Effectiveness of various cleaning strategies in acute and long-term care facilities during novel corona virus 2019 disease pandemic-related staff shortages.

BACKGROUND: Cleanliness of hospital surfaces helps prevent healthcare-associated infections, but comparative evaluations of various cleaning strategies during COVID-19 pandemic surges and worker shortages are scarce. PURPOSE AND METHODS: To evaluate the effectiveness of daily, enhanced terminal, and contingency-based cleaning strategies in an acute care hospital (ACH) and a long-term care facility (LTCF), using SARS-CoV-2 RT-PCR and adenosine triphosphate (ATP) assays. Daily cleaning involved light dusting and removal of visible debris while a patient is in the room. Enhanced terminal cleaning involved wet moping and surface wiping with disinfectants after a patient is permanently moved out of a room followed by ultraviolet light (UV-C), electrostatic spraying, or room fogging. Contingency-based strategies, performed only at the LTCF, involved cleaning by a commercial environmental remediation company with proprietary chemicals and room fogging. Ambient surface contamination was also assessed randomly, without regard to cleaning times. Near-patient or high-touch stationary and non-stationary environmental surfaces were sampled with pre-moistened swabs in viral transport media. RESULTS: At the ACH, SARS-CoV-2 RNA was detected on 66% of surfaces before cleaning and on 23% of those surfaces immediately after terminal cleaning, for a 65% post-cleaning reduction (p = 0.001). UV-C enhancement resulted in an 83% reduction (p = 0.023), while enhancement with electrostatic bleach application resulted in a 50% reduction (p = 0.010). ATP levels on RNA positive surfaces were not significantly different from those of RNA negative surfaces. LTCF contamination rates differed between the dementia, rehabilitation, and residential units (p = 0.005). 67% of surfaces had RNA after room fogging without terminal-style wiping. Fogging with wiping led to a -11% change in the proportion of positive surfaces. At the LTCF, mean ATP levels were lower after terminal cleaning (p = 0.016). CONCLUSION: Ambient surface contamination varied by type of unit and outbreak conditions, but not facility type. Removal of SARS-CoV-2 RNA varied according to cleaning strategy. IMPLICATIONS: Previous reports have shown time spent cleaning by hospital employed environmental services staff did not correlate with cleaning thoroughness. However, time spent cleaning by a commercial remediation company in this study was associated with cleaning effectiveness. These findings may be useful for optimizing allocation of cleaning resources during staffing shortages.

Infection preventionist staffing levels and rates of 10 types of healthcare-associated infections: A 9-year ambidirectional observation.

OBJECTIVE: To quantitatively evaluate relationships between infection preventionists (IPs) staffing levels, nursing hours, and rates of 10 types of healthcare-associated infections (HAIs). DESIGN AND SETTING: An ambidirectional observation in a 528-bed teaching hospital. PATIENTS: All inpatients from July 1, 2012, to February 1, 2021. METHODS: Standardized US National Health Safety Network (NHSN) definitions were used for HAIs. Staffing levels were measured in full-time equivalents (FTE) for IPs and total monthly hours worked for nurses. A time-trend analysis using control charts, t tests, Poisson tests, and regression analysis was performed using Minitab and R computing programs on rates and standardized infection ratios (SIRs) of 10 types of HAIs. An additional analysis was performed on 3 stratifications: critically low (2-3 FTE), below recommended IP levels (4-6 FTE), and at recommended IP levels (7-8 FTE). RESULTS: The observation covered 1.6 million patient days of surveillance. IP staffing levels fluctuated from ≤2 IP FTE (critically low) to 7-8 IP FTE (recommended levels). Periods of highest catheter-associated urinary tract infection SIRs, hospital-onset Clostridioides difficile and carbapenem-resistant Enterobacteriaceae infection rates, along with 4 of 5 types of surgical site SIRs coincided with the periods of lowest IP staffing levels and the absence of certified IPs and a healthcare epidemiologist. Central-line-associated bloodstream infections increased amid lower nursing levels despite the increased presence of an IP and a hospital epidemiologist. CONCLUSIONS: Of 10 HAIs, 8 had highest incidences during periods of lowest IP staffing and experience. Some HAI rates varied inversely with levels of IP staffing and experience and others appeared to be more influenced by nursing levels or other confounders.

THE VALUE OF A REGIONAL 'LIVING' COVID-19 REGISTRY AND THE CHALLENGES OF KEEPING IT ALIVE.

