Five Unforeseen Challenges of Automation in Medical Record Reviews

27 February 2023

Automation is quickly becoming an integral part of many industries, from manufacturing to healthcare. It is at the forefront of technical revolutions, enabling businesses to save time and money by streamlining their processes with the help of advanced technologies and AI-powered tools. When it comes to healthcare sector, medical records review management is not an exception to this technological revolution. Automation has revolutionized the way medical records are reviewed and managed.

IMEs often take up the daunting task of navigating through thousands of medical records to determine the cause and severity of an injury to help insurance companies and law firms make informed decisions on personal injury claims. However, medical records come to their table unorganized, containing duplicates and irrelevant data. So, IMEs rely on medical records review service providers who often seek automation to de-duplicate, organize, and summarize medical records to make IMEs’ work easier and more productive.

As medical records reviews become increasingly digitized, independent medical examiners (IME) need to be aware of this transition’s implications on their processes. Automation works best when closely aligned with specific criteria. The flip side of this convenience is that if these criteria aren’t met, the automation can make the lives of IMEs and medical record reviewers a nightmare. Therefore, it is crucial for IMEs to be aware of some potential issues that may arise from automated medical records reviews before they proceed further with their evaluations. This blog discusses five critical challenges of automated medical records reviews.

Data Standardization and Migration

An EMR (Electronic Medical Record) interface provides numerous benefits to healthcare workers, which may improve patient experiences when the system is optimally used. Despite this, clinical data migration is one of the most challenging aspects of implementing this platform. Data migration is selecting and transferring data from one system or platform to another. However, for this to work as intended, the transferrable data must be standardized to be compatible with the new platform.

Otherwise, incorrect clinical data migration can negatively impact in reviewing a patient’s diagnostic reports and results. Furthermore, data migration errors may result in losing access to the entire database. As a result, additional time and money will be required to rectify the migration error. Management may find the automation process more expensive and complex than anticipated.

Lack of Training

Training employees who are involved in medical record review management is key to ensuring that they have the skills necessary to effectively utilize the technology. By investing in proper training, companies can ensure that their employees can efficiently manage large amounts of data while keeping up with the latest trends and regulations in the industry. Moreover, employees who understand how automation works can provide quality service to customers and remain competitive. This may entail an organized campaign and required training to acquaint them with the technology. An effective change implementation plan must be planned at the organizational level to reduce staff resistance to automation and make it beneficial.

Technical Limitations or Platform Compatibility

It is necessary to have an appropriate technical infrastructure to ensure well-functioning automation. A specialized system and a technically sound data management infrastructure are needed for an optimized EMR (Electronic Medical Record) platform. Moreover, EMR necessitates artificial intelligence (AI) to ensure its cybersecurity, which can be prohibitively expensive. In addition to being expensive, if automation is not properly deployed in EMR, it results in data compatibility errors and loss of data in medical records. Unless this is taken care of, the data will not be standardized to implement automation in medical records review.

Data Access Management

With an EMR, all clinical and non-clinical professionals can access patient information from any location. As a result, data privacy and confidentiality is jeopardized. Potential data security compromise warrants careful distribution of data access to the respective personnel. Any change in data format or process misalignment might compromise the underlying automation.

Cost Structure

Cost of EMR implementation is high because the process typically includes several steps, such as hardware setup, staff training, software cost and maintenance, and network fees. Also, if implementation costs increase during the implementation or maintenance phase, it can lead to technical glitches, non-compliance, data inconsistencies, and automation failure. A medical records review provider under such duress would put financial stress on their IT infrastructure maintenance budget.


Accuracy and completeness of electronic health records can be demanding in an automated medical records system. Security and privacy of sensitive patient information are key priorities, and ensuring that automated medical records meet regulatory requirements such as HIPAA is taxing. Although automation makes a medical records reviewer’s productivity easy, it has the potential to become complicated and expensive if not implemented and maintained correctly. The experience of a seasoned medical records reviewer will ensure the efficiency and accuracy of medical records review. PreludeSys experts use the power of AI in conjunction with human intervention to effectively review medical records. To learn more about our services, talk to our experts today.

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