AAAA (The Four A’s) – Healthcare Blog
AAAA (The Four A’s) – Healthcare Blog
By matthew holt | Published: 2025-10-17 06:26:00 | Source: The Health Care Blog
Written by Jacob Ryder
I haven’t written this down yet, which kind of surprises me, since I find myself describing it a lot.
Let’s start with an overview. We can look at health information through a life cycle lens.
The promise of health IT has been to help us – ideally achieve optimal health for the people we serve.
The concept at the beginning of HITECH’s business was: “Adopt, Connect, Improve”.
These were the three pillars of Meaningful Use Incentive Programs.
Adopt Technology so we can Calls systems therefore It improves health.
Simple, yes?
Years later, one could argue with that Adoption And even communication It was (mostly) done.
But the bridge between measurement and health to improve It’s not something we can easily get around with the current tools at our disposal.
Why?
Many technical solutions, especially those that promote Information boardsthey’re missing the most important piece of the puzzle. They came close to us, but then they dropped the ball.
This is where the simple “AAAA” model comes in handy.
For data and information to be truly valuable in healthcare, it needs to complete a full cycle.
It is not enough to simply collect and display. There are four basic steps:
1. acquires. This is where we collect primary data and information. EHR entries, device readings, patient-reported outcomes… the cascade of information flowing into our systems. Note that I differentiate between Data (Transmitted representations of the physical world: blood pressure, complete blood count, DICOM representation of an MRI, medications actually taken) and Information (Diagnoses, thoughts, symptoms, list of problems, prescribed medications) because the data is reliably correct and the information is as well maybe True, and perhaps inaccurate. We have to weigh these two types of inputs correctly – because data is a much better input than information. (I’ll resist the temptation to go off on a tangent that data is a preferred input to AI models too…perhaps that’s another article.)
2. total. Once obtained, this data and information must be brought together, normalized, and cleaned. It’s about making disparate data sources speak the same language, creating a unified repository so we can ask questions about a single data set rather than dozens or hundreds.
3. analysis. Now we can begin to understand it. This is where clinical decision support (CDS) comes into play, and how we can identify trends, report anomalies, predict risks, and highlight opportunities for intervention. The analytics phase is where most current solutions end. Dashboard, alert, report… they all throw advice – like a bowl of spaghetti – into a human’s lap to sort everything out and figure out what to do.
Sure…you can see patterns, understand the population, identify areas for improvement…all good things. The maturity of health IT means that sophisticated aggregation, normalization, and analysis are now easier and more powerful than ever before. We no longer need dozens of specialized point solutions to handle every step; Modern platforms can integrate all of that. This is good… But not good enough
A dashboard or analytics report, no matter how elegant, is ultimately negative. It shows you the truth, but it doesn’t He does Anything about him.
represents. This is where the rubber meets the road. It is about translating ideas into concrete interventions. What should happen (or not happen) next?
What is the benefit of knowing that a patient is at high risk for readmission if this knowledge does not lead to a specific follow-up protocol, social work consultation, or modified discharge plan? What is the point of defining a prescription pattern if the system does not facilitate change in practice, provide immediate feedback to physicians, or adjust order sets?
We have relied on human intervention to fill this gap. A doctor may see a trend in a report and then initiate the change manually. We see a need to inspect and issue an order… (one by one).
Very sad.
The real power of health IT, especially with the developments we have seen, lies in… Close this loop. We should build systems that not only capture, collect, and analyze data, but also… Facilitate the next best actionprioritizing what is best for the person we serve, and (of course) from Who should be the beneficiary of this directive?
Imagine a system that not only flags a potential problem, but also:
* Automatically creates a personalized patient education document.
* Suggests an updated medication order (or set of orders) with one click.
* Schedule follow-up appointments with the appropriate specialists.
* Sends notification to care coordinator for intervention.
It is not about removing human judgment; It’s about empowering it. It’s about making the right thing to do the easiest thing to do.
The beauty of this cycle is its iterative nature.
The actions we take then generate new data and information, feeding it back into the “acquisition” phase, allowing us to continually improve our understanding and improve our interventions. The faster and more frequently we can move through these four steps, the more responsive, efficient and patient-focused our healthcare teams will become.
Next time you’re evaluating a new health IT solution, ask the crucial question: How does this system help us? represents?
Dr. Jacob Rader is a family physician who previously served as Deputy National Coordinator at ASTP/ONC, CMIO at Allscripts and Albany Medical Center, and CEO of the Alliance for Better Health and currently does angel investing, counseling and angel investing. Find his occasional thoughts on It is one of the few blogs older than THCB!
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