AAAA (the four A’s) – The Healthcare Blog

By JACOB REIDER

I haven’t blogged about this topic yet, which surprises me a little, because I find myself describing it often.
Let’s start with an overview. We can look at health information through the lens of the life cycle.

The promise of health information technology has been to help us – ideally, achieve optimal health in the people we serve.

The concept at the beginning of the HITECH act was: “ADOPT, CONNECT, IMPROVE”.

These were the three pillars of meaningful use incentive programs.

Adopt technology so that we can connect systems and therefore improve health.

Simple, right?

Years later, we can say that adoption and even connection have (mostly) been accomplished.

But the bridge between measurement and health improvement is not one that we can easily overcome with the current tools at our disposal.

For what?

Numerous technical solutions, notably those which promote dashboardsthe most crucial piece of the puzzle is missing. They bring us closer, but then they drop the ball.

And this is where this “simple” AAAA” model comes in handy.

For data and information to be truly useful in healthcare, it must complete a full cycle.

It is not enough to simply collect and display. There are four essential steps:

1. Acquire. This is where we gather the raw data and information. EHR entries, device readings, patient-reported outcomes…the whole gamut of information flowing through our systems. Note that I differentiate between data (transduced representations of the physical world: blood pressure, CBC, DICOM representation of an MRI, medications actually taken) and information (diagnoses, ideas, symptoms, list of problems, prescribed medications) because the data is true and the information is reliable. maybe true, and perhaps inaccurate. We need to properly weigh these two types of inputs, because data is a much better input than information. (I’ll resist the temptation to go off on a premise that data is also a preferable input for AI models…maybe that’s another article.)

2. AGGREGATE. Once acquired, this data and information must be collated, normalized and cleaned. It’s about making disparate data sources speak the same language, creating a unified repository so we can ask questions about one set of data rather than dozens or hundreds.

3. Analyze. Now we can start to make sense of it. This is where clinical decision support (CDS) begins to take shape, through which we can identify trends, flag abnormalities, predict risks, and highlight opportunities for intervention. The analysis phase is the end of most current solutions. A dashboard, an alert, a report… they all drop advice – like a bowl of spaghetti – into the hands of a human to sort through it all and figure out what to do.

Sure… you can see trends, understand populations, and identify areas for improvement… All good things. The maturity of health information technology means that aggregation, standardization and sophisticated analysis are now far more accessible and robust than ever before. We no longer need a dozen specialized point solutions to manage each step; modern platforms can integrate everything. It’s good – but not good enough

A dashboard or analytics report, no matter how elegant, is ultimately passive. It shows you the truth, but it’s not TO DO anything about it.

Act. This is where the rubber meets the road. It’s about translating ideas into tangible interventions. What should happen (or not happen) next?

What good is knowing that a patient is at high risk for readmission if this knowledge does not trigger a specific follow-up protocol, social work consultation, or tailored discharge plan? What is the point of identifying a prescribing pattern if the system does not facilitate a change in practice, provide immediate feedback to clinicians, or adjust prescription sets?

We have relied on human intervention to close this gap. A clinician can detect a trend in a report and then manually initiate a change. We see a need for testing and place an order… (one by one).

So sad.

The real power of health IT, especially with the advancements we’ve seen, lies in close this loop. We should build systems that not only acquire, aggregate and analyze data, but that facilitate the next best actionprioritizing what is best for the person we serve, and (of course) WHO should he be the recipient of this advice?

Imagine a system that not only flags a potential problem, but:

* Automatically generates a personalized patient education document.

* Suggests an updated medicine order (or set of orders) with just one click.

* Schedules follow-up appointments with appropriate specialists.

* Pushes a notification to a care coordinator to intervene.

This is not about removing human judgment; it’s about giving it power. It’s about making the right thing the easiest thing to do.

The beauty of this cycle lies in its iterative nature.

The actions we take then generate new data and information, which feeds into the “Acquire” phase, allowing us to continually refine our understanding and improve our interventions. And the more quickly and frequently we move through these four steps, the more responsive, efficient and patient-centered our healthcare teams become.

The next time you evaluate a new health IT solution, ask the crucial question: How does this system help us? Act?

Jacob Reider MD is a family physician who previously served as Deputy National Coordinator at ASTP/ONC, CMIO at Allscripts and Albany Medical Center, CEO of Alliance for Better Health and currently does angel investing, consulting and pickleball. Find his occasional reflections at http://www.docnotes.net which is one of the few blogs older than THCB!