Economic incentives created by the HITECH Act have driven adoption of electronic health record systems (EHRs) across the healthcare industry. In 2008, just 9% of hospitals had an EHR. By 2013, 80% did—and today, they are nearly universal.1,2,3
Electronic health records (EHRs) facilitate aggregation of some data, but most systems were not designed to integrate and analyze information in a way that flexibly supports changing quality and safety initiatives. Even those that can pull from all of a hospital's data sources, including admissions/discharge/transfer, laboratories, radiology, surgery, pharmacy, vital signs and medical records, typically lack the algorithms and clinical rules that turn that data into actionable information.
Hospitals need proactive technology for identifying outbreaks and implementing clinical best practices as financial pressure to reduce readmissions (and unnecessary admissions) and healthcare-associated infections has increased and more payers adopt value-based payment arrangements.
Many hospitals have turned to electronic surveillance systems to meet these needs. These systems can aggregate and analyze data from a variety of data streams. By enabling data visualization through a dynamic dashboard, surveillance systems allow clinicians and program managers to quickly see trends and emerging issues, and to take action based on evidence-based recommendations to prevent complications. Prioritized alerts further assist providers by helping them determine who needs an intervention most urgently.
Clinicians are able to maintain focus on initiatives that have the greatest effect on cost, quality and safety. These initiatives may include antimicrobial stewardship programs, reduction of healthcare-associated infections or rapid identification and treatment of potentially critical conditions such as sepsis. For example, this type of clinical decision support helps prescribers select the right antimicrobial for a specific condition—avoiding the costs of extended length of stay, complications and treatment failures—or recommend a less expensive, but still effective course of therapy.
Clinical surveillance systems can flag possible outbreaks by analyzing microbiology and pharmacy records or the readmission of a patient known to have been infected previously with Clostridioides difficile (or C. difficile). They can even alert physicians to emerging infections up to 24 hours before they would otherwise be detected, saving lives.4
Some hospitals may use their EHR to identify high-risk patients and flag possible healthcare-associated infections (HAIs), but they take a risk in doing so. Coding and billing data in the EHR identify just 20% of HAIs predicted by surveillance technology, while three-quarters of HAIs identified through coding data would not meet NHSN definitions.5 Surveillance systems rely on far more reliable regression analysis and algorithms to pick up potential problems.
In addition, using a surveillance system's alert functionality can deliver clinical decision support based on appropriate, evidence-based, organization-specific guidelines to providers when and where they need it. Studies have shown that physicians often fail to follow clinical recommendations because they lack familiarity with the guidelines or because of the inertia of previous practice. In some specific clinical situations, nine out of ten physicians report they were unaware of the recommendations,6 a problem likely to grow as professional organizations and national boards increasingly promote evidence-based best practices through published guidelines. Embedded, automatically updated clinical decision guidance improves on the goal of optimal delivery of care, without relying on the memory of providers.
Surveillance systems also provide closed-loop reporting that can show how clinical recommendations and interventions, such as changes in antibiotic choice or need to initiate therapy, and how often clinicians accepted the recommendation on a both a facility-wide basis as well as by provider. These reports help program managers or administrators to track adoption rates for new initiatives and provide additional education or adjust incentives. Reports can also be sent to state and federal regulators and submitted to the National Health Safety Network.
- Jha A. The Final Stage of Meaningful Use Rules: Will EHRs Finally Pay Off? Health Affairs Blog. March 25, 2015.
- Doctors and hospitals' use of health IT more than doubles since 2012. HHS press release. HHS.gov. May 22, 2013.
- Health IT Quick Stats. Fast Facts about Health IT Adoption in Health Care. HealthIT.gov.
- Beyman M. Big data's powerful effect on tiny babies. CNBC.com. Sept. 13, 2013.
- APIC Position Paper: The Use of Administrative (Coding/Billing) Data for Identification of Healthcare-Associated Infections (HAIs) in US Hospitals. APIC. October 12, 2010.
- Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PAC, Rubin HR. Why Don't Physicians Follow Clinical Practice Guidelines? JAMA. 1999;282(15):1458-1465.