VitalWare

Medical Code Reviewer

Product Background

The app provides access to current medical coding information, making the once laborious code review process intuitive and faster. The app is accessible for any hospital personnel who need access to coding, billing, and regulatory information.

Challenge

The product’s front end was built on an early version of Ext JS and needed significant rework. The client had a contract with Sencha and was satisfied with the framework performance and various enterprise tools it provided. Afterward, they decided to stick to Ext JS and upgrade Ext JS 4 to Ext JS 7. In short, the main problem turned out to be a global lack of available developers with solid experience using Ext JS.

Solution

At Glorium, we ally with the best developers offering our clients a diverse range of skills and technologies. As our services adhere to enterprise needs, our in-house devs team is trained in Ext JS to fill in the gaps. This is what allowed us to pick out four employees to extend the client’s team. The newly formed squad included a database developer, two Ext JS developers, and a manual QA.

Results

Our dedicated Ext JS crew rewrote the app following two years of close cooperation with the client’s team. Such changes led to:

  • better app performance
  • revamped UX/UI
  • app resilience and adaptability for enterprise workflow
  • support of up-to-date technologies

The client was more than satisfied with our team’s efficiency and value for money that they couldn’t find onshore.

TECH STACK:

  • FRONT-END:
    Sencha Ext.JS 7.x
  • BACK-END:
    .Net
  • DB:
    MS SQL

Dextro

Data-scraping tool for interpreting physicians and healthcare professionals

Product Background

Workload automation for day-to-day routine activities for interpreting physicians is difficult without the assistance of Robotic Process Automation (RPA). Such software decreases the need for manual re-input of the same data across different applications, thus increasing speed and productivity for reading the studies.

To fill in the gaps, our client commissioned us to build and integrate a data-scrapping solution to help radiologists acquire total visibility across different PACS systems. As a result, specialists receive one unified worklist with proper task prioritization retrieved from different exam providers.

Challenge

Our main task was to develop a mechanism that minimizes the time doctors spend on repetitive tasks. For example, searching through different PACS systems/worklists to find a required study or manually organizing studies existing in different applications to comply with overall priority across them. For that purpose, we had to enhance the current doctor’s workflow with RPA which emulates human actions by interacting with the digital systems and scrapping the data. Eventually, we created robots that were ready to merge different data and push that into a unified worklist.

Solution

We created a set of robots to leverage the existing infrastructure without disrupting the related systems. In short, it uses the interface to capture and manipulate data just like humans do; however, instead of taking breaks to eat and sleep, it works around the clock, 24/7.

Robots can:

  • log into accounts with given credentials
  • find required studies
  • extract content from required worklists
  • refresh deliverables after each session
  • control data amendments in a sourcing system
  • operate fully in the background

Results

Our team has built data-scraping robots, suitable for multiple systems, that can automate repetitive and routine tasks. This software was developed from scratch and seamlessly integrated into radiologist-related workflows.

Finally, with the help of Dextro, doctors are free from spending countless hours and resources interpreting worklists thanks to this accurate and efficient automation technology.

TECH STACK:

  • FRONT-END:
    .Net Core

  • BACK-END:
    .Net Core
    WinAppDriver Selenium Web Driver
    DB:
    MS SQL

  • CLOUD:
    AWS

ITR Software

Patient Flow and Bed Management Solution

Product Background

The performance of many hospital departments depends on the way beds are managed across wards. Our client has developed a web app that allows a department to easily handle, manage and reorganize bed requests. The system increases usage efficiency of beds and minimizes any potential issues between patients who share the same hospital room. 

Challenge

In order to deliver better care and empower visually-impaired staff with automated hospital bed allocation, our client decided to overhaul and rewrite the app’s entire front-end. 

As the existing front was outdated and not user-friendly, our mission included:

  • Creating a brand new UX/UI design;
  • Updating user-effectiveness & job satisfaction;
  • Adjusting the operational efficiency;
  • Enhancing the patient journey;
  • Enhancing the accessibility design (contrast mode, font size, light & dark color scheme).

