Skip to main content

Making the Most of Data to Improve Falls Prevention Programs

The 2025 National Falls Prevention Action Plan, highlighted at the September 2024 National Falls Prevention Summit, outlines six strategic priorities to reduce falls among older adults. One such priority: improving data systems to better understand why and how older people fall.  

This includes gathering both needs-based data, which highlights service gaps and areas of risk, and asset-based data, which focuses on community strengths and resources. 

The 2025 National Falls Prevention Action Plan seeks to “Improve data by increasing the quality and range of information, both quantitative and qualitative, about why older people fall and under what circumstances...and expand research via longitudinal (e.g., lasting 10 years) studies...” 

By aligning their local initiatives with this national strategy, community groups and organizations can more effectively plan, evaluate, and sustain falls prevention efforts. Data strengthens falls prevention programs by helping organizations tailor interventions to community needs and improve program effectiveness. 

Why use data in falls prevention programs? 

Data-driven decision-making ensures that falls prevention programs are: 

  • Targeted—Directing resources to communities with the highest need. 
  • Fundable—Providing evidence to support grant applications and public investment. 
  • Collaborative—Strengthening partnerships through shared goals and measurable impact. 
  • Accountable—Enabling continuous improvement through outcome monitoring. 

Gather and leverage your own falls data  

A strong program starts with a comprehensive needs and resource assessment. Combining needs-based and asset-based approaches offers a balanced picture: 

  • Needs-based mapping identifies service gaps and barriers. This approach can sometimes feel stigmatizing or deficit-focused, limiting solution-building. 
  • Asset-based mapping highlights existing community strengths, resources, and networks, which can inspire and guide sustainable, community-driven change. 

Approaches to data collection: 

  • Interviews with older adults, caregivers, service providers 
  • Focus groups or listening sessions 
  • Community observations and needs/resource mapping 
  • Photovoice or appreciative inquiry 
  • Surveys (paper, digital, or phone) 
  • Review of existing reports or assessments 

Engaging the community to understand data  

Sharing data with the community is a powerful way to ensure falls prevention efforts are transparent and community-driven. Data is often collected from communities but never shared back with them. Closing this feedback loop can foster trust, build partnerships, and turn insights into action. 

Rather than presenting data in a static report, interactive approaches invite community members to interpret, question, and apply the data themselves. This process can uncover local insights, highlight new priorities, and support shared decision-making. 

Solutions to common challenges and data limitations 

  
Challenge 

Solution 

Some rural areas may lack reliable data collection.  

These areas can address data scarcity through multi-sector collaboration. For example, a rural county health department might partner with local EMS providers, a regional hospital, and university geographic information system (GIS) experts to combine call logs, hospital admissions, and mapping tools to identify falls “hot spots.” 

Small programs lack staff dedicated to data or technical tools.  

Larger organizations can support smaller partners with data tools, training, and shared resources.

HIPAA/data sharing limits can prevent access to information. 

Using HIPAA-compliant data-sharing agreements can responsibly allow access to health system data. 

Success stories: using data to make a greater impact  

Sanford Health, South Dakota 

Through its “Stand Strong” initiative, Sanford Health used cross-sector data to design and expand a statewide falls prevention system.  

How they got the data:  

  • Partnered with one urban and four rural Emergency Medical Services (EMS)/fire departments to access lift-assist call data. These partnerships were formalized with data use agreements that allowed for HIPAA-compliant referrals to community programs. 
  • Worked with the South Dakota Department of Health to analyze statewide injury surveillance data (hospital discharges, mortality statistics) to monitor trends and support funding. 
  • Collaborated with local GIS experts to map fall injuries by ZIP code, using aggregated health and EMS data to identify rural “hot spots.” 

How they used the data: 

  • Analyzed EMS lift-assist data monthly to flag repeat fallers, leading to targeted outreach and referrals to programs like CAPABLE and A Matter of Balance. 
  • Used geographic mapping to guide where to expand classes, ensuring rural communities were not left behind. 
  • Conducted ongoing data reviews to track fall-related mortality and program outcomes and strengthen funding proposals and sustainability. 
  • Strengthened the sustainability of both its cross-sector referral platform and its evidence-based programs by training university students and volunteers, offering continuing education units (CEUs) to health professionals, and embedding referral processes across EMS and health systems. 

