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      The effect and implementation of the COVID Box, a remote patient monitoring system for patients with a COVID-19 infection in primary care: a matched cohort study

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          Abstract

          At the onset of the COVID-19 pandemic, the pressure on hospitals increased tremendously. To alleviate this pressure, a remote patient monitoring system called the COVID Box was developed and implemented in primary care. The aim was to assess whether the COVID Box in primary care could reduce emergency department (ED) referrals due to a COVID-19 infection. A matched cohort study was performed between December 2020 and June 2021. Patients with a COVID-19 infection in need of intensive monitoring based on the clinical judgement of their own general practitioner received the COVID Box in primary care combining home monitoring of vital parameters with daily video consultations. The control group was retrospectively matched by propensity score matching. We conducted a subgroup analysis in higher-risk patients with oxygen saturation measurements, considering oxygen saturation as a critical parameter for assessing the risk of a complicated infection. We included 205 patients, of whom 41 patients were monitored with the COVID Box (mean age 70 and 53.7% male) and 164 in the control group (mean age 71.5 and 53% male). No difference was found in ED referrals between the intervention and control groups in our primary analysis. In the subgroup analysis, we found a nonsignificant trend that remote monitoring could reduce the ED referrals. While the overall study found comparable ED referrals between groups, the subgroup analysis suggested a promising prospect in reducing ED referrals due to remote monitoring of higher-risk patients with acute respiratory disease in primary care.

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          OpenSAFELY: factors associated with COVID-19 death in 17 million patients

          COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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            The Fear of COVID-19 Scale: Development and Initial Validation

            Background The emergence of the COVID-19 and its consequences has led to fears, worries, and anxiety among individuals worldwide. The present study developed the Fear of COVID-19 Scale (FCV-19S) to complement the clinical efforts in preventing the spread and treating of COVID-19 cases. Methods The sample comprised 717 Iranian participants. The items of the FCV-19S were constructed based on extensive review of existing scales on fears, expert evaluations, and participant interviews. Several psychometric tests were conducted to ascertain its reliability and validity properties. Results After panel review and corrected item-total correlation testing, seven items with acceptable corrected item-total correlation (0.47 to 0.56) were retained and further confirmed by significant and strong factor loadings (0.66 to 0.74). Also, other properties evaluated using both classical test theory and Rasch model were satisfactory on the seven-item scale. More specifically, reliability values such as internal consistency (α = .82) and test–retest reliability (ICC = .72) were acceptable. Concurrent validity was supported by the Hospital Anxiety and Depression Scale (with depression, r = 0.425 and anxiety, r = 0.511) and the Perceived Vulnerability to Disease Scale (with perceived infectability, r = 0.483 and germ aversion, r = 0.459). Conclusion The Fear of COVID-19 Scale, a seven-item scale, has robust psychometric properties. It is reliable and valid in assessing fear of COVID-19 among the general population and will also be useful in allaying COVID-19 fears among individuals.
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              Psychometric assessment of three newly developed implementation outcome measures

              Background Implementation outcome measures are essential for monitoring and evaluating the success of implementation efforts. Yet, currently available measures lack conceptual clarity and have largely unknown reliability and validity. This study developed and psychometrically assessed three new measures: the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM). Methods Thirty-six implementation scientists and 27 mental health professionals assigned 31 items to the constructs and rated their confidence in their assignments. The Wilcoxon one-sample signed rank test was used to assess substantive and discriminant content validity. Exploratory and confirmatory factor analysis (EFA and CFA) and Cronbach alphas were used to assess the validity of the conceptual model. Three hundred twenty-six mental health counselors read one of six randomly assigned vignettes depicting a therapist contemplating adopting an evidence-based practice (EBP). Participants used 15 items to rate the therapist’s perceptions of the acceptability, appropriateness, and feasibility of adopting the EBP. CFA and Cronbach alphas were used to refine the scales, assess structural validity, and assess reliability. Analysis of variance (ANOVA) was used to assess known-groups validity. Finally, half of the counselors were randomly assigned to receive the same vignette and the other half the opposite vignette; and all were asked to re-rate acceptability, appropriateness, and feasibility. Pearson correlation coefficients were used to assess test-retest reliability and linear regression to assess sensitivity to change. Results All but five items exhibited substantive and discriminant content validity. A trimmed CFA with five items per construct exhibited acceptable model fit (CFI = 0.98, RMSEA = 0.08) and high factor loadings (0.79 to 0.94). The alphas for 5-item scales were between 0.87 and 0.89. Scale refinement based on measure-specific CFAs and Cronbach alphas using vignette data produced 4-item scales (α’s from 0.85 to 0.91). A three-factor CFA exhibited acceptable fit (CFI = 0.96, RMSEA = 0.08) and high factor loadings (0.75 to 0.89), indicating structural validity. ANOVA showed significant main effects, indicating known-groups validity. Test-retest reliability coefficients ranged from 0.73 to 0.88. Regression analysis indicated each measure was sensitive to change in both directions. Conclusions The AIM, IAM, and FIM demonstrate promising psychometric properties. Predictive validity assessment is planned. Electronic supplementary material The online version of this article (doi:10.1186/s13012-017-0635-3) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Fam Pract
                Fam Pract
                famprj
                Family Practice
                Oxford University Press (UK )
                0263-2136
                1460-2229
                April 2025
                21 September 2024
                21 September 2024
                : 42
                : 2
                : cmae045
                Affiliations
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                National eHealth Living Lab (NeLL), Leiden University Medical Centre , The Netherlands
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                National eHealth Living Lab (NeLL), Leiden University Medical Centre , The Netherlands
                Department of Biomedical Data Sciences, Leiden University Medical Center , 2333 ZA, Leiden, The Netherlands
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                National eHealth Living Lab (NeLL), Leiden University Medical Centre , The Netherlands
                National eHealth Living Lab (NeLL), Leiden University Medical Centre , The Netherlands
                Department of Cardiology, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                Department of Public Health and Primary Care, Leiden University Medical Centre , 2333 ZA, Leiden, The Netherlands
                National eHealth Living Lab (NeLL), Leiden University Medical Centre , The Netherlands
                Author notes
                Corresponding author. Department of Public Health and Primary Care, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands. E-mail: n.e.van_hattem@ 123456lumc.nl
                Author information
                https://orcid.org/0000-0001-8990-9445
                https://orcid.org/0000-0002-9664-2985
                Article
                cmae045
                10.1093/fampra/cmae045
                11878381
                39305513
                863a1822-9f9e-486f-9e91-3e68b373ce4c
                © The Author(s) 2024. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 7
                Funding
                Funded by: departmental resources;
                Categories
                Health Service Research
                AcademicSubjects/MED00780

                Medicine
                infectious diseases,respiratory tract diseases,telemedicine,primary care,practice management,covid-19

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