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Telehealth Solution with a Remote PatientMonitoring Module

Telehealth Solution
Explore how we helped our client:
Enhance an existing telehealth solution via integration with IoT technologies
Improve patient–doctor tele and text communication and data sharing thanks to implementing a remote patient monitoring module
Provide clinicians with patients’ critical data collected from IoT devices for making informed medical decisions
Obtain ONC Health IT Certification to demonstrate compliance with government requirements for healthcare solutions

Business context

Our client is a US-based technology company that focuses on medical facility automation. They offer smart hospitals and clinics customizable healthcare software as well as integrations with third-party service providers to meet their individual demands.

Examining the effectiveness of medical IoT solutions for healthcare, their potential, and their popularity, our client saw an opportunity to use IoT devices in telemedicine to help clinicians treat remote patients more efficiently.

Previously, Yalantis had developed customizable modules for the client — specifically, a hospital administration module, a patient portal module, and an extendable EHR module. This time, the company appealed to Yalantis to bring IoT technology into their existing telemedicine system.

Goals of our cooperation

Our project objectives were:

To address the lack of vital patient data necessary for an extensive analysis of patient health conditions
To enable clinicians to consider a more sophisticated health background of remote patients for a more tailored treatment approach

To achieve these goals, we needed to extend the client’s existing telemedicine solution with a remote patient monitoring module through integration with medical IoT for healthcare devices for acquiring data on patients’ vital signs. This involved:

Accommodating data collected from monitoring devices within the EHR storage and access policies
Enhancing a patient-facing app with device onboarding, real-time health tracking, and data sharing features
Improving a clinician-facing app with patient monitoring functionality

Analysis of needs

The integration of IoT devices into the existing telemedicine solution began with a thorough examination of the various kinds of data that could be collected. We studied the forms of data that a doctor collects during a personal visit based on a patient’s age and general health condition. Besides that, we took into account the current COVID-19 situation to choose the most important parameters to track.

After a discussion with clinicians, we focused on two categories of data:

Clinical data

EKG-gathered parameters
Blood pressure
Oxygen saturation level
These parameters require high accuracy, which is why we had to choose appropriate personal medical devices and integrate them into the existing medical solution.

Fitness data

Physical activity
Historical heart rate data
We agreed that data from wearables like fitness trackers and smartwatches could supplement a patient’s health background. We figured out which devices patients use most and integrated them into the system.

Integration of IoT devices in patient–clinician communication

Personal medical devices

Our goal was to identify an appropriate supplier that could provide devices that were both convenient for patients to use and met our technology requirements.

Our client initiated a strategic partnership with the most suitable vendor. This cooperation allowed us to use modern BLE-enabled medical devices and a provider’s SDK for direct data gathering.

As a result, we configured such IoT applications for healthcare as Bluetooth EKG monitors, Bluetooth blood pressure monitors, and Bluetooth pulse oximeters to collect data on a person’s vitals that is accurate and appropriate for analysis.

Smartwatches and fitness trackers

After deciding to adopt wearables, we had to decide what types of data we would collect from them, since different models can collect different types of data. After examining the data collection capabilities of widely used wearables with clinicians, we shortened the list of data to collect to the most practical parameters:

Number of steps
Pulse rate over time

These two parameters aid doctors in determining a patient’s condition during daily activities and regular physical load. As a result, doctors can consider the broader context of a patient’s health and provide more accurate suggestions regarding specific routines.

To enable patients to use their own wearables, we ensured smooth integration with the most popular and widely used models.

Main technical challenges

Find ways to optimize the data flow from wearables

Hundreds of terabytes of disorderly data can come to the client’s system from wearables on an hourly basis — and even by the minute. This disorderliness complicates data analysis. To make wearable devices truly beneficial to doctors, we needed to optimize the data flow and sort this data according to medical requirements.


We created a schedule-based data control mechanism that collects device data from the provider’s cloud storage, processes it, and summarizes it. As a result, clinicians have access to a summary of a patient’s vitals taken from wearables via the EHR system.

Design mechanisms for proper data storage

Regularly updating data on patients’ vitals taken from wearables requires a lot of storage. This would lead to additional costs for data of secondary importance. We needed to resolve the issue of storage limits and develop the means to save data conveniently.


Data compression

We used a data compression method to manage data older than three months from different types of devices. After compression, data is delivered to the archive where it’s stored. A doctor can submit a special request to the IT department to receive archived information.

Data overview

Data that is more than a year old is transformed into overviews of specific periods. The system generates weekly summaries based on daily information, then destroys daily measurements.

Data limits

Overall data storage has a time limit as well. The system discards data that is no longer valid based on criteria established by physicians for the sake of conserving resources and ensuring smooth system operation.

Ensure proper security measures

Integrating personal medical devices and wearables into the system entails the transmission of sensitive information about patients’ health problems. A new module had to meet security requirements to protect patients’ health information.


