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Innowise developed a wound care app as part of the remote patient monitoring software to enhance healthcare delivery and patient management.
Our client is a leading entity in the healthcare domain, specializing in advanced digital care management solutions. Operating predominantly in the medical sector, the company’s services span over 4,000 facilities.
Detailed information about the client cannot be disclosed under the provisions of the NDA.
Wound assessment has always been challenging due to manual methods prone to human error. Inaccuracies in measuring wound dimensions, such as depth and color variations, often resulted in extended hospital stays for patients, placing a strain on healthcare resources.
As the need for accurate, remote wound monitoring grew, so did the demand for remote patient monitoring solutions. However, the progression toward healthcare digitization brought about its own set of challenges.
Current remote patient monitoring solutions, while aiming to enable remote monitoring, struggle with fragmented data storage and lack effective communication platforms. This hinders collaboration among doctors, slowing decisions and potentially compromising care. As technology advances, it must address these complexities to truly benefit wound care.
Recognizing these challenges, our client sought to improve the remote patient monitoring system to be implemented in clinics in order to:
Given the complexity and gravity of these challenges, our client leaned on Innowise, expecting a mobile remote patient monitoring software solution to assist doctors in wound care.
Our team created a digital wound care management tool with skin visualization and touchless 3D wound measurement through smartphone-ready software.
This wound care app harnesses the power of AI to gauge the complexity and potential severity of wounds, considering depth, coloration, and other parameters. This allows doctors to determine the most effective treatment strategy. The application functions as a central repository, safeguarding patient data, wound analysis, and medical observations on servers and individual devices.
Our team primarily focused on developing the mobile wound care app for doctors and patients as well as the machine learning implementation, while the client’s team handled the web version of the solution.
To enhance the wound assessment process for clinicians, we integrated the measurement tool within the iOS- and Android-based wound care app tailored for medical professionals.
When patients visit the clinic, doctors use the mobile device’s camera to document the wound. The app automatically identifies the wound’s contour, gauging its depth, dimensions, and providing detailed statistics on its positive or negative dynamics. This real-time information supports physicians in evaluating the treatment course and making timely adjustments if required.
Additionally, we introduced a version of the app for patients, enabling them to send scheduled photographs of their wounds to doctors remotely, making it easier to monitor the healing process without requiring constant physical appointments.
Furthermore, the wound care app is equipped with thermal imaging capabilities. With the integration of an auxiliary camera connected via Bluetooth, the app can discern skin temperatures, adding an extra layer of information to wound assessment.
Thanks to background synchronization, all the captured wound data is instantly available for review on the web platform, ensuring seamless integration between the mobile wound care app and web interface.
Understanding the diversity of wounds and the need for human judgment, we integrated a feature allowing doctors to also manually input data into the system. They can adjust and define colors, shades of the wound, and delineate different affected areas, providing a comprehensive visual mapping. This feature facilitates the inclusion of nuances that automated systems might overlook.
To foster collaboration among medical professionals, we incorporated a feature where doctors can append notes, classify wound types, and mark their criticality levels. This way, other attending physicians or medical staff can glean insights from previous observations and adjust care accordingly. Additionally, the wound care app facilitates the provision of treatment recommendations, analyzing skin injuries and allowing practitioners to share their expertise and suggested interventions.
Acknowledging the hierarchy and diverse responsibilities within a medical establishment, we implemented a two-tiered user role remote patient monitoring system: one at the organizational level and another at the individual level. When an institution creates an account, they can stipulate access levels. While some staff may only view or capture images, others, particularly doctors, can make edits based on their designated role permissions. This system safeguards patient data, ensuring only authorized personnel can make pertinent modifications, thereby upholding the integrity of the patient’s medical record.
On the doctor-side interface, there’s a straightforward option to ‘create a new process’ or to ‘confirm or decline’ a wound diagnosis. Once a wound is logged or confirmed, the analytical module of the remote patient monitoring system works in the background to evaluate the data about the healing progress.
Our team integrated AI-driven progress tracking into the wound care app. This allows for the determination of wound circumference, type, and evolution but also enabled a streamlined, point-of-care experience for clinicians. By utilizing convolutional neural networks and edge computing, we were able to facilitate rapid image recognition and processing.
For patients, this meant quicker feedback on wound conditions, reducing the anxiety of waiting and ensuring timely interventions. For clinicians, it enabled efficient bedside consultations, eliminating the need for transferring data between devices or referencing bulky machinery.
The wound care app maintains a continuous connection with the the AWS infrastructure, minimizing data redundancy and guaranteeing that all stakeholders have access to the most recent wound data from any authenticated device. Importantly, the AWS infrastructure is HIPAA-compliant, ensuring that patient data is handled with the utmost security and adherence to medical data protection standards.
Operating systems
iOS, Android
iOS
Swift Storyboard / XIB / Code programmed UI, UIKit, MVP, StateMachine, CoreData
Android
Kotlin, MVP, Clean Architecture, Multimodules, different Flavors, Single Activity Architecture, Google Services(Auth), Mockito
Machine Learning
Libraries
Databases
Room
Analytics
Web Server
Cloud
AWS
In collaboration with our client, we embarked on a structured and well-coordinated path to technological evolution. The project unfolded through the following phases:
Deployment and training: After rolling out the finalized remote patient monitoring software solution, a dedicated phase ensured medical professionals were adeptly trained to utilize the mobile solution with ease.
The introduction of our mobile wound care management solution brought about significant changes for both our client and clinics. These transformations were palpable across different levels of care:
After launching our solution, the wound care app demonstrated its success, with dozens of clinics now actively using it in their patient care routines. As we continue to receive feedback from both patients and medical professionals, our developers are currently focused on introducing new features based on the recommendations of the clinic’s clients.
33%
40%
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