Comparison of Data Collection for Healthcare-Associated Infection Surveillance in Nursing Homes

Healthcare-associated infections and antimicrobial use in Belgian nursing homes: results of three point prevalence surveys between 2010 and 2016

Background

Belgium monitors the burden of healthcare-associated infections (HAIs) and antimicrobial use in nursing homes (NHs) by participating in the European point prevalence surveys (PPSs) organised in long-term care facilities (HALT surveys). We present the main findings of the three national PPSs conducted in NHs participating in at least one of these surveys, and in a cohort that participated in all three consecutive surveys.

Methods

All NHs were invited to voluntarily participate and conduct the survey on one single day in May-September 2010 (HALT-1), in April-May 2013 (HALT-2) or in September-November 2016 (HALT-3). Data were collected at institutional, ward and resident level. A detailed questionnaire had to be completed for all eligible (i.e. living full time in the facility since at least 24 h, present at 8:00 am and willing to participate) residents receiving at least one systemic antimicrobial agent and/or presenting at least one active HAI on the PPS day. The onset of signs/symptoms had to occur more than 48 h after the resident was (re-)admitted to the NH.

Results

A total of 107, 87 and 158 NHs conducted the HALT-1, HALT-2 and HALT-3 survey, respectively. The median prevalence of residents with antimicrobial agent(s) increased from 4.3% (95% confidence interval (CI): 3.5-4.8%) in HALT-1 to 4.7% (95% CI: 3.5-6.5%) in HALT-2 and 5.0% (95% CI: 4.2-5.9%) in HALT-3. The median prevalence of residents with HAI(s) varied from 1.8% (95% CI: 1.4-2.7%) in HALT-1 to 3.2% (95% CI: 2.2-4.2%) in HALT-2 and 2.7% (95% CI: 2.1-3.4%) in HALT-3. Our post-hoc analysis on the cohort (n = 25 NHs) found similar trends. In all three surveys, respiratory tract infections were most frequently reported, followed by skin/wound infections in HALT-1 and urinary tract infections in HALT-2 and HALT-3. Antimicrobials were most commonly prescribed for the therapeutic treatment of an infection: 66.4% in HALT-1, 60.9% in HALT-2 and 64.1% in HALT-3. Uroprophylaxis accounted for 28.7%, 35.6% and 28.4% of all prescriptions, respectively.

Conclusions

None withstanding the limitations peculiar to the study design, the PPSs enabled us to assess the occurrence of and to increase awareness for HAIs and rational antimicrobial use in NHs at both local and national level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00818-1.

International comparison of pressure ulcer measures in long-term care facilities: Assessing the methodological robustness of 4 approaches to point prevalence measurement

INTRODUCTION

Pressure ulcer indicators are among the most frequently used performance measures in long-term care settings. However, measurement systems vary and there is limited knowledge about the international comparability of different measurement systems. The aim of this analysis was to identify possible avenues for international comparisons of data on pressure ulcer prevalence among residents of long-term care facilities.

MATERIAL AND METHODS

A descriptive analysis of the four point prevalence measurement systems programs used in 28 countries on three continents was performed. The criteria for the description and analysis were based on the scientific literature on criteria for indicator selection, on issues in international comparisons of data and on specific challenges of pressure ulcer measurements.

RESULTS

The four measurement systems use a prevalence measure based on very similar numerator and denominator definitions. All four measurement systems also collect data on patient mobility. They differ in the pressure ulcer classifications used and the requirements for a head-to-toe resident examination. The regional or country representativeness of long-term care facilities also varies among the four measurement systems.

CONCLUSIONS

Methodological differences among the point prevalence measurement systems are an important barrier to reliable comparisons of pressure ulcer prevalence data. The alignment of the methodologies may be improved by implementing changes to the study protocols, such as aligning the classification of pressure ulcers and requirements for a head-to-toe resident skin assessment. The effort required for each change varies. All these elements need to be considered by any initiative to facilitate international comparison and learning.

