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Access to Lung Cancer Screening Services: Preliminary Analysis of Geographic Service Distribution Using the ACR Lung Cancer Screening Registry
ORIGINAL ARTICLE
HEALTH SERVICES RESEARCH AND POLICY
Access to Lung Cancer Screening Services: Preliminary Analysis of Geographic Service Distribution Using the ACR Lung Cancer Screening Registry Paniz Charkhchi, MD a, Giselle E. Kolenic, MA b,c, Ruth C. Carlos, MD, MS a,b,d Abstract Purpose: Lung cancer has the highest mortality rate among all types of cancer in the United States. The National Lung Screening Trial demonstrated that low-dose CT for lung cancer screening decreases both lung cancer–related mortality and all-cause mortality. Currently, the only CMS-approved lung cancer screening registry is the Lung Cancer Screening Registry (LCSR) administered by the ACR. The aims of this study were to assess access to lung cancer screening services as estimated by the number and distribution of screening facilities participating in the LCSR, by state, and to evaluate state-level covariates that correlate with access. Methods: The ACR LCSR list of participating lung cancer screening facilities was used as a proxy for the availability of lung cancer screening facilities in each state. Additionally, we normalized the number of facilities by state by the number of screening-eligible individuals using Behavioral Risk Factor Surveillance System data. State-level demographics were obtained from the 2015 Behavioral Risk Factor Surveillance System: poverty level, insured population, unemployed, black, and Latino. State-specific lung cancer incidence and death rates, number of active physicians per 100,000, and Medicare expenditure per capita were obtained. Linear regression models were performed to examine the influence of these state-level covariates on state-level screening facility number. QGIS, an open-source geographic information system, was used to map the distribution of lung cancer screening facilities and to estimate the nearest neighbor index, a measure of facility clustering within each state. Results: As of November 18, 2016, 2,423 facilities participated in the LCSR. When adjusted by the rate of screening-eligible individuals per 100,000, the median population-normalized facility number was 15.7 (interquartile range, 10.7-19.3). There was a positive independent effect (coefficient ¼ 12.87; 95% confidence interval, 10.93-14.8) between state-level number of screening facilities and rate of screening-eligible individuals per 100,000. There were no significant correlations between number of facilities and lung cancer outcomes, state demographic characteristics, or physician supply and Medicare expenditure. In most states, facilities are clustered rather than dispersed, with a median nearest neighbor index of 0.65 (interquartile range, 0.51-0.81). Conclusions: Facility number correlated with the rate of screening-eligible individuals per 100,000, a measure of the at-risk population. Alignment of screening facility number and distribution with other clinically relevant epidemiologic factors remains a public health opportunity. Key Words: Lung cancer, screening, access to care, Medicare, guidelines, registry J Am Coll Radiol 2017;14:1388-1395. Copyright 2017 American College of Radiology
INTRODUCTION Lung cancer, the leading cause of cancer mortality [1], has a high incidence rate and causes a significant portion of new cancer cases [2]. Despite widely available data on lung cancer hazards, late-stage diagnosis limits effective
treatment options [1,2]. Diagnostic delay highlights the importance of lung cancer screening as an effective measure to reduce the mortality and treatment cost of lung cancer. The National Lung Screening Trial demonstrated that low-dose CT (LDCT) for lung cancer
a
This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD, and Mitchell D. Schnall, MD, PhD, group cochairs) and supported by the National Cancer Institute of the National Institutes of Health under awards CA189828 and CA180801. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. Dr Carlos receives salary support as deputy editor of JACR. All other authors have no conflicts of interest related to the material discussed in this article.
