What clinical data management looks like in 2023

The number of registered clinical trials has skyrocketed in the last decade, and the life sciences technology landscape is constantly evolving with them. Gone are the days of a researcher sitting with a participant and marking results off on a clipboard. Now, data can be accurately collected and managed from virtually anywhere with the help of smart devices and reliable digital communication options.

Today, data can be virtually managed from anywhere with any device

Managing trial data could be as simple as manual entry to a localized storage solution — such as a desktop computer — or it could be a highly efficient process, enabled by automatic entry into a centralized space that offers collaboration, visualization, and reliability. Let’s explore what clinical data management (CDM) looks like today and how the right tools enable success.

Table of Contents:

  • The challenges of clinical data management
  • Cloud services solutions
  • Benefits of cloud CDM
  • Cloud implementation trends in life sciences
  • Explore life sciences solutions
  • Improve your clinical data management with a CDM solution

The challenges of clinical data management

CDM tools help organizations improve efficiency, speed up innovation, and stay competitive

Clinical data management refers to the generation and handling of clinical trial data. This broad umbrella covers many parts of the clinical trial process, from concept work to archiving. There are a lot of factors that influence how clinical trial data is handled:

  • Ingestion
  • Organization
  • Interoperability
  • Automation
  • Confidentiality
  • Access control
  • Integrity
  • Collaboration
  • Regulatory demands
  • Context

Many older systems weren’t designed to offer these capabilities because the landscape didn’t demand them. But today, unprecedented amounts of information need to be effectively managed for optimal results.

Yet while medical and technological advances have been occurring at breakneck speed, traditional CDM strategies struggle to keep up. They often rely on disparate tools that lack interoperability and may come from different vendors. Data might be unreliable and hard to access, and the infrastructure is inflexible. It can also put data quality at risk — with duplicate information and non-standardized protocols running rampant.

Traditional CDM systems evolve slowly and have difficulty adjusting to new demands. Rather than being tools to fuel innovation and progress, they’re used as a replacement for pen and paper, which doesn’t make the most of today’s digital technologies. If a CDM solution doesn’t meet modern demands, it isn’t helping a company use new capabilities to improve efficiency, innovate, or compete.

Modern healthcare and research environments are increasingly complex. These facilities need to meet demands for more patient-centered care while working with complicated protocols, sophisticated technology, and decentralized clinical trials. They may work with data from dozens of different sources, ingesting high amounts of it and organizing it in an understandable and actionable way. Balancing many data streams with the need for adaptability, collaboration, a 360-degree view of health, and faster workflows calls for more sophisticated technology than ever before.

While solving these challenges, a new data strategy has to keep security front and center. Healthcare facilities are some of the most attractive targets for hackers, with plenty of critical data and a critical need to stay up and running. Hospitals can't pause on offering life-saving care, and all life sciences organizations need to maintain their image as trusted wardens of patient data. With so many data sources and new types of technology, a CDM platform must offer top-tier security.

Cloud services solutions

Life sciences organizations can unify complex processes in a single environment with the cloud

Cloud-service solutions are some of the best ways to create a well-rounded approach to CDM strategies. Globally, the healthcare cloud computing market is expected to jump significantly, with a compound annual growth rate of 28.5% predicted between 2020 and 2026. Life sciences organizations are taking advantage of everything the cloud has to offer.

A cloud-based CDM tool stores its data in a main server, where people can access the information from any authorized device or location. Often, this server is public, located off-site, and managed by teams of data professionals. Private and hybrid options are also available. When your data is located in cloud servers, you get a host of benefits:

  • One centralized location for all content
  • Easy collaboration
  • Trusted, up-to-date information
  • Automation
  • Scalability
  • Security
  • Data backups

In the world of clinical data, cloud CDM solutions are the ideal repository for the vast array of information being used. In the collaborative, innovative clinical research environment, the cloud offers a go-to location for everyone to work.

Team members can access the same documents, work on projects simultaneously, and collaborate more efficiently. Cloud CDM tools help with everything from sharing datasets with regulatory agencies to developing a report summary with input from dozens of team members.

Moving to the cloud solves the challenges of traditional CDM solutions. It unifies complex processes under a single, highly capable environment. This infrastructure is scalable, flexible, and interoperable. All of the data and processes you’re working with can be used alongside industry-leading technology and platforms, and cloud-based solutions can evolve with industry trends and organizational demands smoothly and easily.

