Commentary: Why Pharma Wants EHR Data
Leanne Larson, global head of observational research at clinical research organization PAREXEL International, explains the expanded knowledge base that electronic health records data can bring to the drug development and market access processes:
Leanne Larson, global head of observational research at clinical research organization PAREXEL International, explains the expanded knowledge base that electronic health records data can bring to the drug development and market access processes:
Bringing a biopharmaceutical product to market in todays rapidly evolving healthcare system is a complex process. In addition to the purely scientific challenge of developing new and innovative treatments for diseases of great complexity, gaining broad market access for these products demands answers far beyond those offered by traditional clinical trial data. Yet broad market and patient access is the ultimate goal the only way to truly realize the promise offered by these new and often ground-breaking therapies.
Growing cost pressures in healthcare have dramatically shifted reimbursement and market-access decisions globally, and have altered the data needed to support these decisions. As these newer requirements take shape, payors have begun to draw a line in the sand paying only for what works. Many payors, in fact, are now entering into risk-sharing agreements with pharmaceutical companies, reimbursing only for drugs that produce measurable improvements in patient health. (Groves, et al. 2013)
Answering the Call for Evidence
These agreements, along with other key coverage and reimbursement decisions, often require data that cannot be easily if at all - gathered in a clinical trial setting. While research is still the foundation for evidence generation, that research today increasingly focuses on patient outcomes on how patients are treated, and respond to that treatment, in the real-world.
With observational research playing a larger role in these decisions today, the healthcare industry is able to better understand critical patient outcomes, and provide the data necessary to support meaningful clinical and market-access decisions. Within this field, though, a number of approaches and data sources have emerged as key elements of a successful evidence-generation program. Patient registries, healthcare claims data, electronic health records (EHRs) and even big data have all proven valuable in this area, supporting decisions that have been instrumental in driving successful product market entry and access in recent years.
In one notable example, German payor G-BA rejected coverage for Sanofis premium-priced Lantus, a form of insulin. Sanofi responded with a comparative-effectiveness study of Lantus versus human insulin, drawing upon a large claims database; in this analysis, Lantus was associated with higher persistence rates, and a delay in progression to higher-priced conventional therapy. With this real-world evidence in hand, G-BA reversed its decision, and Sanofi was able to secure contracts with more than 150 individual payors in Germany, in turn providing 90 percent of the German population access to Lantus. (Groves, et al. 2013)
EHR Data Play a Growing Role in Decision-making
EHRs present a different, yet equally compelling and innovative, opportunity to bring emerging technology and data to bear in these critical market-access decisions. EHR data offer several notable advantages over claims data, including the availability of clinical data such as vital signs and lab values, and - perhaps most importantly - a view of real-world, retrospective, longitudinal treatment patterns. When employed as one element of a research portfolio that also includes prospective research to fully explore key research objectives, EHR data offer a less-expensive opportunity to identify clinical outcomes practice patterns and trends.
EHRs are also rapidly penetrating the healthcare system, with the promise of broad access to large patient datasets for retrospective analysis. EHR usage in the U.S. rose from approximately 30 percent of physician offices and hospitals in 2005, to more than 50 percent of physician offices and 75 percent of hospitals by the end of 2011. (Groves, et al. 2013) Moreover, many key EHR providers, such as Epic and Cerner, offer contracted access to their deidentified, aggregated datasets, further advancing the opportunity to utilize these data in a broad range of analyses.
While there are important limitations to these data including missing information and inconsistent data-recording across providers/facilities - the ability to look retrospectively at a patients course of treatment and associated clinical outcomes, over a period of months or even years, is fueling strong interest in using data from EHRs to support numerous research programs and decisions.
Additionally, EHR data are also expected to play an important role in prospective observational research in coming years. As technology advances allow for a more universal interface between electronic data-capture (EDC) systems and EHRs, this application will likely have a significant impact on the design and operation of observational research. In this setting, the EHR will pre-populate the research case-report form with data available from the EHR, streamlining the research process and reducing data-entry and other errors. As more EHRs allow this connection with research-operations processes central to clinical and market-access decision-making, EHRs will provide even greater support and value to the healthcare system, enabling patient access to important new therapies.