Stony Brook Southampton Hospital, New York 

Stony Brook is developing a long-term integrated data strategy that connects health system-based fall risk screening with community prevention efforts.  

How they get the data:  

  • Electronic Medical Record (EMR) reports are used to track the proportion of older adult patients screened for fall risk (nearly 100%) and the proportion of positive screens. The EMR is being modified to standardize the fall risk care order set to be able to discretely record what interventions (i.e. referrals) are prescribed by the provider for at-risk patients during an encounter, across the enterprise (inpatient/outpatient). 
  • Collaborating with their hospital network’s trauma and rehabilitation departments, they access discharge records for patients treated for falls. Internal analytics staff de-identify and segment the data by age and ZIP code.  
  • Partner with community-based organizations and local health departments to layer ZIP code-level fall injury data from surveillance systems and Community Health Needs Assessments (CHNAs).  
  • Collecting a custom patient survey in partnership with their quality improvement team to gather insights into fall prevention attitudes, preferences, and barriers for patient presenting to the Emergency Department for a fall-related injury.  

How they use it:  

  • Updated EMR fall risk care order set will allow providers to refer at-risk patients to the evidence-based falls prevention team within the EMR. The evidence-based falls prevention team receives email alerts when patients are referred within the EMR for prompt follow-up. Any provider can also utilize a fall prevention message pool within the EMR to request the falls prevention team conduct follow-up and coordination. 
  • A referral feedback loop will allow the falls prevention program team to share outreach outcomes with referring clinical teams, demonstrating impact and improving coordination.  
  • ZIP code mapping prioritizes new class locations in rural areas and other communities with limited access.  
  • Patient survey results reveal a gap in fall risk perception, prompting the development of more tailored discharge instructions and education materials.  

Looking ahead: 

  • The team will analyze EMR records to identify the impact of systematic and coordinated clinical-community integrated fall prevention efforts to demonstrate potential cost-savings and improved patient outcomes. 

Practical tips for getting started 

  • Ask your local health department: “Do you track falls-related injuries at the ZIP code or county level?” 
  • Ask your state health department: “Do you track falls-related injuries at the ZIP code or county level?” 
  • Start with what’s available—Web-based Injury Statistics Query and Reporting System (WISQARS), CHNAs, EMS logs, or one ZIP code 
  • Data on older adult falls is collected for a variety of purposes by a range of stakeholders. Consider the following falls data sources and how they might support your efforts. 
  • Keep requests clear and focused (e.g., "fall-related ER visits, ages 65+, by ZIP code, past 3 years"). 
  • Keep in mind that the most recently available public health data might be several years old, as data collection and analysis take time to process. 
  • Build relationships: Approach hospitals, EMS, and public health as data collaborators, not just sources. 
  • Consider data-sharing agreements early if working with clinical or HIPAA-protected data. 
  • Partner with universities or students for help with mapping, data analysis, or surveys. 

Data Source 

Type of Data Provided 

Best Use 

How to Access 

Gaps / Limitations 

ER visits, hospitalizations, and deaths (ICD-10 W00–W19) 

Injury type, severity, ICD codes, procedures, LOS, discharge outcomes 

Monitoring trends in serious falls injuries; identifying high-risk populations 

CDC WISQARSCDC WONDERHCUP, state hospital associations 

Misses minor/unreported falls; limited location/environmental context 

Maps of injury frequency by ZIP code 

Aggregated rates by geographic area 

Targeting prevention in high-risk ZIPs, mapping falls “hotspots” 

Local health departments, state GIS dashboards, university mapping teams 

Only includes reported cases; update frequency varies 

Community Health Needs Assessments (CHNAs) 

Qualitative and quantitative data on health priorities 

Elevating falls prevention in health planning 

RTI Community Benefit Insight Tool, hospital websites 

Falls data often absent or outdated; varies in depth 

State Department of Aging Community Needs Assessments 

Aging-specific data on health needs, service gaps, and social determinants 

Informing state plans on aging and falls prevention priorities 

HHS State Resources Page (links to every State Unit on Aging) 

