IoT in Healthcare: Market Overview, IoMT System Architecture, Use Cases
In healthcare IT since 2005 and having experience with IoT solutions since 2011, ScienceSoft designs and develops efficient medical IoT systems for remote patient monitoring, diagnosing and treatment, early symptom detection, staff, patient, and hospital asset tracking.
IoT in Healthcare: Market Overview
The global medical Internet of Things (IoMT) market is projected to grow from $72.5 billion in 2020 to $188.2 billion by 2025 at a CAGR of 21%. IoMT is popular for remote patient monitoring, hospital asset tracking, medical staff location tracking, and more. It enables uninterrupted real-time monitoring and helps automate routine care delivery operations and administrative tasks and ensure secure patient stay at the hospital.
IoT Adoption in the Healthcare Industry
Already in 2019, Gartner revealed that 79% of surveyed healthcare organizations with $100+ million annual revenues were using the IoT technology in their processes. According to Deloitte, 87% of surveyed medtech companies believe that connected medical devices will be central to delivering value and efficiency for healthcare providers.
The key drivers of IoT adoption in healthcare:
- The challenges of the COVID-19 pandemic like staff shortage, increased patient flow, etc.
- Need to reduce costs associated with healthcare services by optimizing routine tasks (e.g., patients’ health parameters monitoring) and overall operations efficiency.
- Focus on active patient engagement and patient-centric care, high demand for a personalized approach to care.
IoMT System Architecture
An IoMT application usually connects a set of devices (e.g., smart medical devices for remote patient monitoring, RFID tags and readers for IoT-based tracking) via gateways to a cloud server. The cloud server hosts data storage, processing, and analytics modules, solution business logic, and control applications. The user and admin apps enable patients, medical staff, and other employees involved to access the collected and analyzed data, send commands to control apps (e.g., to turn off ward air conditioning), and more.
Remote patient monitoring
Remote patient monitoring (RPM) solutions enable continuous health data collection (e.g., body temperature, blood pressure), early symptom detection, alerting on abnormal health parameters, and more. RPM solutions provide patients with accessible care, improve care continuity, patient support and engagement.
How IoT-enabled patient monitoring works: Connected medical devices (e.g., ECG patches, EEG sensors, glucometers) or wearable biosensors collect health parameters and send them to a cloud server for storage and analysis. If the health parameters exceed or go below the pre-set thresholds, a doctor and a patient get notified.
Use cases:
- Monitoring patients with chronic diseases like cardiovascular diseases, neurological diseases (e.g., Parkinson’s disease), COPD, cancer.
- After-surgery monitoring of outpatients.
- Advanced analytics for diagnostic monitoring to detect the early symptoms of diseases (e.g., prediabetes, arrhythmia).
- Analytics to identify disease course patterns and potential complications.
- Monitoring of medication adherence (e.g., using smart medication dispensing devices for geriatric patients, smart pill bottles).
- Sports medicine.
Hospital asset tracking
Hospital asset tracking solutions help minimize asset loss and theft and deliver patient care more efficiently due to decreased search time of medical supplies, medications, etc.
How IoT-enabled hospital asset tracking works: RFID tags are attached to or embedded into hospital assets (e.g., medical devices, surgical tools). When an asset is moved, RFID readers located in the hospital rooms or halls (e.g., on the walls, by the doors) read the tag and send information on the asset location to the cloud server. The hospital asset tracking solution can display movable assets on an interactive hospital map or show the nearest assets upon a search request.
Use cases:
- Medication inventory tracking.
- Hospital equipment utilization monitoring (e.g., MRI scanners).
- Prevention of hospital items use by unauthorized people.
Patient and staff tracking
Monitoring the location of patients and medical staff in hospitals enhances security, helps identify and address inefficiencies in the staffing and scheduling processes of a healthcare organization (e.g., lack of on-duty nurses), and improves bed allocation.
How IoT-enabled patient and staff tracking works: Each patient and staff member gets a bracelet with an RFID tag containing relevant information (e.g., ID, name, position, electronic medical record, current health condition). When a patient or a staff member moves around the hospital, RFID readers on the hospital walls and ceilings receive the tag’s location and send it to the cloud server for further processing and analysis.
