Survey: Do Spreadsheets Still Hamper Clinical Trial Speed & Quality?
By Ed Miseta, Chief Editor, Clinical Leader
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Clinical trial operations is fraught with many hurdles, including quality, cost, and timeliness. To successfully bring new medicines to market, operations managers have to successfully overcome these challenges. Application software provider Comprehend recently produced a “Clinical Operations Benchmark Report,” in which it surveyed executives at leading life science companies. The goal was to determine how companies can speed up trials and more quickly get to quality results across a portfolio of products.
The survey was able to uncover strong consensus from clinical operations leaders on their goals and challenges. The main goals were increasing productivity while reducing cost and risk. But most responders noted there were numerous processes and issues that prevented them from attaining those goals. The path forward is an interactive approach to clinical operations, called “clinical intelligence,” which will enable sponsors to deliver increased speed to trials with quality results.
Dealing With Uncertainty
With the uncertainty that exists in the clinical trials process, is it possible to fund initiatives that will assist companies with meeting their goals? The report notes that in order to deliver a high-quality study on time, clinical operations managers have to make important decisions on both short- and long-term resource allocations. Unfortunately, 80 percent of respondents noted they regularly miss milestones and only 10 percent deliver results on time.
All 300+ respondents noted they are funding initiatives to eliminate uncertainty and improve milestone achievement. Emphasis is being placed on initiatives such as centralized risk monitoring, study quality metrics, continuous quality, and CRO oversight and collaboration. In fact, 100 percent of respondents had at least one milestone achievement initiative underway. By investing in clinical intelligence, respondents hope to eliminate study uncertainty by gaining real-time insight into where they stand on a project and what needs to be done to get it back on track.
Interestingly, each of these initiatives has several objectives in common. They set out to proactively identify issues in order to take corrective action before they become bigger problems. Each initiative also works to ensure data integrity is not compromised during the trial, increasing the probability results will be accurate and reliable.
In order for clinical managers to achieve milestones, it is also important for them to understand their portfolios. Typical questions they raise revolve around:
- What is the status of the project?
- How does our current status compare to our projected benchmarks?
- Do we need to make adjustments to get back on track?
These questions are repeatedly asked by executives, study managers, and CRAs, and are being asked at the portfolio, program, study, and site levels. Clinical intelligence is increasingly being looked at to help answer the questions.
Clinical Intelligence Focuses On Three Areas
After determining the top improvement goals, the survey asked respondents what processes need to be improved to achieve timely, quality results. Three processes were cited by a majority of respondents:
- Subject enrollment, including each stage from screening to completion
- Subject compliance, including protocol deviations, adverse events, and subject visits
- Site productivity, including query rates, data entry rates, and query resolution rates
Complicating the oversight of these three areas is the fact that the data resides in disparate systems, such as electronic data capture (EDC) and clinical trial management systems (CTMS.) Operations teams also obtain data from various third-party vendors, which adds additional complexity to the process. Information on investigative drugs can come from interactive response technology (IRT) or an inventory management system. Endpoint data will come in from various labs and ancillary vendors.
While there is a lot of complexity with the incoming data, most respondents (65 percent) note they rely primarily on manually compiled spreadsheets to gain a view of issues across a portfolio of studies. Those same spreadsheets are used to drive decision making at both single-study and cross-study portfolio levels. While that is not the most efficient manner of managing decision making, less than 10 percent indicated they had an alternative to spreadsheets for portfolio analytics. More than 90 percent of managers indicated they derive data directly from their CTMS and EDC systems, only to manually roll them into a central spreadsheet with data from other systems.
The survey also found 92 percent of managers noted milestone achievement initiatives are not yet automated, meaning key study risks are being rolled up manually into a spreadsheet for the monthly risk-based monitoring (RBM) program readout. Finally, spreadsheets are even used for monthly CRO oversight.
Put all of this together, and it’s easy to see why so many clinical operations executives are having difficulty managing their processes. The challenge for these executives is too much uncertainty due to a lack of transparency. Gaps in their key processes keep them from knowing if studies are performing to plan, what issues exist regarding enrollment, which sites require additional resources, and where risks exist regarding study compliance. All of this leads to the biggest driver of uncertainty: The inability to investigate issues in real-time. “People will literally work nights and weekends just to pull together an obsolete report,” notes one respondent. “By the time the VP gets it and has questions, reality has changed and uncertainty prevails.”
A Roadmap To Milestone Achievement
There is some good news in the report, and that is the hope that lies in clinical intelligence. Today managers are forced to choose between speed and quality. Risk can be mitigated by slowing down the trial and putting a greater focus on quality. Or quality can be sacrificed in lieu of increased speed. For most companies, throwing additional bodies at the problem is no longer an option.
The hope for clinical intelligence is that it will eventually eliminate the need for managers to make the choice between quality and timeliness. Clinical teams will be able to leverage a single system with data aggregation, monitoring, collaboration, and analytical capabilities to manage enrollment funnels, patient compliance, data quality, and site productivity. They will be able to do so across sites as well as studies. It will also provide executives with continuous portfolio monitoring on key performance indicators (KPIs). This will allow them to deliver on the milestones of lowering cost, time, and risk in their trials.
Finally, the report asked respondents about their requirements to implement clinical improvement initiatives. Fifty-two percent cited cross-system and cross-study data aggregation as their number one requirement, followed by unified dashboards, best practice visualizations, dashboard drilldown, and monitoring KPIs.
For this report, the authors surveyed over 300 clinical operations leaders from global life sciences companies. They were interviewed for the express purpose of creating benchmarks that participants could leverage to achieve goals and develop best practices. Eighty-three percent of respondents were from U.S.-based sponsor companies and 89 percent worked for pharmaceutical or biotech companies. The remaining 11 percent were with medical device companies. Thirty-four percent identified as clinical operations executives, 48 percent were clinical operations managers, and 18 percent were eClinical or clinical systems analysts/managers.
For more information, or to obtain a copy of the report, click here.