HL7 protocol

Data is transferred from patients’ mobile applications to the EHR system according to the HL7 protocol, complying with its specific security requirements. This helps to smoothly and safely share data between patient- and clinician-facing applications.

Educated consent

Our remote patient monitoring module necessitates the acquisition and use of exceedingly sensitive data (with medical intent). We designed this module with in-depth explanations concerning the use of data so that patients understand exactly what they are consenting to.

Device onboarding

We implemented device onboarding to ensure device inventory and improve security flows. Patients receive a patient onboarding box containing personal medical devices and instructions for using the patient-facing web and mobile applications from our client. Using a unique patient number to be entered when pairing a device with the patient app, patients let the system recognize devices and assign them to individuals.

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Refinement of the existing telemedicine solution

Implementing a remote patient monitoring module and addressing arising challenges required enhancements throughout the whole platform that the Yalantis team successfully provided.

We modernized the EHR system to enable it to receive and store data on patients’ vitals and devices:
Non-intermediary data gathering
We used Bluetooth technology to smoothly transfer data from personal medical devices to the IoT-based application. Once in the application, each piece of patient data is promptly sent to the EHR system. This helped us avoid confusion that would cause endless API requests to the third-party provider’s database. All information from patients is meticulously classified according to its nature, timing, and other critical parameters.
Fitness data collection
Data taken from wearables goes through the preprocessing stage and is delivered to the EHR system in an optimized format. Clinicians have access to average results and can use these statistics for a background understanding of patients’ conditions during everyday activities.
Personal medical device assignment module
After device onboarding completes, the system keeps data on its carrier, size, serial number, condition, efficiency, and timeliness in the internal catalog. This approach helps clinicians properly maintain, update, and replace patients’ devices.
Architectural scheme of the revamped EHR system
Design of logical and physical workflows of the EHR system
The patient-facing application underwent updates aimed at ensuring a smooth data flow and use of personal medical and wearable devices:
Synchronous measurement tracking
Patients can now take and send their measurements during an online session with a physician. We modified the application so that it recognizes when a session is in progress and allows patients and doctors to collect, send, and review fresh data without disrupting the session.
User-centered interface improvements
We presented patients with a more user-friendly interface. We adjusted it to new user flows so that patients can easily send their data, follow preset regimens, and track their progress at every age and with any health condition.
Scheduled routines
To improve the quality of therapy and monitoring, we created a routine scheduling tool. Using it, a doctor can assign timing for medication, vital sign checks, and physical activity. Patients receive notifications so they don’t miss any of these activities.
Accumulated measurement overview
Patients now have access to a dashboard with average statistics regarding their health right inside the digital healthcare application.
We renovated the clinician-facing application so that clinicians can prescribe activities, receive and analyze new data on vitals from patients, and be notified of changes in patients’ conditions:
Control over patients’ routines
Clinicians can assign patients to routines for engaging in physical activity, tracking vitals, and taking medications. Clinicians use a basic rule-builder and an exercise template library to develop customized commands and prescribe routines based on their patients’ conditions.
Extended data monitoring and control
We improved a method of dissecting patients’ vital signs by improving the visual presentation of statistics. We introduced reports, reviews, and graphs to make it easier for doctors to evaluate enormous amounts of data.
Review measurements received during the session
Doctors can ask patients to take measurements in the middle of a session and analyze them straight away. The IoT platform now allows parties to exchange fresh data and continue the consultation without interruptions.
Alerts and warnings
Clinicians can now monitor patients’ worsening conditions due to alerts and warnings. The application sends out push notifications to physicians when a patient’s vitals have been consistently decreasing or suddenly decrease.
Architectural scheme of the interaction of patient- and clinician-facing applications through an EHR system for acquiring patients’ data after the integration of IoT devices

Value delivered: tripled the functionality

As a result of IoT device integration, this product allowed our client to present clinicians with a more comprehensive background on patients’ health than they can acquire during an office visit.

Enhancements to the patient-facing application

Before the integration, patients could:
Schedule an appointment with a doctor
Have an online consultation (chat and video)

Enhancements to the clinician-facing application

Before the integration, doctors could:
See a schedule of appointments
Hold online video and text sessions
Access patients’ health records

Our client decided to go through the ONC Health IT Certification Program with guidance from Yalantis experts. Now, the upgraded telemedicine solution demonstrates that it meets government requirements for technological capabilities, functionality, and security.
Thanks to this project, our client has increased their market share and is proceeding to create cutting-edge software for the modern healthcare industry and contributing to the further healthcare transformation.

Future plans

The enhancements we have mentioned here are part of the first release. We are continuing to work on the project and have established the following goals for the next release:

Include an FDA-approved continuous glucose monitoring system
Implement an AI-based smart analysis system
Add tools for a comparative study of the reliability of pulse oximeter data from wearable devices
Extend the list of supported wearable devices

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