Department of Radiology, University of Michigan, Ann Arbor, Michigan. Program for Women’s Health Effectiveness Research, University of Michigan, Ann Arbor, Michigan. c Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan. d Institute for Health Policy and Innovation, University of Michigan, Ann Arbor, Michigan. Corresponding author and reprints: Ruth C. Carlos, MD, MS, Department of Radiology, University of Michigan, 1500 E Medical Center Drive, Ann Arbor, MI 48109-0030; e-mail: [email protected]. b
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Covariates of the Primary Outcome. We used population-based data from the 2015 Behavioral Risk Factor Surveillance System (BRFSS) to estimate the lung cancer screening–eligible population. The BRFSS, which is described in detail elsewhere [10,11], is an
annual random telephone survey that uses stratified sampling methods for data collection and provides estimates that are representative of US noninstitutionalized residents aged 18 years. The BRFSS produces a large data set of information regarding health, health risk behaviors, and health service utilization, which for many states is the only source of data available to policymakers [12]. The USPSTF recommends lung cancer screening for current or former smokers aged 55 to 80 years who quit smoking fewer than 15 years previously, with a 30 pack-year history. We defined current smokers as those who smoke every day or some days, and former smokers as those who stopped smoking within the past 10 years. The BRFSS response choices precluded assessment of pack-year history and those who quit within the past 15 years. The BRFSS sampling yielded state-specific proportions of screening-eligible individuals, rather than the absolute number of at-risk individuals. We chose 79 years as the upper age limit to enable estimation of the absolute number of screening-eligible individuals using US Census Bureau data, which report population data at 5-year intervals from 55 to 79 years. We then expressed this as the rate of screening-eligible individuals per 100,000 individuals 55 to 79 years of age. Age-adjusted lung cancer death and incidence per 100,000 persons representing lung cancer-related outcomes were obtained from the US Cancer Statistics Working Group [13]. Smoking prevalence in 2015 was obtained from Centers for Disease Control and Prevention [14]. The following state-level demographic data were obtained from the 2015 BRFSS: proportions of those below the poverty level, insured, unemployed, black, and Latino. We defined the poverty level as an annual household income less than $25,000. Insured individuals were those who reported, any kind of health care coverage, including commercial insurance and noncommercial plans such as Medicare or Medicaid. Individuals were considered unemployed if they reported having been unemployed for any period of time. Physician supply, defined as the number of active physicians per 100,000 individuals, was obtained from the 2015 State Physician Workforce Data Book [15], which provides state-specific data about active physicians and physicians-in-training. Medicare standardized riskadjusted per capita costs were obtained from the CMS Geographic Variation Public Use Files [16]. All correlates were estimated at the state level.
Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
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screening decreases both lung cancer–related mortality by 20% and all-cause mortality by 6.7% compared with chest radiographic screening methods [3,4]. This mortality benefit underscores the importance of rapid diffusion of lung cancer screening to practice and eliminating barriers to its implementation. The US Preventive Services Task Force (USPSTF) recommends that adults 55 to 80 years of age who are asymptomatic, current smokers or those who have quit smoking within the past 15 years, with tobacco-smoking histories of at least 30 pack-years, undergo annual LDCT (grade B) [5]. With this recommendation, nongrandfathered commercial insurers must cover LDCT in this population without any outof-pocket cost requirement to reduce financial barriers to access effective preventive services [6]. Currently, the only CMS-approved lung cancer screening registry is the Lung Cancer Screening Registry (LCSR) administered by the ACR [7]. The LCSR registers practices that provide LDCT and collects standardized information regarding those individuals who undergo lung cancer screening at these registered practices. The LCSR also facilitates reimbursement of LDCT services among Medicare patients for these registered providers [8]. Although some of the financial barriers to screening have been reduced, geographic access to services, including proximity of at-risk populations to screening facilities, represents a potential barrier. We aimed to assess the relationship between the availability of lung cancer screening facilities and the size of the at-risk population as well as state-level clinically relevant epidemiologic and demographic variables.
METHODS Data Sources Primary Outcome. The publicly available list of screening facilities participating in the LCSR was accessed on November 18, 2016, from the ACR [9]. Facility number by state, the primary outcome, was used as a proxy for the availability of lung cancer screening facilities in each state. Additionally, we normalized the number of facilities by state by the number of screening-eligible individuals, defined later.
