Refining Physician Quality Indicators for Screening Mammography in Older Women: Distinguishing Appropriate Use from Overuse

Abstract

OBJECTIVES To assess the feasibility of refining physician quality indicators of screening mammography use based on patient life expectancy. DESIGN Retrospective population-based cohort study SETTING Texas PARTICIPANTS 3,595 usual care providers (UCPs) with at least 10 women in their patients aged 67+ on 1/1/2008 with an estimated life expectancy of ≥7 years (222,584 women) and at least 10 women with an estimated life expectancy of <7 years (90,903 women), based on age and comorbidity. MEASUREMENTS Screening mammography use in 2008–09 by each provider with each population. RESULTS The average adjusted mammography screening rates for UCPs were 31.1% and 55.2% for women with a life expectancy of <7 years and ≥7 years, respectively. For women with limited life expectancy, 3.7% of UCPs had significantly lower and 9.2% had significantly higher than average adjusted mammography screening rates. For women with longer life expectancy, 16.7% and 19.7% UCPs had significantly lower and higher than average rates, respectively. UCP adjusted screening rates were stable over time (2006–2007 vs. 2008–2009, r=0.65, p<0.001). There was a strong correlation among UCPs between screening rates of their women patients with a life expectancy of <7 years and for those with a life expectancy of ≥7 years (r=0.67, p<0.001). Most physician characteristics associated with higher screening rates (e.g., being female and foreign trained) in women with longer life expectancy were also associated with higher screening rates in women with limited life expectancy. CONCLUSION Providers with high mammography screening rates for women with longer life expectancy also tend to screen women with limited life expectancy. Quality indicators for screening practice can be improved by distinguishing appropriate use from overuse based on patient life expectancy.

Receipt of Cancer Screening Is a Predictor of Life Expectancy

“…28,30 Receipt of cancer screening by those with limited life expectancy can be used as a quality measure, and physicians could be assessed by the proportion of their patients with limited life expectancy who receive screenings, just as they are currently assessed by the proportion of their patients who do not receive screenings. [2][3][4]9 The results of this paper add a layer of complexity to that concept. Within any stratum of estimated life expectancy, those who had received screening had longer actual survival then those who did not.…”

“…[2][3][4] One example of over-testing is the case of a patient with limited life expectancy receiving a screening test for cancer. [5][6][7][8][9][10][11] There is a lag between when a cancer is diagnosed by screening and when it would be diagnosed through symptoms, and a further lag before screening lowers the risk of death from the cancer. 12 Thus, patients with limited life expectancy who undergo cancer screening are at risk of diagnosis and treatment of a cancer that would not otherwise have affected their health.…”

“…12 Thus, patients with limited life expectancy who undergo cancer screening are at risk of diagnosis and treatment of a cancer that would not otherwise have affected their health. [8][9][10] Therefore, such Bover-screening^could be used as a quality indicator, where physicians would be evaluated based on the percentage of patients with low life expectancy who are overscreened, similar to measuring the percentage with normal life expectancy who do not receive screening (under-screened). [2][3][4] We have conducted preliminary work on developing quality measures for over-screening using Medicare data and estimating the life expectancy of individual patients.…”

“…[2][3][4] We have conducted preliminary work on developing quality measures for over-screening using Medicare data and estimating the life expectancy of individual patients. 9,11,13 However, individuals who are screened are healthier on average than those who are not screened-the so-called healthy user effect that is found with many tests and treatments. 14 It is possible that these differences in health status are not completely captured by the data included in life expectancy algorithms, which in insurance claims data tend to rely on age, gender, and comorbidity.…”

Delivering High-Quality and Affordable Care Throughout the Cancer Care Continuum

“…These include overuse or inappropriate use of prostate-specific antigen (PSA) -based prostate cancer screening, 6 colonoscopy, 7 and mammography. 8,9 At the same time, underuse of mammography, Pap smear, and colonoscopy has been documented in some populations. 6,8,10 The culture of US medicine favors intervention.…”