By Chris Plance and Kunal Patrawala, healthcare experts, PA Consulting.
Artificial intelligence tools, such as natural language processing (NLP), can be applied to unstructured data to produce real-time and nuanced insights. NLP can be applied to many types of unstructured data in a provider setting, however, the ideal approach is to apply these tools to a non-clinical source of unstructured data first.
Non-clinical unstructured data provides organizations with a perfect platform to develop their skills. Two well-known sources of such non-clinical unstructured data are consumer assessment of healthcare providers and systems (CAHPS) and hospital consumer assessment of healthcare providers and systems (HCAHPS) surveys. Applying NLP to CAHPS and HCAHPS surveys can help providers improve their top-box scores, build confidence and capabilities in their data skills, increase revenue, and allow organizations to take the crucial first steps towards the journey of unlocking 100% of their data.
CAHPS and HCAHPS Surveys play an important role in today’s Healthcare environment and are a substantial source of structured and unstructured data
CAHPS and HCAHPS are rating scale-based surveys that help providers discern patient perspectives such as patient experience and satisfaction. In 2019, more than 3 million patients completed HCAHPS surveys. Patient experience metrics from HCAHPS surveys create 25% of Hospital Value-Based Purchasing total performance scores, while CAHPS surveys are used by providers enrolled in the Merit-based Incentive Payment System (MIPS) program.
Similarly, private payers are also tying these metrics to reimbursement. The advent of healthcare consumerism has also led to patients extensively using tools such as CMS’s Star Ratings to make informed decisions. As a result, CAHPS and HCAHPS surveys have downstream effects on reimbursement, star ratings, and brand loyalty which makes improving top-box CAHPS and HCAHPS scores vital to a provider’s financial and operational health.
CAHPS and HCAHPS contain both structured (numerical ratings) and unstructured data (patient comments). These patient comments are accessible, and approximately 50% of the patients who take HCAHPS surveys leave comments. Unlocking this unstructured data can provide more comprehensive and specific information that cannot be gauged from only structured numerical ratings.