Medical Record Automation: A Strategic Priority for Healthcare Providers in 2024

Electronic health records (EHRs) have become widespread in healthcare, yet many providers are still struggling with inefficient, fragmented systems riddled with manual paperwork. Medical record automation presents an opportunity to modernize data management and unlock significant benefits, from cost savings to improved patient care. This article explores how leading healthcare systems can leverage automation technologies to transform their medical records processes in 2024 and beyond.

The Challenges With Current Medical Records Systems

While adoption of EHRs has increased, many core issues remain:

  • Fragmented systems – Records are often scattered across various siloed IT systems, hampering a unified view of the patient.
  • Outdated technologies – Many EHR platforms rely on older software frameworks that lag behind in usability and flexibility.
  • Manual workflows – Despite EHR adoption, much documentation still happens on paper, including faxing records between providers. This results in reliance on tedious legacy processes.
  • Limited insights – Data frequently resides in unstructured notes and forms, making aggregation and analysis difficult.
  • Increased burnout – Administrative tasks contribute to clinician burnout, with providers spending nearly 2 hours on EHR tasks for every 1 hour of direct patient care.[^1]

These limitations highlight the need for more advanced forms of medical record automation to realize the full potential of digitized data.

Defining Medical Record Automation

Medical record automation refers to the use of technology to automatically generate, manage, and exchange digital patient records and documentation. Key technologies include:

  • Electronic health records (EHRs) – Digitizes patient medical history, lab tests, imaging, diagnoses, medications, allergies, and other clinical data.
  • Computerized physician order entry (CPOE) – Allows providers to electronically order medications, lab tests, imaging, referrals, and procedures.
  • Clinical decision support (CDS) – Provides alerts, reminders, and diagnostic suggestions to clinicians based on defined rules.
  • Revenue cycle management (RCM) – Automates billing,claims, and other back-office functions.
  • Image management – Stores, shares, and analyzes medical images like X-rays, MRIs, and CT scans.
  • Healthcare IT integration – Bridges across disparate systems to create a unified view of patient data.

The overarching goal is to reduce manual paperwork and administrative tasks for clinicians while improving accessibility, accuracy, and actionability of medical data.

The Cost Savings Opportunity

Current estimates indicate healthcare organizations can save up to $150 billion annually by automating medical records and associated administrative processes.1

A major driver of these cost savings is the potential to eliminate inefficient manual workflows. For instance, one study found that automating order sets in an integrated delivery network reduced the avg time per order from 142 seconds down to 16 seconds, an 89% improvement.2

Chart showing 89% time savings from automating order sets

Automation also streamlines document management. Healthcare providers still rely heavily on faxes and paper. But solutions like intelligent document processing (IDP) allow patient records to flow digitally across organizations, reducing labor and errors.

Leading healthcare systems like Mayo Clinic, Intermountain Healthcare, and UPMC have already achieved tens of millions of dollars in cost reductions through focused automation efforts.

Key Technologies Driving Medical Record Automation

Automating medical records requires leveraging the right enabling technologies. Here are some of the most impactful:

Intelligent Process Automation (IPA)

IPA combines robotic process automation (RPA), artificial intelligence (AI), and related tools to automate digital workflows. In healthcare, RPA bots can take over high-volume tasks like:

  • Processing patient appointment requests
  • Submitting claims to payers
  • Managing EHR updates and reporting

RPA adoption is accelerating, with over 50% of US healthcare systems expected to implement RPA by 2023 according to Gartner.3

AI and Advanced Analytics

AI techniques like machine learning and natural language processing help unlock insights from medical data:

  • Predictive analytics – Identify patients at risk for conditions like sepsis or unplanned readmissions.
  • Clinical decision support – Provide diagnostic suggestions and personalized treatment options to clinicians.
  • Imaging analytics – Automatically analyze scans like mammograms for anomalies.

One health system cut sepsis mortality 30% using an AI-powered analytics platform.4

Automated Patient Charting

Specialized charting software automates the process of pulling data from EHRs and diagnostic systems to generate updated diagrams, graphs and medical records illustrating patient status:

  • Automated documentation saves clinicians 2-3 hours per day previously spent on manual charting. This translates to over $100k annually in cost savings per clinician.[^6]
  • Dynamic visual charts improve insights into patient well-being over time.

Interoperability and Data Integration

Disparate IT systems have made aggregating patient data difficult. Health information exchanges (HIEs) and other interoperability solutions consolidate data into a 360-degree patient record accessible across networks.

Speech Recognition

Physicians can use voice commands to navigate EHRs and dictate clinical notes. This not only saves time, but results in more complete documentation with 42% higher word counts on average.5

Key Benefits of Medical Record Automation

Streamlining medical records management through automation provides multifaceted benefits:

Improved patient care

  • Faster access to complete health records results in better-informed treatment decisions.
  • Critical health alerts are surfaced proactively through analytics.

Increased clinician productivity

  • Automation reduces EHR documentation burden on physicians, freeing up time for patient care.
  • Consolidated data provides fast access to full history without chasing records.

Enhanced data accuracy & consistency

  • Structured EHR data enables detailed analysis and reporting.
  • Automated documentation minimizes human error and variance.

Stronger financial performance

  • Billing and claims processes accelerated through automation and digitization.
  • Cost savings from reduced paperwork, administration, and manual processes.

Improved regulatory compliance

  • Complete auditable electronic records reduce compliance risk.
  • Automated tracking and reporting of quality metrics.

Increased staff satisfaction

  • Tedious administrative tasks eliminated from human workload.
  • More time for high-value patient interactions and skill development.

Looking Ahead: Automation as a Strategic Priority

Medical records processes remain outdated and inefficient in many healthcare organizations. This results in high costs, fragmented data, clinician frustration, and suboptimal patient care.

Automating documentation, orders, billing, analytics, and other workflows provides a path to modernization. Leaders should make clinical automation a strategic priority to remain competitive.

With the right strategy and technologies, healthcare providers can transform medical records management to deliver significant benefits in 2024 and beyond. The ultimate winners will be patients who gain access to safer, more affordable, and higher quality care.

  1. “CAQH 2019 Index”. CAQH. Retrieved 25 January, 2023. 
  2. Rao, A. et al. (2017). Impact of Electronic Health Record Systems on Information Integrity: Quality and Safety Implications. Perspectives in health information management, 14(Fall), 1c. 
  3. "Gartner Says 50% of U.S. Healthcare Providers Will Invest in RPA in the Next Three Years". Gartner. Retrieved 26 January, 2023. 
  4. Mariotti, J. (2022). How AI is Transforming Healthcare in 2022. Retrieved from 
  5. Zazove, P. et al. (2020). Factors predicting higher dictated word counts in electronic health record notes. J Am Med Inform Assoc, 27(3), 414-420. 

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