Solution

In order to gain a competitive edge regarding bed management software, our team completed: 

  • An investigation of national regulations about bed assignment;
  • Detailed business analysis;
  • New responsive design with an intuitive interface; 
  • Mock-ups with user-flow & multiple screens; 
  • Customizable user dashboards; 
  • Calendar for scheduling requests;
  • Advanced search engine for filtering & sharing personal lists.

The software covers all necessary information about beds: whether they are dirty or clean; which rooms they are placed in; and patient-related information, such as address, relatives, insurance, etc.

Results

The new intuitive interface guides the user all the way from the patient’s admission to a hospital, until final discharge. These changes boosted staff efficiency by saving time and allowing management to meet hospital performance targets.

With a graphical representation of wards and a list of the beds, it becomes easy for the bed management staff to carry out the allocation process. Information is updated in real-time, allowing a team to omit the manual counting process and improve turnover rates. Disabled users also feel more comfortable with the accessibility design when enhancing patient coordination, contributing to the hospital’s sound operability. 

TECH STACK:

  • FRONT-END:
    Angular
  •  

Project Ipsilon

App for cognitive testing and training

Product Background

MCI (mild cognitive impairment) and signs of early dementia are hard to detect; however, studies show that playing the piano has the ability to highlight even the slightest cognitive abnormalities.

Playing the piano involves multiple sensory processing, comprehension, quasi-simultaneous decision-making, and action execution. In short, it is a sure-fire way to analyze and evaluate brain functions and train minds. In order to test and prevent cognitive disorders, our client (a musician) came up with the idea of building a piano emulator from scratch.

Challenge

In order to build a piano emulator app that could detect and calculate the probability of developing cognitive abnormalities associated with MCI and early-stage dementia, the emulator had to be:

  • Fast and accurate, with gamified cognitive checkups that fit the clinical workflow;
  • Suitable for assessing pre-clinical, early dementia and MCI;
  • Operable by a non-specialist.

Solution

The app was released with the following features:

  • Visuospatial and motor encoding;
  • Time-stamped finger responses;
  • Audio cues;
  • Integrated the tool for different PACS archives/VNAs compatibility;
  • An algorithm that collects user-response and analyzes data;
  • Integrations with EEG and eye-tracking;
  • Recording history;
  • Data export;
  • GDPR and HIPAA compliance.

Results

This app evaluates executive functions, such as inhibition control, attention, multisensory memories, and various brain-region activities. In this way, the software acts as a dementia prevention tool, contributing to remote care for cognitive monitoring. As for now, our client is looking for opportunities to collaborate with Philips as their headsets could enhance app performance and function.

This software is expected to launch as a medical device in the EU at any moment.

TECH STACK:

  • FRONT-END:
    Angular
  •  

  • BACK-END:
    .Net


  • CLOUD:
    AWS

PACS Harmony

Radiology Workflow Management Tool

Product Background

The product allows hospitals to automate the workload and distribution of studies for interpreting radiologists. To meet the SLA time frames, the app’s AI engine defines exam priorities, locates qualified doctors (based on their preferences), and assigns a specific exam to a particular expert. The software balances the workload so that all radiologists receive the correct amount of work they are committed to cover.

Challenge

The main difficulties in the previous version of the app, which became the source of customer disappointment, were poor operational performance combined with a confusing UI. Medium to large hospitals with a significant study turnover rate reported that slow app responsiveness and overall balancing inefficiency were affecting the number of medical exams reviewed. Following some fruitless attempts with other teams to redesign the software, the client finally turned to us to help improve the overall performance right away.

To improve impending faults and to preserve existing customers, we set out to:

  • Find and fix the reasons linked to the app’s slow performance;
  • If needed – change healthcare app architecture to raise performance;
  • Verify the studies distribution algorithm and implement the desired business-logic elements;
  • Significantly decrease the capacity of the infrastructure required to use the application;
  • Improve app UI to make it more responsive and user-friendly.