Falls-specific details may be limited; varies by state 

State-level aging and injury surveillance reports 

Statewide breakdowns by age, outcome, geography 

State planning, grant proposals, needs assessments 

State public health departments, CDC WISQARS 

Data quality and update frequency vary by state 

National Vital Statistics System (NVSS) 

Death records with falls-related ICD-10 codes 

Calculating falls mortality rates; advocacy 

CDC WONDER, state vital records offices 

Only fatal falls; lacks detail about incident context 

CDC’s National Syndromic Surveillance Program (NSSP) 

Real-time ED data on falls via chief complaints 

Early detection of local or regional trends 

NSSP Info, state ESSENCE platforms 

Not universal; requires technical access and coding knowledge 

Trauma registries (ACS Trauma Quality Programs) 

Injury mechanisms, severity scores, trauma outcomes 

In-depth insights into serious falls and recovery 

State trauma registry leads, ACS National Trauma Data Bank 

Limited to trauma-center patients; requires agreements 

911 and EMS call data 

Incident data including location, severity, repeat calls 

Spotting falls “hotspots”; EMS collaboration 

NEMSIS, local EMS/fire departments, NASEMSO 

Only covers EMS-activated events; lacks follow-up info 

United Way 211 system 

Community referrals for services like housing, mobility 

Understanding social needs tied to falls 

211.org, regional 211 call centers 

Data varies by location; lacks clinical specifics 

Hospitals and healthcare partners 

EHR records on falls, assessments, and follow-up care 

Linking referrals and monitoring intervention success 

Through direct partnerships, requires HIPAA-compliant agreements 

Access barriers; siloed from community data 

STEADI Implementation Data 

Count of people screened, assessed, and given plans 

Tracking clinical implementation of falls prevention 

EHRs, clinic-level program tracking, STEADI resources 

Process-focused; not always systematically reported 

BRFSS (Behavioral Risk Factor Surveillance System) 

Self-reported falls incidents and risk factors 

Understanding non-clinical falls and behavioral risks 

CDC BRFSS Web Tool, state BRFSS coordinators 

Recall bias; falls module is optional for states 

CMS / All-Payer Claims Databases 

Claims data related to falls treatment and rehab 

Estimating healthcare costs and insurance impact 

CMS ResDAC, state Medicaid/Medicare offices, AHRQ APCD 

Application required; falls mechanism may be unclear 

Social Variables & Vulnerability Indices 

Contextual data on housing, isolation, disability, etc. 

Addressing whole health for all, and layered falls risks 

CDC/ATSDR Social Vulnerability IndexCounty Health RankingsRural Health Chartbook 

Not falls-specific; best used in combination with other sources 

Tools  

Sample data request email 

Subject: Request for Falls-Related Injury Data 

Dear [Health Department Contact], 

I’m writing on behalf of [Organization/Coalition Name], which provides falls prevention programming to older adults. To better target our services and support funding requests, we’re hoping to access local level data related to falls. 

Specifically, we’re looking for: 

  • Falls-related emergency room visits or hospitalizations 

  • Data by ZIP code or county, ideally from the past 3–5 years 

Please let me know if this data is available or if there is a preferred contact for injury surveillance. Thank you! 

Best, 
[Your Name] 
[Title/Organization] 
[Email/Phone] 

Checklist—what data to ask for 

  • Emergency room visits or hospitalizations due to falls 
  • Fall-related deaths by location 
  • ZIP-code or county-level injury maps 
  • Trends over time (e.g., last 3–5 years) 
  • EMS/911 fall call volumes 

Resources 

The Healthy Aging Programs Integrated Database

Learn more about the Healthy Aging Program Integrated Database (HAPID®), a one-stop shop for all grantees and database users to enter workshop data and track performance for both falls prevention and CDSME evidence-based programs.  

Get NCOA in Your Inbox

Choose where we'll send you resources to support your health and financial well-being. Select the option(s) below that best describes you to get communication that matches your interests.

This field is required.
This field is required.
Please enter a valid email address.
Back to Top