Clinical Financial Analytics & Forecasting: Leveraging Investigator Payment Data as a Strategic Management Tool
By Kyle Cunningham, Vice President of Product, Greenphire
Running a clinical trial has become more complex, and more costly, than ever before. The average cost of taking a new drug to market is astronomical, with figures ranging from $350 million for a single drug to over $5 billion for large pharmaceutical companies that work on dozens of drug projects at once1. The expense of running clinical trials is a significant contributor to these costs. In fact, Phase III trials now represent about 40% of pharmaceutical companies’ total R&D spend and up to 90% of the costs of developing an individual drug.2 One factor is that clinical trials themselves have become more complex, and consequently, more difficult to manage. Between 2001 and 2011, protocol complexity and the related administrative burden grew significantly. The average number of unique procedures per protocol has increased from 20.5 to 30.4, and the number of total procedures per protocol has risen from a median of 105.9 to 166.6.3 Research estimates that this has increased the workload on investigative sites by over 60%.4
Global trials have added to the complexity of managing investigators by introducing issues such as language barriers, different regulatory environments and currency exchange. This increased complexity and burden on investigative sites has a significant impact on costs. By one estimate, investigator costs account for an average of 48% of the total cost of clinical trials5 ,while completing a trial on-time is also an issue, with 72% running over schedule by more than a month.6 Although the picture of growing costs and complexity may appear grim, it is also clear that there are opportunities to manage and reduce expenditure. Adjustments to a number of study factors including site management and selection, as well as the automation of data capture, all hold the potential to reduce costs without compromising scientific validity.
As investigator payments represent a large proportion of costs, evaluating site selection and performance is important in budget management. Analyses conducted by Pfizer and Lilly in 2011 found that sites that have performed well on one study are 70% more likely to perform well on subsequent studies.7 Therefore, centralising, aggregating and analysing investigator data is vital. Despite this, payment data that could be used to evaluate cost and performance remains a largely untapped resource. Since many organizations have not yet centralized investigator payments across studies, using this data for evaluation is near impossible. However, if investigator payments are centralised in a single system, they can be aggregated into a source of analytics to help proactively manage and reduce costs throughout a trial.
Clinical Financial Analytics
To understand the complexity of trial payments, Greenphire worked with a sponsor to determine how many payments it made to investigators during a typical Phase III study. Each of the 1,200 patients involved made an average of 14 visits. In this instance, these visits took place at 200 different investigative sites across multiple countries; each site had up to three separate contracts that govern payment milestones. In total, the study included 50,000 payment milestones across 600 contracts. Not only is this number of payments difficult to manage and track, but it is clear that if this data could be mined, the sponsor could derive important information related to cost drivers and site performance in order to optimise cash flow management and enrolment planning.
Centralising data creates a strategic tool for use throughout the lifecycle of a trial, however, the complexity and volume of data can be overwhelming. Clinical financial analytics are simply a way of collecting and analysing the vast amount of payment data into metrics, reports and usable information to render it actionable and enable better decision-making and pro-active management. Accessing this data has many advantages including predictive cost modelling and the ability to understand the cost impact of country, study and site level contract decisions, as well as forecasting the impact of enrolment activities on costs. Effective cash flow management can be better ensured through the ability to project costs and payment exposures, while the opportunity to identify patterns in country- and site-specific performance can inform future planning.
Cost Forecasting & Testing Assumptions
When planning a trial, sponsors often use benchmarking tools to create a budget for investigator- and patient-related costs. By the end of the trial, significant variance between budgeted and actual costs are often observed. This can be due to changes in enrolment, contracted rates with individual investigators that differ from what was originally benchmarked, investigator performance, patient retention rates and currency fluctuations. Predicting and managing these issues can ensure a trial is completed on-time and on-budget and that cost expectations are set appropriately.
