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Big Data in Healthcare Interoperability: All You Need to Know

Author: Martin Ostrovsky
by Martin Ostrovsky
Posted: Jan 17, 2022
interoperability hea

What is Interoperability in Healthcare?

Interoperability in healthcare is the ability for different healthcare information technology (HIT) systems to access, exchange, interpret, integrate, and use data cohesively. Because the existing software in the industry is developed in silos, it leads to disconnected communications when paired. Integrations do work to an extent but interoperability offers a holistic view of patients despite the different technologies used across hospitals, medical practitioners, pharmacies, etc.

Why Does Healthcare Interoperability Matter?

It matters for the sake of delivering much-needed value-based care that supports enhanced patient care and critical healthcare outcomes. Interoperability in healthcare helps to access and share clinical data such as a patient’s lab results or treatment plan. Interoperability ensures that patient data is secure even as it is accessed across several systems, irrespective of the technology or the operating system used. Also importantly, interoperability can lead to a better understanding of a patients’ symptoms because of integrated patient data and help in developing their treatment plan in a more timely and efficient manner.

Interoperability in healthcare relies on health information exchange networks (HIE) that are purposefully designed to assure secure transferring of healthcare information. Healthcare utilizes HIE along with electronic health records (EHR) meant to store all healthcare data digitally, and so supports in maintaining patient data in the best possible way.

How Does Interoperability In Healthcare Support Patients And Medical Professionals?

Both, medical professionals and patients, benefit a great deal from interoperability in healthcare.

  • Patients

  1. Secured sensitive data protection is amongst the most prominent advantages of healthcare interoperability because it ensures the protection of every detail of a patient record within the healthcare system. Since these machine learning platforms can be cloud-based or on-prem behind your firewall, data security ensures there is no data leak or misuse.

  2. Improved care of the patient when correct data is available at the right time. Better decisions can be expected with all critical patient information accessible. Since the interoperability manages data from start to end - patients get improved care based on tangible results and diagnosis. Further, since patient information is already within the system, the patient need not go through the cumbersome process of filling out repeat details upon subsequent visits.

  • Medical Professionals

  1. There is accelerated productivity amongst healthcare professionals with healthcare interoperability. They get to invest more time in the patients rather than managing their reports. When medical professionals seamlessly access data from different systems securely, they perform better and can share inputs with their peers and ask for reviews and discussions.

  2. Minimized errors are found in patients’ data with interoperability because it makes storing information easier and simpler. Not only does this make things faster but also reduces the risk of incorrect diagnosis, and additional costs to the hospital due to delays in treatment because of inaccurate medical advice. This also helps in a hospital’s reputation management.

Main Challenges Of Data Interoperability In Healthcare

There could be a few of them but most prominently-

  1. Need for a well-coordinated strategy

A well-thought-out plan and strategy are important to make interoperability truly successful. Also needed is coordination amongst the AI systems, healthcare organizations, and medical professionals, where training is frequent and an openness to new technology important.

  1. Customized solutions

With every healthcare body having highly specialized requirements, it is a challenge to develop a one-size-fits-all strategy that works seamlessly for all organizations.

  1. Budgeting Issues

Machine learning-based automated healthcare platforms can be expensive and not all organizations can afford them as most such platforms are priced seat-based and meant for large enterprises. Customizations can be an additional cost to procuring these systems.

How Does Healthcare Benefit From Data Interoperability?

Healthcare interoperability ensures timely and efficient hospital record storing/delivery, which has been a concern over the years. It improves the rate of accurate diagnosis and treatments and enables the management of the patient history in a more efficient manner. Not only does it help in patient care but also in helping with staff efficiency, productivity, and workload management. Other benefits include:

  1. Easily locating the patient’s data, without delays or interruptions. Data is accessible to medical professionals automatically.

  2. Seamless access to all critical information of every patient sorted and categorized.

  3. Higher productivity due to seamless management of patient data and operations.

  4. Better diagnosis and treatment plans based on historic patient data, medicine dosages, procedure history, allergies, medical reactions, etc.

In What Cases Are Third-Party Healthcare Software Development Providers Useful?

Third-party healthcare software development providers are particularly helpful in cases where the healthcare organization is not able to automate its processes or serve patients with modern solutions. A third-party vendor supports such organizations with the right set of AI-enabled automation for a number of critical functions such as:

  • Up-to-date medical records

  • Video consultations

  • Complete hospital inventory management

  • Quick lab tests and results management

  • Doctor appointments

  • Automated operational management

  • Data security and secure communication

  • Sentiment analysis of voice of patient data for increased patient care as Repustate has done for multiple customers in the healthcare sector.

Ending Notes

Big data in healthcare is complicated to handle and process. Repustate and many other AI-based companies helped healthcare companies and decision-makers analyze this data and transform it into valuable information through platforms powered by artificial intelligence. This is a necessity as growing demands on the medical industry explode as the world becomes smaller and more connected, and as can be seen with the Covid19 pandemic.

AI-based healthcare data management and interoperability can lead to vital insights on how to handle communicable diseases, exchange important R&D developments, as well as better operational management in crisis and healthcare strategies. With an increase in the acceptance of AI technologies as well as government policies and tax regulations that favour innovation through machine learning, healthcare big data can be used for better patient care the world over.

About the Author

Martin Ostrovsky is the founder and CEO of Repustate. He is passionate about AI, ML, and NLP. He sets the strategy, roadmap, and feature definition for Repustate’s Global Text Analytics API, Sentiment Analysis and Named Entity Recognition.

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Author: Martin Ostrovsky

Martin Ostrovsky

Member since: Jan 14, 2022
Published articles: 2

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