New Infrastructure Is Needed to Create Value
Developing and commercializing personalized medicine requires that top executives at life sciences companies become value managers and support a value management infrastructure, Jeff Elton examines and explains...
Those life sciences companies which are advancing personalized and targeted therapeutics are realizing the vast amounts of increasingly diverse data they must access, combine and analyze if they are to interpret and communicate the value of their innovative therapeutics.Data from patient-specific electronic medical records (EMRs), genomic and genetic data, electronic patient-reported data, and financial data offers practical insight into how to optimize patient care and determine those therapies that can provide the highest overall value to patients and health care systems.
Unfortunately, few companies have made the necessary preparations to take on the challenge of this data analysis . In contrast, the sophistication of the payers and risk-bearing providers, with whom they interact, moves forward. This imperative to be ‘value managers’ must be anchored, catalyzed, and overseen at the highest corporate levels. Value management represents a new operating model in which multiple business functions share the same data and analytics capabilities.
Corporate Strategic Transformation Required
Establishing the required infrastructure and data governance, and integrating analytics at the core of executive management are both a strategic and transformative activity. As a result, companies will have new talent requirements for data scientists, and will have to establish imperatives for continuous longitudinal analytics and prospective analytics if they are to make significant decisions or direct strategies.
“In many developed countries more than 50% of patients have their data captured in EMRs.”
A Data Tsunami and Analytics Desert
A data tsunami and analytics conundrum is building for which few life science companies are prepared. The volume of data generated internally at life sciences companies has been increasing, generated by:
- R&D groups using next generation sequencing tools.
- Researchers harnessing electronically captured clinical trial data and patient samples.
- Scientists utilizing enterprise-wide operations data, and third party acquired datasets and services.
The amount of external data on these therapeutic products has been increasing at an even greater rate. In many developed countries more than 50% of patients have their data captured in EMRs. This will rise to close to 100% in many European countries, the US, and a number of Asian countries in the next two to four years. To date, this data has rarely been meaningfully transformed through analytics into practical, value-delivering insights. But this is beginning to change.
The Impact of New Data
When analyzed, this data will help define whether a company’s products deliver value relative to competitors and comparators. The data will be the basis for new care management approaches. Many government and private payers already support the need to use data as the basis for making decisions to reimburse new and existing therapeutics. In the US, almost every national private payer or coalition has developed a separate data and analytics business to accelerate this transition to a new care management approach.
Meeting the challenge requires life sciences companies to access external EMR-derived clinical data, genomic, financial, and other data organized around the patient, with an understanding that minimizing cost and optimizing therapeutic performance are important. Typically this is done by working with third parties to access and understand unstructured data such as physician notes, combine different types of data, and harmonize them in a consistent data model. The greatest insights can be gained when this data can be combined with proprietary internal and other third party data.
New Operating Model
An important part of this process requires companies to establish the operating model and supporting processes through which these analytics will drive value management. This entails using value analytics throughout the enterprise, establishing a common data substrate, having a common view of what drives product value, and utilizing differentiated analytics that support key business functions and customer solutions.
To deliver this operating model, a new set of internal data infrastructure and capabilities are needed, centered on enabling technologies, analytics capabilities, and new data. The effort requires a significant investment in technology, managed services relationships with partners, and a clear roadmap for capabilities and talent development.
In most organizations there is no single executive responsible for these efforts. Traditionally, the CIO is focused on internally generated data, applications and the functions supporting internally consumed services. Corporate medical functions have not historically driven enterprise-wide IT or analytics solutions. Commercial functions have generally been therapeutic-area driven, except for specific sales force tools. Some organizations have evolved a new integrating role of chief medical information officer, borrowing on a role found among health providers and payers. However, this new role is focused primarily on new clinical data sources and not enterprise-wide association and analytics.
“Defining, deploying and utilizing data and analytics that support value management must be the responsibility of top executives.”
Value Infrastructure as a Leadership Imperative
Defining, deploying and utilizing data and analytics that support value management must be the responsibility of top executives, with clear leadership coming from them. Accenture has seen organizations in which the CIO partnered with medical leadership to catalyze change. In others, it has been a commercial, IT and medical triumvirate.
Companies who are initiating this transformation are seeing benefits from piloting new operating models and go-to-market structures focused on care management solutions that benefit patients and provider system economics. For other companies, the transformation is changing which therapeutics are resourced from late discovery through full commercialization, eliminating those therapeutic development programs that offer no clear value.
CEOs of life sciences companies are becoming chief value officers, assuring that personalized therapeutics and intellectual property assets of a company are fully valued by, and compensated for, by the market. The role is necessarily externally focused, assuring that data and insights from critical provider and payer relationships are accessible to the entire company. To successfully address future needs, the role requires integrating data from medical, research and development, managed markets, and commercial business functions, and then creating value at the intersection of these data.
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