Sustainable and scalable data management services with skilled resources are paramount to meet your clinical trial and research goals.
Health systems, oncology centers, academic researchers, and others must curate and standardize clinical trial data to conduct meaningful analysis. This labor-intensive process is mission critical to accelerate research and improve diagnosis and treatment. Yet the increasing volume of clinical trials and data, industry-wide staffing shortages, and evolving regulatory requirements are hindering the curation of high-quality data and overwhelming already burdened clinicians and researchers.
Sustainable, scalable data management services with skilled resources are essential to ensure high-quality data curation for academic research. As the pressure to process data faster and more inexpensively increases, clinical trial leaders are turning to outsourcing partnerships to meet deadlines and to reduce the time from data abstraction and hypothesis to publication and treatment. Below are four reasons why outsourcing can be a strategic method to meet clinical trial data management goals.
1. The increasing volume of RWD is overwhelming to manage.
As of May 2025, there are approximately 23,000 clinical trials recruiting patients in the U.S.[i] The duration of Phase III clinical trials nearly doubled between 2010 and 2022, increasing from two years to 3.5 years.[ii] The U.S. FDA now puts the high end of the average at four years.[iii]
Real-world data (RWD) is scattered across multiple systems. Typically, healthcare data is maintained in multiple disparate systems — structured data and unstructured patient data in EHRs, claims and billing systems, registries, and more. Clinical trial data includes data in clinical trial management systems (CTMS) and data sets maintained in personal spreadsheets and databases.
In a survey of professionals involved in clinical data management, 50% of respondents reported using up to five different data sources, and 37% use between six and ten.[iv] A typical Phase III trial now uses close to 10 data sources and generates an average of 3.6 million data points — three times the amount reported just a decade ago.[v] CTMS and EHR platforms can yield rich data sets but are often siloed.
The increasing number of trials, siloed data sources, data backlogs, and other factors are driving the need to determine the best way to manage, harmonize, and democratize clinical trial data.
2. Staffing shortages of skilled resources continues to be a challenge.
Healthcare leaders continue to cite staffing shortages and financial concerns as their most pressing challenges. In fact, 77% of life sciences and healthcare companies report having difficulty finding the talent they need.[vi] Turnover is prevalent, and researchers are stretched. They are also high-paid resources that should be focused on research rather than curating data.
Research organizations are exploring options to meet the growing demands of registry data policies, procedures, reporting analysis, and data submission that call for knowledgeable workers. This opens the door to leverage natural language processing (NLP) and AI for improved efficiencies and productivity,[vii] but these technologies also require a highly skilled and specialized workforce.
3. Clinical trial data management is labor intensive.
In a widely cited survey of top clinical data management professionals, 95% of respondents reported manual effort is involved in aggregating, cleaning, and transforming clinical trial data, and two out of three respondents experienced issues with the process.[iv]
In that same survey:
- 81% of respondents indicated data governance issues as the biggest challenge with clinical trial data in meeting regulatory compliance.
- More than half (58%) indicated a lack confidence in quality or completeness of their data from an audit and compliance perspective.
- When asked about the top operational challenges with clinical trial data, data completeness (51%), quality (45%), and cleaning (43%) were the top three concerns.[iv]
Clinically relevant data is often difficult to capture because it’s buried in unstructured content such as physician notes and diagnostic reports. Plus, the increasing complexity of trial and data management results in a higher risk of noncompliance. Improving data management and data governance in clinical research is critical to ensure high-quality clinical trial outcomes and RWD curation.
4. Evolving regulations raise expectations for data quality and oversight.
In January 2025, the International Council for Harmonisation (ICH) released a major update to its Good Clinical Practice (GCP) guidelines: E6(R3).[viii] The new guidance modernizes clinical trial conduct by promoting flexible trial designs, stronger data governance, and a proactive, risk-based approach to quality.
