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Research Informatics: Infrastructure or Competitive Advantage?

Originally published February 15, 2010

In today’s modern work environment, we have grown increasingly reliant on computers and the Internet. We have grown to expect that when we turn on the computer and click on an application, the information will come pouring out like running water from the kitchen sink. Just as email, word processors and spreadsheets are considered staples in business computing, research informatics environments that help us integrate, report and analyze data are achieving that level of prominence in our everyday world.

Over the past decade, ThotWave has been involved in the design and construction of a number of these informatics environments and a flurry of recent activities from vendors that prompted us to ask the question – can informatics environments be a competitive advantage or are informatics merely infrastructure required to operate? In this article, we will look at a few examples from clinical research and healthcare delivery environments and discuss how the creation of informatics environments can be positioned for value beyond just another IT infrastructure component.

Informatics: A Brief Overview

Informatics is a term used in healthcare and life sciences to describe computerized information systems that support a variety of research based business intelligence and analysis requirements. We often hear the terms bioinformatics, medical informatics, health informatics, nursing informatics or clinical informatics to describe the business context in which “business intelligence” is used to analyze information derived from or for research activities. For a more comprehensive history and analysis of the use of informatics and its application in the health and life sciences, I encourage you to review Dr. William Hersh’s treatment of the subject (Hersh, 2009).

Healthcare Informatics

In healthcare, we are seeing a surge in the establishment of formal informatics departments in hospitals, hospital systems, large clinics and integrated delivery networks (IDNs). The focus of these departments is fundamentally the application of business intelligence to supporting the operations, strategic planning, education and/or research using healthcare data. Historically, financial informatics have dominated the business intelligence landscape within the healthcare delivery environment, but we are seeing more and better use of integrated data to help understand patient outcomes, clinical decision support and evidence based medicine, patient safety, nursing education and generally to gain a better understanding patient populations served by the organization. Providers are now utilizing business intelligence to support disease management, EMR adoption (and measurement of meaningful use), and to improve performance on pay for performance (P4P) metrics and other quality initiatives.

The value of creating a healthcare informatics environment can be seen in the results that this information delivers. For example, at Brigham and Women’s Hospital in Boston, business intelligence is used to report on key performance indicators from across the organization. By combining both administrative and clinical data, they have created a unified environment for analyzing information on patient outcomes and operational metrics which help them provide the much needed transparency and accountability that is dominating the business climate in healthcare today. As we shift from patient to consumer, our orientation to how we treat patients and manage the relationship becomes even more critical.

Moreover with programs like P4P, the Physician Quality Reporting Initiative (PQRI) and ever evolving quality measures mandated by the Center for Medicare and Medicaid and private payers, access to high quality, integrated data has become necessary for these organizations to remain competitive and viable. With less than a third of the US based hospitals remaining profitable, using business intelligence for improving reimbursement rates is not only competitive advantage, but critical for their viability. Across the ocean, the National Health Service (NHS) is deriving benefit from business intelligence to create predictive models that help the Primary Care Trusts in the UK predict patients with higher likelihood of requiring hospitalizations. Although the NHS is a government run program, reducing the number of patients that get admitted to the hospital is not only good practice, it is essential given the high cost of healthcare. Organizations that continue to use BI and analytics as preventive medicine will remain on the forefront in healthcare practitioners.

The good news for most healthcare organizations is that with the move to electronic health records (EHR), accessing data is far more achievable than we saw in recent decades, as most records were paper based or stuck in proprietary databases. The opportunity to create centralized environments for the collection, integration and analysis of clinical and administrative data is now upon us. Unfortunately, many organizations are focused on measuring “meaningful use” of the EHR and are up to their eyeballs in implementation. Investing the time to understand the long-term business intelligence strategy both within the hospital/clinic and across the health exchanges is gaining prominence. Developing an informatics road map now while these systems are being designed and implemented will go a long way to providing the decision support capabilities down the road.

Clinical Research Informatics

The pharmaceutical and biotechnology industries have been long time users of informatics to integrate and analyze data from pre-clinical discovery all the way through clinical trials and post-marketing safety and efficacy studies and patient registries. For the whole of this industry, the tools and technologies have evolved slowly over the past 20 years.

