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Early Discharge - Evaluating a Virtual Hospital at Home Model

Early Discharge - a Randomised Controlled Trial Evaluating Mental and Physical Effects on Acutely and Chronically Ill Patients in a Telemedicine Supported Virtual Hospital at Home Model

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05920304
Enrollment
111
Registered
2023-06-27
Start date
2023-06-01
Completion date
2025-05-20
Last updated
2025-05-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Epidemic Disease, Infections

Keywords

Telemedicine, Hospital at Home

Brief summary

This controlled clinical trial will be part of a larger, 'virtual hospital-at-home' (vHaH) project called Influenz-er. vHaH is a care model designed to deliver medical care at home, as a substitute for a continued conventional inpatient hospital admission. The overall aim of Influenz-er is to develop, implement and evaluate a novel Hospital at Home model, that will enable safe and satisfactory admission of hospitalised patients including epidemic patients in their homes.

Detailed description

Various versions of hospital-at-home models have been implemented as an emergency solution to a steep increase in number of hospitalisations during the COVID-19 pandemic crisis. Conventionally, epidemic patients who require medical monitoring, will be admitted to the hospital. Recently, patients hospitalised for COVID-19 requiring medical supervision for an extended period - sometimes for weeks - have been admitted to their own home supported by telemedicine and/or mobile hospital-based care team (MHCT). Various models of home-based admissions of pandemic patients have been implemented internationally with great results regarding safety and effectiveness. These models are mostly based on physical attendance of physicians in the patient's home and in most situations implemented out of need. Home-based models provide promising results regarding costs, but results are based on low-quality evidence. Health systems facing capacity constraints and rising costs needs to allocate resources based on high-quality evidence. Therefore, further research regarding feasibility, safety, satisfaction, costs, and effectiveness of a vHaH model still needs to be done. Danish hospital capacity will not allow for HaH models primarily depending on physical attendance of physicians in the patient's home, nor will it be possible to manually monitor all patient reported data. Therefore, there is a need for a telemedicine supported vHaH model with a smart algorithm alarming clinical staff and thereby aiding in timely handling of patient data and clinical state. Project Influenz-er proposes an option of transfer to telemedicine supported vHaH model as an alternative to continued standard hospital admission for the future. Patient safety is a top priority regarding both the utilised technology and the re-organisation of standard clinical responsibilities and tasks. Therefore, project Influenz-er included several steps prior to the effectiveness evaluation in this clinical trial. In the present study, knowledge from previous studies under project Influenz-er is applied, and the vHaH is now ready to be evaluated in an effectiveness trial.

Interventions

DEVICEvirtual Hospital at Home (vHaH)

Participants randomized to vHaH will transferred home for home-based admission. Participants will be provided with equipment for self-monitoring (respiratory rate, oxygen saturation, blood pressure, heart rate and temperature). They will receive an app on their smartphone or tablet for transferring of self-measurements and communication with the hospital during their home-based admission. Supporting the telemedicine concept, a mobile hospital-based care team will perform clinical tasks including intravenous administration, blood samples and on-site clinical assessment in the participant's home, when relevant. Daily ward rounds will be conducted as video consultations. Before leaving the hospital, participants will receive thorough education on how to self-monitor and how to use the app.

Sponsors

Innovation Fund Denmark
CollaboratorINDIV
University of Southern Denmark
CollaboratorOTHER
Nordsjaellands Hospital
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE

Masking description

Masking of participants is not possible due to the nature of the study

Intervention model description

This study is a randomized clinical trial. Participants will be randomized in the ratio 1:2 (for each participant randomized to vHaH, there will be two participants randomized to continued conventional in-hospital admission)

Eligibility

Sex/Gender
ALL
Age
18 Years to 120 Years
Healthy volunteers
No

Inclusion criteria

* Age 18 years or older * Patients admitted to 1. the Department of Pulmonary and Infectious Diseases (DPID) under any diagnosis or 2. to the Department of Multimorbidity under any diagnosis * Residential address within the catchment area of North Zealand University Hospital * Treatment regimen which can be handled within the vHaH model

