Services: Consulting: Clinical Trials
Consulting Services: Human Clinical Trials
Primary Strengths
  • Big Data and AI in Clinical Studies
  • Site Selection
  • Site Assessment
  • Enrollment & Outreach
  • Feasibility
  • Study Tuning
  • Investigators Database
  • High-Density Practices
  • Referral Patterns
  • Cohort Analytics
  • Much More

Clinical Trials are part of our DNA.


Many members of the core Hagimo team began their careers working in the clinical trials industry. Since 2003, when W. Sean Harrison co-founded Provisio, Inc. (home of iTrials.com), the emphasis on data aggregation and utilizing data and analytics to address clinical trial challenges has remained central to our mission. Today, in 2024, clinical trials consulting and development remains a priority at Hagimo. With our unprecedented access to data and our partnerships with enterprise bulk data providers, Hagimo is uniquely positioned to leverage data and AI in ways that can dramatically improve the efficiency and effectiveness of clinical trials, from initial criteria definitions to feasibility and enrollment / attrition projections, to site selection and investigator onboarding, through data-driven enrollment and post-marketing surveillance. The methods and strategies that Hagimo has developed over the last 20 years bring the promise of using data to drive clinical trial design and enrollment to fruition - put them to work on your biggest challenges today.

Enrollment - Job #1

The primary challenge to achieving success and keeping costs down in clinical trials remains enrollment. Site-selection methodologies, information campaigns, shotgun advertising, and other traditional methods haven't really changed or improved in the last 40 years. Compounding this issue is the reality that Big Pharma has been overwhelmed by an avalanche of data companies over the last 25 years, with nearly every one over-promising and under-delivering. With a track record of success and access to multiple enterprise datasets, Hagimo is capable of delivering real-world analytics and assessments that can help fine-tune your study parameters and drive successful enrollment.

Site Selection, Site Assessment


The likelihood of timely site activation increases dramatically based on how your sites are selected. Were your selections based on data? Sites or investigators you've worked with before? A combination of both? What about factors such as the local and regional concentration of eligible patients, media market metrics, referral patterns, or proximity to centers of excellence, thought leaders, or other resources? The reality is that most sites are selected based on past history and existing relationships with providers or an investigator. Strategically placing sites based on proximity to populations of eligible patients, which may exist outside of population centers, and taking into account referral patterns and other factors, can dramatically improve the likelihood of successful enrollment.

Don't depend on someone's Rolodex and a past history of mediocre performance. The data and metrics that can precisely inform you where to place your sites are available today. Let Hagimo help you leverage them to your advantage.

Enrollment & Outreach


Where the rubber meets the road. Successful enrollment is the number one challenge in getting your study underway on schedule. Hagimo has developed several methods of data-driven enrollment designed to work side-by-side with traditional methods. These include:

Feasibility


You've got your study inclusion and exclusion criteria. You've got your sites. Now, you've got the ability to take this information and lay it out over more than 300 million health histories, each with up to 10 years of data. Enrollment and attrition numbers per site. Projected incidence rates across the entire cohort. Deep provider and practice information, all based on GIS mapping technology that tells you exactly where the patients are, and what sites are performing. Lay the referral patterns over top of it all to see what providers and facilities are receiving the most eligible patients. Don't start the study until you know it's going to be a success.

Study Tuning


Projected populations not what you need them to be? FDA interested in seeing more patients in the study? Last minute changes to compounds or dosages? Change your criteria, re-populate your study project, and then re-assess the feasibility. Add some new investigators since the last projection? Removed some sites? Maybe you's like to see how a hypothetical site located in a population center that you haven't considered yet will perform? Make the changes, hit the switch, and get real-world data-driven answers that can help you fine-tune your study for success.

Investigator Database


Based on the curated data of building site assessments and paring bulk claims data since 2007, Hagimo's database of principal and co-investigators, coordinators, and other site personnel has more than 250,000 entries, each with contact information and a history of study participation. Many have mapped NPI's where applicable, and all are searchable by studfies they've participated in, therapeutic areas, and other criteria. This is where to start if you're ready to select investigators based on data.

High-Density Practices


"Where are the eligible patients?" You can focus on population centers, or large facilities where certain indications are treated, or you can develop a presence near specialty practices, along with all of the other traditional advertising methods that have been used for decades. Or, you can leverage Hagimo's Data Universe to determine exactly what practices the largest concentrations of eligible patients are attending, and place your information directly in front of the eyes that need to see it.

Hagimo builds nationwide cohorts of eligible patients based on your inclusion/exclusion criteria, and then we isolate the associated medical providers and practices that are seeing these patients. We also assess eligible patients within a defined radius to these practices, and then we sort and score them, based on total eligible patients in each practice and total number of eligible patients within those radii. The result is a list of high-density practices that are seeing more of your eligible patients than any other facilities in the country - business intelligence that can minimize your spend, inform your outreach, and maximize your enrollment.

Referral Patterns


Your potential eligible patient base isn't visiting just one provider. In particular, patients with chronic conditions will often see their GP, selected specialists, and other providers. There may be outpatient facilities, imaging centers, and other providers as well. Each of these represents a dynamic pool of potential patients, with each population defined by their referral patterns. Providers tend to refer to other providers that they know and trust, or to thought leaders in their space. This information is also invaluable when it comes to site selection, giving you the opportunity to place sites in close proximity to referral targets, or even bring these facilities and receiving providers online as new sites or investigators.

Cohort Analytics


** - Coming Q2 2024

The same platform and analytics that Hagimo depends internally on are now available to you. With a subscription to Hagimo's Data Universe™, you can specify your inclusion and exclusion criteria, build your cohorts, fine-tune your study parameters, project enrollment and attrition on a per-site basis, and run real-time actionable analytics across your patient cohort. Some of these analytics include:
  • Patient Analytics I
    • Patient Density Totals
    • Counts by Diagnoses
    • Counts by Procedures
    • Basic Financial Metrics
  • Patient Analytics II
    • Financial Metrics by Payor
    • Isometry and Divergence Analysis
  • Provider Analytics I
    • Providers by Patient Counts
    • Specialty Breakouts
  • Provider Analytics II
    • In-Cohort Referral Networks
    • Practice Financials
    • Clinical Coding Trending
  • Provider Analytics III
    • Nationwide Referral Networks
    • Patient Proximity Radii Analytics
    • Site Proximity Mapping
  • Facility Metrics
    • Patient Counts by Payor
    • Transaction Financials
    • ER Coding and Return Visits
  • GIS and Visualizations I
    • Nationwide Cohort Point and Heat Maps
    • Nationwide Patient, Practice and Facility Maps
  • GIS and Visualizations II
    • Patient / Site Proximity Maps
    • Patient Cluster and Supercluster Maps
    • Media Market Populations
  • Clinical Studies I
    • Site Selection
    • Site Assessment
  • Clinical Studies II
    • Enrollment and Attrition Projections
    • Feasibility Report
    • AI Inclusion / Exclusion Criteria Tuning