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Reducing Inappropriate Antibiotic Prescribing in Nursing Homes

Reducing Inappropriate Antibiotic Prescribing in Nursing Homes. Rosanna Bertrand 1 , Lauren Olsho 1 , Sheryl Zimmerman 2 , Louise Hadden 1 , Alrick Edwards 1 , Philip Sloane 2 , Madeline Mitchell 2 , Donna Hurd 1

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Reducing Inappropriate Antibiotic Prescribing in Nursing Homes

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  1. Reducing Inappropriate Antibiotic Prescribing in Nursing Homes Rosanna Bertrand1, Lauren Olsho1, Sheryl Zimmerman2, Louise Hadden1, Alrick Edwards1, Philip Sloane2, Madeline Mitchell2,Donna Hurd1 1Abt Associates Inc.,US Health Division, Cambridge, MA, 2 University of North Carolina Chapel Hill, NC.

  2. Presenter DisclosuresRosanna M. Bertrand I have no personal financial relationships with commercial interests relevant to this presentation existed during the past 12 months to disclose.

  3. Background • Antibiotics are among the most commonly prescribed pharmaceuticals in nursing homes (NHs). • A high proportion are inappropriate causing major public health concerns. • They result in multiple adverse consequences including increased risk of morbidity and mortality. • Loeb and colleagues developed minimum criteria (LMC) for the initiation of antibiotics in NH settings.

  4. Loeb Minimum Criteria • A set of minimum criteria to assess symptoms and signs of: • Skin/soft-tissue infections • Respiratory infections • Urinary tract infections • Fever of unknown origin • Example of LMC for urinary tract infections with catheter • Temperature on day of prescription greater than 2.4 degrees above average routine temperature or greater than 100 degrees Fahrenheit; OR • New case of costovertebral angle tenderness, or symptoms of rigors, or new symptoms of delirium.

  5. Quality Improvement (QI) Intervention Program • Abt/UNC developed a QI intervention that integrated: • An evidence-based conceptual model • A community-based participatory approach • Guidelines for when to prescribe (LMC) • Guidelines for when not to prescribe (12 conditions) • For example, a positive culture in an asymptomatic patient

  6. QI Intervention Program Multi-Level Target Audience • Prescribers • Medical Doctors • Nurse Practitioners • Physician Assistants • Other NH staff • Administrators • Nurses • Residents and Families

  7. QI Intervention ProgramMulti-Method Approach • On-Site Trainings • Pocket Cards

  8. QI Intervention ProgramPocket Card

  9. QI Intervention ProgramMulti-Method Approach • On-Site Trainings • Pocket Cards • Written Materials and Forms • Meetings/Gatherings

  10. Evaluation Design • Quasi-experimental design • Six intervention NHs - part of UNC consortium • Six comparison NHs - matched by bed size and profit status • Three-month baseline and six-month intervention periods • N = 3,568 prescriptions over 336,522 resident days

  11. Primary Outcomes • Antibiotic prescribing rates • Overall and by infection type: urinary, skin/soft tissue, and respiratory • Prescriber adherence to the LMC • Conducted on a random sample of prescribing events • Developed an indication-specific algorithm based on LMC • Coded whether or not the LMC were met

  12. Analyses • Prescribing Rates Related to LMC Adherence • Multivariate analyses using three months baseline from intervention and comparison site data • Dependent variable: count of prescriptions per resident per day • Primary explanatory variable: NH-level measure of percent of prescriptions/month meeting the LMC • Impact of the QI Intervention • Multivariate difference-in-differences analyses to determine: • Increase in adherence to the LMC • Decrease in antibiotic prescribing rates

  13. Results - LMC Adherence

  14. Results – QI Intervention

  15. Conclusions • NHs increasingly recognized as reservoirs of antibiotic-resistant bacteria • Inappropriate overprescribing is a major contributor to resistance • Lack of support for relationship between adherence to LMC and reduced prescribing rates • Yet, significant decline in prescribing rates in intervention sites only • QI program likely effective via other mechanisms • Recommend continued efforts to reduce prescribing

  16. Acknowledgments • The Abt/UNC team is grateful to the Agency for Healthcare Research and Quality for funding this project. • Contract No. HHSA290200600019i, Task Order No. 11.

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