Exclusion criteria

* Unstable clinical condition defined by a current early warning score (EWS) \> 6 or single score = 3. * Permanent physical or cognitive impairment or observed non-compliance that might negatively affect the ability to perform any of the required actions during the intervention such as self-measurements, data transfer by the app, and/or communication via telephone or video consultation. a. This may include, but is not limited to conditions such as dementia, post-stroke sequelae, deafness, extreme tremor of the upper limbs. * Unproficiency in Danish language skills * Pregnancy

Design outcomes

Primary

MeasureTime frameDescription
Physical activity levelWill be measured during admission (home-based vs. hospital), an average of 5 days after study enrollmentDaily step count and time in different activity levels will be measured using an accelerometer placed on the thigh of the participant.
Patient mental wellbeing (quantitative)14 days post dischargeEvaluation through questionnaires
Patient mental wellbeing (qualitative)14 days post dischargeEvaluation through semi-structured interviews
Patient satisfaction (quantitative)14 days post dischargeEvaluation through questionnaires
Patient satisfaction (qualitative)14 days post dischargeEvaluation through semi-structured interviews
Patient perceived safety (quantitative)14 days post dischargeEvaluation through questionnaires
Patient perceived safety (qualitative)14 days post dischargeEvaluation through semi-structured interviews

Secondary

MeasureTime frameDescription
Number of patient app deficiencies for participants enrolled in intervention armdaily registration during home-based admission, an average of 5 days after study enrollmentData will be extracted from patient record data
Number of health care provider dashboard deficienciesdaily registration during home-based admission, an average of 5 days after study enrollmentData will be extracted from patient record data
Costs related to initiation of home-based admissionthree months post dischargeEconomic endpoint
Number of in-hospital daysthree months post dischargeEconomic endpoint
Number of outpatient visitsthree months post dischargeEconomic endpoint
Demographic characterisation of patients eligible for vHaH14 days post dischargeEvaluation through questionnaires
Number of contacts in primary care (general practitioner, physiotherapy etc.)three months post dischargeEconomic endpoint
Costs of primary care resource usethree months post dischargeEconomic endpoint
Total costs of health care utilisation per patientthree months post dischargeEconomic endpoint
Health-related Quality of Lifethree months post dischargeEconomic endpoint, evaluated using questionnaire EQ-5D-5L (EuroQol, 5 dimensions, 5 levels questionnaire). On a scale 1 to 5, a score of 1 indicates the best health state, and higher scores indicate more severe or frequent problems. In addition, there is a visual analogue scale (VAS) to indicate the general health status with 100 indicating the best health status.
Productivity losses (resources lost when participants work at suboptimal levels or are absent from work)three months post dischargeEconomic endpoint
Costs of hospital resource usethree months post dischargeEconomic endpoint
Rate of adverse events of special interest (AESI)Immediately after dischargeEvaluation through patient record data
Readmittance rate post discharge (30 days and 90 days)30 and 90 days post dischargeEvaluation through patient record data
Mortality during admissiondaily registration during hospital admission or home-based admission, an average of 5 days after study enrollmentEvaluation through patient record data
Mortality post-discharge (7 days, 30 days, and 90 days)7, 30 and 90 days post dischargeEvaluation through patient record data
Percentage of timely service delivery in response to red alarms as a sign of clinical deterioration (health workers demonstrate adequate ability in telemedicine service delivery).daily registration during home-based admission, an average of 5 days after study enrollmentData will be extracted from patient-monitoring platform mit e-hospital and patient record data
Percentage of scheduled video consultation which were delivereddaily registration during home-based admission, an average of 5 days after study enrollmentData will be extracted from patient-monitoring platform mit e-hospital and patient record data

Countries

Denmark

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jun 24, 2026