The business problem for these industries is clear: they are focused on creating products that produce better outcomes and improved quality of life for patients through safe and effective therapies. The myriad of organizations that operate in this ecosystem produce a dizzying array of products that include drugs, devices, biologics, nanotechnology, cosmetics, vaccines and so on. And while these companies produce different products, they all, for the most part, have the same core functions that must be managed through information technology and processes. These include:
  • Protocol Design and Study Start-Up

  • Patient and Investigator Recruitment

  • Clinical Trial Management

  • Clinical Data Management

  • Data Analysis

  • Clinical Supplies

  • Regulatory and Safety

While some of these are operational in nature (e.g., electronic data collection and trial management), most contain rich repositories of information that could and should be used across the BioPharma life cycle for both clinical decisions as well as economic and operational. Unfortunately, we rarely see that level of integration, but rather best of breed informatics systems that perform boutique functions.

From NCE to market is estimated to take 8 to 12 years (DiMasi, 2001) and up to $800 million (DiMasi, Hansen, & Grabowski, 2003). About 45% of this cost is accrued during the clinical trial phase (U.S. Congress, Office of Technology Assessment, 1993). Additionally, studies suggest that 80% of all trials conducted in the United States are behind schedule by one to six months (Mattingly, 2003) – a delay which would represent over $30M in additional costs, and a far greater amount in lost revenue.

The silver lining in all of this is that we are seeing a number of advances in clinical informatics technology (sometimes referred to as a Statistical Computing Environment and the announcement of integrated solutions – see, for example, Hopkins, A., Duke, S. & Subman, S. 2010). Some of the vendors include SAS' SAS Drug Development, Phase Forward’s Waban, Oracle’s Life Sciences Hub and even open source offerings such as the National Institutes of Health i2b2 (Informatics for Integrating Biology and the Bedside) platform.

The challenge for organizations that want to adopt one of these enterprise packages is how to justify the cost of software, hosting fees and implementation. As most of these new solutions are in early stage development, experiencing complete re-writes or have limited install bases, the question remains – how can these be positioned as more than just an infrastructure play? Can clinical informatics systems be a true competitive advantage – and how do we measure return on investment (ROI)?

At present, our company is involved in the implementation of a number of these systems, so understanding how these organizations think about the technology was insightful for us as we wrote this. The value of a system that can integrate clinical research data into a repository whereby reporting and analysis can be conducted is essential to any organization doing this type of work. Study organizers first develop a theory based on the belief that some therapy is better than the alternative. They put their theory to test using an experimental design and identify the statistical plan that will help demonstrate that their hypothesis is true. Data collection mechanisms are designed and implemented, data is collected and then biostatisticians, data management and statistical programmers use programs like SAS to analyze data and produce tables, figures and listings. Counts and statistical results are then presented to medical researchers and submitted to regulatory agencies as proof positive that the therapy is safe and effective.

This process has been formalized for the last several decades and it works. As the BioPharma industry has seen dramatic downturns in the economy, the changing payer landscape and reimbursement profiles and shrinking pipelines combined with patent expirations, efficiency and effectiveness have become the mantra to drive down costs and yield stakeholder returns. It is reported that BioPharma companies spend between 20% and 45% of their total budget in acquiring, processing, analyzing and reporting results in the clinical trials process.  Improvements in single digit productivity would produce billions of dollars of savings across the industry.

So is clinical informatics a competitive advantage? If we could optimize the process by which we acquire, process, analyze and report on clinical results – yes. The other question that is often raised, however, is: is this the place in the BioPharma value chain to focus on performance improvement? Should we be focused on sales and marketing effectiveness as so many companies are? Perhaps the focus should be on early discovery and killing therapies / compounds earlier in the life cycle. Or should the focus remain in portfolio optimization?

For most companies, improving how clinical research is done is infinitely achievable. By applying practices from Lean and Six Sigma, we can use methods to select projects that have potentially large savings in efficiency and productivity gains. Until then, the return on investment for new technologies will remain unknown.


