Satish Pala, CTO-Indium Software
- How do Big Data and AI help hospitals handle complaints better?
Being a fast-paced sector, hospitals often miss out on complaints, lose records of diagnosis, and have increased wait times. In addition to this, storing, tracking and maintenance of enormous data is a challenge that majorly results in poor complaint redressal. Automation through AI, ML and Data Analytics enables better complaint management and saves time.
Automation can be primarily through complaint routing and the use of chatbots. This helps in easing the process and information management. In automation through complaint routing, an IVR user query is analysed and checked with the Information repositories in the hospitals and then routed to the intended department automatically. To make this more efficient, AI use cases such as Smart Search, Entity Generation and Classification can be used. Besides, Chatbots are interactive and smart platforms that can be deployed in mobile applications as well as web portals.
- What are some of the ways in which new age technologies help to speed up the processes and enhance operational efficiency in the healthcare sector?
To speed up the processes and better enhance operational efficiency, hospitals need to adopt technology in three key areas. Firstly, paperwork needs to be replaced by digital data entry, storage and retrieval. This is where EHR-Electronic Health Records come into the picture, Other methods include electronic prescription, call recordings and integrating with healthcare tech companies for external data.
The second area of focus is ensuring operational efficiencies using technologies such as Big Data, Data Visualisation and Artificial Intelligence. Building a platform to measure KPI and enhance better decision making can give an overall insight into the overall efficiency of the hospitals. For instance, Operational Equipment Efficiency (OEE) KPIs such as quality, availability and productivity can be determined using the new-age technologies.
The third and most important area is staffing and the biggest challenge for any hospital is to maintain the staff ratio. Often, hospitals face issues because of over-staffing and under-staffing. This may affect the overall operations as well as the impact the cost and patient care. Predictive analytics techniques can be used to predict the staff requirement based on patterns and history.
- Can you brief us on the role of Text Analytics in the Healthcare industry?
The Healthcare industry stands as one of the top data generating industries. The data is structured or unstructured, manual, and sometimes digitised or acquired data sets.
Text analytics plays a vital role in managing these data. For instance, Text Analytics can be used to increase the effectiveness of treatment by analysing various treatment outcomes and patterns. Another way is to make informed decisions thanks to better profiling of patients by collecting various sorts of data and having a patient 360-degree view. It is equally important to increase operational efficiencies by digitization and mitigate fraud by identifying abnormal patterns in healthcare documentation.
Additionally, the redaction feature helps comply with data privacy laws such as general data protection regulation (GDPR), health insurance portability and accountability act (HIPAA) and FDA compliances.
- How can the pharma industry meet regulative commitments using big data and AI?
The Pharma industry has been relatively slow to embrace digitalisation, however, covid-19 played a catalyst role. Since then there is a higher adoption across analytics, connectivity, Big data, and integrated automation technologies.
Big data and AI could facilitate the pharma firms to fulfil regulatory commitments like HIPAA, GDPR & Food and Drug Administration compliance in multiple ways. These technologies enable data Storage, High availability, Easy and Secure Access to data that is needed to fulfil regulatory requirements, ensures continuous and real-time monitoring of the drug manufacturing processes and product feedback to conform to compliance. additionally, it allows claim referencing to trial reports through AI.
The compliance reviews and audits require close checks on safety and efficacy claims lining back to the initial clinical test. AI models can be trained to identify safety and effectiveness claims and suggest links to the relevant sections of the connected trial report. This process is usually tedious and takes a long time.
- Share with us some of the services/specialisation indium offers, in specific, to the healthcare segment
Indium Software with its suite of services in digital engineering incorporating application engineering, data & analytics, cloud engineering, digital assurance, DevOps and automation has contributed to the care and Life Sciences industry in various ways like building healthcare applications rapidly using low code platforms and applications to combat Covid-impacts.
A telehealth platform was designed for a healthcare consumer to deal with the Covid impact on physical consultations. This platform includes a Mobile & web application with options, like Hospital Registrations, data Export, Audio/Video streaming, conferencing etc.
Another application was created using a low code platform for a pharma company, to manage the lifecycle of a product from plan to launch. There was a great demand for this application to be designed, to increase the efficiency of the pharma product launch process.
