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Cloudmedx Working with the University of California San Francisco (UCSF) to Automate the Clinical Documentation and Coding Process

CloudMedx, a healthcare AI company announced that it is working with the Department of Orthopaedic Surgery at the University of California, San Francisco (UCSF) to automate and improve the clinical documentation (CDI) process for surgical procedures in areas of spine, hip, and knee replacements.

For each patient and physician encounter at a hospital or clinic, there is a ton of operational and administrative work that needs to take place in order to document the entire visit or procedure. This requires hours of manual and labor-intensive work put in by the hospital staff that includes doctors, nurses, medical coders, and documentation experts. The doctors and nurses fill out the clinical aspect of the workflows and the medical coders and documentation experts make sure that correct medical codes are generated, and documentation quality is maintained. This requires expertise in clinical domain as well as compliance, regulation, and changing reimbursement models for accuracy. For hospitals that see thousands of patients and performs hundreds of complex surgeries each year, this amounts to a lot of work that needs to take place inside the electronic health record, and outside of it. This cumbersome process leads to a lot of staff burn out and fatigue.

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For example, coding and documentation experts are only able to review a limited number of patient charts per hour in the surgical areas due to their complexity. This adds to administrative and back office burdens. With augmentative tools such as CloudMedx, this process can potentially be automated and allow for hundreds, even thousands, of charts to be processed and analyzed in tandem with humans in a very short time. This has huge potential to not only improve the clinical documentation experience but also may remove any errors and highlight clinical risks that may have been missed. This is a huge opportunity for health systems to reduce the burden on their staff and achieve operational efficiencies, as well as improve documentation, quality metrics and outcomes.

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In the current phase of its work with UCSF, CloudMedx will receive data on surgical notes and chart encounters in order to automatically perform analysis on the clinical documentation using its AI and to identify codes and conditions from the unstructured and structured data. It will identify opportunities where documentation could be improved so that quality metrics and operational efficiencies may be achieved. The purpose of automating this workflow is to provide UCSF Department of Orthopedics with an augmentative tool that reduces staff burden and improves clinical documentation processes to achieve higher quality outcomes.

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According to the CEO of CloudMedx, Tashfeen Suleman, “Healthcare has advanced in the delivery of care over the past few years, but there are still some aspects that can be significantly improved through automation. One of those is using the latest and greatest technologies and algorithms to generate clinical insights and improve documentation workflows. At CloudMedx, our goal is to automate parts of these processes so that hospital staff and care providers are freed up to focus on more important things – such as taking care of patients and further improving care delivery and well-being of their patients.”

Richard Capra, Chief Administrative Officer in the UCSF Department of Orthopaedic Surgery, stated, “Documentation for surgical procedures is a very complex process. It requires a lot of manual work and depends upon the skill and knowledge of individual coders and documentation experts. For complex surgeries, there can be a huge variability in documentation and coding and this requires coders to have a great deal of knowledge of anatomy and regulations associated with a specific subspecialty. With CloudMedx, we are looking to automate parts of this process and improve communication between all stakeholders so that this process is streamlined and made efficient. Doing so could improve accuracy and quality measures to drive operational and clinical efficiencies.”

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