Electronic medical record systems are nearly universal in U.S. hospitals. While they have enabled hospitals to make significant strides in tracking patient care, they are ill-suited to the task of analyzing the huge amount of data they, and other IT systems used by hospitals, produce.
Most hospitals do not have the technology that enables them to leverage their data to improve outcomes, yet penalties for failing to do so continue to mount:
- For fiscal year 2017, up to 6% of a hospital’s Medicare reimbursement could be at risk for failure to reduce healthcare-associated conditions (HACs) and readmissions or meet value-based purchasing criteria that include hospital-acquired infections (HAIs).
- The Department of Health and Human Services plans to link 85% of all Medicare fee-for-service payments to quality or value measures by the end of 2016 and 90% by 2018.1
- Private payers such as UnitedHealthcare and Humana have also implemented value-based programs that focus on reduction of HACs as well as achievement of specific quality measures.
In-house development of systems that can analyze data can be very costly and typically addresses specific types of analysis rather than create a broad-based functionality that can adapt to the hospital’s needs over time. Internal development also requires the commitment of a substantial amount of time from the hospital’s IT staff, a group often already overburdened and under-resourced.
Implementing a real-time clinical decision support system alongside an EMR allows the system to aggregate data from multiple systems and locations and apply clinical rules and algorithms to identify at-risk patients. These systems can alert clinicians to attend those patients who require immediate clinical intervention to head off HAIs, adverse drug events, and other negative outcomes.
These electronic surveillance systems can also identify gaps in care, such as evidence-based treatments or medications for the patient’s indication that have not been performed or ordered. With today’s rapidly evolving clinical recommendations, few physicians can keep up to date without automated support that brings the latest advice to them when and where they need it. Clinical decision support enables optimal delivery of care and rapid adoption of new recommendations and hospital policies.
In the increasingly vital area of antimicrobial stewardship, advanced clinical decision support and intelligent alerts help 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. Surveillance systems can flag possible outbreaks by analyzing microbiology and pharmacy records, alerting clinicians to the readmission of a patient known to have been infected previously with Clostridium difficile and rapidly identifying patients admitted with symptoms consistent with measles or other highly contagious pathogens. They can even alert physicians to emerging infections up to 24 hours before they would otherwise be detected, saving lives.2
Clinical decision support systems also dramatically simplify reporting--whether for National Health Safety Network requirements or tracking the impact of interventions in terms of reduced costs and improved outcomes or monitoring adoption of new initiatives across a facility or by provider. As a result, hospital administrators and program managers can readily see which initiatives have taken hold in the organization’s culture, which may require additional resources, and which have produced the best return on investment.
- Better Care. Smarter Spending. Healthier People: Paying Providers for Value, Not Volume. CMS.gov Fact Sheet. January 26, 2015.
- Beyman M. Big data’s powerful effect on tiny babies. CNBC.com. Sept. 13, 2013.