Both latent errors and noninjurious errors are important to identify and correct, as these ultimately may lead to patient injury. It is imperative to educate the caregivers and to give them feedback, if we are to reduce the total number of errors. Moreover, because injurious errors usually involve multiple errors, often by multiple caregivers, the chain of undetected errors and the sequence of errors may result in an injurious error. Medicine is a high-risk endeavor and errors are frequent. Although most errors are corrected by the person who made them, multiple errors often include some that escape detection and cause harm. As an example, the development of DKA de novo in a hospital setting, still a far-too-common event, usually involves multiple people and multiple errors of omission and may result in an injurious or even lethal event.
Diagnostic Errors
No discussion of errors in insulin therapy is complete without discussing the role of the individual and the human factor in errors in insulin therapy. Although defective systems may create potential for “error traps” or situations in which different individuals make the same error, the role of the individual at the POC is key to understanding how to prevent injurious errors.
Humans frequently make errors and, when candid, most people will admit that they frequently have slips and lapses that, for the most part, they correct themselves. Not only do people have different cognitive abilities, but most people have two distinct mental processes active at any time, often termed by cognitive psychologists as type 1 and type 2 thinking.34 Type 1 is intuitive, rapid, and almost automatic, relying upon a vast warehouse of experience and knowledge. Many people use this method of thinking much of the time because of its ease and speed. Examples of this type of thinking include what we do when driving a car or when a jazz musician is playing with their fellow musicians. This type of thinking, however, although blindingly fast and intuitive, is still error prone, subject to cognitive biases, and not at all quantitative. Type 2 thinking, by contrast, is slow, deliberative, and analytic. This form of thinking is more likely to be useful in quantitating risk, but may be just as prone to some cognitive biases as type 1 thinking. We would prefer our accountant to use type 2 thinking. But when it comes to the formulation of a medical diagnosis, particularly when the diagnostician feels confident or is working quickly, pattern recognition, which is usually a function of type 1 mental processes, is the predominant pattern. Although the experienced diagnostician may be correct, the pattern of thinking they most often use is particularly prone to overconfidence and a premature closing of the possibility that the diagnosis may either be incorrect or incomplete.
In a seminal study of the causes and frequency of diagnostic errors, Graber et al.35 looked at 100 cases of diagnostic error. These resulted in 90 injuries and 33 deaths. Of the 100 cases, seven were due to no-fault errors alone. Of the remaining 93 cases, many had system-related factors (63%) and cognitive errors. The system-related factors were most often organizational problems (94.3%). Only 5.6% of the system-related factors were the result of technical and equipment problems.
In 74 cases of diagnostic errors resulting from faulty cognition, cognitive factors were noted 320 times (4.3/case). The most common problems were faulty synthesis (82.8%) or faulty data gathering (14.6%). Surprisingly, inadequate knowledge or skill accounted for only 3.4% of the diagnostic errors resulting from faulty cognition. Put another way, it wasn’t common that the errors occurred because of a lack of knowledge, but rather because of how the clinician collected and put together the data to formulate a diagnosis.
Certain cognitive and system-related factors co-occur commonly, such as an inadequate history leading to misinterpretation of lab results. In general, faulty information gathering greatly increased the risk that there would be a faulty synthesis of data and premature closure, as for example, “it can only be this.” Faulty data gathering was identified in 45 instances by Graber et al.,35 but they identified inadequate or faulty knowledge or skills least often, in only 11 cases overall in the study. The researchers also identified failure to consult an expert as a significant cause of diagnostic error (15 cases), as well as failure to periodically review the situation (10 cases) or failure to gather other important information to verify the diagnosis.
Medical diagnostic errors are common when the presentation of the patient is atypical, as for example if a young woman appears in the emergency room with right lower quadrant pain that in actuality is due to undiagnosed DKA and not appendicitis. If therapy for DKA is delayed or even not done, the results may be catastrophic. It is likely that many of the so-called never events noted by CMS were due to diagnostic errors early in the development of DKA, HHS, or severe hypoglycemia.
Another not uncommon example of a diagnostic error that may occur is in the elderly patient with diabetes with HHS. The patient may present with focal signs of limb weakness that mimic a cerebro-vascular accident (CVA), but the real diagnosis is severe HHS, and if care is delayed the risk for mortality is very high.
The routine checking of other providers’ work and conclusions in real-time is crucial in preventing such diagnostic errors. It is always useful for the diagnostician to ask whether there is some other explanation for what they see than the diagnosis they have decided on. It is also useful to provide feedback to all members of the diabetes care team. Often the feedback of relevant data will allow people to revise their initial impression and protect the patient from serious errors in insulin therapy.
It is surprising that rule-based errors are often difficult to correct. The presence of a rule that is easy to use, but incorrect, often generates resistance to change. Probably the best known example is sliding-scale insulin (SSI). It is an example of a simple, clear rule of giving insulin that is “strong, but wrong.” Because of the simplicity of such rules, there is often resistance to discontinue using these, even when people know that the rule does not work well. Ideally, SSI as monotherapy should not be allowed to be part of a computerized insulin order set, and basal-bolus insulin orders promoted as the alternative.
Types of Insulin Errors
In 2013, the ASHP convened a panel of experts to focus on the goal of enhancing the safety of insulin use in hospitals. They began by grouping the types of errors in insulin therapy into six categories: prescribing, transcribing, dispensing, storage, administering, and monitoring. Their nomenclature is a useful place to begin.4
Prescribing Errors
These errors are among the most common and the most important. Among the common examples is when the prescriber chooses an incorrect dosage or a method of insulin dosing that is irrational, as for example, SSI as monotherapy. More variables should affect the choice of insulin dosage than just the immediate glucose result. SSI monotherapy is both a rule-based error and also a knowledge-based error, because it indicates both an illogical belief and a lack of understanding of insulin therapy. The evidence shows that it is an inferior method of prescribing insulin at best, and at worst, it has resulted in severe morbidity and even mortality when prescribed to a patient with DKA or HHS.
During insulin prescribing in hospitals, the prescriber needs to provide for both basal and bolus insulin requirements, the bolus doses used to balance nutritional intake, and correction doses when the glucose is outside of the optimal glycemic range. The basal needs may be highly variable, affected by the underlying comorbid conditions and by concurrent medications, which may increase or decrease insulin resistance, or by other mechanisms increasing the risk for hyper- or hypoglycemia. Some examples are shown in Tables 4.2 and 4.3.
Table 4.2—Comorbid Conditions
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