Project description:BackgroundThe Texas Department of State Health Services (DSHS) Healthcare Safety Unit (HCSU) conducts remote infection control assessments (tele-ICARs) in long-term care facilities (LTCFs) to evaluate COVID-19 infection prevention and control (IPC) knowledge and practices using a standardized assessment tool. Tele-ICARs are used to gauge different IPC measures specific to SARS-CoV-2 and are either proactive--conducted prior to identified cases--or responsive to an outbreak, which is defined as a new SARS-CoV-2 infection in any staff or any facility-onset infection in a resident. State and local partners use findings from the assessments to aid LTCFs by providing targeted and timely resources and support to mitigate identified gaps.MethodsData from tele-ICARs conducted between March 1 and October 30, 2020 were analyzed to assess major gaps across LTCF types. A major gap was defined as 10% or more of facilities not satisfying a specific IPC measure, excluding missing data. Gaps were also assessed by tele-ICAR type: proactive or responsive. Fisher's exact tests and univariate logistic regression were used to characterize significant associations between major IPC gaps and LTCF or tele-ICAR type.ResultsDSHS conducted tele-ICARs in 438 LTCFs in Texas during 8 months; 191 were nursing homes/skilled nursing facilities (NH/SNFs), 206 were assisted living facilities (ALFs) and 41 were other settings. Of the assessments, 264 were proactive and 174 responsive. Major gaps identified were: (1) 22% did not have a preference for alcohol-based hand sanitizer (ABHS) over soap and water; (2) 18.1% were not aware of the contact time for disinfectants in use; (3) 17.9% had not stopped resident communal dining; (4) 16.8% did not audit hand hygiene and PPE compliance; and (5) 11.8% had not stopped inter-facility group activities and extra-facility field trips. When restricting analyses to proactive tele-ICARs, one additional gap was identified: 11.1% of facilities lacked a dedicated space to care for or cohort residents with confirmed SARS-CoV-2 infection. Significantly more ALFs than NH/SNFs had not suspended resident communal dining (P < .001) nor identified a dedicated space to cohort residents with confirmed SARS-CoV-2 infection (P < .001). Significantly more LTCFs that received a responsive ICAR compared to a proactive ICAR reported a preference for ABHS over soap and water (P = .008) and reported suspending communal dining (P < .001) and group activities (P < .001). Also, significantly more LTCFs that received a responsive ICAR compared to a proactive ICAR had identified a dedicated space to cohort residents with confirmed SARS-CoV-2 (P = .009).ConclusionsIncreased facility education and awareness of federal and state guidelines for group activities and communal dining is warranted in Texas, emphasizing the importance of social distancing for preventing the transmission of SARS-CoV-2 in LTCFs, particularly ALFs. CDC recommendations for ABHS versus hand washing should be emphasized, as well as the importance of monitoring and auditing HCP hand hygiene and PPE compliance. Facilities may benefit from additional education and resources about disinfection, to ensure proper selection of disinfectants and understanding of the contact time required for efficacy. Analysis by tele-ICAR type suggests facilities may benefit from identifying space for dedicated COVID-19 units in advance of an outbreak in their facility. Conducting tele-ICARs in LTCFs enables public health agencies to provide direct and individualized feedback to facilities and identify state-wide opportunities for effective interventions in response to SARS-CoV-2.

Project description:Rationale Due to the cluster and associated comorbidities in residents of long-term care facilities (LTCFs), COVID-19-associated morbidity and mortality are significantly increased. Multiple therapeutic options, including hydroxychloroquine (HCQ) and azithromycin (AZI), were tried initially to treat moderate to severe COVID-19 and high-risk patients in LTCFs, but they were abandoned due to unfavorable reports. As a less toxic option, we initiated treatment with doxycycline (DOXY) very early in the course of illness. DOXY has antiviral, cardioprotective, immunomodulatory, and anti-inflammatory properties, but the efficacy of early intervention with DOXY in high-risk COVID-19 patients in LTCFs is unknown. Objective The goal of this retrospective study is to describe the clinical outcomes of high-risk COVID-19 patients with moderate to severe symptoms in LTCFs after early intervention with DOXY. Design Case-series analysis Setting LTCFs in New York Participants This observational study examines 89 patients who were diagnosed with COVID-19 from March 18 to May 13, 2020. Exposure All patients who were diagnosed with COVID-19 received DOXY and regular standard of care within 12 hours of the onset of symptoms. Additionally, four patients received meropenem, three patients received Zosyn, two patients received linezolid, and two patients received Bactrim DS. Four patients were on chronic ventilator support. No patients received any steroids or any other antiviral or immunomodulatory agents. The majority of the patients received zinc and calcium supplements as well. Main outcomes and measures Assessed measures were patients' characteristics, fever, shortness of breath (SOB), cough, oxygen saturation/pulse oximetry (POX), radiologic improvements, laboratory tests, DOXY side effects, hospital transfers, and death. Results Eighty-nine (89) high-risk patients, who developed a sudden onset of fever, cough, SOB, and hypoxia and were diagnosed with COVID-19, were treated with DOXY (100 mg PO or intravenous (IV) for seven days) and regular standard of care. Eighty-five percent (85%) of patients (n=76) demonstrated clinical recovery that is defined as resolution of fever (average 3.7 days, Coeff = -0.96, p = 0.0001), resolution of SOB (average 4.2 days), and improvement of POX: average 84% before treatment and average 95% after treatment (84.7 ± 7% vs. 95 ± 2.6%, p = 0.0001). Higher pre- and post-treatment POX is associated with lower mortality (oxygen saturation (Spo2) vs. Death, Coeff = -0.01, p = 0.023; post-Spo2 vs. Death, Coeff = -0.05, p = 0.0002). Within 10 days of symptom onset, 3% of patients (n=3) were transferred to hospital due to clinical deterioration and 11% of patients (n=10) died. The result was followed for 30 days from the onset of symptoms in each patient. Conclusion Early treatment with DOXY for high-risk patients with moderate to severe COVID-19 infections in non-hospital settings, such as LTCFs, is associated with early clinical recovery, decreased hospitalization, and decreased mortality.