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Analysis The location and distribution of screening facilities by state were graphically represented using QGIS version 2.18, an open-source geographic information system application that provides data viewing and analysis [17]. We calculated the nearest neighbor index within each state to investigate state-specific facility location clustering and dispersion patterns. If the index is less than 1, the pattern exhibits clustering; an index greater than 1 indicates dispersion. The magnitude in either direction indicates the degree of clustering or dispersal. We used BRFSS sampling weights and stratum indicators to adjust for the complex sampling design. We first used descriptive statistics to describe the sample’s characteristics. Continuous data were summarized using means and SDs; categorical data were summarized using weighted percentages. We performed multivariate linear regression models to further examine the influence of these covariates on state-level screening facility number. We specifically controlled for the screening-eligible population in the model. We chose to use nonnormalized screening facility number rather than facility number normalized to screening-eligible population to enable explicit estimation of the independent effect of the rate of screening-eligible individuals per 100,000 compared with other covariates. All statistical analyses were performed using Stata version 11 (StataCorp, College Station, Texas). RESULTS As of November 18, 2016, 2,423 facilities participated in the LCSR (Table 1), with a median number of 32 facilities per state (interquartile range, 13-76), with the largest number in Florida (n ¼ 198) and the smallest number in the District of Columbia and Montana (n ¼ 3). When adjusted by the rate of screeningeligible individuals per 100,000, the median population-normalized facility number was 15.7 (interquartile range, 10.7-19.3). Figure 1 graphically represents the location and distribution of lung cancer screening facilities by state-specific rates of screening-eligible individuals. Figure 2 depicts screening facility location and distribution by nearest neighbor index. Seventy-one percent of states had significant facility clustering, whereas 12% demonstrated significant dispersal. Of these states with dispersed facilities, 60% were western states (Utah, Wyoming, and Montana). When evaluating the independent effects of state-level covariates on the availability of lung cancer screening 1390
services, we demonstrated a positive independent effect (coefficient ¼ 12.87; 95% confidence interval [CI], 10.93 to 14.8) between state-level number of screening facilities and the rate of screening-eligible individuals per 100,000 (Table 2). There were no significant correlations between facility number and state-specific lung cancer death rates, smoking prevalence, demographic characteristics, physician supply, or Medicare expenditure, although there was a trend toward a positive correlation between lung cancer incidence rates (coefficient ¼ 1.25; 95% CI, 0.15 to 2.65; P ¼ .08) and facility number and a trend toward a negative correlation between the proportion of the population in poverty (coefficient ¼ 2.14; 95% CI, 4.48 to 0.19; P ¼ .07).
DISCUSSION We demonstrated state-level variability in lung cancer screening facility number when normalized to the rate of screening-eligible individuals as well as variability in facility clustering. Appropriately, the number of lung cancer screening facilities correlated with the estimated number of individuals eligible for screening by state; however, the frequency of screening facilities was not associated with lung cancer incidence and death rates, smoking prevalence, or other state-level demographic variables. Equitable and efficient use of proven preventive services requires reduction of a host of barriers to access. The Patient Protection and Affordable Care Act expanded the number of insured individuals to decrease the lack of insurance coverage as a barrier to care. Furthermore, cost of care even for those insured limits use of these services, therefore, the Affordable Care Act concomitantly eliminated