Diabetes Mellitus Performance Measures in Individuals with Limited Life Expectancy


  • Sei J. Lee MD, MAS,

    1. Division of Geriatrics, San Francisco Veterans Affairs Medical Center and University of California at San Francisco, San Francisco, California
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  • Cynthia M. Boyd MD, MPH

    1. Division of Geriatric Medicine and Gerontology, Department of Health Policy and Management, The Johns Hopkins University, Baltimore, Maryland
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Although individual clinicians and performance measures both focus on improving 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, informing consumers and influencing 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 an individual, but because no intervention is beneficial for all individuals with a specific disease, there are many instances in which performance measures encourage an intervention that the clinician believes is unlikely to help an individual.[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 and colleagues highlight a common situation in which this tension occurs by focusing on individuals with diabetes mellitus (DM) and limited life expectancy in the Veterans Affairs (VA) health system.[8] Because medically complex patients with limited life expectancy have greater risks and less benefit with intensive glycemic control,[9, 10] guidelines recommend less-intensive control for them,[9, 11, 12] but VA performance measures (like nearly all performance measures) do not exclude these patients. Thus, for individuals with limited life expectancy, performance measures may encourage more aggressive glycemic treatments which are more likely to harm than help. Focusing on individuals with limited life expectancy, Woodard and colleagues describe how clinicians in the VA health system are navigating this situation.

In a national sample of veterans receiving care in the VA health system, Woodard and colleagues found that individuals with DM who had a limited life expectancy were less likely to meet the glycemic control performance measure at baseline (77% vs 78%, P < .001) and were less likely to receive treatment intensification if they were not at goal (20% vs 28%, P < .001). Some may view these results as showing that, despite the incentives tied to performance measures, clinicians continue to individualize care and appropriately treat individuals with DM with limited life expectancy differently from those with a longer life expectancy. Others may view the small differences between the individuals 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 two 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.

The article highlights three important areas for future research.

First, this study highlights the need for further research to determine the appropriate level of glycemic control for individuals with DM with limited life expectancy. At least 8 years of intensive glycemic control (glycosylated hemoglobin (HbA1c) < 7%) is required before decreases in microvascular outcomes are seen.[12, 13] Thus, individuals with limited life expectancy are unlikely to benefit from fewer microvascular complications. However, individuals with limited life expectancy may benefit from avoiding poor glycemic control (HbA1c > 9%), because poor control can lead to immediate symptoms. Because of glycosuria, most experts recommend avoiding poor glycemic control in individuals with urinary incontinence.[14, 15] Studies in younger individuals suggest that hyperglycemia may lead to fatigue.[16] Thus, there are reasons to believe that HbA1c greater than 9% may lead to worse outcomes (such as incontinence or fatigue) for individuals with limited life expectancy. Studies in these individuals are urgently needed to determine whether poor glycemic control (HbA1c > 9%) is associated with worse outcomes. Only then will the evidence base be available to guide ideal clinical care and determine whether a performance measure of HbA1c of less than 9% is appropriate for individuals with limited life expectancy.

Second, this study highlights the need to design, test, and implement performance measures for individuals with limited life expectancy rather than excluding them from performance measurement altogether. Although individuals 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 individuals 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 methodological achievement of this work is the development of a method for identifying individuals with limited life expectancy using administrative data. The authors convened an expert panel to develop administrative data algorithms for five common life-limiting conditions to identify patients with a limited life expectancy. The algorithm successfully identified patients who had a 55% risk of 5-year mortality (compared with 15% risk for patients not identified through the algorithm). Because guidelines recommend targeting intensive glycemic control (and cancer screening) to individuals with a long life expectancy,[9, 11, 12] this algorithm could be implemented within the VA to identify individuals 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's decision-making, although relying solely on administrative data simplifies the implementation of this algorithm to identify individuals 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 adults with DM with limited life expectancy.

What's Next for DM Quality Indicators?

A recent American Diabetes Association consensus report on DM performance measurement noted two factors that are especially important for older adults with DM and limited life expectancy.[18] First, individuals with limited life expectancy are a remarkably heterogeneous group. A 90-year-old person with advanced DM and dementia and a 65-year-old individual with DM and New York Heart Association Stage 3 heart failure both have limited life expectancy but would be likely to benefit from different interventions for their DM.[19] Performance measures need to be flexible so that clinicians are encouraged to provide the ideal care for each individual. Second, for DM performance measures to encourage patient-centered, individualized care, they need to account for individual preferences. Although clinicians are able to focus on individual patients and their preferences, performance measures’ focus on decreasing undesirable variation can lead to discouraging appropriate variations in care that stem from differing care preferences.[7]

One possible solution that would address the heterogeneity of the population of individuals with limited life expectancy and patient preferences has been proposed in the 2010 National Program of All-inclusive Care for the Elderly Association Primary Care Committee Preventive Care Guidelines. (See Appendix S1, supporting information.) The Preventive Care Committee proposed categorizing individuals in terms of their goals of care and determining which performance measures are appropriate for each type of individual. For example, a palliative approach, in which symptom management and quality-of-life are the overriding considerations, may best serve individuals who are focused primarily on symptoms. Performance measures would be evaluated in terms of whether they encourage care that improves symptoms; if a performance measure is inconsistent with the goal of symptom management, individuals who have chosen a palliative approach to care would be excluded from that performance measure. Other goals of care include life prolongations for healthier people and maintenance of function for people who are intermediate between the life prolongation and palliative approaches. Although individuals may not fit neatly into one of these categories, these goals of care are common, suggesting that this approach may lead to performance measures that encourage individualized, patient-centered care for the heterogeneous population of older adults.

Finally, although this editorial has focused exclusively on DM performance measures, the questions raised here apply to all performance measures across a variety of common chronic diseases in older adults. Measurement of the quality of care for all conditions in medically complex older adults lags far behind the measurement of quality for younger, healthier adults,[20] and the Assessing Care of Vulnerable Elders Project has provided on-going efforts to improve the ability to measure performance in this population.[17] This work by Woodard and colleagues reminds us that we must focus on accurately measuring quality in this population so that (1) the application of inappropriate performance measures do not harm them, and (2) they benefit from measures that encourage the most important aspects of care for their clinical situation. This study also provides insights into how performance measures are affecting older adults with limited life expectancy, focusing on DM as a model for other chronic conditions. Further work is urgently needed to develop and test optimal, feasible quality measures for all older adults, including those with limited life expectancy.


Conflict of Interest: Dr. Lee was a consultant on the Agency for Healthcare Research and Quality project: Quality Indicators for Home and Community Based Services for the Medicaid population. Dr. Boyd has been funded by the National Quality Forum on a project titled: Performance Measurement for People with Multiple Chronic Conditions, Commissioned Paper and Steering Committee Consultation to the National Quality Forum.

Dr. Lee was supported by the Paul Beeson Career Development Award from the National Institute of Aging and the American Federation for Aging Research (K23AG040779). Dr. Boyd is funded by the Robert Wood Johnson Physician Faculty Scholars Program and the Paul Beeson Career Development Award Program from the National Institute of Aging and the American Federation for Aging Research (K23AG032910).

Author Contributions: Dr. Lee: Drafted the manuscript. Dr. Boyd: Critical revisions of the manuscript. No other parties contributed substantially to this research or the preparation of this manuscript.

Sponsor's Role: The sponsors had no role in this editorial. The views expressed here are solely those of Drs. Lee and Boyd.