Use cases:
- Patient safety monitoring in hospitals.
- Prevention of infant abduction.
- Monitoring of flight-risk patients.
- Staff location monitoring in emergency rooms.
- Patient flow optimization in hospitals.
Smart hospital solutions
Smart hospital use cases are numerous – from room environment monitoring to the identification of security incidents (e.g., unsolicited access to a laboratory). Smart hospital solutions bring benefits like decreased power, water consumption and associated expenses, optimized ward conditions to support patients’ recovery, etc.
How IoT-enabled smart hospital solution works: Using sensors (e.g., motion sensors, temperature sensors), a smart hospital solution collects necessary information about a room condition to analyze and initiate a set of pre-defined actions. For example, when the motion is detected, the solution turns on the lights; when the ward temperature is above 77 degrees, the solution turns on air conditioning.
Use cases:
- Climate control (e.g., to maintain a lower temperature in empty wards, adapt ward humidity).
- Smart room lighting.
- Hospital energy efficiency monitoring.
- Hospital security monitoring.
Remote care delivery and self-management for patients
Used primarily for patients with chronic diseases, remote care delivery IoT solutions facilitate patient treatment in home settings, ensuring secure and efficient care decisions without the direct participation of the doctor.
How IoT-based self-management for patients with chronic diseases works: Via the connected medical devices or sensors, the IoMT solution gets data on patients’ health state, and, if necessary, triggers the treatment delivery (e.g., insulin injection using an insulin pump), calculates the necessary medication dose, etc.
Use cases:
- Diabetes management (e.g., using continuous glucose monitors, smart insulin pens, continuous glucose monitors, smart insulin pumps, or closed-loop artificial pancreas systems).
- IoT-based spirometer therapy for patients with COPD.
Real-time data streaming
Data lakes
Databases / data storages
SQL
Our Microsoft SQL Server-based projects include a BI solution for 200 healthcare centers, the world’s largest PLM software, and an automated underwriting system for the global commercial insurance carrier.
We’ve implemented MySQL for Viber, an instant messenger with 1B+ users, and an award-winning remote patient monitoring software.
ScienceSoft's team has implemented Oracle for software products used by GSK and AstraZeneca. We’ve also delivered Oracle-based SCM platform for Auchan, a retail chain with 1,700 stores.
ScienceSoft has used PostgreSQL in an IoT fleet management solution that supports 2,000+ customers with 26,500+ IoT devices. We’ve also helped a fintech startup promptly launch a top-flight BNPL product based on PostgreSQL.
NoSQL
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
ScienceSoft has helped one of the top market research companies migrate its big data solution for advertising channel analysis to Apache Hive. Together with other improvements, this led to 100x faster data processing.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
With ScienceSoft’s managed IT support for Apache NiFi, an American biotechnology corporation got 10x faster big data processing, and its software stability increased from 50% to 99%.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
Cloud databases / data storages
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Azure
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
Google Cloud Platform
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
IoT data analytics
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Azure
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
Others
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
By request of a leading market research company, we have built a Hadoop-based big data solution for monitoring and analyzing advertising channels in 10+ countries.
A large US-based jewelry manufacturer and retailer relies on ETL pipelines built by ScienceSoft’s Spark developers.
Back end
Practice
19 years
Projects
200+
Workforce
60+
Our .NET developers can build sustainable and high-performing apps up to 2x faster due to outstanding .NET proficiency and high productivity.
Practice
25 years
Projects
110+
Workforce
40+
ScienceSoft's Java developers build secure, resilient and efficient cloud-native and cloud-only software of any complexity and successfully modernize legacy software solutions.
Practice
10 years
Projects
50+
Workforce
30
ScienceSoft's Python developers and data scientists excel at building general-purpose Python apps, big data and IoT platforms, AI and ML-based apps, and BI solutions.
Practice
10 years
Workforce
100
ScienceSoft delivers cloud-native, real-time web and mobile apps, web servers, and custom APIs ~1.5–2x faster than other software developers.
