Someone is in an accident and is being rushed to the nearest hospital. Seconds determine the difference between life and death. Arriving at the hospital, the patient’s emergency contact in­forms the hospital staff that the patient has mul­tiple life-threatening allergies. The staff quickly access their medical records, change their plan of approach and save the patient’s life. This is one of many scenarios where storage and management of health-related data becomes indispensable and even lifesaving.

The first instances of medical records date as far back as 1600 BC to the ancient Egyptians, Ro­mans, and Greeks that used everything from pa­pyrus, clay tablets, and parchment paper to store medical records. This indicates an awareness about the need for health records even in the early civi­lizations. However, it would take until the 1900s for modern-day paper medical records to become commonplace in the hospital setting. Unsurpris­ingly, their use faced several challenges including but not limited to lack of reproducibility – only one copy was available, the potential for miscom­munication, and difficulty in its storage, sharing, and maintenance.

In the years following the 1970s, the advent of technology – computers, floppy disks, hard drives, and eventually the internet, enabled electronic health records (EHRs) to become an asset medical professionals could not overlook. Like any large change, the transition from paper was not entirely smooth. The reluctance of physicians, associated costs, and limit­ed storage capacities of computers meant that EHRs were mostly used in academic institutions for medical research purposes. But as technology improved, EHRs were soon adopted into medical practices worldwide.

Undoubtedly, there is a world of difference be­tween the EHRs of the 1970s and the ones today. Back then, EHRs were used by database manage­ment systems to only track hospital billing and scheduling. Physicians had limited scope to record data related to drug prescriptions, allergens, and related fields. Nowadays, EHRs are more compre­hensive and include entries about overall physical and mental health and well-being. Such EHRs are also sometimes referred to as Personal Health Re­cords or PHRs. They may also contain nuanced details like major life changes, such as moving cit­ies, that could impact a patient’s health status.

Widespread support for EHRs came in 1992 when the health arm of the National Academy of Sciences, the Institute of Medicine, urged that re­cords no longer be paper based. Initially, as with any change, EHRs were first used in conjunction with paper records. This posed a new set of chal­lenges as it led to inconsistencies that in some cas­es, did more harm than good. That being said, it was increasingly evident that EHRs made sharing critical patient information to healthcare profes­sionals easier, quicker, and more reliable than ever before, provided they had access to the internet. This cre­ated more avenues to make informed clinical decisions regarding diagnoses and treatments.

As technology over the next two decades became more accessible and cheaper, so did the use of EHRs. However, its implementation led to the use of third-party applications that called for regulations owing to concerns over data privacy and security. In 1992, a non-profit, ac­credited organization named Health Level Seven Inter­national, developed a set of international standards for the use and storage of medical data, aptly named Health Level 7 (HL7). It was later enhanced and expanded to include data from a range of medical devices such as bed­side monitors, infusion pumps, and electrocardiograms along with laboratory and other supporting results. The need for standardized semantics eventually gave rise to the Universal Medical Language System (UMLS).

In the early 2000s, cloud-based services started to gar­ner attention as Google, IBM, and several universities began using this system for data storage. This method was implemented soon after into the healthcare system as uploading, sharing, and re­trieving data was simple, cost-ef­fective, and solved concerns over disk-space. This was particularly a boon for specializations like radiation oncology that heavily relied on clinical data from different departments to create informed treatment plans. However, this system was not without drawbacks as it again highlighted issues with data privacy, cy­ber security, and reliability. The possibility of data tampering, manipulation, and purposeful omission was alarming and needed to be addressed.

In the current era of big data and, with the devel­opment of artificial intelligence (AI), machine learn­ing (ML), and the Internet of Things (IoT), tech­niques such as blockchain technology have proven helpful. Blockchain technology, as its name implies, chains together data points as they enter the system creating something similar to a list of items. These chains in turn form blocks of data. In essence, block­chain acts like a digital ledger that tracks changes within a shared database that can be accessed by multiple parties. In this way, blockchains decentral­ize the medical data, making it tamper-proof and extremely reliable. Blockchain technology was first de­veloped over three decades ago as a way to timestamp documents. Think of blockchain like a shared Google Doc, invited parties can make changes to it, but everyone else can see what the changes are, when they were made, and who made them. The difference lies, however, in the fact that once a transaction is made in the blockchain, it cannot be changed. This technology would go mostly unnoticed until the financial crisis of 2008 where it saw a resurgence for unrelated reasons. Nevertheless, this reviv­al proved immensely beneficial to the healthcare industry as it addressed security concerns that were impeding the widespread use of cloud-based health data.

Clinical outcomes using a combination of AI, ML, IoT, and blockchain technology need to be systematically studied. Their limitless potential in enhancing data ex­change between medical facilities and data processing enables health providers to arrive at better and more informed decisions on patient care. The development of 5G wireless technology has now enabled the Internet of Things (IoT) to connect every device and person via the internet at much fast­er speeds. During the pan­demic, virtual consultations became commonplace, and day-to-day healthcare was delivered with little to no physical human interaction. This highlighted the true potential of technology to make healthcare more accessible and efficient. Personalized med­icine holds a promising future with the availability of real-time data from wearable devices and sensors. The IoT can collect data that can be stored and retrieved through blockchains and eventually processed by machine learning and deep learning algorithms to derive mean­ing from the collected data. Thus, the juxtapo­sition of these emerging technologies holds the unprecedented potential to significantly impact and improve healthcare as we know it.

The Internet of Things (IoT) is a term used to de­scribe an electronic ecosystem where every person and every device (considered as an ‘object’ or ‘thing’), is inter-connected via a wireless network or the internet.


References:

  1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5171496/
  2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517570/
  3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078068/
  4. https://www.dataversity.net/brief-history-cloud-computing/
  5. https://www.jmir.org/2021/11/e19846/
  6. https://www.healtheuropa.eu/cloud-based-services-storing-health-data-in-the-cloud/93053
  7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8555946/
  8. https://www.frontiersin.org/articles/10.3389/fbloc.2021.732112/full
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