The potential for variance presents an opportunity. As the planning and contract negotiation phase of the trial progresses, managers can use scenario-testing tools to understand relevant cost drivers. Scenario A (Figure 1) and B (Figure 2) help visualise the dramatic effect of patient enrolment and contract negotiation performance on costs. Scenario A depicts a cost example in which subject enrolment and contract negotiation with clinical sites are not carefully managed. As a result, enrolment numbers are slightly high for the needs of the study and site costs are relatively high. In Scenario B, however, enrolment is maximised at the lowest-cost sites, whilst maintaining distribution across all six sites. Additionally, each contract is negotiated and slightly lower rates are obtained for site overhead costs.
Figure 1: Scenario A
Figure 2: Scenario B
Patient-related costs remain constant between the two scenarios. Scenario B is 20% less costly than Scenario A. Assuming that this 20% savings was extended across a trial that includes 200 sites globally and had similar costs, this would save almost $2million over the study. Although this example is a simplification of the many potential scenarios, it does show the importance of scenario planning and assumption-testing in projecting and managing actual costs. By entering and testing assumptions, trial managers can determine which factors are important in a trial, determining where to focus oversight efforts.
As contract negotiations begin and site agreements are ultimately executed, an opportunity presents itself to create better projections of actual costs as the trial unfolds. Linking budget data is therefore necessary to accurately project variances and to set appropriate cost expectations. Figure 3 shows how linked data allows the evaluation of contract negotiations versus original assumptions in order to proactively identify cost risks and opportunities before enrolment has progressed. The example shows that the initial budget accounted for 20 patients in the US for a total of $20,000 in patient costs. During the contract negotiation phase, sites were contracted to enrol 26 patients, raising the patient-related cost by 34% to $26,800. This increase should raise a red flag that careful oversight of the enrolment process is needed.
Figure 3: Contracted v. budgeted costs
Trial managers could use dynamic clinical financial analytics to evaluate when enrollment should be capped (Figure 4). With access to real-time analytics, Trial Managers can understand when enrolment requirements have been reached in order to contain patient-related costs. Beyond this, the constant refinement of cost projections based on real-time information on the status of patient enrolment at each site helps to provide continually revised cost estimates that are significantly more accurate than previous budgeted numbers.
Figure 4: Contracted costs v. budgeted costs v. actual costs
Cash Flow Projections
Once the enrolment phase is completed, analytics begin to play a different role. Since contracted rates and patient numbers are likely to remain relatively static, managers are more likely to be looking at costs issues from an operational perspective. This means evaluating whether the trial is on track from a cost perspective, and keeping track of cash outflow needs, current liabilities and payments to CROs. At the outset of a study, a first step in predicting cash outflows involves protocol analysis. By combining financial information with contract logic and protocol information (e.g. timing of visits), projections can be made on when cash outflows will be expected over a study. The protocol analysis can then be combined with enrolment projections or actuals, expected drop-out rates and operational visits to create a full cash-slow projection for a study.
When payments are underway, sponsors or CROs can also monitor the amount of payments owed, or the amount of payments paid versus the amount contracted to be paid. This can be easily compared to the current activities completed, so current exposures and potential future liabilities can be identified (Figure 5). Access to this information is also useful for identifying sites that are slow to create invoices and pro-actively addressing the problem, ensuring all contracted obligations are met and ensuring successful close-down of the study from a financial perspective.
Figure 5: Identifying current exposures and potential future liabilities
Cycle Times & Site Management
Using financial analytics, managers can keep track of performance in terms of speed and accuracy of payments to sites. Using this data, it is possible to keep careful tabs on how long it takes the typical site to progress between specific milestones. For example, tracking the average number of business days from the date an invoice is generated to the date the payment is confirmed gives financial managers insight into the average cycle time for payments to investigators.
This number is particularly relevant as sites continually cite cycle time as a business challenge for them in managing clinical trials. In fact 37% of investigators say that the typical reimbursement from a sponsor takes more than 90 days8, and 40% of sites see slow payments as a primary operating concern.9 Sponsors and CROs that can improve operational performance when it comes to paying sites are likely to keep their sites more satisfied.