out-of-pocket cost sharing for high-value preventive services for those with commercial insurance. With regard to lung cancer screening, Medicare has similarly extended coverage with no cost sharing as long as patients participate in an approved registry. Having eliminated cost to the patient and lack of reimbursement to the practice as barriers to screening, access to services may still be limited by geographic availability. For example, western states demonstrated significant lung screening service dispersal, likely mirroring a metropolitan area or population distribution that should reduce geographic limitations on access; however, individuals who live in more remote locations may have to travel farther to access these screening services compared with those who live more centrally. Conversely, states with highly clustered services but large geographic areas may similarly restrict Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
Table 1. Lung screening service availability and clinically relevant epidemiologic and demographic factors, by state
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Access to Lung Cancer Screening Services
State
Facility Number
Rate of ScreeningEligible Individuals per 100,000
PopulationNormalized Facility Number*
Lung Cancer Incidence Rate†
Lung Cancer Death Rate†
Poverty (%)
Insured (%)
Unemployed (%)
Black (%)
Latino (%)
Physician Supply‡
Medicare Expenditure§
Nearest Neighbor Index
Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware DC Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire
32 6 22 12 97 49 38 13 3 198 65 10 16 76 67 39 32 80 30 19 54 47 93 59 21 43 3 30 16 11
2.98 0.35 3.66 2.01 12.74 2.54 1.69 0.63 0.32 12.61 5.52 0.57 0.70 7.28 4 1.69 1.54 3.15 3.05 0.85 2.94 3.04 6.32 2.84 1.82 4.03 0.66 0.92 1.55 0.70
10.73 16.98 5.99 5.94 7.60 19.26 22.39 20.48 9.17 15.69 11.76 17.41 22.72 10.42 16.74 23.00 20.66 25.32 9.82 22.22 18.33 15.42 14.70 20.73 11.50 10.65 4.54 32.50 10.29 15.51
66.7 54.7 48.4 78.7 42.6 42.2 62.3 69.1 55.3 58.8 64 49.3 46.9 63.2 71.6 62 61.8 93.4 68 74.8 56.6 62.6 62.4 56.6 75.2 73.7 58 60.1 60.1 64.8
54.7 47.3 35.3 60.4 32.1 29.9 37.7 47.6 42.7 42.6 46.4 32.3 36.2 45.9 54.3 46.8 44.2 69.5 53.8 55.1 41.1 41.6 47.9 39 58.6 54.8 37.6 42.8 45.5 42.1
34.48 21.73 33 36.26 29.79 21.21 22.72 22.75 25.9 31.08 32.13 22.91 26.92 26.01 28.84 21.87 25.58 28.97 34.3 28.26 20 22.11 26.79 19.65 42.39 26.73 26.87 23.72 29.41 18.53
86.66 86.36 85.5 86.81 88.12 88.62 92.03 90 90.9 82.91 82.14 91.11 85.71 90.37 88.05 92.7 86.2 92.64 83.8 90.69 90.37 93.51 89.28 93.45 82.22 87.7 87.5 87.71 85.22 90.69
19.33 11.81 11.59 17.58 11.95 9.58 12.38 11.66 18.63 13.81 14.28 8.66 9.18 10.63 12.93 7.81 9.77 17.64 16.9 12.55 11.22 12.03 13.31 7.73 21.11 12.83 10.62 8.77 12.5 10.69
25.33 5 4.54 14.28 6.93 4.25 10.61 20.33 44.54 15.52 30.19 0.93 0.69 14.43 8.95 2.91 5.97 8.08 30.98 0.97 28.87 6.94 13.63 5.17 37.77 11.22 0.5 4.56 8.86 1.13
3.4 6.36 26.57 5.71 34.69 17.96 13.27 7.33 8.63 22.67 8.11 10.44 10 14.68 5.47 4.68 9.42 2.5 3.23 13.25 8.55 9.72 4.22 4.1 1.4 3.68 3.43 8.42 23.86 2
206 255.6 234 198.1 262.5 273.2 337.8 266.8 849.3 257.2 220.9 296.5 189.6 271.5 222.6 211 214.2 225.1 240.9 313.8 370.6 432.4 271.9 282.9 184.7 260.4 229.5 226 197.4 300.3
$9,887.66 $8,213.33 $9,464.51 $9,307.84 $8,531.57 $9,157.91 $9,004.67 $9,560.28 $8,247.27 $10,298.46 $9,370.97 $6,535.37 $9,189.77 $9,614.56 $9,431.58 $9,073.08 $9,913.07 $9,258.16 $10,300.84 $8,491.39 $9,535.89 $9,001.54 $9,458.63 $8,411.85 $10,267.82 $9,427.52 $8,490.20 $9,781.99 $9,554.72 $8,954.63
0.43jj 0.63 0.25jj 0.57jj 0.36jj 0.42jj 0.8¶ 0.71 3.36jj 0.22jj 0.68jj 0.55jj 0.65jj 0.66jj 0.81jj 0.87jj 0.73jj 0.57jj 0.52jj 0.54jj 0.5jj 0.8¶ 0.6jj 0.84¶ 0.77 0.53jj 3.73jj 0.89 0.08jj 1.19
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Table 1. Continued
Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
State
Facility Number
Rate of ScreeningEligible Individuals per 100,000
PopulationNormalized Facility Number*
Lung Cancer Incidence Rate†
Lung Cancer Death Rate†
Poverty (%)
Insured (%)
Unemployed (%)
Black (%)
Latino (%)
Physician Supply‡
Medicare Expenditure§
Nearest Neighbor Index
New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming
