Are Your Clinical Trial Systems Designed to Run Downhill?

Over the last several years, the American public has grown increasingly frustrated by the inefficiency and cost associated with the US healthcare system. In an effort to improve that system, the HITECH Act was enacted in 2009 to promote adoption and meaningful use of health information technology.

Among other things, the HITECH Act allocated funding to train health information technology (HIT) professionals. I received a grant created under the HITECH Act and recently completed my HIT certification with a focus on Practice Workflow and Information Management Redesign.

As part of this certification, I was trained to assist providers in leveraging health information technology, and more specifically, electronic health records (EHRs). Key components of my coursework related to health information management systems, usability, health workflow process, and quality improvement.

HIT Applications in Clinical Research

Certainly, this training was a bit outside of the scope of clinical research, but for a variety of reasons, I believed it would be worthwhile. In particular, I thought the practices being applied in the broader healthcare system with regard to information technology would provide a valuable perspective in clinical research as well.

And that thought proved to be correct. I was struck by many instances in which these practices and concepts could be applied to clinical research. I can’t possibly describe all of the the potential applications, but I want to highlight a couple of simple concepts in this post and a followup post addressing what healthcare reform can teach us about patient recruitment.

Systems Analysis and Running Downhill

John Gall, who pioneered the use of healthcare information systems in the 1960s, published a book called Systemantics (later renamed The Systems Bible) in 1977. In the book, Gall puts forth several interesting theories about systems with particular attention to how they fail. This book continues to be especially popular among software engineers, but it is applicable in many areas of business.

One point in Gall’s book, in particular, got me thinking about clinical research:

In other words, systems should work with natural human tendencies rather than against them. People will do things if they are easy, but they are less likely to follow processes that require unnecessary or extra steps. Gall’s theory seems like common sense, but his idea is one that is often forgotten in clinical research and in the broader healthcare system.

(For the sake of our lovely running metaphor, I’m going to ignore the fact that running downhill on a steep grade can carry its own set of challenges.)

Are your clinical trial systems designed to run downhill?

Certainly, this question should be considered in the context of operations within sponsors and CROs, and it seems as though it’s being given more consideration than it has been in the past. But sponsors and CROs are less inclined to consider how their systems impact sites and patients, so that’s what I’m going to focus on here.

In fact, attempts by sponsors and CROs to streamline systems internally can even unintentially overcomplicate systems for research sites and patients.

Uphill Systems for Research Sites

One great example of this unintended overcomplication is the increased workload that many EDC systems have created for research sites. EDCs have been such a problem for sites that ClinPage did a 2-part (Part 1, Part 2) series on the subject, and it’s a very informative read.

A quote from Christine Pierre, CEO of investigative site network RxTrials, concisely sums up the primary issue.

We definitely as an industry need to embrace technology far more than we are, it’s just that the development of this particular technology has excluded the site’s perspective,” she says. “The sites get upset, call sponsors, and the circle of frustration begins.

I am a fan of technology but not just for the sake of technology. These systems must be designed to run downhill. Instead, many EDC systems are slow and/or unstable, create duplicate workflow, are user unfriendly (or downright user hostile), and create additional work, among other issues. My experience with EDC as a research coordinator was consistant with what was described in the ClinPage articles.

Clearly, many EDC systems have not been created with the end user in mind, and as a result, using them is like running uphill through a band of zombies equipped with lasers while you argue with a computer. Alright, maybe I’m being a tad hyperbolic.

Uphill Systems for Research Participants

I’ve seen plenty of instances in which systems have created an uphill battle for study participants as well. The systems of sponsors/CROs (and their vendors), as well as those of research sites, greatly determine whether study participation is like running downhill or uphill.

Sponsor Systems and Study Participants

In one instance, I witnessed investigational product packaged in a manner that was both confusing for participants and physically difficult to access. And this investigational product was intended for Alzheimer’s study participants.

This packaging presented both mental and physical barriers for a patient population that certainly did not need them. Furthermore, these barriers served to remind patients of their limitations, which is a reminder that no one enjoys.

Granted, caregivers are often tasked with managing dosing. But if you are familiar with the Alzheimer’s patient population, you know that caregivers are already overburdened and often experiencing limitations of their own.

Though I can’t quantify what this medication packaging cost the sponsor, I’d bet it had a significant impact on patient retention and dosing compliance across a multitude of research sites.

Research Site Systems and Study Participants

Given the close contact research sites have with patients, it’s particularly important that they consider ways to make the experience of study participation as easy as running downhill. Examples of uphill systems that should be eliminated include:

• Difficulty in making appointments, whether that be interaction with a rude receptionist, a long hold time, or other annoyances
• Wasted time during appointments, whether in the waiting room or between study procedures
• Encounters with confusing and/or jargony terminology that is not accompanied by plain language explanation

These examples are just a few instances of uphill research site systems that make study participation difficult.

The Consequences of Uphill Clinical Trial Systems

In a broader healthcare context, uphill systems are somewhat visible because they can result in serious medical error. For example, the traditionally lengthy hours of medical residents are increasingly recognized to be a source of medical errors. As a result, this practice is being questioned by a variety of medical organizations, who have published guidelines that recommend a cap on these hours.

In the clinical research field, uphill systems can result in medical error, but more commonly, problematic systems result in inefficiency. Because the pain point of inefficiency is more blunt than what is experienced when dealing with a sharp pain point like medical error, the full impact of uphill systems can go unrecognized.

A Cascade of Consequences

To use the example of EDC that I discussed above, here are some examples of potential problems an uphill EDC system can generate:

• Site staff grow frustrated with data entry and develop negative attitudes about the study.
• Site staff cannot find the time to deal with the extra workload, and CRAs spend much of their time chasing down staff to catch up on data entry.
• Since staff are spending more time on data entry, they have less time to spend on other aspects of the trial like patient recruitment.
• Site staff lose the motivation to continue enrolling patients because the frustration and time commitment required for that trial is much more than they anticipated.
• CRO staff spend a significant chunk of time fielding complaints from sites and become distracted from their core duties.

As the examples above illustrate, a bad system can create a cascade of consequences, resulting in a trial that runs uphill rather than downhill.

Gall’s metaphor is an interesting way of looking at systems, and I hope you find value in its application to clinical trials. Most of my examples focused on uphill systems, but I’d love to hear your experience with downhill systems as well. What downhill systems make clinical trials successful? What uphill systems create barriers to successful clinical trials? Please share your thoughts in the comments below.

And don’t forget to check out another post about clinical trials systems: What Healthcare Reform Can Teach Us About Patient Recruitment

Thumbnail Image Credit: Flickr