However, IT-enabled collaboration will have a direct impact on all aspects of healthcare, including significant but less visible areas like the relationships between pharma companies and providers. It will enable pharma companies to forge much broader and deeper partnerships with hospitals and health systems in ways that not only benefit each other, but also aid individual patients and patient populations as well.
Facilitating the secondary use of healthcare data is a case in point. Secondary use involves the ability to access patient data from electronic health records (EHRs) and other sources for purposes such as clinical trials, or the monitoring of safety and efficacy following market release of a drug. Pharma companies obviously need such data in order to develop the most effective drugs for patient treatment, but that data currently resides in disparate bits and pieces across individual hospital and health system databases and in many cases, on paper.
Innovation Requires Access
Ultimately, for a pharma company to be innovative, it needs access to patients to test drugs within the context of scientific, data-based research. Historically, the challenge always has been how to gain access to those patients. Hospitals — wary of the public perception that pharma organizations somehow detract from the provision of community care — typically have been quiet partners. In a great number of cases, access to patient data has been achieved through “backdoor” business relationships forged between hospital and pharma executives.
Perhaps not surprisingly, medical centers that traditionally have been the most strongly engaged in clinical trials also have been vertically focused on areas like cancer treatment or translational research that can be applied practically and quickly to the care of patients. Cancer patients, for example, often constitute a ready-and-willing pool of participants in clinical research because they realize that sharing their information could well result in new treatments or even cures for their life-threatening illnesses.
Transparency and Transformation
Times are changing rapidly, however, driven partly by technology advances and partly by the need for accountability within an increasingly complex healthcare environment. Data transparency has become required in healthcare, fueled by factors such as the HITECH stimulus, Meaningful Use, and the emergence of new payment models.
The push to implement EHRs is integral to establishing an IT infrastructure for patient data.
However, EHRs are in essence transaction systems that require highly configured applications, analytics and connectivity with physicians, laboratories, home health agencies, patients and all the other entities that “touch” the patient. For accountable care organizations (ACOs) to support population management, for example, they must have seamless data links that support the longitudinal patient record.
Of course, all this must be done within an environment of diminishing resources.
No one denies that healthcare is on an unsustainable cost curve. Declining reimbursement, bundled payments and regulatory changes mean health systems will not be reimbursed for unnecessary readmissions or hospital-acquired infections. They will have to become accountable for the care of patient populations. While cost-cutting and streamlining work generated returns in a fee-for-service world, in the world of accountable care, mere cost-cutting will only go so far before it begins to hurt the quality of patient care.
This is a new universe, where hospitals have become cost centers. Innovative ways of delivering care outside the hospital and generating revenue streams are of paramount importance. To maintain financial viability, hospitals and health systems have begun to view patient data like currency; it can generate revenue.
Better yet, data can also generate more collaboration. Every healthcare stakeholder — including the patient — becomes both a contributor and a beneficiary of data exchange. Pharmaceutical companies are an integral part of this ecosystem because of the treatments they develop and the data they generate from clinical trials and post-market monitoring. With data exchange as the connector, pharma companies can become part of the extended healthcare enterprise more seamlessly.
Culture Shift: Data Is To Be Shared
It is difficult to overestimate the opportunity for pharma companies presented by IT-enabled collaboration. Just as hospitals increasingly are finding socially beneficial ways to use patient data, drug companies are moving in the same direction. Despite a long history of competition and closely guarded information, pharma organizations are becoming much more open to the idea of data sharing.
Some groups over the past few years have come to realize that what differentiates them in the marketplace is not their data, but how they use it. With the movement toward population health management and tracking patients across the continuum of care, health information exchanges (HIEs) and other data aggregation entities have become the logical distribution pipes for data.
For pharma firms and health systems to successfully collaborate and enable the secondary use of healthcare data, they must do two things:
- collaborate to speed up patient recruitment, and
- invest in the analysis of “big data” that incorporates structured and unstructured data in ways never available before.
In this new context, the process of documenting patient consent to sharing medical records takes on dramatically heightened significance. Patient consent becomes the sluice gate to a potential torrent of data available for secondary use.
Furthermore, as a broader stream of hospitals becomes involved in clinical trials, healthcare can move from a world in which clinical trials are largely the domain of a few specialized medical centers — like MD Anderson Cancer Center and Memorial Sloan-Kettering Cancer Center — to one that engages hundreds of mainstream medical centers all feeding into a rich database.