A Vision for EHR Data
The role of EHRs in supporting biopharmaceutical market entry continues to evolve, as both the technology and the decision-making processes themselves change and advance. With the ability to provide broad, longitudinal data in a retrospective setting, these systems can allow rapid, less-costly analysis and insight, supporting key payor and regulator processes and decisions.
Bringing a biopharmaceutical product to market in todays rapidly evolving healthcare system is a complex process. In addition to the purely scientific challenge of developing new and innovative treatments for diseases of great complexity, gaining broad market access for these products demands answers far beyond those offered by traditional clinical trial data. Yet broad market and patient access is the ultimate goal the only way to truly realize the promise offered by these new and often ground-breaking therapies.
Growing cost pressures in healthcare have dramatically shifted reimbursement and market-access decisions globally, and have altered the data needed to support these decisions. As these newer requirements take shape, payors have begun to draw a line in the sand paying only for what works. Many payors, in fact, are now entering into risk-sharing agreements with pharmaceutical companies, reimbursing only for drugs that produce measurable improvements in patient health. (Groves, et al. 2013)
Answering the Call for Evidence
These agreements, along with other key coverage and reimbursement decisions, often require data that cannot be easily if at all - gathered in a clinical trial setting. While research is still the foundation for evidence generation, that research today increasingly focuses on patient outcomes on how patients are treated, and respond to that treatment, in the real-world.
With observational research playing a larger role in these decisions today, the healthcare industry is able to better understand critical patient outcomes, and provide the data necessary to support meaningful clinical and market-access decisions. Within this field, though, a number of approaches and data sources have emerged as key elements of a successful evidence-generation program. Patient registries, healthcare claims data, electronic health records (EHRs) and even big data have all proven valuable in this area, supporting decisions that have been instrumental in driving successful product market entry and access in recent years.
In one notable example, German payor G-BA rejected coverage for Sanofis premium-priced Lantus, a form of insulin. Sanofi responded with a comparative-effectiveness study of Lantus versus human insulin, drawing upon a large claims database; in this analysis, Lantus was associated with higher persistence rates, and a delay in progression to higher-priced conventional therapy. With this real-world evidence in hand, G-BA reversed its decision, and Sanofi was able to secure contracts with more than 150 individual payors in Germany, in turn providing 90 percent of the German population access to Lantus. (Groves, et al. 2013)
EHR Data Play a Growing Role in Decision-making
EHRs present a different, yet equally compelling and innovative, opportunity to bring emerging technology and data to bear in these critical market-access decisions. EHR data offer several notable advantages over claims data, including the availability of clinical data such as vital signs and lab values, and - perhaps most importantly - a view of real-world, retrospective, longitudinal treatment patterns. When employed as one element of a research portfolio that also includes prospective research to fully explore key research objectives, EHR data offer a less-expensive opportunity to identify clinical outcomes practice patterns and trends.
EHRs are also rapidly penetrating the healthcare system, with the promise of broad access to large patient datasets for retrospective analysis. EHR usage in the U.S. rose from approximately 30 percent of physician offices and hospitals in 2005, to more than 50 percent of physician offices and 75 percent of hospitals by the end of 2011. (Groves, et al. 2013) Moreover, many key EHR providers, such as Epic and Cerner, offer contracted access to their deidentified, aggregated datasets, further advancing the opportunity to utilize these data in a broad range of analyses.
While there are important limitations to these data including missing information and inconsistent data-recording across providers/facilities - the ability to look retrospectively at a patients course of treatment and associated clinical outcomes, over a period of months or even years, is fueling strong interest in using data from EHRs to support numerous research programs and decisions.
Additionally, EHR data are also expected to play an important role in prospective observational research in coming years. As technology advances allow for a more universal interface between electronic data-capture (EDC) systems and EHRs, this application will likely have a significant impact on the design and operation of observational research. In this setting, the EHR will pre-populate the research case-report form with data available from the EHR, streamlining the research process and reducing data-entry and other errors. As more EHRs allow this connection with research-operations processes central to clinical and market-access decision-making, EHRs will provide even greater support and value to the healthcare system, enabling patient access to important new therapies.
A Vision for EHR Data
The role of EHRs in supporting biopharmaceutical market entry continues to evolve, as both the technology and the decision-making processes themselves change and advance. With the ability to provide broad, longitudinal data in a retrospective setting, these systems can allow rapid, less-costly analysis and insight, supporting key payor and regulator processes and decisions.
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