The Sensitivity of Tests

Today's junkmail brought an invitation to have someone ultrasound my arteries to test for heart disease.  This annoys me on many levels, not least the crass advertising gimmicks used.  I'm not planning to participate because I don't think it will tell me anything useful and until they talk to me in the language of science

I'm after the answers of the Positive Predictive Value (PPV) and Negative Predictive Value(NPV) for this test and... well whatever potential future event they're promising me that I don't need to worry about.  As I'm not worried to begin with, I can spend that £150 on cake instead.

I'll explain PPV and NPV, and their related diagnostic terms Specificity and Sensitivity using something far more important to modern life - testing for witches.

Of course: The absolute test for whether someone is a witch or not is if he or she burns in hellfire for all eternity after dying.  For many people, that test doesn't happen soon enough, so there's the more conventional test of whether a witch floats in water or not.  Despite many centuries of refinement, even the best techniques aren't a perfect match for being Satan's future boyfriend/girlfriend.

There are two things that a test needs to be for it to be worthwhile: It needs to tell us what's true is true, and it needs to tell us what's false isn't true.  In our witchcraft example, the suspect needs to float if he/she's a witch and sink if he/she's not a witch.  Unfortunately there are consistently cases of known witches drowning and saints floating on water, so we need to measure how effective this test is.

We call the truthiness of a test specificity.  A high specificity means that if the answer's yes then it means yes, while a low specificity means that if the answer's yes, then it probably doesn't mean yes.  We can give specificity a figure by dividing the number of times that a true positive occured by every time a true witch is tested (which is true positives and the false negatives - the witches that floated and the witches that drowned)

The opposite of specificity in sensitivity.  A high sensitivity means that if the answer's no then it means that he's very unlikely to be a witch, while if the sensitivity is low then even the fact of drowning means that he probably was a witch all along.  We can give sensitivity a figure by dividing the number of tiems a true negative occured by every time an innocent is tested (the true negatives and the false positives - the innocents that drowned and the innocents who floated)

The use of these measures is in deciding whether a test is worthwhile or not, especially because there is a tendency that the more specific the test then the less sensitive it is - particularly when the test gives many answers where the cut-off is drawn somewhere along the scale.  Take blood pressure as an example: The higher you draw the cut-off for hypertension then the more people you're going to include who could potentially have complications of blood pressure (increasing specificity - including the right ones) but you include more that will end up not having complications (decreasing sensitivity - including the wrong ones).

Now instead of looking at a test in terms of whether it will judge a True Witch to be a witch or an innocent, we can look at it the other way - to what degree does a positive mean Witch?

Positive Predictive Value (PPV) uses the maths differently to evaluate whether we have to burn everyone who floats.  PPV is calculated by dividing the number of Floating True-Wtiches by all the times that someone Floats.  A high number means that it's unlikely an innocent has been falsely labelled Witch, while a low number means that we just can't tell.

Meanwhile Negative Predictive Value (NPV) looks at the people who sink.  Are we right to mourn the person who sank, or could they have been a witch all along?  NPV involves dividing the number of Sinking Innocents by all those that sank.  High values means we can have confidence in the immortal soul of the innocents who die passing the test, whereas low values mean that they could have been a witch all along.

Wikipedia has nice tables showing how this all fits together.

We live in an imperfect world, and understanding the statistics of testing allows to determine whether imperfect tests are worthwhile, particularly when the consequences of a false result are as severe as drowning or burning.

==Update 26/12/12==
I've now created a nice one page PDF showing the relationships between the different measures, to add my fellow witchfinders in their quests:

Witchcraft testing

Can we do a better job about Optimisation?

I'm confused.  I don't like being confused.  I particularly don't like being confused by my own professional leaders about something I'm told will define my profession's contribution to healthcare, but which no-one I've asked can give me a clear definition for.

That something is Medicines Optimisation.

The term started being used a few months ago, but (until tonight) I've never clearly seen a definition of it, let alone an explanation of what the difference is between it and the two current concepts about pharmacist practice, those of Pharmaceutical Care and Medicines Management.

I do both daily, so I can define them off the top of my head.  Pharmaceutical Care is the philosophy of practice by me as an individual practitioner dealing with the patient in front of me.  It is the same philosophy used by community pharmacists doing Medicines Use Reviews and hospital pharmacists doing medicine reviews on wards.  Medicines Management, on the other hand, is the collection of systems in place to ensure that medicines are handled to their best, safest, most cost-effective manner.

