Improvement of Parenteral Antibiotic use in a University Hospital in Colombia

1. Improvement of Parenteral Antibiotic use in a University Hospital in Colombia Pérez A, Dennis RJ,Rodriguez B, Castro AY, Delgado V, Lozano JM Clinical Epidemiology and Biostatistics Unit, Pontificia Universidad Javeriana, Bogotá, Colombia

2. ABSTRACT • Problem Statement: In Colombia, there has been no incentive in the past for continuing quality assessment, by ongoing monitoring, of antibiotic prescription practices. • Objectives: To evaluate the effect of an intervention to improve antibiotic prescribing practices in a University- based hospital. • Design: Quasi-experimental before/after study with a planned intervention; interrupted time series analysis. • Setting: Tertiary care hospital caring for private and institutional patients. • Study Population: Hospitalized patient prescription census from 10 clinical services, including Gynecology and Obstetrics, Surgery, Medicine, and Pediatrics. A total of 2716 prescriptions were collected between June, 1997 and April, 2000. • Intervention: A structured antibiotic order form implemented between two data collection phases between week 82 and week 102. All hospitalized and prescribed patients completed the form since week 82.Physicians in charge of grup prescription in each service completed the forms. The Hospital designed the form with the help of the research tem. We also implemented an educational campaign with conferences for physiciansand posters for all the clinical services, and blood pressure cuffs for anaesthesiologists. • Outcome Measures: Hospital weekly rate of incorrect prescriptions of (A) aminoglycosides in dose interval less than 24 hours (gentamicin, amikacin, streptomycin and netilmicin); (B) cephradine and cephalothin in dose interval greater than 6 hours; (C) ceftazidime and cefotaxime in dose interval greater than 8 hours; and (D) any antibiotic prescribed one hour before or after incision in surgery. • Results: Interrupted time series intervention analysis was conducted for three antibiotic groups of the hospital’s weekly rate of incorrect prescriptions. Pre-intervention Auto-Regressive Integrated Moving Average (ARIMA) models were identified, estimated and diagnosed for the four time series (A,B,C,D). Time series (A) was an ARIMA (0,1,2) with corresponding estimates and standard error (SE) as theta1=0.36 (SE=0.102) and theta2=0.49 (SE=0.101), respectively. Time series (B) was an ARIMA (0,1,1) with corresponding estimate =0.82 and SE=0.07. Time series (C) was an ARIMA (0,0,1) with corresponding estimate=-0.72 and SE=0.08. Time series (D) was an ARIMA (0,1,1). These models were used in the post-intervention series to test for pre-post series level differences. An abrupt constant change was significant in A, C and D time series, indicating a 47%, 7.3% and 20% reduction on incorrect prescriptions after intervention. • Conclusions: High rates of incorrect prescription were reduced after the intervention. This intervention, consisting of both an educational campaign and introduction of a structured prescription form with built-in deterrents of selection of inappropriate dosing intervals, can be implemented in a teaching hospital in Latin America. Such an intervention leads to measurable decreases in the proportion of incorrectly prescribed antibiotics.

3. BACKGROUND • Uncontrolled use of antibiotics abuse and potential unwarranted events and costs • Need for: • Ongoing monitoring of antibiotic prescription practices • Implementation of interventions to improve inappropriate behavior • Pharmacy and Infection Control Committees identified a critical area as: • Use of expensive antibiotics

4. BACKGROUND • Pharmacy and Infection Control Committees identified critical areas: • Use of expensive IV antibiotics • Implementation of an adverse drug reaction surveillance program • Use of sedatives and hypnotics • Drug modification as a function of renal condition • Adequate pharmacological prevention of UGI bleeding and thromboembolism

5. RESEARCH OBJECTIVES • To assess the appropriateness of the observed antibiotic prescription patterns. • To implement a hospital wide intervention aimed to improve inappropriate practices. • To assess the potential cost/savings profile of the intervention from the payer point of view.