Say you have a large new trial coming up that will demand more data than your current infrastructure can handle. With a traditional solution, you’d need to purchase and implement costly new hardware and wait for the IT team to get everything in place before you could move forward. With a cloud solution, you can access space on your provider’s servers almost immediately. You can scale up as needed and then downgrade if the demand spike is temporary. You can adapt to new technology and industry changes right away, staying ahead of the curve.

While solving the major challenges of a traditional CDM system, the cloud offers an array of other features that accelerate life sciences operations, like automation and advanced data processing. These tools have become vital in dealing with the vast amounts of data collected in trials today.

Benefits of cloud CDM

Cloud data management offers collaboration tools, flexibility, and affordability

The features and capabilities of the cloud translate into significant benefits for clinical research organizations (CROs) and other life sciences organizations. From up-to-date information and data aggregation to collaboration tools, flexibility, and affordability, cloud data management is the way forward for CROs.

Real-time data access

Traditional systems may involve sharing information the old-fashioned way: sending emails, saving a local file, editing it, and sending it back. This process creates a sizable delay and creates inefficiency. There’s also a strong possibility that the information will be outdated by the time it reaches different people.

In the cloud, updates occur in real time and are immediately visible to everyone. Data becomes dynamic, and you see developments as they happen. This real-time access eliminates slow processes, like waiting for an important file or cross-checking information to verify its recency. It also makes it easier to identify potential problems based on up-to-date information. Quicker identification means quicker resolutions and fewer hiccups.

Consider a trial in which you’re collecting patient vitals from wearable devices throughout the day. Due to an error, data hasn’t been transferring correctly. In a traditional solution, the data might be entered once a week — meaning a week could go by before anyone would notice that vitals haven't been collected. In a cloud solution, the numbers update immediately. Researchers spot the error, fix it quickly, and ensure the trial stays on track.

Real-time data access also allows for easier decision-making. With all of the information up to date and at your fingertips, you can quickly make decisions with confidence.

Improved data aggregation

Stages of clinical trial processes: concept, protocol, research, analysis, security

Many healthcare companies have siloed data systems where teams and departments work in separate environments. They don’t share data, and they don’t work together. In these systems, it’s common for teams to duplicate data or spend time entering the same data into multiple systems.

Cloud systems eliminate these siloes, allowing teams to dip into the same pool of information. That data pool is standardized and confidential, easily sorting through massive amounts of data and delivering it to the right places. Only the right personnel are allowed to access and edit content.

Data is central to any clinical trial, and there can be a lot of it. Cloud solutions make sense of this information, aggregating it into an optimized environment and significantly reducing the middleman — and the greater risk for error — involved in manual data entry. The cloud organizes the data into a centralized location, but it also extends capabilities far beyond simple document storage.

  • Concept: Gather and store insights from various stakeholders about the trial’s design and goals
  • Protocol: Work with administrators, researchers, regulators, and others to establish up-to-date protocols
  • Research: The cloud can easily manage data from tens of thousands of sources, making it accessible to everyone who needs it
  • Analysis: Standardize your data, visualize it, and send it through regimented workflows and processes
  • Security: Extensive security underpinning the platform allows for secure data storage and transmission, while features like access controls, logs, and archiving policies help meet regulations

Throughout the process, cloud-based CDM systems add visibility. Data is clearly organized and accessible. Supervisors can pop into a folder to check on progress, and team members can easily access the datasets they need. Project management becomes easy with clear activity tracking and workflows.

Many cloud CDM tools also maintain detailed audit logs and allow for complete control over data governance policies, so you know where your data goes and when.

Interoperability and collaboration

Cloud CDM solutions allows the use of other collaborative platforms

Collaboration is a key part of innovation, the driving force for most CROs. Bringing together new ideas and unique perspectives contributes to exciting discoveries. Research depends on input from many parties, such as scientists, clinicians, data analysts, academic institutions, and stakeholders. From a business perspective, collaboration is necessary for efficient operations, allowing different players to work together faster and more easily.

The cloud enables collaboration from anywhere. Whether team members are in the same building or remotely dispersed, they can work together in the cloud, accessing and editing content simultaneously.

Robust features like virtual whiteboards, in-document comments, and version histories allow for extensive communication during content-centric processes. With granular permissions, creators can restrict access and editing permissions as needed. It’s also easy to securely share content with options for password protection and up-to-date visibility, even for people outside of the organization.

Cloud CDM solutions can even extend collaborative tools and access to other platforms you use every day. From integrations with popular business platforms like Microsoft and Zoom to custom application programming interfaces (APIs) embedded in your systems, the cloud enables easy interoperability. Send a dataset in a Slack message, or upload a local Word doc to a cloud file that supports multiple editors. You can collaborate with other people within the company and those outside of it with a direct connection to the data held in the cloud.


