This is a cross-post, plus commentary at end, starting with an item today by SPM member Alexandra Albin (@MsAxolotl, a frequent patient herself), from her blog: My life in the Bush of Doctors. It arose from a boiling discussion on the SPM member listserv. To participate in the SPM listserv, join here

The views in Alex’s post are hers, and mine are mine; neither is a policy of the SPM. — e-PatientDave

First, Alex’s cross-post:

Today, on my listserv group at the Society for Participatory Medicine, the question was raised about the NY Times Well Blog post by Tara Pope on FICO’s new Medication Adherence Score. I was also inspired by @epatientDave pointing out that @nyceve1 had a blog post this morning FICO-scoring-millions-of-Americans-on-medication-compliance .

And yes I am angry…because if you look FICOs website here is what they say about their new tool, that is easy to implement. I recommend that any self respecting patient contact them, because they are not in the business of helping patients, they really seem targeted to the pharma companies, and “Care Organizations” and “Health Care Payers” (I don’t think they are talking about us).

Check out the tabs and pdfs for some fun reading…this is a dangerous tool that doesn’t really measure true compliance, i.e. whether someone took the medication. [It only monitors whether you paid for a prescription that a doctor ordered. – Ed.] What if I picked up the medication, or opened the glowing cap? As someone on the #SPM listserv pointed out, “We will not be able to fix compliance problems if the denominator is as wrong as the numerator!!

The words that rub me the wrong way are highlighted in bold. Nor do they really say what data they are pulling…only the following: “third party data sources, name and address, prescription claims when available.”

So, yes, I have got my cynical hat on….and my take away is (unless we revolt) pharma companies are given tools so they can better target their marketing budget and relationships can be further leveraged with doctors … and, enable deeper relationships with insurance companies who can have further control of what medications are on their formularies, or potentially use the data to develop additional criteria (of course they will use pretty words to make it seem fine) for dropping coverage for patients due to a poor FICO score.

It is bad enough that pharma companies sell their drugs direct to patients, and take doctor offices out to lunch…Anyone see the movie “Love and other Drugs”?

So, I sent them an email. Let’s see what they say…..and you can too on their contact page or call US (toll free): +1 888 342 6336

Here is information from the PDF on the FICO site: (Cynic Hat on)….. [emphasis added] Oh, and it’s easy to implement….

FICO® Medication Adherence Score is a powerful tool for predicting individual consumer’s likelihood of adhering to a drug regimen over the next year. This fully HIPAA-compliant solution helps brands identify patients at highest risk for non- compliance, direct marketing tactics where they have the greatest impact on medication adherence and health outcomes, and maximize the return on the consumer marketing budget. While pharmaceutical marketers typically rely on self-reported adherence data to identify non- compliance, FICO can score an entire patient database or list quickly and efficiently using only an individual’s name and address. Many pharmaceutical companies help address this challenge through a variety of consumer-directed programs. FICO can boost the effectiveness of these programs through a revolutionary data-driven approach to identifying a patient’s propensity toward medication adherence. Using the same world- class predictive analytics used to create the FICO® Score, the FICO® Medication Adherence Score accurately predicts an individual’s adherence propensity using a wide array of third-party data sources commonly used by direct marketers in a variety of industries.

FICO® Medication Adherence Score leverages a patient’s prescription claims history when available and pulls on other third-party data sources when no other information is present. The result is a powerful and versatile score that can be applied universally across a patient base to predict each patient‘s adherence over the next 12 months. This tool enables care organizations to gauge the right level of action across the patient base to optimize care, case and utilization programs— setting a universal baseline assessment on which survey results or other information can be overlaid if desired/present. The result is a powerful and versatile score that can be applied universally across a patient base to predict each patient‘s adherence over the next 12 months. This tool enables care organizations to gauge the right level of action across the patient base to optimize care, case and utilization programs—

The Medication Adherence Score is available for common chronic conditions, including diabetes, asthma, high cholesterol, hypertension and depression. Harnessing the predictive power of multiple, rich third-party data sources, Medication Adherence Score improves the effectiveness of all intervention targeting efforts.

Recent FICO research has shown that third- party data sources can effectively identify drug adherence propensity and can enhance the precision of models using claims data only. While some of these predictors, such as age and gender, are known to be associated with disease prevalence and adherence trends, FICO has unlocked the predictive power of other data sources, such as retail purchase behavior, geo-credit profiles and income/wealth indicators. The result is a powerful assessment tool that works across a prospective, new or existing patient base with minimal information requirements.

Learn how your organization can benefit from the most advanced analysis solution for predicting medication adherence. Email us …

End of Alex’s post

____

Commentary by Dave –

This may win my all-time prize for Worst Use of Medical Data.

I’ve written before about inept use of poorly chosen data, with nasty consequences for anyone who believes the data without checking its origin, but this scheme is shot through with logical errors, making it a particularly unreliable measure of what it claims to measure.

For one thing, it has no idea whether you actually took the pill; it only knows whether you bought the prescription. So anyone who wanted to game the system (to protect their “credit score”) could just buy the stuff and throw it out.

And that would drive up healthcare costs, costing insurance companies for the purchase of products that were not actually used.

Question:

Could this be a scam to maximize prescription sales, by putting a FICO gun to every patient’s head? I’m sure it’s not, but if you were to design one, it would look a lot like this.

But let’s be real  – what patient has money to throw away, just to defeat a credit score? More common is patients at the poor end of the scale, which @nyceve1 cited in her Daily Kos post. She notes, among other things, the Commonwealth Fund’s data on the extraordinary payment problems experienced by US patients. In short, a lot of people in the US – far more than any other country, 10x more than in the UK – simply can’t afford their prescribed medications. To construe this as non-compliant behavior – an “adherence risk” – is simply false logic.

Or, perhaps FICO believes they’re justified in giving a lower rating to poor people and the uninsured? You want to kick ’em while they’re down, Fair Isaac? (FICO is Fair Isaac Corporation.)

Some have wondered whether this score won’t be used by insurers to price differentially, just like the interest rates on loans that vary depending on your FICO score today. Wouldn’t that be a lovely screw for the poor: “Buy the scripts, or we’ll charge more for your insurance. Your choice. (We don’t care whether you take it – just buy it.)” If regulations don’t already exist to block that predatory behavior, let’s hope HHS will promptly create them.

Finally, the Kos post links to one by analytics geek @MedicalQuack Barbara Duck, which cites books like insurance whistle blower Wendell Potter’s Deadly Spin and Charles Seifer’s Proofiness, the Dark Side of Mathematical Deception.

My bottom line: if data is going to be used to measure something, it better be valid data, and it better truly measure what it thinks it’s measuring – or it’s just not fair to use it against someone. (And the buyers of the service will be defrauded.)

As Barbara Duck said in her post: has Wall Street not taught us about credit ratings and how those numbers get skewed?

 

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