Infection Control & Hospital Epidemiology
hospital admission triggered a prospective clinical review by an ASP pharmacist as part of routine weekday ASP operations. All NAAT tests ordered during weekend hours were not subject to review and were processed as ordered. Briefly, a line list of NAAT orders received by the microbiology laboratory were for- warded to the ASP team twice daily during the day shift for review. TheEHRfromthose patients on the line list were reviewed for clin- ical signs and documented symptoms consistent with C. difficile infections based on an institutionally approved algorithm (Fig. 1). Analysis of each case was based primarily on documentation of 3 or more liquid stools per day. Documentation or presence of clinical factors evaluated by the ASP team included the following: presence of leukocytosis (eg,WBC>15,000 cells/mm3), fever, recent NAAT results, administration of stool softeners or laxatives within the preceding 24 hours, receipt of oral contrast, tube feeding initiation, imaging results consistent with colitis or ileus, as well as other alter- native explanations of diarrhea for each patient.1 ASP team mem- bers evaluated whether CDI symptoms were absent or could be explained by plausible alternatives (eg, laxative use), which would classify the patient as not meeting test criteria. In cases where NAAT orders failed to meet preauthorization criteria, a recom- mendation to cancel the test was discussed with the ordering pro- vider. ASP recommendations to cancelNAATcould be accepted or rejected after discussion. If ordering or covering providers did not follow-up with initial communications, orders not meeting criteria were cancelled and documented. Discrepancies in clinical assess- ment were adjudicated by the medical director of ASP. NAAT orders meeting preauthorization criteria were processed as ordered. In February 2017, education on appropriate use of NAAT was
reinforced using computer decision support which was embedded within the test order set (Cerner, Millennium). Briefly, providers were prompted at the point of order entry to complete a two-step assessment. In step 1, providers had to attest to new onset of patient diarrhea (3 or more large watery stools within prior 24 hours), presence of ileus on exam, verbal history of continued diarrhea beginning prior to arrival (many large watery stools within prior 24 hours), or admission to the SCT unit. In step 2, the order was cross-referenced against existingNAAT to determine whether a test had been sent within the prior 7 days. ASP pre-authorization continued throughout this period. ASP team members continued to alert providers if clinical and/or laboratory criteria were not met and notified them of cancellation of tests failing to meet the estab- lished criteria. Discussion with the ASP medical director was offered if providers felt an exception should be made.
Statistical analyses
In the present quasi-experimental study, the primary outcome was the change in the incident rate (IR) of HO-CDI per 10,000 patient days. The change in themonthly CDI SIR and consumption of oral vancomycin days of therapy (DOT) per 1,000 patient days were also evaluated. The preintervention period was defined as January 1, 2014, through September 30, 2016, and the postinter- vention period was defined as October 1, 2016, through April 30, 2018. The overall study period, including before and after the implementation of the ASP preauthorization program, was 52 months. Univariate differences in HO-CDI-IR, SIR, and vancomycin
consumption before and after protocol implementation were evaluated using the Student t test or Wilcoxon rank-sum test, as appropriate. Segmented regression models were constructed to
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evaluate changes in the dependent variable level, slope, or both as a function of time-dependent predictors. Regressions followed the generalized form:
f ½YðtÞ ¼ β0 þ β1 x Timeðt¼1;52Þ þ β2 x Interventionð0;1Þ þ β3 X Timeðt¼34;52Þ
where f[Y(t)] is a function of the dependent variable Y, time(t=1,52) is increasing months from 1 to 52, intervention is a binary classifier of the preauthorization intervention, and time(t=34,52) is increasing months from 34 to 52 used to define the postintervention step and slope change interaction. Generalized linear models were fit to observed data using the
Stats package within R version 3.2.4 software.11 Poisson or log- linked gamma regression models were utilized according to the distribution of the dependent variable, as appropriate. Models incorporating step-change (ie, intercept P value; Pstep), step and slope change (ie, intercept P value; Pstep and slope P value; Pslope), and each of the study periods (ie, education only versus pre-authorization plus education) were iteratively constructed and compared using goodness of fit analyses. Significant differences in model fitness were considered P<.05 inmodel com- parisons. The simplest most explanatory models were selected as final. Data plots were constructed in R, as previously described.12 Relationships between antibiotic use and HO-CDI-IR measures were evaluated using least-squares regressions. To explore the durability of the intervention, the proportion of NAAT classified asHO-CDI that were placed on weekdays (ie, when ASP preautho- rization was in effect) compared weekends (when ASP preautho- rization was not in effect), which was calculated as a percent change from baseline.
Results
Overall, 743 HO-CDI NAAT results were documented during the 52 months between January 1, 2014, and April 1, 2018. The mean (± standard deviation [SD]) monthly number of HO-CDI NAAT results were 14.3±4.2, the mean HO-CDI-IR was 7.8 ± 2.3 per 10,000 patient days, the mean SIR was 0.9 ± 0.25, and the mean oral vancomycin was 10.8 ± 2.4 DOT per 1,000 DP at the facility-wide level. The mean monthly number of positive NAAT results decreased after versus before implementation (12.4 vs 15.4; P = .018) as did the HO-CDI-IR (6.5 vs 8.5 per 10,000 patient days; P = .0036) and the SIR (0.78 vs 0.97; P = .015). Mean vancomycin consumption was similar before and after implementation at the univariate level (10.8 vs 10.7 DOTper 1,000 DP; P=.91). Within the SCT population, the mean HO-CDI-IR was 32.8±19.8 per 10,000 patient days, and the mean HO-CDI-IR was similar after and before implementation (36.5 vs 30.3 per 10,000 patient days; P = .34) at the univariate level. A summary of the Facility-wide HO-CDI-IR per 10,000 patient
days is displayed in Fig. 2. The segmented regression analysis identified significant time-dependent decrease in the HO-CDI- IR trend (Pstep = .06; Ptrend = .008) after implementation of the ASP clinical review and preauthorization intervention: mean rate change −3.4% (95% confidence interval [CI], −0.90% to −6.1%) per month postimplementation. Concurrently, the HO-CDI-IR within the noninterventional control unit (ie, SCT unit over 45 months) did not change after protocol implementation (Pstep = .125; Ptrend = .115). A summary of the Facility-wide SIR is displayed in Fig. 3. Segmented regression analysis identified
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