The term “clinical inertia” has been used to describe “lack of treatment intensification in a patient not at evidence-based goals for care”.5
Our findings suggest that many such apparent “failures” to intensify medication regimens reflect potentially appropriate decisions in many cases. These findings suggest that part of the explanation for previously reported low intensification rates is appropriate inaction. Our empirically derived model of clinical inaction presents a framework that narrows the focus from all encounters at which medications were not intensified, to only a subset with more potential for improvement. Distinguishing potential clinical inertia from appropriate inaction is an important initial step for interventionists seeking to identify strategies to improve care and for policy makers seeking to measure quality of health care.
Although some have proposed that intensification should occur at 80% of encounters where risk factors are not controlled,6
this study suggests that appropriate intensification rates may be substantially lower. Indeed, 61.5% of the total available votes for important reasons not to intensify reside in the “appropriate inaction” neighborhood of the cognitive map. Importance as rated by physicians may not reflect actual prevalence of these reasons in practice, and our study was not able to determine this prevalence. However, in a study of lipid management, medical record review revealed that apparent failure to intensify lipid medications actually reflected acceptable quality of care in 24% of cases.18
Additional study of actual prevalence rates of appropriate inaction would help to quantify the size of the problem of true inertia.
It is worth noting that each reason even in the neighborhood of potential clinical inertia could in some cases represent clinically appropriate care. Consider the reason “at best level of control.” If the patient has had a trial of 1–2 antihypertensive medications and is currently on only 1 agent, the patient might in fact be able to achieve better control if additional medications were tried. On the other hand, in the Antihypertensive and Lipid Lowering to Prevent Heart Attack Trial, only 68% of trial participants achieved the target blood pressure level after an average of over 4 years in the aggressive medication management environment of a clinical trial.7
The 32% of trial participants who remained uncontrolled were likely to have received appropriate care.7
In addition, “best level of control” may appropriately differ from patient to patient as patients increase in complexity, especially in the geriatric population.19–21
The fact that none of the reasons generated by the physicians in our study stands out as clear instances of clinical inertia is noteworthy. We note that we purposely focused on physicians in this study, and it is possible that social undesirability may have prevented “forgetting to intensify” from emerging as a reason cited, leaving only more socially acceptable reasons. It is possible that observing actual practice could uncover reasons not generated by the physicians.
In contrast to the ambiguity in the potential clinical inertia neighborhood, many of the reasons grouped by the analyses into the appropriate inaction neighborhood are more clear-cut and potentially detectable. For example, acute complaints that warrant attention may be documented in the medical record. Medication nonadherence may not be consistently documented in medical records, but it may be detected in pharmacy data. Our empiric model can be used to define detectable exclusion criteria for intervention studies and in performance measures, focusing attention on where improvement is needed. Simplistic performance measures that do not separate appropriate inaction from opportunity for improvement may alienate American doctors, many of whom are disenchanted with aspects of the accountability movement.22,23
Our model of clinical inaction differs from previous models of clinical inertia such as O’Connor’s et al.,5
which defines clinical inertia broadly to include all patients with uncontrolled risk factors without evidence of intensification. O’Connor’s model was not empirically derived, but includes 3 major domains that are proposed to contribute to clinical inertia, namely, physicians, patients, and the health system. Our empirically derived model is from only the physician perspective, and mapped reasons into 2 extended families that were also proposed in O’Connor’s model, namely, physicians and patients. O’Connor proposed that physicians are responsible for 50% of clinical inertia, patients 30%, and the health system 20%; these proportions were not empirically derived. While it is possible that physicians may not focus on health system factors when generating reasons for not intensifying, the reasons offered by O’Connor as lying in the health system domain were not generated by either of our panels. These reasons included lack of guidelines or disease registries, no visit planning, no outreach, no decision support, lack of team approach to care or poor communication between physician and staff. A strength of the empiric approach is that it sheds some light on whether these theoretical reasons are actually considered important by practicing physicians in their day-to-day decision making. In fact, most reasons in the ‘potential opportunity’ area of the map are in the physician extended family, suggesting that physicians themselves view the greatest opportunity to overcome clinical inertia as lying within their own power.
Some limitations to this study are worth noting. We developed the empiric model based on a qualitative study of a convenience sample of 22 practicing primary care physicians, therefore it is possible that our results may not be representative. Nevertheless, the remarkable agreement between the 2 NGT panels on reasons why they do not intensify medications suggests that their opinions might reflect those of similar physicians. The empirically derived model is limited to the primary care physician’s perspective, and it is possible that subspecialists, nurses, health administrators, and patients could generate different lists of reasons, rate very different specific reasons as most important, and group them differently. While these other perspectives are important, hypertension management is performed mostly by primary care physicians in the US, therefore understanding their unique perspective is an important initial step in better understanding clinical inertia. Lastly, our interpretation of the axes and underlying cognitive similarities of the empiric model is not the only interpretation possible.