Diabetes mellitus performance measures in individuals with limited life expectancy

Although individual clinicians and performance measures both strive to improve the quality of care, they do so from different perspectives on the healthcare system. Performance measures evaluate health systems by measuring processes and outcomes of care and aim to drive improvement by decreasing undesirable variations in care, inform consumers, and influence payment.1,2 By reporting the proportion of patients receiving a given evidence-based intervention divided by the number of patients eligible for that intervention, performance measures provide an explicitly population-level view of healthcare.3 Paradoxically, to improve care, performance measures must influence individual-level decisions by changing the practice of individual clinicians who must maintain a patient-level perspective. Often these two perspectives align with the performance measure encouraging an intervention that the clinician recognizes is likely to help the individual patient. However, because no intervention is beneficial for all patients with a specific disease, there are many instances where performance measures encourage an intervention that the clinician believes is unlikely to help an individual patient.4–7 In today’s healthcare environment with financial incentives tied to performance measures, it is critical to understand how clinicians reconcile this tension between performance measures and their clinical judgment. In this issue of the Journal of the American Geriatrics Society, Woodard et al highlight a common situation where this tension occurs by focusing on diabetic patients with a limited life expectancy in the Veterans Affairs (VA) health system.8 Because medically complex patients with limited life expectancy experience both higher risks and less benefit with intensive glycemic control,9,10 guidelines recommend less intensive control for patients with limited life expectancy.9,11,12 However, VA performance measures (like nearly all performance measures) do not exclude these patients. Thus, for patients with limited life expectancy, performance measures may encourage more intensive glycemic control in patients who are more likely to be harmed than helped by these treatments. Focusing on patients with limited life expectancy, Woodard et al describe how clinicians in the VA health system are navigating this situation. In a national sample of veterans receiving care in the VA, Woodard et al found that patients with diabetes mellitus (DM) who had a limited life expectancy were less likely to meet the glycemic control performance measure at baseline (78 vs 77, p<0.001) and were less likely to receive treatment intensification if they were not at goal (20 vs 28%, p<0.001). Some may view these results as showing that despite the incentives tied to performance measures, clinicians continue to individualize care and appropriately treat diabetic patients with limited life expectancy differently than diabetic patients with an extended life expectancy. Others may view the small differences between the patients with and without limited life expectancy and conclude that performance measures are decreasing appropriate variations in care and encouraging clinicians to provide “one-size-fits-all” care. Without more detailed clinical data, it is impossible to know which of these 2 interpretations of the results is more accurate. Additional research with detailed patient-level clinical data is needed to determine whether the small differences seen in this study are appropriate. This paper highlights 3 important areas for future research. First, this study highlights the need for further research to determine the appropriate level of glycemic control for diabetic patients with limited life expectancy. Because decreases in microvascular outcomes occur after 8 years of intensive glycemic control (Hemoglobin A1c or HbA1c ≤7%),12,13 patients with limited life expectancy are unlikely to benefit through decreased microvascular complications. However, even patients with limited life expectancy may benefit from avoiding poor glycemic control (HbA1c > 9%). Because of glycosuria, most experts recommend avoiding poor glycemic control in patients with urinary incontinence .14,15 Studies in younger patients suggest that hyperglycemia may lead to fatigue.16 Thus, there are reasons to believe that HbA1c >9% may lead to worse patient-centered outcomes (such as incontinence or fatigue) for patients with limited life expectancy. Studies in these patients are urgently needed to determine whether poor glycemic control (HbA1c >9%) is actually associated with worse patient-centered outcomes. Only then will we have the evidence base to guide ideal clinical care and determine whether a performance measure of HbA1c <9% is appropriate for patients with limited life expectancy. Second, this study highlights the need to design, test and implement performance measures for patients with limited life expectancy rather than excluding them from performance measurement altogether. Although patients with DM and limited life expectancy may not benefit from intensive glycemic treatment, they are likely to benefit more from other interventions such as advance care planning.17 Thus, although patients with limited life expectancy may need to be excluded from some quality measures, they need their own set of quality measures that encourage the care that is most likely to help them. Third, a major methodologic achievement of this work is the development of a method for identifying patients with limited life expectancy using administrative data. For 5 common life-limiting conditions, the authors convened an expert panel to develop administrative data algorithms to identify patients with a limited life expectancy. The algorithm successfully identified patients who had a 55% risk of 5-year mortality (compared to 15% risk for patients not identified through the algorithm). Since guidelines recommend targeting intensive glycemic control (and cancer screening) to patients with an extended life expectancy,9,11,12 this algorithm could be implemented within the VA to identify patients who are unlikely be benefit from intensive glycemic control or cancer screening.7 Not incorporating clinical data makes this algorithm less useful as a prognostic index to guide an individual patient’s decision making. However, relying solely on administrative data simplifies the implementation of this algorithm to identify patients at high risk for limited life expectancy at a population-level. Future research should focus on the effect of implementing this algorithm to improve the targeting of intensive glycemic control of older diabetic patients with limited life expectancy.