proposed by teams were (in alphabetical order):
Cocke County, TN,
DeBaca County, NM,
Essex County, VT,
McIntosh County, ND,
Monona County, IA,
Montmorency County, MI,
Pemiscot County, MO,
Red River County, TX.
All teams picked their county of interest based on the highest overall mortality rate among the counties shortlisted by team members. The teams identified evidence-based programs in these counties and submitted their proposals for review. During the cross-checking process, four organizations were identified as good candidates for donations based on the decision matrix:
The Black Heart Association, serving📍Red River County, Texas, offers blood pressure screening, an evidence-based intervention aligned with USPSTF grade A recommendations (U.S. Preventive Services Task Force, 2021).
New Mexico Heart Institute, serves multiple regions in New Mexico, including 📍De Baca County, and offers cardiac rehabilitation, an evidence-based intervention in accordance with USPSTF grade B recommendations (U.S. Preventive Services Task Force, 2020).
McLaren Northern Michigan, serving 📍Montmorency County, Michigan, provides cardiac rehabilitation and treatment, which is an evidence-based intervention aligned with USPSTF grade B recommendations (U.S. Preventive Services Task Force, 2020).
Burgess Health Center in 📍Monona County, Iowa, offers vascular screening for abdominal aortic aneurysms (AAA), an evidence-based intervention as per USPSTF grade B and C recommendations (U.S. Preventive Services Task Force, 2019).
ORGANIZATION | EVIDENCE-BASED INTERVENTION | COUNTY/REGION SERVED 📍 |
Black Heart Association | Blood pressure screening | Red River County, Texas |
Mexico Heart Institute | Cardiac rehabilitation | Counties in New Mexico, including DeBaca County |
McLaren Northern Michigan | Cardiac rehabilitation and treatment | Montmorency County, Michigan |
Burgess Health Center | Vascular screening for abdominal aortic aneurysms (AAA) | Monona County, Iowa |
All four organizations passed most of the decision matrix criteria. Although the review team was unsure whether any donations would specifically be allocated to the counties of interest (Criteria 4).
Based on our overall evaluation, we decided to donate $187 to each of the four organizations summarized above.
Conclusions
Many amazing organizations were working on evidence-based solutions to reduce heart disease or prevent heart disease. Through reviewing mortality rates across most of the U.S., we believe that we were able to prioritize counties where resources would be well-utilized.
Attribution
A huge thank you to the team members and leaders of the Wonder Track Spring Track Program 2026.
Methods Author List:
Citations
Data Source:
Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS) (2026). Underlying Cause of Death 2018-2023 on CDC WONDER Online Database, released 2026. Data are compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Retrieved from http://wonder.cdc.gov/controller/saved/D158/D507F921 in Feb 2026.
References:
U.S. Preventive Services Task Force. (2021). Hypertension in adults: screening. https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/hypertension-in-adults-screening
U.S. Preventive Services Task Force. (2020). Healthy Diet and Physical Activity for Cardiovascular Disease Prevention in Adults With Cardiovascular Risk Factors: Behavioral Counseling Interventions.
U.S. Preventive Services Task Force. (2019). Abdominal Aortic Aneurysm: Screening. https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/abdominal-aortic-aneurysm-screening