85 9 115 91 7 124 21 22 133 18 36 13 80 173 10 6 80 48 15 52 4
4.19 1.27 9.91 6.08 0.37 7.48 2.62 2.36 7.82 0.51 2.97 0.48 4.38 11.02 0.65 0.36 4.28 3.48 1.39 3.25 0.31
20.28 7.08 11.60 14.95 18.63 16.56 8.00 9.30 16.99 34.94 12.10 26.57 18.24 15.69 15.32 16.36 18.65 13.77 10.78 15.99 12.70
57.5 39.6 59.5 68.5 56.4 67.4 68.7 55.6 64.3 69.9 64.4 59.4 74.1 52.7 26.1 59.1 58.2 55 79.1 59 38.7
38.6 30.5 39.6 49.1 41 51.3 56.8 42.2 45.1 50.5 49.3 40.9 56.4 38.7 18.7 42.5 43.3 39.9 56.9 42.5 35.9
22.76 36.92 29.56 32.43 20 27.85 30.76 27.64 23.19 25.31 32.23 22.8 33.66 31.57 19.04 22.5 23.39 21.52 32.72 22.27 21.57
88.12 88.88 89.53 84.19 91.3 91.08 85.59 90.47 91.31 91.17 85.52 92.3 86.27 76.04 87.95 95 88.84 89.59 91.52 92.69 83.33
11.51 13.96 13.36 14.83 7.82 12.25 15.25 12.69 11.16 14.7 15.78 8.07 17.15 12.34 6.62 10.5 10 10.85 18.64 9.55 10
13.3 2.38 16.26 21.61 2.43 11.97 7.45 2.22 10.42 5.58 26.31 1.07 16.17 12.34 1.09 0.55 19.23 3.52 3.72 5.61 0.94
18.34 44.44 17.39 7.41 2.69 2.75 8.22 10.31 5.7 12.05 4.21 2.61 3.03 34.93 12.04 1.1 8.07 9.95 1.08 5.28 8.8
290.1 235.3 353.8 244 237 279.8 201.8 291.3 306.4 346.5 223.1 231.4 247.1 213.3 207.5 337.7 255.9 268.7 246.7 254.9 196.7
$9,467.34 $7,983.15 $8,597.49 $9,075.11 $9,419.42 $9,394.39 $9,961.87 $7,906.94 $9,246.61 $8,524.63 $9,733.01 $9,284.06 $9,580.76 $10,156.71 $9,779.76 $8,238.74 $9,089.89 $8,332.85 $8,825.58 $8,572.58 $9,230.26
0.52jj 1.21 0.38jj 0.51jj 7.39jj 0.65jj 0.8 0.72¶ 0.65jj 0.9 0.47jj 0.59jj 0.38jj 0.33jj 1.44jj 1.52¶ 0.42jj 0.54jj 0.75 0.6jj 2.24jj
*Number of facilities/screening-eligible rate. † Age-adjusted rates per 100,000. ‡ Number of active physicians per 100,000. § Medicare standardized risk-adjusted per capita costs. jj Statistically significant (P < .01). ¶ Statistically significant (P < .05).
Fig 1. Distribution of lung cancer screening facilities and the rate of lung cancer screening-eligible individuals per 100,000 by state.
geographic access, such as California or Texas, because of travel distance or duration. Conducting these analyses is beyond the scope of the current study but represent key areas for future work. That the availability of screening services correlates strongly with the number of screening-eligible individuals, for whom practice reimbursement is ensured,
may suggest response to market forces and local demand. Nonetheless, opportunity to align lung screening availability with relevant clinical variables, such as state-level lung cancer deaths, or other population risk factors, such as smoking prevalence, remains as a public health consideration. Smoking trends continue to shift from cities, where most facilities are located, to rural areas
Fig 2. Distribution of lung cancer screening facilities and state-specific nearest neighbor index, a measure of site clustering or dispersal. If the index is less than 1, the pattern exhibits clustering; an index greater than 1 indicates dispersion. Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
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Table 2. Correlates of screening site availability and state-specific clinically relevant epidemiologic and demographic characteristics Facility Number
Coefficient
95% Confidence Interval
P
Rate eligible per 100,000 Lung incidence Lung death Physician supply Poverty Insured Unemployed Black Latino Medicare expenditure Smoking prevalence
12.871 1.255 0.741 0.006 2.144 1.349 0.176 0.044 0.212 0.003 0.667
10.939 to 14.803 0.150 to 2.658 2.827 to 1.345 0.083 to 0.096 4.481 to 0.192 3.618 to 0.920 4.211 to 3.858 0.821 to 0.909 0.726 to 1.152 0.006 to 0.013 1.402 to 2.737
<.01 .08 .48 .89 .07 .24 .93 .92 .65 .46 .52
