A Retrospective Study on “Effectiveness of Remote Patient Monitoring in Covid-19 patients"

Corona virus disease19 has spread over the world, affecting millions of people. It has put enormous strain on the global healthcare system. Due to frequent mutations, the pandemic is spreading rapidly. The world requires a technology that will facilitate the effective diagnosis, treatment, and discharge of COVID19 patients. A model like remote patient monitoring [RPM] makes it easier to handle Covid 19 patients. RPM helps in remotely diagnosis, treatment, as well as allowing for prompt interventions. The RPM makes use of mobile technology and IoT platforms to take clinical interventions. In this study out of 151 covid19 positive subjects 91% of them were shifted to home monitoring within 5 days of MVM monitoring with few readmissions. The study investigated the effectiveness of RPM in the Indian healthcare system, as well as the performance and usability of the Vigocare mobile application by patients and doctors.

Remote Patient Monitoring in Diabetes: How to Acquire, Manage, and Use All of The Data

The ability of patients and health care providers to use various forms of technology for general health has significantly increased in the past several years with the expansion of telehealth, digital applications, personal digital devices, smartphones, and other Internet-connected platforms and devices. For individuals with diabetes, this also includes connected blood glucose meters, continuous glucose monitoring devices, and insulin delivery systems. In this article, the authors outline several steps to facilitate the acquisition, management, and meaningful use of digital diabetes data that can enable successful implementation of both diabetes technology and telehealth services in primary care clinics.

Remote Patient Monitoring for Healthcare

Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.

Feasibility of Wearable-Based Remote Monitoring in Patients During Intensive Treatment for Aggressive Hematologic Malignancies

PURPOSE Intensive treatment protocols for aggressive hematologic malignancies harbor a high risk of serious clinical complications, such as infections. Current techniques of monitoring vital signs to detect such complications are cumbersome and often fail to diagnose them early. Continuous monitoring of vital signs and physical activity by means of an upper arm medical wearable allowing 24/7 streaming of such parameters may be a promising alternative. METHODS This single-arm, single-center observational trial evaluated symptom-related patient-reported outcomes and feasibility of a wearable-based remote patient monitoring. All wearable data were reviewed retrospectively and were not available to the patient or clinical staff. A total of 79 patients (54 inpatients and 25 outpatients) participated and received standard-of-care treatment for a hematologic malignancy. In addition, the wearable was continuously worn and self-managed by the patient to record multiple parameters such as heart rate, oxygen saturation, and physical activity. RESULTS Fifty-one patients (94.4%) in the inpatient cohort and 16 (64.0%) in the outpatient cohort reported gastrointestinal symptoms (diarrhea, nausea, and emesis), pain, dyspnea, or shivering in at least one visit. With the wearable, vital signs and physical activity were recorded for a total of 1,304.8 days. Recordings accounted for 78.0% (63.0-88.5; median [interquartile range]) of the potential recording time for the inpatient cohort and 84.6% (76.3-90.2) for the outpatient cohort. Adherence to the wearable was comparable in both cohorts, but decreased moderately over time during the trial. CONCLUSION A high adherence to the wearable was observed in patients on intensive treatment protocols for a hematologic malignancy who experience high symptom burden. Remote patient monitoring of vital signs and physical activity was demonstrated to be feasible and of primarily sufficient quality.

Quality Management of Patient Generated Health Data from Wearables: Development of a Guideline for Remote Patient Monitoring (Preprint)

BACKGROUND Patient-Generated Health Data (PGHD) collected from innovative wearables are enabling healthcare to shift to outside clinical settings through Remote Patient Monitoring (RPM) initiatives. However, PGHD are collected continuously under the patient’s responsibilities in rapidly changing circumstances during the patient’s daily life. This poses risks to the quality of PGHD and, in turn, reduces their trustworthiness and fitness for use in clinical practice. OBJECTIVE Using a socio-technical health informatics lens, this research aimed to investigate how Data Quality Management (DQM) principles can be applied to ensure that PGHD from wearables can reliably inform clinical decision making in RPM. METHODS First, clinicians, health information specialists and MedTech industry representatives with experience in RPM were interviewed to identify DQM challenges. Second, those groups were joined by patients in a workshop to co-design potential solutions to meet the expectations of all stakeholders. Third, the findings along with literature and policy review results, were interpreted to construct a guideline. Finally, we validated the guideline through a Delphi survey of international health informatics and health information management experts. RESULTS The resulting guideline comprised 19 recommendations across seven aspects of DQM. It explicitly addressed the needs of patients and clinicians but implied that there must be collaboration among all stakeholders, to meet these needs. CONCLUSIONS The increasing proliferation of PGHD from wearables in RPM requires a systematic approach to DQM so that these data can be reliably used in clinical care. The developed guideline is a significant next step toward safe RPM.

A Study Protocol for Occupational Rehabilitation in Multiple Sclerosis

Digital medical solutions can be very helpful in restorative neurology, as they allow the patients to practice their rehabilitation activities remotely. This work discloses ReMoVES, an IoMT system providing telemedicine services, in the context of Multiple Sclerosis rehabilitation, within the frame of the project STORMS. A rehabilitative protocol of exercises can be provided as ReMoVES services and integrated into the Individual Rehabilitation Project as designed by a remote multidimensional medical team. In the present manuscript, the first phase of the study is described, including the definition of the needs to be addressed, the employed technology, the design and the development of the exergames, and the possible practical/professional and academic consequences. The STORMS project has been implemented with the aim to act as a starting point for the development of digital telerehabilitation solutions that support Multiple Sclerosis patients, improving their living conditions. This paper introduces a study protocol and it addresses pre-clinical research needs, where system issues can be studied and better understood how they might be addressed. It also includes tools to favor remote patient monitoring and to support the clinical staff.

Results from Telehealth

Telemedicine and telehealth have a wide range of definitions and understanding. Telehealth has been described as taking many forms and having many terms to describe its activities such as; home health care, telecare, tele-dermatology, tele-psychiatry, tele-radiology, telemonitoring, and remote patient monitoring. In general, the purpose of telehealth is to acquire information on a patient in one location, make that information available in a separate location, usually for the convenience of the clinician, and then use that information to provide management to a patient, who may be in a further location, through the mediation of a remote clinician, or directly to the patient. Typically this has taken the form of the patient being in their own home or at a clinical establishment remote from the hospital such as the district hospital, remote clinic, and primary care, with clinical information being collected and transferred using technology between locations. This chapter focuses on results from telehealth in the form of remote patient monitoring (RPM), in which data is collected from the patient whilst they are in their own home, or other non-clinical setting such as residential care.