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EHR, mHealth, Telemedicine, ICD-10, Meaningful Use and the overall Healthcare front - A KMG Initiative



The healthcare industry is undergoing a significant transformation. From placing greater reliance on bots to unlocking the value of data, healthcare providers foresee a tremendous amount of work to do.

Technology encompasses a major role in the healthcare lifecycle, including diagnosis of disease, continuous monitoring and subsequent treatments. Talking about digital health, a lot of questions persist – are hospitals and other healthcare organizations prepared to deploy digital health solutions effectively? According to a recent survey, about 59 per cent healthcare organizations say that either they don’t have a digital health strategy or it’s has become obsolete.

Technology in Healthcare

Healthcare experts believe digital technologies will allow providers to help patients manage chronic conditions. Technology will reshape healthcare via medication management, imaging analysis, AI-assisted diagnostics and precision medicine. While a lot of healthcare organizations value in virtual technologies to enable communications with patients, few plans to adopt video consultations or remote monitoring.

Technology in healthcare will help providers improve the patient experience and make patients more responsible for their own health. This will also reduce the administrative burden, so doctors could have more face time with their patients.

Roadblocks in Technology

1. Unstructured Data

Healthcare data is growing more complex daily. It comes from pharmacies, lab and imaging results; besides data more traditionally found in physicians’ offices, hospitals and public clinics. Add in it are data from wearables and mobile health apps, and it’s clear that the data collected per patient is enormous. It is structured and unstructured, so it’s hard to use for data analytics.

With the large volume of data, there is a massive loss of data at the backend. All of this can be addressed with technological advancements.

2. Interoperability

Healthcare information is fragmented and not structured. When doing analytics, this is messy. It can be difficult for the analytics team to handle different section headers (in medical records) that all mean ‘medication’ or ‘health history’; similarly, abbreviations and misspellings.

NLP (Natural Language Processing) operating system can be used to overcome complex language issues in medical records and machine learning to create a “smart system”. NLP is a terminology server that tracks different usage in medical terms. This provides healthcare experts with an unambiguous, complete history of a patient’s visit.

In a Nutshell

If care providers use the right technology and process the data at the point of care, healthcare industry won’t accumulate millions of medical notes daily. Instead, physicians will have all the data with them in a structured form and can inform the patients about their condition, before it gets worsens.

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