Antimicrobial Use in a Cohort of US Nursing Homes, 2017

IMPORTANCE

Controlling antimicrobial resistance in health care is a public health priority, although data describing antimicrobial use in US nursing homes are limited.

OBJECTIVE

To measure the prevalence of antimicrobial use and describe antimicrobial classes and common indications among nursing home residents.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional, 1-day point-prevalence surveys of antimicrobial use performed between April 2017 and October 2017, last survey date October 31, 2017, and including 15 276 residents present on the survey date in 161 randomly selected nursing homes from selected counties of 10 Emerging Infections Program (EIP) states. EIP staff reviewed nursing home records to collect data on characteristics of residents and antimicrobials administered at the time of the survey. Nursing home characteristics were obtained from nursing home staff and the Nursing Home Compare website.

EXPOSURES

Residence in one of the participating nursing homes at the time of the survey.

MAIN OUTCOMES AND MEASURES

Prevalence of antimicrobial use per 100 residents, defined as the number of residents receiving antimicrobial drugs at the time of the survey divided by the total number of surveyed residents. Multivariable logistic regression modeling of antimicrobial use and percentages of drugs within various classifications.

RESULTS

Among 15 276 nursing home residents included in the study (mean [SD] age, 77.6 [13.7] years; 9475 [62%] women), complete prevalence data were available for 96.8%. The overall antimicrobial use prevalence was 8.2 per 100 residents (95% CI, 7.8-8.8). Antimicrobial use was more prevalent in residents admitted to the nursing home within 30 days before the survey date (18.8 per 100 residents; 95% CI, 17.4-20.3), with central venous catheters (62.8 per 100 residents; 95% CI, 56.9-68.3) or with indwelling urinary catheters (19.1 per 100 residents; 95% CI, 16.4-22.0). Antimicrobials were most often used to treat active infections (77% [95% CI, 74.8%-79.2%]) and primarily for urinary tract infections (28.1% [95% CI, 15.5%-30.7%]). While 18.2% (95% CI, 16.1%-20.1%) were for medical prophylaxis, most often use was for the urinary tract (40.8% [95% CI, 34.8%-47.1%]). Fluoroquinolones were the most common antimicrobial class (12.9% [95% CI, 11.3%-14.8%]), and 33.1% (95% CI, 30.7%-35.6%) of antimicrobials used were broad-spectrum antibiotics.

CONCLUSIONS AND RELEVANCE

In this cross-sectional survey of a cohort of US nursing homes in 2017, prevalence of antimicrobial use was 8.2 per 100 residents. This study provides information on the patterns of antimicrobial use among these nursing home residents.

Risk adjustment for benchmarking nursing home infection surveillance data: A narrative review

Until recently, there was no national surveillance system for monitoring infection occurrence in long-term care facilities (LTCF) in the United States. As a result, there are no national benchmarks for LTCF infection rates that can be utilized for quality improvement at the facility level. One of the major challenges in the reporting of health care-related infection data is accounting for nonmodifiable facility and patient characteristics that influence benchmarks for infection. The objectives of this paper are to review: (a) published infection rates in LTCF in the United States to assess the level of variability; (b) studies describing facility- and resident-level risk factors for infection that can be used in risk adjustment models; (c) published attempts to risk-adjust LTCF infection rates; and (d) efforts to develop models specifically for risk adjustment of infection rates in LTCF for benchmarking. It is anticipated that this review will stimulate further study of methods to risk-adjust LTCF infection rates for benchmarking that will facilitate research and public reporting.

Self-reported National Healthcare Safety Network knowledge and enrollment: A national survey of nursing homes

Predictors of nursing home staff knowledge of the National Healthcare Safety Network (NHSN) and facility enrollment were explored in a national survey. Facility participation in Quality Innovation Network-Quality Improvement Organization initiatives was positively associated with both knowledge and enrollment. In addition, engaging clinical personnel in decision making on NHSN enrollment was positively associated with staff knowledge of NHSN.

Systems Modeling Approach for Reducing the Risk of Healthcare-Associated Infections

Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.