Case Study Review: Astrata and CDPHP
If you are contemplating using an NLP vendor to help you move to prospective HEDIS®, we know you have questions! Here are a few answers to common questions we receive that can help you plan for your evaluation of vendors.
Our experience delivering products in a cloud-based environment allows us to accurately estimate and bundle all costs together. This offers our customers a predictable single price that is inclusive, easier to budget, and without surprises. As your population’s volume changes over time and your measure focus shifts, our transparent pricing approach can flex to meet your needs.
We are familiar with pricing models that charge based on the number of documents processed. We think that may work fine for small volumes such as hybrid sample season, or second pass review. But as students of scale, we also know that this approach can get extremely expensive as you ramp up your data volume. That is why Astrata offers a model with minimal additional costs as data volume increases in support of our customers’ digital quality goals.
The cost of the platform includes a one-time set-up fee and a recurring fixed fee. The price covers a single performance year, which typically runs from February 1 to January 31, aligned with the HEDIS® season and prospective review. Your instance is updated each year to reflect your measure selection and tuned to your data. Pricing includes new capabilities added to the Platform according to planned releases. Our model also enables customers to start with Astrata any time of the year and realize value from the platform.
The recurring monthly charge is based on three factors: (1) the number and complexity of the selected measures, (2) the total number of members in the included denominators, (3) the number of data integrations, and/or an estimate of heterogeneity of the data. Of these three factors, selected measures are the primary driver of platform pricing.
No. Organizations typically use 5-12 of our sub-measures, and they deploy them on targeted populations (e.g., specific Lines of Business). NLP-assisted Prospective HEDIS® is meant to complement other sources of clinical data and gap closure via claims and other sources from measures where near-real-time clinical data is less impactful.
Number of abstractors does not meaningfully affect our costs, and therefore are not passed along to our customers. Your organization can have as many users as you wish. Number of charts or documents does not impact our pricing. We encourage you to collect as much data as possible on your members, to improve your ability to manage these populations.
We are happy to meet with you to provide a pricing proposal. Please contact us and we can provide a short list of questions to get started.