Background: The availability of accurate, reliable, and timely clinical data is crucial for clinicians, researchers, and policymakers so that they can respond effectively to emerging public health threats. This was typified by the recent SARS-CoV-2 pandemic and the critical knowledge and data gaps associated with novel Coronavirus 2019 disease (COVID-19).We sought to create an adaptive, living data mart containing detailed clinical, epidemiologic, and outcome data from COVID-19 patients in our healthcare system. If successful, the approach could then be used for any future outbreak or disease. Methods: From 3/13/2020 onward, demographics, comorbidities, outpatient medications, along with 75 laboratory, 2 imaging, 19 therapeutic, and 4 outcome-related parameters, were manually extracted from the electronic medical record (EMR) of SARS-CoV-2 positive patients. These parameters were entered on a registry featuring calculation, graphing tools, pivot tables, and a macro programming language. Initially, two internal medicine residents populated the database, then professional data abstractors populated the registry. Clinical parameters were developed with input from infectious diseases and critical care physicians and using a modified COVID-19 worksheet from the U.S. Centers for Disease Control and Prevention (CDC). Registry contents were migrated to a browser-based, metadata-driven electronic data capture software platform. Eventually, we developed queries and used various business intelligence (BI) tools which enabled us to semi-automate data ingestion of 147 clinical and outcome parameters from the EMR, via a large U.S. hospital-based, service-level, all-payer database. Statistics were performed in R and Minitab. Results: From March 13, 2020 to May 17, 2021, 549,691 SARS-CoV-2 test results on 236,144 distinct patients, along with location, admission status, and other epidemiologic details are stored on the cloud-based BI platform. From March 2020 until May 2021, extraction of clinical-epidemiologic parameter had to be performed manually. Of those, 543 have had >/=75 parameters fully entered in the registry. Ten clinical characteristics were significantly associated with the need for hospital admission. Only one characteristic was associated with a need for ICU admission. Use of supplemental oxygen, vasopressors and outpatient statin were associated with increased mortality.Initially, 0.5hrs -1.5 hours per patient chart (approximately 450-575 person hours) were required to manually extract the parameters and populate the registry. As of May 17, 2021, semi-automated data ingestion from the U.S. hospital all-payer database, employing user-defined queries, was implemented. That process can ingest and populate the registry with 147 clinical, epidemiologic, and outcome parameters at a rate of 2 hours per 100 patient charts. Conclusion: A living COVID-19 registry represents a mechanism to facilitate optimal sharing of data between providers, consumers, health information networks, and health plans through technology-enabled, secure-access electronic health information. Our approach also involves a diversity of new roles in the field, such as using residents, staff, and the quality department, in addition to professional data extractors and the health informatics team.Initially, due to the overwhelming number of infections that continues to accelerate, and the labor/time intense nature of the project, only a small fraction of all patients with COVID-19 had all parameters entered in the registry. Therefore, this report also offers lessons learned and discusses sustainability issues, should others wish to establish a registry. It also highlights the registry's local and broader public health significance. Beginning in June 2021, whole-genome sequencing results such as lineages harboring important viral mutations, or variants of concern will be linked to the clinical meta-data.

A cluster-control approach to a coronavirus disease 2019 (COVID-19) outbreak on a stroke ward with infection control considerations for dementia and vascular units.

OBJECTIVE: We sought to contain a healthcare-associated coronavirus disease 2019 (COVID-19) outbreak, to evaluate contributory factors, and to prevent future outbreaks. DESIGN: Quasi-experimental cluster-control outbreak evaluation. METHODS: All patients and staff on the outbreak ward (case cluster), and randomly selected patients and staff on COVID-19 wards (positive control cluster) and a non-COVID-19 wards (negative control cluster) underwent reverse-transcriptase polymerase chain reaction (RT-PCR) testing. Hand hygiene and personal protective equipment (PPE) compliance, detection of environmental SARS-COV-2 RNA, patient behavior, and SARS-CoV-2 IgG antibody prevalence were assessed. RESULTS: In total, 145 staff and 26 patients were exposed, resulting in 24 secondary cases. Also, 4 of 14 (29%) staff and 7 of 10 (70%) patients were asymptomatic or presymptomatic. There was no difference in mean cycle threshold between asymptomatic or presymptomatic versus symptomatic individuals. None of 32 randomly selected staff from the control wards tested positive. Environmental RNA detection levels were higher on the COVID-19 ward than on the negative control ward (OR, 19.98; 95% CI, 2.63-906.38; P < .001). RNA levels on the COVID-19 ward (where there were no outbreaks) and the outbreak ward were similar (OR, 2.38; P = .18). Mean monthly hand hygiene compliance, based on 20,146 observations (over preceding year), was lower on the outbreak ward (P < .006). Compared to both control wards, the proportion of staff with detectable antibodies was higher on the outbreak ward (OR, 3.78; 95% CI, 1.01-14.25; P = .008). CONCLUSION: Staff seroconversion was more likely during a short-term outbreak than from sustained duty on a COVID-19 ward. Environmental contamination and PPE use were similar on the outbreak and control wards. Patient noncompliance, decreased hand hygiene, and asymptomatic or presymptomatic transmission were more frequent on the outbreak ward.

Temporal, Spatial, and Epidemiologic Relationships of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Gene Cycle Thresholds: A Pragmatic Ambi-directional Observation.

Prospective serial sampling of 70 patients revealed clinically relevant cycle thresholds (Ct) occurring 9, 26, and 36 days after symptom onset. Race, gender, and corticosteroids apparently did not influence RNA positivity. In a retrospective analysis of 180 patients, initial Ct did not correlate with requirements for admission or intensive care.