Diagnostic Error: What Harm Can It Do?
Research reveals that diagnostic error in the US may cause up to 800,000 serious outcomes annually.
Has your lab made a diagnostic error? The answer is almost certainly yes, given that an estimated 10–15 percent of diagnoses issued are incorrect1 and up to 25 percent of autopsy studies reveal major diagnostic discrepancies.2 These errors, which can carry significant legal, financial, and health costs, are a major concern for laboratory professionals—but just how serious are the consequences? A group of researchers from Harvard and Johns Hopkins universities recently set out to answer the question through an in-depth analysis of publicly available data.
Laying the Groundwork
In 2015, the Institute of Medicine established a patient-centric definition of diagnostic error: “the failure to (a) establish an accurate and timely explanation of the patient’s health problem(s) or (b) communicate that explanation to the patient.”3 This definition highlights that failures in patient information and education are no less problematic than those in the testing process itself—a claim supported by the revelation that 18 percent of diagnosis-related medical malpractice cases involve failure to communicate with the patient and 15 percent involve errors in working with patients to establish a follow-up plan.4
Diagnostic error is the most common issue raised in malpractice claims and accounts for over one-third of all payments. It’s a heavy burden; from 1986 to 2010, the inflation-adjusted total reached $38.8 billion, with a mean claim value of $386,849.5 Worse than the financial costs, 40.9 percent of the errors behind the claims resulted in the death of a patient and a further 34.7 percent resulted in disability.5 Analyzing legal cases, however, can understandably be expected to skew toward the more serious outcomes—so, on a population level, how much serious harm actually arises from diagnostic error?
Analyzing the Impact
To find out, David Newman-Toker, MD, PhD, director of Johns Hopkins’ Armstrong Institute Center for Diagnostic Excellence, and colleagues interrogated a broad range of observational data from across the US, including hospital discharges, cancer registries, and more.6 After estimating the annual incidence of 15 “Big Three” diagnoses (vascular events, infections, and cancers), the group multiplied these numbers by rates of diagnostic error and serious harm derived from existing literature. They further validated their work by calculating uncertainty, analyzing sensitivity, and comparing their numbers to previously published estimates.
Literature review yielded a weighted mean diagnostic error rate of 11.1 percent, with serious harm at 4.4 percent. Over half of all serious harm involved “Big Three” diagnoses, with the top five conditions—stroke, sepsis, pneumonia, venous thromboembolism, and lung cancer—accounting for 38.7 percent.
Ultimately, the authors concluded that nearly 800,000 people each year in the US alone undergo serious harm, such as permanent disability or death, as a result of diagnostic error.
This may not be as grim as it sounds, though; the fact that so many serious outcomes arise from just five conditions suggests that meaningful harm reduction may be within reach. “A disease-focused approach to diagnostic error prevention and mitigation has the potential to significantly reduce these harms,” Newman-Toker said in a press release.7 “Reducing diagnostic errors by 50 percent for stroke, sepsis, pneumonia, pulmonary embolism, and lung cancer could cut permanent disabilities and deaths by 150,000 per year.”
The Economic Question
The financial implications of diagnostic error are obvious—from additional testing and treatment costs to potential legal fees and insurance increases for malpractice claims. Defensive medicine (ordering tests and treatments to preempt claims of malpractice) alone is estimated to cost the US healthcare system over $55 billion annually.8 The price of preventing diagnostic error may be less obvious since it can be difficult to determine whether a test is truly necessary or worth its potential cost and risk. It’s for this reason that initiatives such as Choosing Wisely9 have developed to guide medical professionals in test utilization management and reduce the waste—and the risks—of unnecessary testing and treatment.
Most lab professionals understand that test underuse may lead to delayed or missed diagnoses with serious implications. The downsides of overuse are less well understood, but include high-risk or expensive tests that may have more appropriate alternatives or may not be necessary at all, as well as falsely or subclinically positive results. Misuse, the third type of inappropriate testing, involves failures in administering a correctly selected test or managing the patient undergoing that test.
In 2013, Newman-Toker and two colleagues proposed an economic analysis framework for diagnostic testing that measures test outcomes in terms of their quality-adjusted life years (QALYs).10 They proposed establishing a cost threshold per QALY below which diagnostic strategies would be considered cost-effective, with those offering the best QALY-to-cost ratio preferred. Using this framework, the authors concluded that tests and strategies with the highest burden of harm and cost should be the first targets for improvement; low-harm approaches or those whose remediation is expensive or difficult should be deprioritized.
“Funding for these efforts remains a barrier,” Newman-Toker acknowledges.7 “If we are to achieve diagnostic excellence and the goal of zero preventable harm from diagnostic error, we must continue to invest in efforts to achieve success.” But with just 15 conditions contributing to over half of all serious outcomes from diagnostic error, the door to reducing diagnostic error and its harms is wide open.
Your Improvement Journey
Many serious harms from diagnostic error arise in the laboratory: They can appear at any step from sample handling and storage to reporting and follow-up. Labs aiming to reduce the impact of diagnostic error in their work should focus on tests relevant to common conditions such as the “Big Three,” as well as others identified as having a high burden of harm or high QALY-to-cost ratio for improvements. Though it can be challenging to identify improvements and obtain funding for their implementation, the resultant savings in both money and lives make the journey to error reduction worthwhile.
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