We’ve built and deployed several applications for Healthcare, both on-premise and on cloud. We understand compliances well, and all of our applications are HIPAA-compliant. Our application developers work in sprints, and understand Agile and Scrum processes as well as they know their tech. Besides, we leverage deep Healthcare experience, having built a PaaS of our own from scratch, as well as a comprehensive e-procurement platform. With our combined tech know-how and domain leadership, application development in the Healthcare space is second nature to us.
We leverage deep domain and tech experience, having successfully built, tested and launched several mobile applications for the Healthcare sector. Aside from building applications from scratch, we also have a range of starter packs that you can use to get up and running quickly. These solutions range from a simple mobile-compliant patient portal, to an application for remote video visits (built on Sinch).
If there’s one industry we really get, it’s Healthcare. We’ve spent years building products for clients and rolling out products of our own, so it’s only natural that we think of ourselves as experts in the space.
We understand compliances well, and all of our applications are HIPAA-compliant. Our application developers work in sprints, and understand Agile and Scrum processes as well as they know their tech.
We’ve built and deployed several applications for Healthcare, both on-premise and on cloud. Besides, we leverage deep Healthcare experience, having built a PaaS of our own from scratch, as well as a comprehensive e-procurement platform.
We’ve successfully built, tested and launched several mobile applications for the Healthcare sector. Aside from building applications from scratch, we have a range of starter packs that you can use to get up and running quickly.
We have a high-pedigree team of data scientists – Ph.Ds and top-tier university graduates, headed by a Stanford alum. We solve some very interesting problems in the Healthcare space using Machine Learning, Deep Learning and other techniques.
We have an Application Development and Test Lab where QA is the primary focus. We implement a BA- QA model for Healthcare – Business Analysis to ensure sound operations, and QA to ensure performance.
We have a modular platform built using the best of breed technology components to quickly deploy data transformation-logical components and data science models, with CI/CD in mind.
In our 10-plus years of experience working with Healthcare organizations, we’ve built a multitude of applications for delighted clients. Here are some of them.
It is a growing desire for patients to be able to understand their health conditions, diagnosis and prognosis. Practitioners need to use very technical jargons and domain specific vocabulary to ensure preciseness. This makes the documentation opaque and very difficult to understand for the patients. We created a dictionary of medical jargons and abbreviations for specific domains in healthcare leveraging existing documentation. Parsed the clinical narratives, and used NLP to ensure the grammatical correctness of the simplified narrative.
Many medical events are buried in the notes made by the doctors in multiple documents and many of them have only partial descriptions. We identified medically significant events like ‘infections’, ‘antibiotics’, ‘surgery’, ‘x-ray’, ‘lab test’ etc. Used NLP to arrive at the occurrence time of significant events by identifying temporal expressions like ‘today’, ‘two weeks ago’ etc. extracted from the multiple
documents and correlating them with the date of document creation. We then stored this data in a structured repository for easy retrieval to construct the time line graph of the significant clinical events.
In USA, hospitals are liable for penalties if the 30 day re-admission rate crosses the threshold for the particular clinical condition stipulated under the Affordable Healthcare act. We analyzed past patient history of readmissions. Then, we clustered patients based on clinical, social and behavioral factors like clinical conditions age, gender, associated clinical conditions, weight, life style, ethnicity, economic indicators, geo etc. With this data, we derived a model based on the training set to predict the risk of readmission for a patient. Finally, we tested the model on the testing data set and fine tune for accuracy and ran it across the new patients to predict the readmission risk.
At Ideas2IT, we learn every day. From product engineering to data science, from blockchain to chatbots, our experts discuss driving forces at the intersection of tech and business. We look at business through the lens of technology, and break down how cutting-edge tech will alter the way companies in various industries operate. These are some of our learnings from working with the best in the Healthcare business.
HIPAA – stands for Health Insurance Portability and Accountability Act. HIPAA laws were enacted in 1996 years before the advent of iOS and Android devices. Smartphones have hitherto brought in a flood of apps in the Healthcare industry.
Until recently, when patients wanted illnesses treated, or had specific complaints that they wanted diagnosed, they went to see a doctor. They were then charged a consultation fee by the doctor, or had a third-party insurance cover the cost partially or completely. Now, we have a new option - Telemedicine.
Apple seems pretty focused on tapping into the immense need of the industry on supporting mobile healthcare. As an application developer or provider, there has never been a better time to dive into mobile healthcare and trust us, we have been in this game for quite a while now.
Let us know which of our services you’re interested in, and our team will get back to you shortly!
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