Qualitative validation of the CAUTI Guide to Patient Safety assessment tool

Intervention to reduce unnecessary urinary catheter use in a large academic health science centre: A one-group, pretest, posttest study with a theory-based process evaluation

AIM

To evaluate an intervention to reduce unnecessary urinary catheter use and prevent catheter-associated urinary-tract infections (CAUTI) in hospitalized patients across an academic health science centre.

METHODS

We conducted a one-group, pretest, posttest study with a theory-based process evaluation. Phase 1 consisted of a pre/postintervention to test the impact of a CAUTI protocol. Audits on four units were conducted, and data were analysed descriptively. Phase 2 consisted of a theory-based process evaluation to understand the barriers/enablers to the implementation. Semistructured interviews were conducted and then analysed using a systematic approach.

RESULTS

In Phase 1, all inpatients with urinary catheters admitted to the units (N = 4) during the study period (N = 99, pre) and (N = 99, post) were included. CAUTI prevalence rate was 18.2% pre versus 14.1% post (p = .563). In Phase 2, participants (N = 18) who worked on the units were interviewed, and a total of 13 barriers and 19 enablers were found.

Multistate programme to reduce catheter-associated infections in intensive care units with elevated infection rates

Background

Preventing central line-associated bloodstream infection (CLABSI) and catheter-associated urinary tract infection (CAUTI) remains challenging in intensive care units (ICUs).

Objective

The Agency for Healthcare Research and Quality Safety Program for ICUs aimed to reduce CLABSI and CAUTI in units with elevated rates.

Methods

Invited hospitals had at least one adult ICU with elevated CLABSI or CAUTI rates, defined by a positive cumulative attributable difference metric (CAD >0) in the Centers for Disease Control and Prevention’s Targeted Assessment for Prevention strategy. This externally facilitated programme implemented by a national project team and state hospital associations included on-demand video modules and live webinars reviewing a two-tiered approach for implementing key technical and socioadaptive factors to prevent catheter infections, using principles and tools based on the Comprehensive Unit-based Safety Program. CLABSI, CAUTI and catheter use data were collected (preintervention 13 months, intervention 12 months). Multilevel negative binomial models assessed changes in catheter-associated infection rates and catheter use.

Results

Of 366 recruited ICUs from 220 hospitals in 16 states and Puerto Rico for two cohorts, 280 ICUs completed the programme including infection outcome reporting; 274 ICUs had complete outcome data for analyses. Statistically significant reductions in adjusted infection rates were not observed (CLABSI incidence rate ratio (IRR)=0.75, 95% CI 0.52 to 1.08, p=0.13; CAUTI IRR=0.79, 95% CI 0.59 to 1.06, p=0.12). Adjusted central line utilisation (IRR=0.97, 95% CI 0.93 to 1.00, p=0.09) and adjusted urinary catheter utilisation were unchanged (IRR=0.98, 95% CI 0.95 to 1.01, p=0.14).

Conclusion

This multistate programme targeted ICUs with elevated catheter infection rates, but yielded no statistically significant reduction in CLABSI, CAUTI or catheter utilisation in the first two of six planned cohorts. Improvements in the interventions based on lessons learnt from these initial cohorts are being applied to subsequent cohorts.

Testing of the WHO Infection Prevention and Control Assessment Framework at acute healthcare facility level

BACKGROUND

Monitoring and evaluation are an essential part of infection prevention and control (IPC) implementation. The authors developed an IPC assessment framework (IPCAF) to support implementation of the World Health Organization (WHO) guidelines on core components of IPC programmes in acute healthcare facilities.

AIM

To evaluate the usability and reliability of the IPCAF tool for global use.

METHODS

The IPCAF is a questionnaire with a scoring system to measure the level of IPC implementation according to the eight WHO core components. The tool was pre-tested qualitatively, revised and translated selectively. A convenience sample of hospitals was invited to participate in the final testing. At least two IPC professionals from each hospital independently completed the IPCAF and a usability questionnaire online. The tool's internal consistency and interobserver reliability or intraclass correlation coefficient (ICC) were assessed, and usability questions were summarized descriptively.

FINDINGS

In total, 46 countries, 181 hospitals and 324 individuals participated; 52 (16%) and 55 (17%) individual respondents came from low- and lower-middle income countries, respectively. Fifty-two percent of respondents took less than 1 h to complete the IPCAF. Overall, there was adequate internal consistency and a high ICC (0.92, 95% confidence interval 0.89-0.94). Ten individual questions had poor reliability (ICC <0.4); these were considered for revision according to usability feedback and expert opinion.

CONCLUSIONS

The WHO IPCAF was tested using a robust global study and revised as necessary. It is now an effective tool for IPC improvement in healthcare facilities.

Identification of urinary tract infections using electronic health record data

BACKGROUND

Population ascertainment of postoperative urinary tract infections (UTIs) is time-consuming and expensive, as it often requires manual chart review. Using the American College of Surgeons National Surgical Quality Improvement Program UTI status of patients who underwent an operation at the University of Colorado Hospital, we sought to develop an algorithm for identifying UTIs using data from the electronic health record.

METHODS

Data were split into training (operations occurring between 2013-2015) and test (operations in 2016) sets. A binomial generalized linear model with an elastic-net penalty was used to fit the model and carry out variables selection. International classification of disease codes, common procedural terminology codes, antibiotics, catheterization, and common procedural terminology-specific UTI event rates were included as predictors. The Youden's J statistic was used to determine the optimal classification threshold.

RESULTS

Of 6,840 patients, 134 (2.0%) had a UTI. The model achieved 92% specificity, 80% sensitivity, 100% negative predictive value, 16% positive predictive value, and an area under the curve of 0.94 using a decision threshold of 0.03.

CONCLUSIONS

A model with 14 predictors from the electronic health record identifies UTIs well, and it could be used to scale up UTI surveillance or to estimate the impact of large-scale interventions on UTI rates.