This has come to a head because of an article I saw earlier today which sought to explain what medicines optimisation was.  However no easy answer was forthcoming:
"Chief pharmaceutical officer for England Keith Ridge is reluctant to offer a simple definition for medicines optimisation"

Okay then, so it defies easy definition - what does it involve?  Improving quality and outcomes, value for patients, concordance/adherence, closer working with patients, better relationships with other health professionals, relating contract payments to clinical performance - all the things have been demanded by the grass-roots since the days of Pharmacy in a New Age.  We want these, but how is this  more than just a shopping list of applehood-and-mother-pie things that we'd all love to see.

We are told that medicines optimisation is more sophisticated than medicines management - but how?  Let us remind ourselves of what medicines management is and was.  The National Prescribing Centre defined medicines management as "Medicines management (MM) is a system of processes and behaviours that
determines how medicines are used by patients and by the NHS. Effective MM
will place the patient as the primary focus, thus delivering better targeted care and
better informed individuals.... (leading to) improve health, Improve patient care and satisfaction, Make better use of professional skills, Deliver effective clinical governance (and) Maximise the effective use of resources available"

The article ends with describing  how the term is currently being "socialised" and a communication strategy to explain the term to patients.  Perhaps the powers that be need do a better job of explaining it to medicines managing and pharmaceutically caring pharmacists like me?

We need a clear, universally accepted definition.  I found one with this evening from UKMI.

"Medicines optimisation is an approach that seeks to maximise the beneficial clinical outcomes for patients from medicines with an emphasis on safety, governance, professional collaboration and 
patient engagement"

However, this still needs work.  How does this approach vary from the daily practice of any pharmacist who seeks to benefit patients through maintaining safe governance systems, and their work with other professionals?  And this is before you start looking at whether you can determine patient engagement through 3 for 2 offers.  Everything I have seen relates to Medicines Optimisation being the answer to all our problems, yet I struggle to see how it answers them.

I have no objection to the promised land that the prophets of Medicines Optimisation are portraying, I'm just remaining confused by what this new term means and how it will enable us to get to Pharmacy Paradise.

An NHS musical

Sometime's it's best to go straight for Godwin's Law, and so I offer up the following attempt at humour based upon the epic musical "Springtime for Hitler"

The NHS was doing nicely
What a great, great story
And then came the elections
Where we elected the Tories

Suddenly we need a new way to be
A liberal economic victory
No top down reorganisation became
Revolution for you and me

And now it's springtime for Lansley and Jeremy
Corporations are happy and gay
Dismantling the nation's safety net
On multinationals, our health we gladly bet

Springtime for Lansley and Jeremy
Winter for Pensioners and Plebs
Springtime for Lansley and Jeremy
Come on patients, come offer your thanks

I was born thanks to Virgin Care, and that is why they call me Rare
Don't be stupid, be a smarty, make sure you vote for the Tory party

Springtime for Lansley and Jeremy
Healthcare with healthy margin
Never mind the needs of the populace
Private care is on the rise again

Springtime for Lansley and Jeremy
Huge debts will build up once more
Springtime for Lansley and Jeremy

Means that
Soon there'll be no need
We've get to where there's no need
You know there'll be no more tax

Free Market's Revenge

The fluctuations in the prices of medicines have long been a source of consternation in pharmacy circles. While free markets often lead to low prices, it need not be necessarily so. Having to explain why a tablet that genuinely costs pence to make now costs hundreds of pounds for 28 isn't something I enjoy.

However it rarely makes the national news. This morning was an exception:  Phenytoin, an epilepsy drug, has had a sudden surge in price. The reason appears to be that the drug manufacturer has changed from one that was producing it below the cost of manufacture (as a loss-leader) to one that wants to make enough profit to survive in today's economic environment.

Pharmacists have long argued that medicines shouldn't be, despite actions of pharmacy chains and pharmaceutical manufacturers, treated as ordinary items of commerce. This drug is a perfect example: the properties of Phenytoin mean there are very limited options for a competing product to force the price down.

You sometimes win, you sometimes lose when you try to manage healthcare through a free market. Every so often the free market takes it's revenge on you.

And there's no point sulking when that happens.