[18,19], increasing the challenge of optimizing screening facility distribution. Changes in smoking prevalence raise the need for further investigation on how resources should be allocated geographically [20]. From analogous studies of breast cancer screening, geographic access increases the use of screening mammography and potentially decreases stage at diagnosis [21,22]. Having geographic access to a facility alone insufficiently guarantees access to screening. Full implementation of lung cancer screening requires increasing screening capacity per facility, particularly in areas with currently constrained care delivery. Smieliauskas et al [23] estimated that lung cancer screening implementation would increase imaging procedures by 4% across the United States, representing a significant workforce issue and likely to result in disparities to access lung cancer screening. Manpower constraints can limit temporal service availability with office closures and limited hours. We demonstrated no correlation between physician supply as measured by the total number of active physicians per 100,000 individuals and the number of screening facilities. The LCSR gives the physical locations of screening facilities, not the hours that service is provided, another measure of access. Although the physical structures exist to render services, the low supply of radiologists in some states may represent a limiting factor. A key limitation of this brief report is the inability to precisely define the distribution of the population considered at risk, particularly of those with the risk profile specified by the USPSTF and Medicare as eligible for LDCT coverage, as the BRFSS has insufficient data to define those with at least a 30-pack-year smoking history or those who have quit within the past 15 years. We likely underestimated the number of 1394
screening-eligible individuals, which, however, would further bias toward the observed correlation between facility availability and the rate of screening-eligible individuals. As with all self-reported data, BRFSS responses are subject to recall bias, similar to the bias encountered when clinically implementing a lung screening program and ascertaining smoking status. Nevertheless, we derived the most representative state population estimates of screening-eligible individuals by using the BRFSS. Using the BRFSS to estimate the screening-eligible population precludes evaluation of county-level contributors of geographic access and limits analyses to state-specific variables. This latter focus may underestimate the geographic availability of screening services, particularly for those who reside in border communities straddling more than one state. Similarly, it is beyond the scope of our analyses to measure travel distances and durations to the nearest screening facility, particularly for individuals who live in these border communities. However, we are able to describe the relationship of state-specific variables. The LCSR itself presents only the geographic locations of screening sites, not an estimate of relative use or the potential clinical impact of actual use among screeningeligible individuals. However, we used the LSCR as a source of screening service availability. It is beyond the scope of the study to assess actual screening use at these facilities and the impact on lung cancer mortality reduction.
CONCLUSION Despite heterogeneity in lung cancer screening service distribution and the tendency toward facility clustering for the vast majority of states, encouragingly, the number of screening facilities in each state correlated with the rate of screening-eligible individuals per 100,000, a measure Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
of the at-risk population. However, there remains a need to evaluate the extent to which geographic clustering or dispersal affects service access. The lack of correlation with other variables such as state-specific lung cancer mortality or smoking prevalence presents an opportunity to align service provision with clinically relevant epidemiologic factors.
TAKE-HOME POINTS -
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At the state level, the number of lung cancer screening facilities correlates with the rate of screening-eligible individuals per 100,000, a measure of the at-risk population. Despite correlation of the number of screening facilities with the size of the at-risk population, the geographic distribution of the screening sites may still result in disparities to screening access. The potential mismatch in screening facility distribution with other clinically relevant epidemiologic factors, such as lung cancer mortality and smoking prevalence, remains a public health opportunity.
