For decades, medical records existed as little more than printed forms, test results, and even handwritten
notes, but the passing of the Health Information Technology for Economic and Clinical Health Act in 2009,
which provided nearly $36 billion in Meaningful Use incentive payments, spurred transformation across the
healthcare industry. In fact, by 2015 nearly all hospitals (96%) possessed certified EHR technology.1
With this large-scale adoption of EHRs, healthcare organizations gained the capability to electronically process
data, and experienced the efficiencies and benefits associated with doing so. However, the industry’s move to
value-based care — where reimbursement is based on the quality of care provided and outcomes achieved, not
merely the volume of services delivered — is prompting healthcare organizations to move beyond the transactional use of data.

Electronic clinical decision support (CDS) systems have the potential to improve the quality, safety, efficiency and effectiveness of healthcare.1 Yet, according to a 2018 HIMSS Media survey, sponsored by Red Hat, many existing CDS systems are falling short.
Although 70 percent of respondents believe CDS is a “critical” or “high priority,” only 40 percent are “extremely satisfied” or “very satisfied” with their current CDS tools.2 The survey results shed light on the specific ways existing CDS tools are failing, in addition to
the ways that open source can help CDS achieve its full potential.  The ubiquity and maturity of electronic health records
(EHRs) means that clinicians have access to more data than ever before. In fact, the volume of data can be overwhelming. CDS systems have a significant role to play only if they can cut through the noise of the almost infinite amount of patient information, clinical guidelines and related data and provide the clinician with the specific data they need, at the precise time they need it.