Reduce Healthcare-Associated Infections (HAIs) and Improve Patient Outcomes Through Technology

According to the CDC, one-to-three million healthcare-associated infections (HAI) occur every year within U.S. nursing homes. Reports also show that antibiotics are among the most frequently prescribed medication in facilities, with 6–10% of residents receiving antibiotics on any given day. However, 40–75% of those prescribed antibiotics may be unnecessary or inappropriate – causing risk of serious complications, development of serious gastrointestinal infections (i.e., Clostridium difficile), increased adverse drug events, growth of multi drug resistant organisms, and/or even death. HAIs also carry a huge financial burden, costing the healthcare industry upwards of $2 billion annually for hospitalizations.

Although daily surveillance and tracking of infections and antibiotic use in Skilled Nursing Facilities has traditionally been an arduous and timely process, this session explores how technology can provide timely surveillance and identify early warning signs of HAIs, highlighting the need for possible testing to determine the appropriate pharmacological and non-pharmacological interventions – resulting in avoided hospitalizations. We will also discuss how by automating the tracking and reporting of infections and antibiotic use facility-wide, operators can leverage live-data analytics to meet state and federal requirements, prepare for regulatory reporting, and improve survey outcomes.

Learning Objectives:

• Identify strategies and best practices to leverage technology and data analytics to strengthen Infection Prevention and Control efforts
• Manage efficient regulatory reporting and onsite surveys through early identification of HAIs, proactive interventions, and avoiding HAI-related hospitalizations
• Illustrate how live data analytics can be utilized to help reduce regulatory burden and improve HAI reporting outcomes

Speaker:

• Cheryl Scalzo, RN, Clinical Account Specialist, Real Time Medical Systems

This session will be presented at the NADONA LTC 37th National Conference.