Practice
16 years
Projects
170
Workforce
55
ScienceSoft's PHP developers helped to build Viber. Their recent projects: an IoT fleet management solution used by 2,000+ corporate clients and an award-winning remote patient monitoring solution.
Practice
4 years
ScienceSoft's developers use Go to build robust cloud-native, microservices-based applications that leverage advanced techs — IoT, big data, AI, ML, blockchain.
Front end
Practice
21 years
Projects
2,200+
Workforce
50+
ScienceSoft uses JavaScript’s versatile ecosystem of frameworks to create dynamic and interactive user experience in web and mobile apps.
Practice
13 years
Workforce
100+
ScienceSoft leverages code reusability Angular is notable for to create large-scale apps. We chose Angular for a banking app with 3M+ users.
Workforce
80+
ScienceSoft achieves 20–50% faster React development and 50–90% fewer front-end performance issues due to smart implementation of reusable components and strict adherence to coding best practices.
ScienceSoft uses Meteor for rapid full-stack development of web, mobile and desktop apps.
By using a lightweight Vue framework, ScienceSoft creates high-performant apps with real-time rendering.
With Next.js, ScienceSoft creates SEO-friendly apps and achieves the fastest performance for apps with decoupled architecture.
When working with Ember.js, ScienceSoft creates reusable components to speed up development and avoid code redundancy.
Mobile
Practice
16 years
Projects
150+
Workforce
50+
ScienceSoft’s achieves 20–50% cost reduction for iOS projects due to excellent self-management and Agile skills of the team. The quality is never compromised — our iOS apps are highly rated.
Practice
14 years
Projects
200+
Workforce
50+
There are award-winning Android apps in ScienceSoft’s portfolio. Among the most prominent projects is the 5-year-long development of Viber, a messaging and VoIP app for 1.8B users.
Practice
11 years
Projects
85+
Workforce
10+
ScienceSoft cuts the cost of mobile projects twice by building functional and user-friendly cross-platform apps with Xamarin.
ScienceSoft uses Cordova to create cross-platform apps and avoid high project costs that may come with native mobile development.
ScienceSoft takes the best from native mobile and web apps and creates the ultimate user experience in PWA.
Practice
8 years
Projects
300+
ScienceSoft reduces up to 50% of project costs and time by creating cross-platform apps that run smoothly on web, Android and iOS.
ScienceSoft will save you from double or even triple expenses associated with platform-specific coding by creating cross-platform apps in Flutter.
With Ionic, ScienceSoft creates a single app codebase for web and mobile platforms and thus expands the audience of created apps to billions of users at the best cost.
IoT in Healthcare: Consulting and Development by ScienceSoft
Having 18 years in healthcare IT consulting and development services, 12 years in IoT, and an ISO 13485 certified quality management system, ScienceSoft is ready to bring your medical IoT projects to life.
Consulting on IoMT adoption
What we do:
- Identify and analyze your medical IoT and related business needs.
- Outline the functionality of future IoMT software.
- Create a high-level APIs design to enable required integrations (with EHR, CRM, practice management software, etc.).
- Design tailored IoMT software with a flexible architecture to allow you to add new features when required.
- Estimate the cost, ROI, and software delivery timelines.
- Regulatory compliance roadmap (e.g., to comply with HIPAA, HITECH regulations).
Development of IoMT software products
What we do:
- Conceptualize IoMT software based on high-level or detailed requirements.
- Create a comprehensive feature list of healthcare IoT software.
- Plan IoMT software architecture with a focus on flexibility and scalability.
- Develop the MVP of the IoMT system with priority features in 3-6 months and roll out other functionality upon the agreed schedule.
- Ensure IoMT software compliance with required regulations (HIPAA, HITECH, etc.).
- Support and maintain software (if required).
About ScienceSoft
Established in 1989, ScienceSoft is an international IT consulting and software development vendor headquartered in McKinney, Texas, US. Being ISO 13485 and ISO 27001 certified, we assist healthcare organizations and software product companies in designing and developing high-quality medical IoT software.