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8. American College of Radiology. Lung Cancer Screening Registry. Available at: https://www.acr.org/Quality-Safety/National-RadiologyData-Registry/Lung-Cancer-Screening-Registry. Accessed February 13, 2017. 9. American College of Radiology. LCSR registrants as of June 26, 2017. Available at: https://www.acr.org/w/media/ACR/Documents/PDF/ QualitySafety/NRDR/Lung-Cancer-Screening-Practice-Registry/Listof-LCSR-Participants.pdf. Accessed February 13, 2017. 10. Centers for Disease Control and Prevention. Methodologic changes in the Behavioral Risk Factor Surveillance System in 2011 and potential effects on prevalence estimates. Available at: https://www. cdc.gov/mmwr/preview/mmwrhtml/mm6122a3.htm. Accessed July 13, 2017. 11. Centers for Disease Control and Prevention. About the Behavioral Risk Factor Surveillance System (BRFSS). Available at: https://www. cdc.gov/brfss/about/about_brfss.htm. Accessed July 13, 2017. 12. Pierannunzi C, Hu SS, Balluz L. A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS) 2004–2011. BMC Med Res Methodol 2013;13:1. 13. US Cancer Statistics Working Group. United States cancer statistics: 1999-2013 incidence and mortality web-based report. Atlanta, Georgia: US Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute; 2013. 14. Centers for Disease Control and Prevention. Map of current cigarette use among adults. Available at: https://www.cdc.gov/statesystem/ cigaretteuseadult.html. Accessed February 13, 2017. 15. Center for Workforce Studies. 2015 State Physician Workforce Data Book. Washington, District of Columbia: American Association of Medical Colleges; 2015. 16. Centers for Medicare and Medicaid Services. Geographic variation public use files. Available at: https://www.cms.gov/Research-StatisticsData-and-Systems/Statistics-Trends-and-Reports/Medicare-GeographicVariation/GV_PUF.html. Accessed April 11, 2017. 17. QGIS - The leading open source desktop GIS. Available at: http://www.qgis.org/en/site/about/index.html. Accessed February 2, 2017. 18. Liu L, Edland S, Myers MG, Hofstetter CR, Al-Delaimy WK. Smoking prevalence in urban and rural populations: findings from California between 2001 and 2012. Am J Drug Alcohol Abuse 2016;2990:1-10. 19. Aloise-Young PA, Wayman JC, Edwards RW. Prevalence of cigarette smoking among rural adolescents in the United States. Subst Use Misuse 2002;37:613-30. 20. Dwyer-Lindgren L, Mokdad AH, Srebotnjak T, Flaxman AD, Hansen GM, Murray CJ. Cigarette smoking prevalence in US counties: 1996-2012. Popul Health Metr 2014;12:5. 21. Khan-Gates JA, Ersek JL, Eberth JM, Adams SA, Pruitt SL. Geographic access to mammography and its relationship to breast cancer screening and stage at diagnosis: a systematic review. Womens Health Iss 2015;25:482-93. 22. Elkin EB, Ishill NM, Snow JG, et al. Geographic access and the use of screening mammography. Med Care 2010;48:349-56. 23. Smieliauskas F, MacMahon H, Salgia R, Shih Y-CT. Geographic variation in radiologist capacity and widespread implementation of lung cancer CT screening. J Med Screen 2014;21:207-15.
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HEALTH SERVICES RESEARCH AND POLICY
Access to Lung Cancer Screening Services: Preliminary Analysis of Geographic Service Distribution Using the ACR Lung Cancer Screening Registry Paniz Charkhchi, MD a, Giselle E. Kolenic, MA b,c, Ruth C. Carlos, MD, MS a,b,d Abstract Purpose: Lung cancer has the highest mortality rate among all types of cancer in the United States. The National Lung Screening Trial demonstrated that low-dose CT for lung cancer screening decreases both lung cancer–related mortality and all-cause mortality. Currently, the only CMS-approved lung cancer screening registry is the Lung Cancer Screening Registry (LCSR) administered by the ACR. The aims of this study were to assess access to lung cancer screening services as estimated by the number and distribution of screening facilities participating in the LCSR, by state, and to evaluate state-level covariates that correlate with access. Methods: The ACR LCSR list of participating lung cancer screening facilities was used as a proxy for the availability of lung cancer screening facilities in each state. Additionally, we normalized the number of facilities by state by the number of screening-eligible individuals using Behavioral Risk Factor Surveillance System data. State-level demographics were obtained from the 2015 Behavioral Risk Factor Surveillance System: poverty level, insured population, unemployed, black, and Latino. State-specific lung cancer incidence and death rates, number of active physicians per 100,000, and Medicare expenditure per capita were obtained. Linear regression models were performed to examine the influence of these state-level covariates on state-level screening facility number. QGIS, an open-source geographic information system, was used to map the distribution of lung cancer screening facilities and to estimate the nearest neighbor index, a measure of facility clustering within each state. Results: As of November 18, 2016, 2,423 facilities participated in the LCSR. When adjusted by the rate of screening-eligible individuals per 100,000, the median population-normalized facility number was 15.7 (interquartile range, 10.7-19.3). There was a positive independent effect (coefficient ¼ 12.87; 95% confidence interval, 10.93-14.8) between state-level number of screening facilities and rate of screening-eligible individuals per 100,000. There were no significant correlations between number of facilities and lung cancer outcomes, state demographic characteristics, or physician supply and Medicare expenditure. In most states, facilities are clustered rather than dispersed, with a median nearest neighbor index of 0.65 (interquartile range, 0.51-0.81). Conclusions: Facility number correlated with the rate of screening-eligible individuals per 100,000, a measure of the at-risk population. Alignment of screening facility number and distribution with other clinically relevant epidemiologic factors remains a public health opportunity. Key Words: Lung cancer, screening, access to care, Medicare, guidelines, registry J Am Coll Radiol 2017;14:1388-1395. Copyright 2017 American College of Radiology
