Healthcare Sector is under immense stress due to increased costs, reduced utilization and regulatory restrictions. Due to the COVID-19 pandemic, regular patient footfalls into the hospitals are impacted. These changing dynamics are compelling Healthcare delivery organizations to look for newer delivery models.
To support the Hospitals achieve these objectives, NASSCOM CoE is organizing Healthcare Innovation Challenge (HIC), which is focused on creating a competitive edge & operational excellence for the Hospitals by enabling Collaborative & Frugal Innovation. Healthcare Innovation Challenge is meant for Hospitals so that they may nominate Use Cases relevant to them, which will be followed by curation & evaluation of Technology led Innovative solutions and enable their deployment to address the nominated Use Cases.
The key objectives of Healthcare Innovation Challenge (HIC) are:
Healthcare Innovation Challenge was officially launched on 18th December, 2020 by
18th Dec, 2020
Inauguration
31th Jan, 2021
Application Close
12th March, 2021
Jury Round Complete
19th March, 2021
Demo Day
Hospitals starts POC
UseCase | Use Case description | Platform | Integration |
---|---|---|---|
USE CASE 1: OUT-PATIENT (OPD) CARE AUTOMATION |
A Solution that has the below given capabilities (please note that different hospitals may ask for subset of the capabilities):
|
Patient facing Native mobile/Web application |
The solution has to integrate with the Hospitals HIS system HIS being used is ICT Health may be Hinai or some other system developed for the hospital. Integration support will be available. With Hikvision’s ANPR based Parking management system, to:
|
USE CASE 2: IN-PATIENT (IPD) CARE AUTOMATION |
Patient room solution (combination of software & hardware/IoT device) which should take care of the complete nursing care & patients requests and having the below-mentioned capabilities:
|
Android based Mobile app for Nurses, Android based Desktop / Tablet dashboard for Nursing Station & Touch panel on Patient bedside. |
The solution should be able to integrate With the Wipro On-premises HIS system, to:
With Billing system, to:
With Medical equipment via IoT devices, to:
|
USE CASE 3: PRESCRIPTION DIGITALIZATION |
The Hospital has doctor Application, which is having the in-patient details. The Handwriting recognition solution should allow the doctor to scribble on his/her tablet, and convert it to text. The solution should be able to integrate with Srishti PARAS HMIS and signed handwritten notes should be published to the HIS, to be able to do an accuracy audit. The solution should have Machine Learning based algorithm that can increase its recognition accuracy as the doctor does manual edit & review. The hospital has previously worked with a solution provider having handwriting recognition capabilities but it necessitated the use of A4 size sheet with expensive digital pens, which were prone to getting misplaced, which made the solution unviable. Alternatively, the solution should allow the Doctor to enter voice note via the existing Doctor Application, which should be converted to text. The Voice file along with the text note should be published to the HIS. The solution should have Machine Learning based algorithm that is able to train on the doctor voice, based on manual edit &review |
||
USE CASE 4: DIGITIZING PATHOLOGY SLIDES |
Digitizing Histopathology slides for long for life time storage and creating datasets for AI based diagnosis. There is no slide scanner currently deployed and solution provider needs to make the suggestions for required hardware. End-to-end low cost solution is needed. |
||
USE CASE 5: INTEGRATION OF DIAGNOSTIC EQUIPMENT WITH EMR |
The medical equipment used for diagnosis, investigation or treatment are mostly standalone. Data from these equipment are important and currently recorded manually or by screen capturing tools and then populated in the EMR. There is a need for easy integration of these diagnostic devices / equipment with the electronic medical records by developing appropriate interfaces / platform that mediates the software application with the devices and captures the output from the devices after investigation or treatment into application seamlessly. All the results and images will be stored as part of the EMR for referring in subsequent visits of the patients. The equipment have various types of connectivity protocols and produce different forms of outputs. |
||
USE CASE 6: AI BASED TOOL FOR RESPIRATORY SYNDROME DIAGNOSIS | The features of infected lungs and hearts seen on medical images can help assess disease severity, predict response to treatment, and improve patient outcomes. However, a major challenge is to rapidly and accurately identify these signatures and evaluate this information in combination with many other clinical symptoms and tests. There is a need to deploy an AI based assisted tool which can differentiate the respiratory disorders like flu, pulmonary and other lung disorders to screen the patient based on radiology images like Chest X-ray, CT scan etc. This will allow the quick intervention of therapy as the symptoms for these disorders are all similar towards its severity. |