Beyond the abacus: Leveraging the electronic medical record for central line day surveillance

Manual counting is considered the gold standard for device day recording by the National Health Safety Network. We describe the development of a process for an electronic count of central line days across our ten-hospital health care system. Our validation process identified discordance between the electronic count and the manual count for 71% of patient care units. Adjudication of the count differences by chart review identified the electronic count to be correct 97% of the time.

Measuring the impact of varying denominator definitions on standardized antibiotic consumption rates: implications for antimicrobial stewardship programmes

Objectives

To quantify the impact of varying the at-risk days definition on the overall report of at-risk days and on the calculated standardized consumption rates (SCRs) for piperacillin/tazobactam, amikacin, daptomycin and vancomycin.

Methods

Data were evaluated for two system hospitals, an 894 bed academic centre and a 114 bed community hospital. Aggregate inpatient antibiotic administration and occupancy data were extracted from electronic databases at the facility-wide level. Occupancy data were reported from admission-discharge-transfer systems. At-risk days were defined as hospital days present (DP), patient days (PD), persons present (PP) and billing days (BD). Inpatient antimicrobial days of therapy (DOT) across four major antimicrobial agents were used to calculate facility-wide SCRs using each denominator and were evaluated by least-squares regression and R2 values.

Results

Within the 894 bed academic hospital, the average monthly facility-wide days were 28 424, 22 198, 15 957 and 14 789 by the DP, PP, PD and BD definitions, respectively. Within the 114 bed community hospital, the average monthly facility-wide days were 5175, 3523 and 2816 by the DP, PP and PD definitions, respectively. Strong concordance was observed between facility-wide SCRs using the DP and PP definitions in both the academic (R2 = 0.99, y = 0.78x - 0.001) and community (R2 = 0.99, y = 0.68x - 0.03) centres across all four inpatient antibiotics evaluated. In an analysis of piperacillin/tazobactam SCRs, rates were over-predicted by 28%-93% at the facility-wide level across centres using alternative denominators.

Conclusions

We found that data source and definitions of at-risk denominator days meaningfully impact antibiotic SCRs. Centres should carefully consider these potential sources of variation when setting consumption benchmarks and internally evaluating use.

Surveillance for central-line-associated bloodstream infections: Accuracy of different sampling strategies

BACKGROUND

Active daily surveillance of central-line days (CLDs) in the assessment of rates of central-line-associated bloodstream infections (CLABSIs) is time-consuming and burdensome for healthcare workers. Sampling of denominator data is a method that could reduce the time necessary to conduct active surveillance.

OBJECTIVE

To evaluate the accuracy of various sampling strategies in the estimation of CLABSI rates in adult and pediatric units in Greece.

METHODS

Daily denominator data were collected across Greece for 6 consecutive months in 33 units: 11 adult units, 4 pediatric intensive care units (PICUs), 12 neonatal intensive care units (NICUs), and 6 pediatric oncology units. Overall, 32 samples were evaluated using the following strategies: (1) 1 fixed day per week, (2) 2 fixed days per week, and (3) 1 fixed week per month. The CLDs for each month were estimated as follows: (number of sample CLDs/number of sampled days) × 30. The estimated CLDs were used to calculate CLABSI rates. The accuracy of the estimated CLABSI rates was assessed by calculating the percentage error (PE): [(observed CLABSI rates - estimated CLABSI rates)/observed CLABSI rates].

RESULTS

Compared to other strategies, sampling over 2 fixed days per week provided the most accurate estimates of CLABSI rates for all types of units. Percentage of estimated CLABSI rates with PE ≤±5% using the strategy of 2 fixed days per week ranged between 74.6% and 88.7% in NICUs. This range was 79.4%-94.1% in pediatric onology units, 62.5%-91.7% in PICUs, and 80.3%-92.4% in adult units. Further evaluation with intraclass correlation coefficients and Bland-Altman plots indicated that the estimated CLABSI rates were reliable.

CONCLUSION

Sampling over 2 fixed days per week provides a valid alternative to daily collection of CLABSI denominator data. Adoption of such a monitoring method could be an important step toward better and less burdensome infection control and prevention.

Evaluating the Accuracy of Sampling Strategies for Estimation of Compliance Rate for Ventilator-Associated Pneumonia Process Measures

BACKGROUND Measuring processes of care performance rates is an invaluable tool for quality improvement; however, collecting daily process measure data is time-consuming and burdensome. OBJECTIVE To evaluate the accuracy of sampling strategies to estimate monthly compliance rates with ventilator-associated pneumonia prevention measures. SETTING AND PARTICIPANTS A total of 37 intensive care units affiliated with 29 hospitals participating in a 2-state 35-month ventilator-associated pneumonia prevention collaborative. Analysis was limited to 325 unit-months with complete data entry rates. METHODS We calculated unit-month level actual and sample monthly compliance rates for 6 ventilator-associated pneumonia prevention measures, using 4 sampling strategies: sample 1 day per month, sample 1 day per week, sample 7 consecutive days per month, and sample 7 consecutive days per month plus additional consecutive days as necessary to obtain at least 30 ventilator-days for that month whenever possible. We compared sample versus actual rates using paired t test and χ2 test. RESULTS Mean sampling accuracy ranged 84%-97% for 1 day per month, 91%-98% for 1 day per week, 92%-98% for 7 consecutive days per month, and 96%-99% for 7 consecutive days with at least 30 days per month if possible. The most accurate sampling strategy was to sample 7 consecutive days with at least 30 ventilator-days per month if possible. With this strategy, sample rates were within 10% of actual rates in 88%-99% of unit-months and within 5% of actual rates in 74%-97% of unit-months. CONCLUSION Sampling process measures intermittently rather than continually can yield accurate estimates of process measure performance rates. Infect Control Hosp Epidemiol 2016;37:1037-1043.

