There are hundreds of individual data points created in just one healthcare interaction at the point of care. Often, these are stored in the electronic medical record through structured or – more often – unstructured fields where they are often left ignored until the next visit. While this information is helpful for informing future care interactions, it lacks the ability to improve immediate care quality for the patient. It’s no wonder that healthcare experts believe as much as 95% of health data goes unused.
Clinically speaking, better data capture at the point of care – but also the integration of tools and intelligence to ensure the accuracy and future applicability of the data captured – enables improved care quality and billing accuracy. These data can be combined with information captured outside of point of care diagnosis and standardized across data moments to uncover new insights using advanced analytics.
Improved documentation accuracy and financial health
At the point of care, providers are required to quickly document patient encounters; however existing tools are rigid making the process more complicated than it should. Further, clinicians are required to capture ICD-10 diagnosis codes, which then dictate how an encounter is billed and charged. There is a lot riding on the completeness and accuracy of what the clinician enters. The problem? Physicians are not taught how to code in medical school. And while this shouldn’t be expected of them, today’s clinical environment does make this skillset seem like a necessity when it shouldn’t have to be.
Instead, what they need is a smarter search tool seamlessly integrated into their EMR that allows them to search and document using terms, abbreviations, and descriptions in their own language, leveraging a proprietary built library of 1.3M+ clinical synonyms, acronyms, abbreviations, and misspellings, that can then be mapped appropriately to recognized, official ICD-10 diagnosis codes and descriptions. This solution must also help guide the clinician to select appropriate details about the diagnosis to ensure the most specified code has been selected, ensuring accelerated claims processing workflows and accurate reimbursement.