Project description:BackgroundLong-term care facilities (LTCFs) are vulnerable to disease outbreaks. Here, we jointly analyze SARS-CoV-2 genomic and paired epidemiologic data from LTCFs and surrounding communities in Washington state (WA) to assess transmission patterns during 2020-2022, in a setting of changing policy. We describe sequencing efforts and genomic epidemiologic findings across LTCFs and perform in-depth analysis in a single county.MethodsWe assessed genomic data representativeness, built phylogenetic trees, and conducted discrete trait analysis to estimate introduction sizes over time, and explored selected outbreaks to further characterize transmission events.ResultsWe found that transmission dynamics among cases associated with LTCFs in WA changed over the course of the COVID-19 pandemic, with variable introduction rates into LTCFs, but decreasing amplification within LTCFs. SARS-CoV-2 lineages circulating in LTCFs were similar to those circulating in communities at the same time. Transmission between staff and residents was bi-directional.ConclusionsUnderstanding transmission dynamics within and between LTCFs using genomic epidemiology on a broad scale can assist in targeting policies and prevention efforts. Tracking facility-level outbreaks can help differentiate intra-facility outbreaks from high community transmission with repeated introduction events. Based on our study findings, methods for routine tree building and overlay of epidemiologic data for hypothesis generation by public health practitioners are recommended. Discrete trait analysis added valuable insight and can be considered when representative sequencing is performed. Cluster detection tools, especially those that rely on distance thresholds, may be of more limited use given current data capture and timeliness. Importantly, we noted a decrease in data capture from LTCFs over time. Depending on goals for use of genomic data, sentinel surveillance should be increased or targeted surveillance implemented to ensure available data for analysis.

Project description:BackgroundShared decision-making, a communicative process to reach decisions based on informed preferences, evidence, and co-created goals, improves care satisfaction and patients' quality of life. However, shared decision-making has not been widely implemented in long-term care facilities, and few studies have examined how to promote the shared decision-making practice. This study aimed to identify the influencing factors of shared decision-making based on the Person-centered Practice Framework in long-term care facilities.MethodsA total of 300 staff (nursing staff, social workers, and personal care workers) in 13 Korean long-term care facilities participated in this study. Data from 280 respondents were finally analyzed, excluding respondents with missing values. Data were collected using structured questionnaires that included items on shared decision-making, personal factors (e.g., knowledge about dementia, person-centered care education, person-centered attitude, communication behavior, and job tenure), and care environment factors (e.g., person-centered climate, staffing level, effective staff relationships, supportive supervisors, and power-sharing). Multilevel linear regression analyses were performed using Mplus Version 8.8.ResultsThe mean shared decision-making score was 35.78 (range 8-45). Staff with experience of person-centered care education (β = 0.198, p = 0.034), a higher person-centered attitude score (β = 0.201, p = 0.007), and a higher communication behavior score (β = 0.242, p < 0.001) were more likely to report a higher shared decision-making score. In addition, staff who viewed their care environment as more person-centered were more likely to report a higher shared decision-making score (β = 0.416, p < 0.001).ConclusionsThis study highlights that personal (e.g., person-centered care education, person-centered attitude, and communication behavior) and care environment (e.g., person-centered climate) factors could influence shared decision-making for long-term care residents. These findings could be foundational evidence for facilitating shared decision-making practice in long-term care settings.

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Environmental Noise in New York City Long-Term Care Facilities: A Window Into the COVID-19 Pandemic.

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