6. METHODS RESEARCH DESIGN • Quasi-experimental pre-post time series design • Reasons for not using an RCT: • Permanent rotation of residents, interns and nurses very high potential for contamination bias within and between wards, which would attenuate any perceived effects • Selection of one other hospital as control: unfeasible control of measurable confounders

7. SETTING • San Ignacio’s Hospital, Bogotá, Colombia. June, 1997 • Hospitalized patients • Obstetrics-Gynecology, Surgery, Medicine, Pediatrics, Intensive Care Unit, others wards. EXPERT PANEL PI, infectologist, representatives from G&O, Pediatrics, Internal Medicine, Surgery and Nursing • Identifying tracer conditions • Developing expected norms regarding the appropriate use of antibiotics in selected conditions • Developing data collection forms • Delineating intervention

8. INTERVENTION 1. Implementation of a new antibiotic order form • 80% in US hospitals, 79% in British hospitals 2. Join educational intervention by researchers and infectologist (lectures and posters) 3. Logo band:blood pressure cuffs “Do not forget the prophylactic antibiotic one hour before surgical incision”. Started in January/1999

9. Condition Aminoglycosides Cephradine/Cephalothin Ceftazidime/Cefotaxime Prophylactic prescription in surgery Incorrect prescription Dose interval < 24 h Dose interval > 6 h Dose interval > 8 h Prescription > 1 hour before and/or after incision OUTCOMES Hospital weekly proportion of incorrect prescriptions

10. SAMPLE SIZE •  = 0.05, two sided test •  = 0.10 • ARIMA (2,0,0) • 1 = 0.3 • 2 = 0.2 20 months of observation before and after intervention = 80 weeks pre-post Gottman JM (1981) Time series analysis. Cambridge Univ. Press, 335-67

11. Abrupt Constant Change Abrupt Temporary Change HYPOTHESIS Stationary series (discrete and equally spaced intervals) Auto-regression process Moving average process Estimated from time series Random shocks

12. ETHICAL ISSUE • Informing staff about prescription pitfalls outside the intervention period may produce temporary changes in habits that may attenuate results • Data collector will not make staff aware of “minor” prescription errors • Data collector will make staff aware of “major” prescription errors • Identification of pre-intervention ARIMA model • Diagnosis checks over residuals • Akaike Information Criterion • No seasonal component expected • SAS 6.12 TSO 51, Unix STATISTICAL ANALYSIS

13. RESULTS Antibiotic Order Form

14. RESULTS: 1.Aminoglucosides Abrupt Constant Change was statistically significant. Pre-Intervention: ARIMA (0,1,2) =-0.477 SE=0.064 p<0.001

15. RESULTS: 2.Cephradine/Cephalothin Pre-Intervention: ARIMA (0,1,1) Neither abrupt constant nor temporary change were statistically significant.

16. RESULTS: 3.Ceftazidime/Cefotaxime Pre-Intervention: ARIMA (0,0,1) Abrupt Constant Change was statistically significant. =-0.073 SE=0.03 p<0.05

17. RESULTS: 4.Prophylactic P. in Surgery Pre-Intervention: ARIMA (0,1,1) Abrupt Constant Change was statistically significant. =-0.199 SE=0.069 p=0.004

18. DISCUSSION • This study confirms previous reports of reductions in the proportion of incorrect antibiotic prescriptions by use of an educational campaign and a structured antibiotic order form. • We believe that our structured prescription form improved the quality of the prescriptions by increasing the awareness of physicians about correct dose intervals which is consistent with previous studies reported in the literature.

19. Reduction in incorrect Prescriptions: 47% : Aminoglycosides 7.3%: Ceftazidime Cefotaxime 20%: Prophylactic P. in surgery No enough reduction in Prophylactic Prescriptions in Surgery. RCT not feasible due to permanent rotation of residents/nurses, etc. Ethical Issue: informing staff about prescription pitfalls. DISCUSSION

20. ACKNOWLEDGMENTS This work was supported by INCLEN, INC (grant # 1004-97-6501) and Pontificia Universidad Javeriana (grant # 12-24-01-31).