Leveraging Financial Analytics
At study completion, clinical financial analytics should be used to assess how and why costs ultimately differed from budgets. Because this information can be obtained at the site- and country-specific level on a study-by-study basis, it is invaluable in planning future trials. Questions relating to patient enrolment analysis (e.g. Which sites enrolled the most patients?), site financial performance analysis (e.g. How much did each site cost relative to the budget?, country performance analysis (e.g. Were certain countries unexpectedly cost-effective/expensive?) and financial management performance analysis (e.g. How well were cash flow needs predicted?), should all be asked at this point. With a full debrief of the issues, sponsors can ensure they understand the cost drivers related to investigator payments in their trials and can plan future studies accordingly.
Clinical financial analytics are a powerful tool for cost management and performance evaluation in a trial, but, to benefit, an organisation needs to take certain steps. The first is to centralize payments, as when payment information remains disbursed in various silos, tracking and analysing remains impossible. A single, web-based platform to centralise and automate clinical payments to investigators can overcome these issues. This type of solution allows data to be pulled together from a range of sources. Combining payment data with contextual data like contracted terms, requirements, enrolment data and completed activities and milestones, creates the opportunity for analysis that can inform strategic management.
The use of these analytics are valuable at different points in a trial and it is important to gather stakeholders together to evaluate the metrics at various stages, particularly during contract negotiations, patient enrolment and study completion. In addition, analytics show trends and particular costs issues, but it is vital that managers are proactive in addressing any issues that arise and to manage expectations when cost projections change dramatically.
Incorporating these practices into trial design will help transform the payment management process into a method of aggregating strategic data that optimises trial forecasting, planning, tracking and quantitative assessment. This enhanced analytics functionality offers unique insight into the financial health of clinical studies and enables sponsors to leverage payment data as a strategic management tool, making more effective business decisions, in real-time, that ensure a trial is completed on-time and on-budget.
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- Herper, Matthew. “The Cost Of Creating A New Drug Now $5 Billion, Pushing Big Pharma To Change.” Forbes. 11 August 2013.
- Roy, Avik. “Stifling New Cures: The True Cost of Lengthy Clinical Drug Trials.” Manhattan Institute for Policy Research. 5 April 2012.
- Getz et al..” Variability in Protocol Design Complexity by Phase and Therapeutic Area.“ DIJ 2011 45(4); 413-420.
- Getz et al..” Variability in Protocol Design Complexity by Phase and Therapeutic Area.“ DIJ 2011 45(4); 413-420.
- Applied Clinical Trials “Benchmarking Investigator Payments” Author: Jeremy Klein, 2012
- Rosenthal, Gary. “Innovative Approaches for Conducting Efficient Lower Cost Pragmatic Clinical Trials.” Institute for Clinical & Translational Science. 31 May, 2012.
- Getz, Ken. “Predicting Successful Site Performance.” Applied Clinical Trials. 2011
- CenterWatch Survey of Global Investigative Sites, 2012; N=257
- CenterWatch Survey of Global Investigative Sites 2011; N=1,205
Kyle Cunningham is Vice President of Product at Greenphire. With more than 15 years’ experience spanning product strategy, development and operations management, Kyle is responsible for ensuring that Greenphire remains both innovative and client-focused, responding rapidly to market needs by identifying and understanding clients’ unique business challenges and building state-of-the-art solutions that solve them.
Greenphire is the industry’s leading provider of clinical payment technology, designed to change the way research professionals work. We leverage our proprietary workflow automation and advanced web‐based payment technologies to help our clients improve operational efficiency, reduce costs, mitigate regulatory risks, increase subject retention and compliance, and produce quantifiable results that improve clinical operations and strategic planning. Learn more at www.greenphire.com.