After putting out the fire, we directed the next flow to complex tasks.

  • To build an integration with the majority of existing dictation systems and image viewers;
  • To gain a competitive edge and remain independent from existing market leaders (Philips, Agfa, etc.);
  • To increase patient satisfaction and shorten the time of studies’ review and finalization.

Solution

After the execution of highly detailed performance tests, our developers reviewed all API calls and database requests and challenged every query’s adequacy.
As a result, we tightened data retrieval and increased the volume of acquired data every step of the way. A large portion of data was cached in order to speed up access to repeatedly queried but rarely changing medical data. Afterward, we implemented the composite pattern approach to enable complicated and nested filters to be compounded, allowing for the instant extraction of data.

We also:

  • Crafted UI / UX for both doctors and hospital admin requirements;
  • Completed integration with multiple image viewers/dictation systems;
  • Added a flexible and robust load balancing mechanism for real-time distribution;
  • Integrated the tool for different PACS archives/VNAs compatibility;
  • Created a mechanism for scheduling systems interoperability;
  • Created an internal audit mechanism to control data access (for HIPAA compliance);
  • Developed a reporting tool for physician performance tracking.

Results

After initial months of working around the clock, the AI engine’s performance and API back-end responsiveness has improved significantly. Presently, the initial infrastructure can efficiently support hospitals with up to 10 million studies per annum. Furthermore, the business-logic of studies distribution was challenged and fixed throughout. Together with UI updates, these achievements lowered the overall page responsiveness to less than one second. Our collaboration has lasted for over 2 years and continues successfully as of the time of writing of this case study, making it possible to polish the product with innovative and competitive features.

TECH STACK:

  • FRONT-END:
    ReactJS

  • BACK-END:
    .Net Core

    Net Framework
    RabbitMQ
  • DB:
    MS SQL

  • CLOUD:
    AWS

CAE Blue Phantom

Understanding ultrasound with CAE Blue Phantom. Mobile educational platform for future doctors.

Client Background

With the release of portable systems, ultrasound, which had once been limited to radiologists, was suddenly being used by a vast number of medical specialties from emergency medicine to anesthesiology. Today, Blue Phantom (acquired by CAE in 2012) is a major producer of the most realistic and durable anatomical task trainers available.

Challenge

CAE has been collaborating with us on other projects, so the company addressed us with a request to develop a new educational platform for ultrasound procedures training.

FEATURES REQUESTED:

  • To lay the virtual model on top of the physical (automatic physical model recognition)
  • To create an ability to train with your student partner and show the training steps results to an instructor
  • To develop an admin panel that manages organizations, users, training models, and training steps
  • To create a price durability calculator

Solution

The tech driver for this app is Augmented Reality (AR), which allows the virtual model to be laid on top of the physical. The model can then change size and switch between the skin and vessel layer.

MORE FEATURES IMPLEMENTED:

  • The ability to work with AR virtual models, rotate, change size and switch between the model layers (skin layer, vessels layer)
  • A way to recognize the real model and put the virtual model on top of it
  • A cross-platform mobile application for iOS and Android
  • An admin panel to manage users, organizations, and training process

Results

We’ve transformed the Client’s idea of building an educational platform into a fully functional app from scratch. The prototype was ready in half a year, and the product was later presented at The International Meeting on Simulation in Healthcare (IMSH) 2020 in USA. Our responsive software added value to the training process and allowed tutors to track the process remotely.

TECH STACK:

  • FRONT-END
    Xamarin
    Unity
    Angular

  • BACK-END
    .Net Core

  • DB
    MS SQL

  • CLOUD
    AWS

Biofeedback App

Mobile app for physiological monitoring and biofeedback.

Product Background

Our Client is the world’s leading biofeedback, neurofeedback, and psychophysiological instrument manufacturer. Their equipment monitors and records a variety of physiological and mechanical signals essential for treating stress-related disorders.

