Liposuction 360

hd liposuction 360, With this feature, companies looking to target healthcare providers based on specific areas of focus can do so with an even greater degree of accuracy and precision. Users can leverage claims-based specialty data to identify groups of physicians based on specialty category or primary specialty – or dig into detailed specialty designations for primary and secondary specialty at the individual level, which means companies can sharpen their sales strategies with a better picture of their audience.The problems with traditional taxonomy
The idea behind creating this new feature began when our data science team saw an opportunity to move past traditional taxonomy-based designations and deliver more up-to-date and precise insights into a healthcare professional’s specialty based on their care practice patterns. We set out with the goal of seeing how our analytics capabilities could break through the challenges we face today.While taxonomy-based designations are adequate, PATIENT-ShineMD-002024 we knew a better option was out there. Companies need specialty insights that don’t rely on outdated and often inaccurate sources.But first, a brief history.

hd liposuction 360 accompanied the implementation of the National Provider Identifier back in 2005. These unique 10-digit codes were designed to specify a provider’s area of expertise within their discipline. This was done to improve the efficacy of health information in a newly digital world and the efficiency of submitting medical claims electronically.

Taxonomy codes, however, are self-reported by the provider, and may not accurately reflect the actual procedures performed or patients diagnosed. As a doctor continues to train, specialize, or even branch out into other areas of focus, their taxonomy code may not change to reflect this journey.

So, what does this mean for our customers? If you are a company trying to sell to healthcare providers and want to be extremely targeted, grounding your strategy on existing taxonomy codes makes that tricky…or murkier than it should be. These are the problems our data science team concluded:
Taxonomy data provides a good baseline but can be inaccurate because codes aren’t updated all that often or are out-of-date since it is self-reported.

Taxonomy classifications also lack the standardized naming conventions required to identify healthcare provider groups.

We’re sixteen years past the introduction of taxonomy codes and the healthcare world is more digitally integrated than ever before. That means accurate healthcare commercial intelligence is critical for companies trying to get a clear understanding of their audience and develop their sales strategy.