In the cloud, teams can collect more data and conduct trials from anywhere

The cloud also adds necessary flexibility to clinical trials, data management, and company infrastructure. As more devices and platforms emerge to help with clinical data collection, the cloud allows researchers to choose from more data collection methods and conduct trials from anywhere. There are fewer limitations for location and device selection, so researchers can broaden their scope and use devices that better fit their trials.

More flexibility means that researchers can:

  • Increase participation through more convenient assessments
  • Gather more data points by eliminating the need for travel to collect them
  • See how data changes throughout the project and make decisions accordingly
  • Partner with organizations and participants from anywhere through various interoperable platforms
  • Reach a broader scope of participants and partners<, and work with larger sample sizes
  • Easily abide by regulations and security standards built into the platform

Along with flexibility for the trial itself, the cloud also offers flexibility for the organization as a whole. You can add storage as needed and use your data alongside popular platforms and agile developer tools.

Cost efficiency

Cloud services are also cost-efficient. Setting up a traditional CDM system comes with considerable expenses, including a skilled IT team and hardware purchases. These systems must be meticulously maintained over time and updated to meet ever-changing demands. If you require more data or infrastructure adjustments, you need to wait while the team implements the upgrades. Even if you already have a traditional system in place, maintenance costs can quickly add up as you find yourself replacing aging components with security and operational risks.

These costs are also tough to plan for. Repairs and upgrades can pull a significant — and unexpected — chunk out of your budget. The initial equipment costs can be hard to work with, especially for smaller organizations that may not have much capital lying around.

With a cloud CDM solution, the provider covers the costs of hardware, maintenance, and expertise. You pay for what you need and can easily scale your usage. You don’t have to rent out server space, maintain in-house IT support, or scramble to accommodate changing business needs.

The cloud can also be easier on your accounting team, since these services are typically charged on a predictable, repeating schedule.

When considering the cost of your CDM solution, it's important to look beyond the hard costs of equipment and service. Improvements to efficiency can save countless labor hours, while security improvements can save millions by preventing data breaches.

Cloud implementation trends in life sciences

The cloud offers benefits for virtually every organization, but it’s supporting several big trends in the life sciences industry.

Improving business agility

Life sciences organizations can benefit from custom solutions, fast data sharing, and flexible infrastructure

As healthcare and clinical trials push through new frontiers, CROs have seen the value of agile operations. Whether that means switching to remote work overnight or implementing new technology as quickly as possible, agility is a key part of staying flexible and competitive.

The cloud’s custom solutions, speedy data sharing, and flexible infrastructure allow life sciences organizations to make adjustments on the fly and maintain flexibility.

Leveraging big data

Making sense of all of the information that comes through a life sciences facility can be challenging, but big data makes it simple. Big data is all about using modern technology, like artificial intelligence (AI) and machine learning, to parse through massive amounts and varieties of information and turn them into valuable, actionable insights.

In life sciences, big data might bring together information like patient vitals, behavioral data, medical records, family histories, staff credentials, outcome reports, and much more to create a more comprehensive picture.

The nature of big data breaks down silos for shared access. With the help of AI and other sophisticated data-processing tools, the cloud can support a 360-degree view of information. Life sciences organizations can use this data to work more efficiently, uncover new connections, and ultimately improve the vital work they do.

Boosting collaboration

Another major goal in the industry driving cloud adoption is a push for more collaboration. While collaboration has always been fundamental to life sciences research, many organizations are beginning to explore what it looks like in the digital sphere.

With decentralized trial environments and more people working from home, helping team members and partners link up and work together looks slightly different than when work primarily occurred in person. The cloud offers extensive collaboration, and many companies have seen how they can use it to extend their connections with new partners.

The cloud is an excellent vehicle for meeting these goals with APIs, easy file sharing, and a wide range of collaborative tools.

Improving remote care

Life sciences organizations improve remote care with cloud-based CDM tools

Telehealth launched to new heights in 2020, and it’s here to stay — 76% of users say they’re interested in using telehealth going forward. Remote patient monitoring is also on the rise. Many life sciences organizations now use cloud-based CDMs to optimize remote care. Researchers might streamline data collection from remote monitoring devices or use big data to help clinicians better understand their telehealth patients’ care.

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**While we maintain our steadfast commitment to offering products and services with best-in-class privacy, security, and compliance, the information provided in this blog post is not intended to constitute legal advice. We strongly encourage prospective and current customers to perform their own due diligence when assessing compliance with applicable laws.