The Electronic Health Record: Downside of Digitalization
The term “too much information” is often used when there is something that we don’t want to hear about a story that our overzealous friend is telling to us. It’s not what comes to mind when talking about one of the most daunting challenges that many people in the medical field deal with.
One of the things that seem to be rather overlooked when looking at healthcare is data. There’s so much of it that goes around, whether that’s patient records, doctor profiles, or new publications on the latest life saving operation/drugs. With all this information, things get extremely difficult to track, especially when dealing with such a large volume of people.
As much as the advent of technology has helped with keeping patient records, it also ends up creating its own problems. For example, many hospitals tend to keep information stored within their specific system in a particular way. Now if that information was to be sent to a different hospital, there’s no way of telling whether or not that information would be received the same way. Chances are that the system that received the information might not have been able to understand what was sent.
The transition to using electronic health records also has privacy and security concerns as well. Storing patient information electronically makes their susceptibility towards breaches and unauthorized access much higher. These breaches can lead to identity theft, fraud, and unauthorized access can lead to HIPAA violations as well as it can expose patient information to those who should not have access to it. Therefore, with the rise in using electronic records, hospitals and providers must also increase their cybersecurity protection.
Another major area of concern arises when looking at how this affects physicians' wellbeing. A breakdown of Dr. Wachter’s “The Digital Doctor” states that physician burnout rates are greater than 50%. In addition to this a report published by the American Medical Association (AMA) highlights that in 2021 burnout rates increased up to 63%.
The EHR has a stronghold on physician well being, but it also represents a shift in priority. Rather than totally focusing on the patient, their attention has been shifted towards feeding into an electronic database. Multiple accounts of this exist within Dr. Wachter’s book, with the most dramatic example being that of a 7 year old child who drew what her visit to the doctor’s office looked like: A person at a chair typing away as the patient was explaining something.
From “The Digital Doctor” by Dr. Robert M. Wachter
The EHR has proven its immense benefits, representing a paradigm shift in how healthcare systems work, how efficient they are, and how cost-effective it is. There’s no doubt that it’s a major advancement from physical records, but there still remain gaps that need to be connected in order to further enhance system’s both nationally and worldwide.
A viable solution that helps to address information overload is the use of Artificial Intelligence (AI) healthcare solutions. As defined by IBM, AI leverages computers and machines to mimic the problem-solving and decision making capabilities of the human mind. With the use of such technology in forms such as ChatGPT or Midjourney AI, it’s not very far-fetched to see how machine learning can be utilized in addressing information overflow.
Take a look at Innovaccer, a biotechnology startup that uses a unique AI driven platform called “HealthCloud”. It’s capable of taking massive amounts of disorganized data, learning from it, and form patterns that provide concise information that is respectively needed. Innovacer also provides a developer's tool kit, which allows for the user to get specific solutions based on what they need via an AI driven platform.
Let’s look at another company, Truveta. It’s a company that collects healthcare data and then analyzes this information for further application, with one of its first ones being applied to COVID-19 vaccination breakthrough infections. They believe in the most high quality and updated data, more specifically for research purposes.
Through their own unique platform making use of AI, they are able to normalize this data to be used by their respective clients. They also offer tools for their clients to use, or they can use their platform to access their real time data. Through the use of their system, they are able to get extremely diverse data sets, with it being used by AI and having it learn from it. It accelerates the process for healthcare workers to figure out what solutions work, saving time that can be used to provide a high quality level of care to patients.
Another major breakthrough in managing data overflow and security is the usage of Ethereum smart contracts in order to send information between different institutions. The fundamental principle underlying Ethereum is to allow for direct transfer of data between 2 parties without an intermediate organization that’s capable of financially exploiting information. The Ethereum platform allows for programmability, meaning that applications can be built that utilize the blockchain to also store information.
Smart contracts are a computer program that exists on the Ethereum blockchain. They can be executed when specific requirement(s) are met. Automated contracts are executed once the transaction/requirement is met, meaning that it’s operational for as long as Ethereum exists.
The beauty behind these smart contracts is that it doesn’t discriminate against users, and it’s always going to be available to use. This is a key property that makes for ease of communication across institutions around the world when it comes to exchanging healthcare related documents. Some common uses of Ethereum smart contracts currently are currency creation, computations, data storage,and insurance policies that are capable of paying out automatically.
Digitalization in medicine was the first major step towards improving our healthcare systems and providing top of the line care for patients. Although there exists critical problems in our current system, the solutions being presented to address these issues are capable of fixing these issues, and setting up a foundation for a brighter future in the field of healthcare.
IBM Watson Health (Now Merative) - IBM Watson Health utilizes artificial intelligence and data analysis to transform healthcare decision making. Their platform assists healthcare professionals by analyzing vast amounts of medical data, including patient records, medical literature and clinical trials. This allows doctors to make more informed diagnosis and treatment recommendations. Their AI capabilities extend to medical imaging interpretation, genomics research, drug discovery, and population health management.
Amazon Comprehend Medical - A part of Amazon Web Services, Comprehend Medical focuses on extracting valuable medical information from unstructured text in medical records, clinical notes, and other sources. This Artificial Intelligence powered service helps healthcare providers and researchers quickly identify relevant information, such as medical conditions, medications, and treatment details. Comprehend Medical ultimately allows streamlined data analysis and supports quicker decision making in healthcare.
Tempus - Tempus combines AI and advanced analytics to provide insights that drive more personalized treatment approaches. The company focuses on integrating and analyzing clinical and molecular data to help oncologists make informed decisions about cancer treatment. Their platform assists in identifying potential treatment options based on a patient’s genetic profile and medical history. Tempus ultimately allows healthcare decision making to be more precise.
Microsoft Healthcare - Microsoft Healthcare offers AI tools and solutions that enhance clinical workflows and patient engagement. Their efforts include developing chatbots powered by AI to provide patients with accurate medical information and assistance in understanding symptoms. Furthermore, Microsoft’s AI capabilities extend to medical image analysis, helping radiologists and doctors identify anomalies more efficiently.
Google Health - Google Health is dedicated to using AI to improve various aspects of healthcare. One of their prominent efforts is in medical imaging analysis, where AI algorithms help radiologists detect and diagnose conditions from X-rays, MRIs, and CT scans. Additionally, Google Health has worked on developing algorithms for predicting patient outcomes and identifying disease patterns. Their AI-powered tool aims to assist medical professionals in making faster and more accurate decisions, reducing stress induced errors.