Evaluating Epidemiology and Improving Surveillance of Infections Associated with Health Care, United States

This national resource provides much-needed data on pathogens, infections, and antimicrobial drug use.

The Healthcare-Associated Infections Community Interface (HAIC), launched in 2009, is the newest major activity of the Emerging Infections Program. The HAIC activity addresses population- and laboratory-based surveillance for Clostridium difficile infections, candidemia, and multidrug-resistant gram-negative bacilli. Other activities include special projects: the multistate Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey and projects that evaluate new approaches for improving surveillance. The HAIC activity has provided information about the epidemiology and adverse health outcomes of health care–associated infections and antimicrobial drug use in the United States and informs efforts to improve patient safety through prevention of these infections.

Strategies to Prevent Central Line-Associated Bloodstream Infections in Acute Care Hospitals: 2014 Update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their central line-associated bloodstream infection (CLABSI) prevention efforts. This document updates “Strategies to Prevent Central Line-Associated Bloodstream Infections in Acute Care Hospitals,” published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates.

Validation of a Sampling Method to Collect Exposure Data for Central-Line–Associated Bloodstream Infections

OBJECTIVE

Surveillance of central-line–associated bloodstream infections requires the labor-intensive counting of central-line days (CLDs). This workload could be reduced by sampling. Our objective was to evaluate the accuracy of various sampling strategies in the estimation of CLDs in intensive care units (ICUs) and to establish a set of rules to identify optimal sampling strategies depending on ICU characteristics.

DESIGN

Analyses of existing data collected according to the European protocol for patient-based surveillance of ICU-acquired infections in Belgium between 2004 and 2012.

SETTING AND PARTICIPANTS

CLD data were reported by 56 ICUs in 39 hospitals during 364 trimesters.

METHODS

We compared estimated CLD data obtained from weekly and monthly sampling schemes with the observed exhaustive CLD data over the trimester by assessing the CLD percentage error (ie, observed CLDs – estimated CLDs/observed CLDs). We identified predictors of improved accuracy using linear mixed models.

RESULTS

When sampling once per week or 3 times per month, 80% of ICU trimesters had a CLD percentage error within 10%. When sampling twice per week, this was >90% of ICU trimesters. Sampling on Tuesdays provided the best estimations. In the linear mixed model, the observed CLD count was the best predictor for a smaller percentage error. The following sampling strategies provided an estimate within 10% of the actual CLD for 97% of the ICU trimesters with 90% confidence: 3 times per month in an ICU with >650 CLDs per trimester or each Tuesday in an ICU with >480 CLDs per trimester.

CONCLUSION

Sampling of CLDs provides an acceptable alternative to daily collection of CLD data.

Infect Control Hosp Epidemiol 2016;37:549–554

Comparison of NHSN-defined central venous catheter day counts with a method that accounts for concurrent catheters

Central venous catheter (CVC) day definitions do not consider concurrent CVCs. We examined traditional CVC day counts and resultant central line-associated bloodstream infection (CLABSI) rates with a CVC day definition that included concurrent CVCs. Accounting for concurrent CVCs increased device day counts by 8.5% but only mildly impacted CLABSI rates.

Prospective Validation of Central Line–Days Derived From an Electronic Medical Record System

Validation of the number of central line–days by hospitals is required by the National Healthcare Safety Network. A prospective study that compared a daily report of such days generated by an electronic medical record with observational audits by nurses revealed that the report was 100% sensitive and 99.9% specific.

Infect. Control Hosp. Epidemiol. 2015;36(9):1098–1099

Estimating central line-associated bloodstream infection incidence rates by sampling of denominator data: A prospective, multicenter evaluation

BACKGROUND

Large-scale, prospective, evaluation of sampling for central line-associated bloodstream infection (CLABSI) denominator data was necessary prior to National Healthcare Safety Network (NHSN) implementation.

METHODS

In a sample of volunteer hospitals from states in the Emerging Infections Program, prospective collection of CLABSI denominators (patient days, central line days [CLDs]) was performed in eligible locations for ≥6 and ≤12 consecutive months using the current NHSN method (daily collection) and also by a second data collector who sampled the denominator data 1 d/wk. The quality of the sampled data was evaluated and used to calculate estimated CLDs and CLABSI rates, which were compared with actual CLDs and CLABSI rates (daily counts).

RESULTS

In total, 89 locations in 66 acute care hospitals participated. Sampled data were collected as intended 88% of the time; the quality of the data was comparable with the data collected daily. In locations with higher CLDs per month (≥75), estimated CLDs and CLABSI rates were similar to actual CLDs and CLABSI rates; however, there were significant differences in actual and estimated values among locations with lower (≤74) CLDs per month.Sampling was successfully implemented, but significant differences in the accuracy of estimated CLDs and CLABSI rates, based on the actual number of CLDs per month, were noted.

CONCLUSION

For locations with a higher number of CLDs per month, sampling 1 d/wk is a valid and accurate alternative to daily collection of CLABSI denominator data.

Strategies to Prevent Central Line-Associated Bloodstream Infections in Acute Care Hospitals: 2014 Update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format designed to assist acute care hospitals in implementing and prioritizing their central line-associated bloodstream infection (CLABSI) prevention efforts. This document updates “Strategies to Prevent Central Line-Associated Bloodstream Infections in Acute Care Hospitals,” published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates.