key: cord-0817690-1j6pt74p
authors: Halverson, Thomas; Mikolajczak, Anessa; Mora, Nallely; Silkaitis, Christina; Stout, Savanna
title: Impact of COVID-19 on Hospital Acquired Infections
date: 2022-03-06
journal: Am J Infect Control
DOI: 10.1016/j.ajic.2022.02.030
sha: 480af77d46c7c55544ca491c24ba91491a5017a0
doc_id: 817690
cord_uid: 1j6pt74p

While there are established and effective guidelines for prevention of hospital-acquired infections (HAIs), the impact of the COVID-19 pandemic on those implemented practices and policies have not been thoroughly investigated. This report examines the impact of COVID-19 on HAI rates at two hospitals within the same healthcare system. HAIs significantly increased during the COVID-19 pandemic which correlated with the use of overtime and agency nursing hours.

The ongoing COVID-19 pandemic has been a shock to the global and U.S. medical 37 system. While there are established and effective guidelines and procedures for prevention of 38 hospital-acquired infections (HAIs), the impact of the pandemic on these best practices have not 39 been thoroughly investigated. It was predicted that the device related infections, catheter-40 associated urinary tract infections (CAUTIs) and central line-associated bloodstream infections 41 (CLABSIs) would increase due to the change in the complexity of hospitalized patients and the 42 safety practices that were implemented to decrease COVID-19 transmission risk to healthcare 43 providers (i.e. enter patient room less frequently). It was also predicted that methicillin resistant 44

Staphylococcus aureus (MRSA) and Clostridiodes infections (CDIs) would decrease due to 45 increased environmental cleaning [1] . Early study results are mixed on the pandemic's impact on 46

HAIs [2, 3, 4, 5]. The aim of this study is to examine the impact that this pandemic had on 47 CAUTIs, CLABSIs, MRSA, and CDIs at two hospitals in Illinois. Surgical site infections were 48 not included due to the large change in surgical volume that coincided with the pandemic. In 49 addition, nurse staffing levels and COVID-19 case rates are included in a linear regression model 50 to determine which covariates are significantly associated with increased HAI rates. 51

This is a multi-center retrospective cohort study of inpatient individuals admitted to two 54 hospitals in Illinois, one 159 bed suburban community hospital and one 894 bed urban academic Covariates 62

The covariates used in this study include: diagnosis of COVID-19, total patient days, 63 device days, SUR, proportion of COVID-19 positive patient days, monthly state and county 64 COVID-19 cases and deaths, total registered nurse (RN) hours per patient day, total RN 65 overtime hours, total agency staff RN hours, proportion of agency premium pay hours, and 66 proportion of RN premium pay hours of total RN hours worked (premium pay is defined as the 67 combined total of overtime hours and agency hours). 68 

When both hospitals' data were combined a significant increase in CLABSI per 1000 80 patient days and 1000 device days was seen during the pandemic (Table 1, with the HAI increases. When adjusting for percent of Illinois and county level COVID-19 cases 90 and deaths, the percent of premium pay hours was significantly associated with an increase in 91 total HAI rates. Every 1% increase in premium pay hours resulted in 0.13 total HAIs when 92 adjusting for Illinois level COVID-19 cases and deaths and 0.13 HAIs in adjusting for county 93 level data. (Table 2 , p<0.05, p<0.05). This was higher than during the non-COVID time period 94 when every 1% increase in premium pay hours resulted in 0.077 total HAIs. 95

The COVID-19 pandemic had a significant impact on the HAI rates at these 2 hospitals with premium 97 pay significantly correlated with total HAIs, particularly during the pandemic as compared to baseline.

Previous studies have found that COVID-19 patients and COVID-19 designated units are more 99 likely to have more HAIs than COVID-19 negative patients and non-COVID-19 units [6, 7, 8] . 100

While these findings are important, they offer little avenues for policy change besides increased 101 clinical practice surveillance. Our finding that premium pay hours, and in particular agency 102 hours, does provide an avenue for further research and potential policy changes related to 103 onboarding and continuing education. Previous meta-analyses have found that non-permanent 104 staff, float nurses, and overtime hours are significantly associated with increased HAI levels [9, 105 10]. This has a renewed importance with the ongoing staffing shortage in the medical field. 106

Ensuring that the proper training and education is in place for staff and that IP is able to audit 107 and partner with staff could help reduce the increased infection rates. 

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