In the world of informatics, we see huge opportunities for improving decision making and optimizing processes that rely on data and data movement. At the point of care, we have seen informatics support primary care and disease management, clinical research, registries, public health and safety and pharmacovigilance. Beyond the point of care, informatics professionals use data for economic and global health outcomes “decisioning,” population metrics, organizational performance improvement, regulatory reporting, understanding patterns of care and for the improvement of billing and claims reimbursements.

As we have taken two examples of informatics in use in the health and life sciences ecosystem – healthcare delivery and clinical research – we do so with intention. Our strong belief is that concepts like translational medicine will continue to bring the worlds of primary research, clinical research and bedside care together. The evolution of the healthcare landscape will eventually get to the point where research, diagnostics and care will occur temporally and proximally so that these become institutionalized in the same work processes. Modern technology and interoperability are key to connecting these worlds.

The question is not whether informatics can be more than just an infrastructure but, rather, how can you turn data into competitive advantage? It has to be more than just technology adoption. Attention should be paid to the impact and a clear definition of the critical success factors that will either make or break the investments.

Our recommendation for the establishment of an informatics practice is straightforward.
  1. Assess the level of maturity in your department division or across the organization. Look for how decisions are made and what data is used to support those decisions. Identify pockets of excellence and bring them together and explore collaborations. It is no longer acceptable to have pockets of isolation when it comes to data and systems.

  2. Profile the data and the processes that each of these organizations has and find out what works best (what processes work for which departments, who has the best data, who has the best analytics experts and what works and why). Understand what data is not only accessible, but which data sources provide the richest source of information for your business challenges.

  3. Create a road map that takes into account your business goals and synthesizes requirements – both technical and business – from all corners of the informatics ecosystem in your organization.

  4. Start small by having a long-term business intelligence road map in place, but don’t build the informatics repository out in one fell swoop. Answer compelling business questions as you go with a core set of data and evolve the data over time. Building incrementally shows value early and often and is a lot less risky than the big bang approach.

  5. Celebrate successes by marketing the value created from your efforts, no matter how small, as long as they have created value for the business – celebrate, acknowledge and translate those successes so that everyone begins to understand the value of informatics.
As others have suggested, interoperability within and among companies in this ecosystem will continue to evolve and the true benefits of industry standardization will serve to benefit informatics departments throughout this ecosystem. As you build success through value-creating activities, you will have the support you need to continue to use information for competitive advantage. Starting now and understanding how analytics can be applied and gaining experience now will serve you well.


DiMasi, J. A. (2001). New Drug Development in the United States from 1963 to 1999. Clinical Pharmacology & Therapeutics.

DiMasi, J. A., Hansen, R. W., & Grabowski, H. G. (2003). The price of innovation: new estimates of drug development costs. Journal of Health Economics, 22 (2), 151-85.

Hersh, William (2009). A stimulus to define informatics and health information technology. BMC Medical Informatics and Decision Making. 9:24.

Hopkins, A., Duke, S. & Subman, S. (2010) Statistical Computing Environments and the Practice of Statistics in the BioPharmaceutical Industry. Drug Information Journal, Vol 44. Pp. 29-42, 2010.

Mattingly, D. S. (2003, April). What does the future hold for CROs? Good Clinical Practice Journal, 10.

U.S. Congress, Office of Technology Assessment. (1993). Pharmaceutical R&D: Costs, Risks and Rewards.

  • Greg NelsonGreg Nelson

    Greg Nelson is the Founder and Chief Executive Officer of ThotWave Technologies, the health and life sciences business intelligence company. Greg provides professional services to healthcare, biopharma as well as government and academic researchers. Greg has served as the Director of Technology for the largest, privately held CRO, Director of Application Development for the Gallup Organization and a director at the University of Georgia’s computer center. He has published and presented more than 150 professional papers in the United States and Europe.  

    While Greg has been a practitioner for the past 23 years, his academic roots began with a BA in Psychology from the University of California at Santa Cruz, in addition to doctoral level work in Social Psychology and Quantitative methods at the University of Georgia. Greg also holds a Project Management Professional Certificate. Greg can be reached at greg@thotwave.com.

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