Hospitalisation at Home of Patients with COVID-19: A Qualitative Study of User Experiences

Heras, José Cerdán de las; Andersen, Signe Lindgård; Matthies, Sophie; Sandreva, Tatjana Vektorvna; Johannesen, Caroline Klint; Nielsen, Thyge L.; Fuglebjerg, Natascha; Catalán-Matamoros, Daniel; Hansen, Dorte Gilså; Fischer, Thea Kølsen

doi:10.3390/ijerph20021287

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…Home hospitalization services (also known as hospital-at-home (HAH) services), were already available prior to the start of the coronavirus pandemic; however, since then, these services have expanded world-wide and, indeed, are now considered to be one of the positive outcomes of the pandemic [1][2][3]. Within this unique realm of clinical medicine, telemedicine-controlled, hospital-at-home services have progressed, catching up with preexisting technologies and methodologies that were already available but poorly adopted by the medical community in previous years [4].…”

Section: Introduction 1current Status Of Hospital-at-home Servicesmentioning

confidence: 99%

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians

Magor,

Berkov,

Siomin

et al. 2023

Diagnostics

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Background. Technological advancement may bridge gaps between long-practiced medical competencies and modern technologies. Such a domain is the application of digital stethoscopes used for physical examination in telemedicine. This study aimed to validate the level of consensus among physicians regarding the interpretation of remote, digital auscultation of heart and lung sounds. Methods. Seven specialist physicians considered both the technical quality and clinical interpretation of auscultation findings of pre-recorded heart and lung sounds of patients hospitalized in their homes. TytoCareTM system was used as a remote, digital stethoscope. Results. In total, 140 sounds (70 heart and 70 lungs) were presented to seven specialists. The level of agreement was measured using Fleiss’ Kappa (FK) variable. Agreement relating to heart sounds reached low-to-moderate consensus: the overall technical quality (FK = 0.199), rhythm regularity (FK = 0.328), presence of murmurs (FK = 0.469), appreciation of sounds as remote (FK = 0.011), and an overall diagnosis as normal or pathologic (FK = 0.304). The interpretation of some of the lung sounds reached a higher consensus: the overall technical quality (FK = 0.169), crepitus (FK = 0.514), wheezing (FK = 0.704), bronchial sounds (FK = 0.034), and an overall diagnosis as normal or pathological (FK = 0.386). Most Fleiss’ Kappa values were in the range of “fare consensus”, while in the domains of diagnosing lung crepitus and wheezing, the values increased to the “substantial” level. Conclusions. Bio signals, as recorded auscultations of the heart and lung sounds serving the process of clinical assessment of remotely situated patients, do not achieve a high enough level of agreement between specialized physicians. These findings should serve as a catalyzer for improving the process of telemedicine-attained bio-signals and their clinical interpretation.

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Section: Introduction 1current Status Of Hospital-at-home Servicesmentioning

confidence: 99%

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians

Magor,

Berkov,

Siomin

et al. 2023

Diagnostics

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How Social Connectedness Helps Patients Stay Home After Hospital at Home Enrollment: A Mixed Methods Study

Ledford,

Cafferty,

Lee

et al. 2024

J GEN INTERN MED

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Background While enrolled in Hospital at Home (HaH) programs, patients rely on their social network to provide supportive behaviors that are routinely provided by hospital staff in the inpatient setting. Objective This study investigated how social connectedness is associated with patient outcomes in a HaH program. Design The explanatory iterative sequential mixed methods design included an electronic health record review to collect quantitative measures to describe the severity of patient illness and healthcare utilization and then qualitative interviews to explain quantitative findings. Participants The quantitative phase included 100 patients (18 years or older) admitted to the hospital who were subsequently enrolled in the HaH program. In the qualitative phase, 33 of the 100 patients participated in semi-structured interviews. Analysis Qualitative data was analyzed using the Sort & Sift, Think & Shift method. Integrated analysis included merged data displays of healthcare utilization data and patient descriptions of their care and genogram-type illustrations to enable variable-oriented analysis of structural support. We then examined patient narratives by two variables: life course and care elevation, to understand differences in the trajectories of six subsets of patients as identified by the quantitative data. Key Results Three factors prompted patients to enroll in HaH: low attention from hospital staff during hospital stay; loneliness and isolation during hospital stay; and family encouragement to enroll. After discharge, social support within the home structure facilitated recovery during HaH. Conversely, HaH patients with limited support within the home were more likely to be readmitted. Conclusions Structural social connectedness facilitates patient recovery in HaH. Before enrolling patients in HaH, clinicians should take an in-depth social history, including questions about social/familial roles, household responsibilities, and technology acceptance. Clinicians should engage formal and informal caregivers in these conversations early and communicate a clear picture of what caregivers should do to support the patient through recovery.

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Clinical Characteristics and Outcomes of Patients With COVID-19 Treated in Mayo Clinic’s Advanced Care at Home Program

Gothot,

Maniaci,

Paulson

et al. 2024

J Patient Saf

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Objectives Mayo Clinic’s hospital-at-home program, Advanced Care at Home (ACH), launched in 2020. While hospital-at-home literature reported safe and effective care for the general patient population and those with COVID, comparative outcomes between these two groups were unknown. The aim of this retrospective analysis was to compare the outcomes of COVID and non-COVID patients enrolled in ACH and evaluate if COVID patients can be safely treated in this setting. Methods Demographics, clinical characteristics, and safety outcomes were retrospectively analyzed to compare COVID and non-COVID patients discharged from ACH between November 2020 and May 2022. Patient characteristics analyzed included severity of illness (SOI) and risk of mortality (ROM), calculated using All Patient Refined Diagnosis Related Groups (APR-DRG). Hospitalization-specific variables included length of stay (LOS), escalation of care, and 30-day readmission rates. Results Of 1051 patients, 173 (16%) had COVID, and 878 (84%) were non-COVID patients. The average age in the COVID cohort was 66.6 (15.3) years, compared with 72.2 (14.0) in the non-COVID cohort. Extreme SOI was higher in the COVID group (43.3% versus 17.4%), as was extreme ROM (46.2% versus 16.2%), but LOS was shorter (5.7 versus 7 days). Escalation of care (7.5% in COVID cohort versus 8.4%) and 30-day readmission outcomes (9.2% for COVID patients versus 12.9%) were not statistically different between the groups. Conclusions Despite higher SOI and ROM, COVID patients had shorter LOS with outcomes that were not statistically different from non-COVID patients. COVID patients can be safely and efficiently cared for in ACH.

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Hospitalisation at Home of Patients with COVID-19: A Qualitative Study of User Experiences

Cited by 4 publications

References 28 publications

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians

How Social Connectedness Helps Patients Stay Home After Hospital at Home Enrollment: A Mixed Methods Study

Clinical Characteristics and Outcomes of Patients With COVID-19 Treated in Mayo Clinic’s Advanced Care at Home Program

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