What is a hospital-at-home program?
Essential categories of tools for HaH programs
Emerging trends in HaH technologies
Advances in remote monitoring and diagnostic tools
Steps to implementing the right tools
References
Further reading
What is a hospital-at-home program?
A hospital-at-home (HaH) program involves providing hospitalization services, including 24/7 monitoring, in the comfort of the patient’s home rather than a hospital facility. Additional advantages associated with the HaH model include reduced healthcare spending, improved patient outcomes, shortened hospital stays, and reduced hospital admissions.
Currently, HaH programs are primarily adopted for the management of patients with chronic diseases, such as heart failure (HF), pneumonia, cellulitis, and chronic obstructive pulmonary disease (COPD), who are cared for by in-personal clinical staff and, when possible, virtual care. Several global studies have reported that HaH programs are associated with non-inferior and, in some cases, superior patient outcomes, along with improved patient quality of life. 1
Image Credit: Ground Picture/Shutterstock.com
Essential categories of tools for HaH programs
Patient monitoring: Devices for vital signs tracking, wearable tech
Recent technological advancements have allowed clinicians to remotely, safely, and effectively provide care to patients in HaH programs through remote patient monitoring. For example, wearable sensors, which can be further classified as biophysical or biochemical sensors, are capable of measuring a wide range of physiological biometrics.
Biophysical sensors utilize acoustic, mechanical, electrical, bioimpedance, thermal, and other signals to obtain data on a patient’s heart rate, blood pressure, respiratory rate, temperature, pulse oximetry, activity, gait, sleep, brain and muscle activity, as well as hydration.
Comparatively, biochemical sensors, which can be noninvasive or minimally invasive, obtain biological fluids from the patient to measure biomarker levels, some of which can include electrolytes, vitamins, lactic acid, creatine, alcohol, urea, levodopa, and cortisol.1
Communication and coordination: Telehealth platforms, secure messaging systems
As the number of wearable sensors and their capabilities have significantly increased, numerous remote patient monitoring applications and software have been developed by numerous companies, such as Apple and Google.
Before the coronavirus disease 2019 (COVID-19) pandemic, several companies were developed with the goal of providing healthcare to patients through a two-way platform. Some of these included Teladoc, Carbon Health, and Firefly Health, which were founded in 2002, 2015, and 2016, respectively.
Following widespread shutdowns of the COVID-19 pandemic and the overwhelming shortage of hospital beds available to care for these patients, video calling platforms like Zoom, Microsoft Teams, Skype, Twilio, and WhatsApp were widely relied on to communicate with patients remotely.
As the volume of patients seeking care through these virtual platforms increased, several companies began incorporating novel sensors into home physical exams that simultaneously facilitated the continuous monitoring of HaH care patients1.
Home-based medical equipment: Portable diagnostic tools, infusion therapy devices
The utilization of any medical technology outside of the hospital setting must be accompanied by guaranteed safety for the patient and quality of care.
Environmental, human, and technological factors must be considered prior to bringing any medical technology into the patient’s home. An example of a human factor includes the number of people who will be handling the device in the patient’s home, as well as the varying extent of training, instruction, or education that has been provided to each user.
Current estimates indicate that over 500,000 different types of medical devices are currently available on the world market. Various advanced medical technologies can be used in a HaH program, some of which include ventilators for respiratory support, homological or peritoneal dialysis systems, and infusion pumps to provide nutrition or medication2.
Image Credit: Ground Picture/Shutterstock.com
Suction devices, external electrostimulation, nebulizers, sleep apnea treatment, patient lifting hoists, vacuum-assisted wound closure, and continuous passive motion technologies may also be used in a HaH model. 2
Emerging trends in HaH technologies
Ambient monitoring technologies utilize various modalities, including cameras and thermal and radio sensors, to remotely monitor patient vital signs and immediately detect any falls that may occur.
Radio sensors, for example, have been used to monitor patients' gait, sleep patterns, and movements. These can be particularly useful in postoperative patients, whose mobility and ability to perform basic activities must be routinely assessed3.
Various clinical risk prediction models, some of which have utilized machine learning (ML) methods, have also been developed to predict the likelihood of a patient’s clinical outcome. These models can be used to predict any potential complications that the patient may experience to ensure that necessary resources are readily available, as well as predict which patients may benefit more from a HaH program as compared to traditional inpatient care.
In addition to the development of models that have been constructed from reported observational data, machine-learning tools can also be directly applied to each individual patient’s records. More specifically, this technology can be applied to learn the patient’s baseline biometrics while also monitoring their current status to quickly identify any subclinical deviations that may reflect a potential complication that requires medical. 3
Advances in remote monitoring and diagnostic tools
Wearable sensors are widely used by both patients and otherwise healthy individuals to monitor their activities. Despite their popularity, wearable sensor nodes are associated with resource limitations that prevent them from always detecting incidents like falls or differentiating these movements from routine activities.
The Internet of Things (IoT) has been proposed as a solution to these problems, as this system can combine a wide range of technologies, such as wireless sensor networks, cloud computing, and sensing data, to improve the quality and accuracy of data provided to healthcare providers monitoring patients in a HaH setting. 4
For example, in a study published in Measurement: Sensors, researchers developed a long short-term memory (LSTM) recurrent neural network that combined data wearable sensor data from Apache Flink and MbientLab devices to achieve a 95.9% accuracy rate in detecting patient falls.
Steps to implementing the right tools
Healthcare providers at the Brigham Women’s Hospital in Boston, Massachusetts, have created a clinical framework that provides details on important steps that the clinical team must follow on each postoperative day for patients who have been transferred to HaH care. These steps include visits from healthcare providers and the different data points that must be collected through laboratory testing and remote patient monitoring (RPM) tools.
Home Hospital Offers Inpatient Care at Home: One Patient’s Story | Mass General Brigham
The success of the BWH program can provide other hospitals seeking to increase their utilization of HaH systems by designing similar workflows that support the continuous monitoring of patients remotely while simultaneously ensuring that all members of the care team can access patient records in real time3.
To ensure that RPM tools can effectively deliver clinicians the data needed to monitor patients remotely, a collaborative environment that acquires insights from both clinicians and software engineers must be maintained. Federal support is also crucial to ensure that patients can access and afford advanced RPM tools as they are being developed.
References
- Pandit, J. A., Pawelek, J. B., Leff, B., & Topol, E. J. (2024). The hospital at home in the USA: current status and future prospects. npj Digital Medicine 7(48). doi:10.1038/s41746-024-01040-9.
- ten Haken, I., Allouch, S. B., & van Harten, W. H. (2018). The use of advanced medical technologies at home: a systematic review of the literature. BMC Public Health. doi:10.1186/s12889-018-5123-4.
- Pathak, K., Marwaha, J. S., & Tsai, T. C. (2023). The role of digital technology in surgical home hospital programs. npj Digital Medicine 6(22). doi:10.1038/s4176-023-00750-w.
- Kulurkar, P., Dixit, C. K., Bharathi, V. C., et al. (2023). AI based elderly fall prediction system using wearable sensors: A smart home-care technology with IOT. Measurement: Sensors 25. doi:10.1016/j.measen.2022.100614.
Further Reading
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