Challenge

The Client turned to us to adjust and extend a mobile application to help users optimize mental performance and achieve advanced self-regulation skills. For this purpose, software must be integrated with sensors for therapeutic applications such as biofeedback, neurofeedback, heart rate variability, and electromyography.
Reports, which play a vital role in the diagnostics, needed to be convenient and user-friendly.

Solution

To provide accurate and sensitive psychophysiological monitoring and biofeedback, we:

  • Built Android/iOS mobile applications integrated with hardware through BLE protocol;
  • Enabled specialized quick evaluation protocols;
  • Implemented advanced reports for all evaluations;
  • Developed a self-regulation screen with success points to engage a performer throughout the training.

Results

After 6 months of ongoing cooperation, the Client extended a psychophysiology training system functionality with mobile apps developed and integrated with hardware. They provide intuitive and understandable information that users can use to learn self-regulation.
Visible feedback promotes relaxation, helps expand the cardiovascular system’s resilience and flexibility, and practices self-regulation.

TECH STACK:

  • MOBILE:
    iOS
    Android SDK

  • BACK-END
    BLE connectivity

Teledentistry Solution

HD live video conferencing and intraoral camera integration for a teledentistry solution.

Product Background

Teledentristy is a broad category of solutions to provide and support dental care delivery, diagnosis, consultation, treatment, transfer of dental information, and education in the field.
Our Client has been operating a teledentistry platform enhanced with costly video streaming. They’ve just developed a new intraoral camera and decided to reimagine the streaming service, making it top-quality but affordable for care providers.

Challenge

The Client was seeking a way to embed a recently created hardware (intraoral camera) with the newest video-streaming tools making it available to use via desktop and mobile devices.

OUR GOALS WERE:

  • To provide uninterrupted, high-quality video conferencing and screen sharing
  • To support integration with the existing dental EHR system
  • To build a product on open-source frameworks
  • To allow multiple participants connecting the same conference

Solution

The stable cross-platform video streaming that allows dental surgery professionals’ collaboration is provided by:

  • WebRTC framework with routing via STUN/TURN servers
  • Bandwidth size and video quality management
  • Streaming support for cellular connections
  • Web and mobile apps.

Results

Our streaming solution stands on the pillars of HIPAA compliancy, EHR integration, and accessibility both from web and mobile. It allows meeting patients or other doctors virtually using live recordable videos, and offers practical evaluations from any location.
It easily incorporates into practice’s daily workflow to facilitate team communication, cover more patients, and store information for further reviews.

TECH STACK:

  • FRONT-END:
    React
    WebRTC
    Kotlin

  • BACK-END:
    .Net Framework
  •  
  • CLOUD:
    MS Azure

  • CONTAINERIZATION:
    Docker
  •  
  • DB:
    MS SQL

CAE ORION

CAE Orion app improves healthcare training providing the connection between mobile devices and training models’ firmware.

Client Background

CAE Healthcare is a division that develops medical simulation products, new equipment validation, medical device trials, educational content, and more. With their mannequin simulators, CAE offers targeted training to hospitals, medical schools, emergency response teams, military branches, nursing, and health programs.

Challenge

Considering our expertise in the Healthcare sector, we developed Orion mobile apps for connectivity to a range of CAE training models.

OUR GOALS WERE:

  • To create connectivity between mobile devices and training model firmware
  • To allow live-tracking of manipulations on the model by a student while an instructor is checking their progress
  • To have customized graphs with models’ parameters changing in real-time.

Solution

FEATURES iMPLEMENTED:

  • BLE connectivity with the firmware of mannequins
  • No-loss data package exchange for live-tracking
  • Cross-platform mobile applications for iOS, Android, Windows
  • Power BI customized graphs with results statistics of training models’ manipulations.

Results

Orion app is a responsive software solution that tracks education processes and showcases heart and lung disease treatment. It can be switched between practice and exam modes, empowering medical training and making coaching tangible.

TECH STACK:

  • MOBILE:
    Xamarin

  • FRONT-END:
    AngularJS

  • BACK-END:
    .NET
    Power BI