In healthcare, data is the equivalent of electricity it powers everything, and more than ever, the role of healthcare data is critical, as it’s the only data that can provide real-world evidence of treatment efficacy and applicability to a patient case.

Healthcare data has gone through several stages over the decades since computer systems were introduced:

• Interfaces: in the early days of computerization, data needed to be shared across applications, in order to reduce duplicative manual efforts. For example, a patient account record was initially typed into the billing system. As scheduling systems became automated, the registration data was interfaced between the two – easing the data entry burden.

• Integration: as real-time systems emerged (especially for patient treatment), the data needed to be shared immediately. For example, a medication order entered in the system had to be immediately shared with the Pharmacy system. International standards began to emerge from industry “workgroups” such as HL7, and the data formats began to be standardized. A new technology platform was introduced as “Interface Engines,” and widely adopted by healthcare providers. While these systems exchanged standardized transactions, the data “payloads” in the transactions was not standardized, and the data sources were vendor-controlled; for example, some systems would have a data field of “patient age,” whereas other systems might only carry a birthdate, and the system would calculate age on-the-fly when requested. Integration was achievable, but extremely resource-intensive to design, deploy, and maintain within an organization.

• Interoperability: Integration efforts proved to be too resource-intensive and inefficient to facilitate the ever-increasing volume and complexity of healthcare data, and system interoperability became the focus; making data natively consumable, from one system to another. For example, patient allergy data could be captured in a Nursing software application, and shared with a Radiology application, without the need for change. In addition, advances in medicine, market forces, new technologies, and stronger stakeholder engagement have all driven the need for accessible, understandable, and interoperative healthcare data – from payers, providers, pharma/life sciences, purchasers, individuals, and government stakeholders.

Market models have emerged in recent years that demand payers, providers, and other stakeholders utilize data from each other. Most stakeholders have tools and experience to make meaningful use of their own data, but are overwhelmed and underprepared to access and transform data from other stakeholders. For example, most payers collect laboratory data for their member’s encounters but don’t have the resources to interpret the “information” contained in the data – such as the role of elevated enzyme levels in cardiac care and treatment.

A new service category is emerging across healthcare – organizations that have the technical knowledge, healthcare domain expertise, security, and associated support services to provide data to healthcare stakeholders. This service can greatly simplify the initial burden, and accelerate the use of data by years, for the stakeholder.