These updates reflect a broader industry shift. Research organizations are now expected to maintain secure, audit-ready data environments, ensure traceability throughout the data lifecycle, and adopt digital tools like eConsent and remote monitoring where appropriate. Annex 1 of E6(R3) outlines more detailed expectations for sponsor oversight, documentation standards, and data integrity — placing greater pressure on research teams to maintain both compliance and quality.[ix]
While the FDA hasn’t formally adopted E6(R3) yet, the European Medicines Agency will begin enforcing it in July 2025. Many sponsors are already aligning processes in preparation, turning to outsourcing partners to help fill resource gaps, manage regulatory oversight, and ensure their data is up to date.
Supplement and scale expertise through outsourcing to help ensure trial success
Outsourcing is an accepted best practice for engaging and scaling skilled resources for studies and trials as needed to ensure high-quality data for a successful clinical trial program.
Outsourcing expertise is effective for:
- Lack of in-house experience
- Rise in need for specialists within CROs, especially across therapeutic or functional areas such as biostatistics, clinical data management, etc.
- Expanding pipeline of new drug development
- Increasing size, complexity, duration, and cost of clinical trials
- Increase of personalized medicine[x]
Collaborate with Omega Healthcare Clinical Data Services (CurateIQ®) to meet clinical trial and research goals
Collaborating with Omega Healthcare Clinical Data Services offers a simple but effective model to make data more usable more quickly. To meet the growing demand for high-quality, research-grade RWD, Omega Healthcare enables organizations to scale up a highly skilled, trained, and flexible workforce quickly.
Founded by researchers for researchers, the Omega Healthcare team understands the complexity of clinical trial data management and data governance. Omega’s expertise is in RWD services, building databases, and providing research-grade records to improve clinical outcomes. Services include curating and unifying a client’s clinical data from disparate sources — all behind the client’s firewall.
[i] ClinicalTrials.gov, U.S. National Library of Medicine, Accessed May 2025.
[ii] “Life Sciences Services Industry Outlook: Winter 2023,” RSM, February 6, 2023. https://rsmus.com/insights/industries/life-sciences/life-sciences-services-outlook.html
[iii] “Step 3: Clinical Research,” U.S. Food & Drug Administration. https://www.fda.gov/patients/drug-development-process/step-3-clinical-research
[iv] “Challenges and Opportunities in Clinical Data Management Research Report,” Pharma Intelligence and Oracle, September 2018. https://www.oracle.com/a/ocom/docs/dc/oracle-clinical-data-report-1809-final-26-sept.pdf
[v] “Clinical Trials Have a Data Problem. Here’s How the Industry Can Solve It,” MedCity News, July 2023. https://medcitynews.com/2023/07/clinical-trials-have-a-data-problem-heres-how-the-industry-can-solve-it
[vi] “2024 Global Talent Shortage,” ManpowerGroup, 2024. https://go.manpowergroup.com/hubfs/Talent%20Shortage/Talent%20Shortage%202024/MPG_TS_2024_GLOBAL_Infographic.pdf
[vii] “Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records,” NIH National Library of Medicine, August 8, 2019. https://pmc.ncbi.nlm.nih.gov/articles/PMC7227798/
[viii] “ICH Adopts E6(R3) Guideline on Good Clinical Practices,” Regulatory Focus, Regulatory Affairs Professionals Society, January 2025. https://www.raps.org/news-and-articles/news-articles/2025/1/ich-adopts-e6(r3)-guideline-on-good-clinical-pract
[ix] “The ICH E6(R3) Guideline: A Major Update to Good Clinical Practice,” FDA Law Blog, Hyman, Phelps & McNamara, P.C., February 2025. https://www.thefdalawblog.com/2025/02/the-ich-e6r3-guideline-a-major-update-to-good-clinical-practice/
[x] “Clinical Trial Outsourcing Trends and Research,” Thomas Underwood, Quanticate, March 10, 2020. https://www.quanticate.com/blog/clinical-trial-outsourcing-and-research-trends