The IT challenge for pharma companies is now one of developing a dynamic relationship to the data in an environment of high diversity. Numerous disparate data sources and formats abound throughout the healthcare and pharma industries.
To overcome this obstacle, pharma firms in the past have developed point-to-point interfaces with individual healthcare partners in order to access the patient information they require. While this old paradigm works, it is hardly efficient or cost-effective. It often requires manual steps, which in turn can lead to problems with delivery time and data integrity.
A newer and more efficient paradigm involves the cloud. The cloud-based model works well in such heterogeneous environments as healthcare because it leverages the internet to allow remotely hosted and shared infrastructure and services on-demand.
In the simplest sense, cloud-based services allow systems to be integrated and data to be aggregated and analyzed more easily and quickly, so more patients can be accommodated in the pool of data for secondary use. Besides eliminating the burden of maintaining the latest systems and standards, pharmaceutical and other businesses can use the cloud to pay as they grow for high-level expertise and services that help solve the major challenges of interoperability — including integration and data harmonization.
A cloud-based model is uniquely suited to the challenges facing pharma companies because it provides leverage, scalability and technology refresh intervals unmatched by traditional software models. In addition, cloud technology can support more than just infrastructure needs; it can also be used to solve business problems because it incorporates three distinct layers of service that build upon each other:
- Infrastructure as a Service (IaaS): Most businesses conjure up this foundational layer when referring to “the cloud.” At this level, organizations pay for space and usage — for hardware, Internet Protocol (IP) addresses, CPU space, memory and firewalls, for example — and expand or reduce them as necessary.
- Platform as a Service (PaaS). Less well-known, PaaS is critical to successful use of the cloud. This level provides the tools, capabilities and — more importantly — services that solve problems. PaaS includes capabilities such as integration as a service, data as a service, and information as a service.
- Software as a Service (SaaS). This level of the cloud hosts the applications — such as dashboards and charting programs — that help visualize services provided in the cloud. Familiar examples of SaaS applications include human resources packages, sales automation dashboards and stock option apps.
Cloud Brings Big Data to Big Pharma
Cloud-based integration, aggregation and harmonization can convert vast amounts of data from clinical trials into actionable information. Outsourcing through the cloud means that scalability, streamlined data mapping, improved data quality and flexible data management all can be obtained through a single solution. Cloud-based solutions can also ensure the privacy and security of patient information just as well as — or better than — other techniques because they can target three distinct risk areas: access control, the security of stored data, and the security of data in transit.
In one example, a global pharma giant recently was able to harness a cloud-based solution to aggregate clinical trial data from multiple disparate sources, normalize that data and put it in a variety of formats for analysis and reporting. The company’s existing IT infrastructure could accommodate standard, small-scale clinical trials, but the organization found that it was hobbled in its data processes and tools — including data mapping — when it tried to take either a large trial or too many simultaneous trials. It was when the data flow became too great that it slowed other trials and began to impair overall corporate performance. That was when the company turned to a cloud-based solution.
Because a well-designed cloud model can offer three levels of service — infrastructure, platform and software applications — the drug giant was able to adopt a complete solution based on a data-mapping platform that included new processes, more scalability, a library of standard form-based data maps, and industry-standard compliance and training to support the new paradigm. The approach was so successful that the company adopted it for all of its clinical trials. The result has been faster data flow, greater agility in the clinical trials process, improved problem resolution and greater capacity to handle multiple trials. It also improved overall data quality and cycle time while achieving lower costs.
Cloud-based solutions have emerged at a critical moment in the transformation of the healthcare and pharma industries. They can be leveraged to engage in deeper and more productive relationships, resulting in improved research and clinical trials that lead to faster results for the betterment of patients. The cloud enables the integration, aggregation and analysis of data that is imperative to the success of accountable care and value-based purchasing. In that sense, the cloud is also the best solution for linking all of the diverse stakeholders together, raising the tide for all boats in the imminent collaborative care environment.
Gary Palgon is the vice president of Healthcare Solutions for Liaison Technologies, which provides pharmaceutical and healthcare organizations with solutions to complex integration and data management needs. He can be reached at firstname.lastname@example.org.