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Many mental health professionals find health information systems clunky, perverse, and intrusive, but their problems go far deeper. Underneath unwieldiness lies the temptation to begin relying on such indicators to such an extent that we stop attending to our internal resources.
Consider the case of the patient who carried a diagnosis of Parkinson’s disease for a decade and presented with recent hypersexuality. The diagnosis was passed along through the record with no critical scrutiny. When a neurologist disputed it and discontinued the patient's antiparkinsonian medications, his complaints vanished.
At stake is what we mean by knowledge. Is what we know defined by our own experience – what we have seen, heard, felt, and perhaps even intuited in the presence of the patient? Or do we instead rely on what is represented on a computer screen? Which is a more likely occasion for us to exclaim, “That can’t be right!” – when what the computer screen indicates does not comport with what we have observed of the patient, or when what we have observed in the presence of the patient does not jibe with what the computer is telling us?
Increasingly, technology obscures our view of the patient. Instead of the patient right in front of us, we see the vital sign or the laboratory value, or the radiologic image, a problem that is as acute in education as patient care. Instead of encountering the human being who is applying to medical school or residency, how often do we see a standardized test score? In the name of lowering costs and enhancing objectivity and fairness, we accept a quantitative score that often tells us little more than how well the candidate is likely to perform on the next standardized test.
There is so much that such scores omit. They tell us nothing about dedication, resilience, creativity, innovation, courage, and wisdom. They do not tell us what kind of human being we are going to be dealing with and what that person is likely to contribute to patients, colleagues, and community. Even worse, by failing to provide any insight about such traits of character, they implicitly undermine our sense of their importance. If we devote less attention than we should to something of real importance, or ignore it altogether, we end up with an unbalanced view of what matters most.
When we are not careful, our tools transform us into tools. Instead of using them, they use us. In fact, they not only use us, but they also transform us. What is most worth attending to? A standardized test score or how candidates handle failure, bring out the best in others, and innovate? The question is not simply what we rely on most in practice but what we look to in theory. Too often, such quantitative scoring systems have merely fostered an arms race or bidding war, driving up scores but doing little to foster meaningful enhancements regarding who candidates are and what they are capable of.
When applied to machine learning and artificial intelligence, the risks of a data-driven model of mental health are magnified. Looking at the complex reality of a patient strictly through the lens of data reveals some aspects but omits far more. We know, in a way that artificial intelligence cannot, that medical records are like photographs – they may reveal a great deal about what we include in the frame, but even more lies beyond its margins. What we don’t see is often as important as what we do – and without stepping back from time to time to take in the larger context, we often don’t really see at all.
Our very language has changed, and with it our thoughts, feelings, and aspirations. Our zest to count too often blinds us to what really counts most. As Abraham Maslow suggested 50 years ago, when our only tool is a hammer, we begin seeing everything as nails. When our tool is a health information system with an insatiable appetite for data, we produce more and more data. But what if our world contains not only nails but screws and bolts and a host of other fittings that a hammer would only destroy? And what if healthcare, however data rich, contains a reality far richer than mere data can ever reveal?