INTRODUCTION Lung cancer, the leading cause of cancer mortality [1], has a high incidence rate and causes a significant portion of new cancer cases [2]. Despite widely available data on lung cancer hazards, late-stage diagnosis limits effective
treatment options [1,2]. Diagnostic delay highlights the importance of lung cancer screening as an effective measure to reduce the mortality and treatment cost of lung cancer. The National Lung Screening Trial demonstrated that low-dose CT (LDCT) for lung cancer
a
This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD, and Mitchell D. Schnall, MD, PhD, group cochairs) and supported by the National Cancer Institute of the National Institutes of Health under awards CA189828 and CA180801. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. Dr Carlos receives salary support as deputy editor of JACR. All other authors have no conflicts of interest related to the material discussed in this article.
Department of Radiology, University of Michigan, Ann Arbor, Michigan. Program for Women’s Health Effectiveness Research, University of Michigan, Ann Arbor, Michigan. c Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan. d Institute for Health Policy and Innovation, University of Michigan, Ann Arbor, Michigan. Corresponding author and reprints: Ruth C. Carlos, MD, MS, Department of Radiology, University of Michigan, 1500 E Medical Center Drive, Ann Arbor, MI 48109-0030; e-mail: [email protected]. b
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Covariates of the Primary Outcome. We used population-based data from the 2015 Behavioral Risk Factor Surveillance System (BRFSS) to estimate the lung cancer screening–eligible population. The BRFSS, which is described in detail elsewhere [10,11], is an
annual random telephone survey that uses stratified sampling methods for data collection and provides estimates that are representative of US noninstitutionalized residents aged 18 years. The BRFSS produces a large data set of information regarding health, health risk behaviors, and health service utilization, which for many states is the only source of data available to policymakers [12]. The USPSTF recommends lung cancer screening for current or former smokers aged 55 to 80 years who quit smoking fewer than 15 years previously, with a 30 pack-year history. We defined current smokers as those who smoke every day or some days, and former smokers as those who stopped smoking within the past 10 years. The BRFSS response choices precluded assessment of pack-year history and those who quit within the past 15 years. The BRFSS sampling yielded state-specific proportions of screening-eligible individuals, rather than the absolute number of at-risk individuals. We chose 79 years as the upper age limit to enable estimation of the absolute number of screening-eligible individuals using US Census Bureau data, which report population data at 5-year intervals from 55 to 79 years. We then expressed this as the rate of screening-eligible individuals per 100,000 individuals 55 to 79 years of age. Age-adjusted lung cancer death and incidence per 100,000 persons representing lung cancer-related outcomes were obtained from the US Cancer Statistics Working Group [13]. Smoking prevalence in 2015 was obtained from Centers for Disease Control and Prevention [14]. The following state-level demographic data were obtained from the 2015 BRFSS: proportions of those below the poverty level, insured, unemployed, black, and Latino. We defined the poverty level as an annual household income less than $25,000. Insured individuals were those who reported, any kind of health care coverage, including commercial insurance and noncommercial plans such as Medicare or Medicaid. Individuals were considered unemployed if they reported having been unemployed for any period of time. Physician supply, defined as the number of active physicians per 100,000 individuals, was obtained from the 2015 State Physician Workforce Data Book [15], which provides state-specific data about active physicians and physicians-in-training. Medicare standardized riskadjusted per capita costs were obtained from the CMS Geographic Variation Public Use Files [16]. All correlates were estimated at the state level.
Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
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screening decreases both lung cancer–related mortality by 20% and all-cause mortality by 6.7% compared with chest radiographic screening methods [3,4]. This mortality benefit underscores the importance of rapid diffusion of lung cancer screening to practice and eliminating barriers to its implementation. The US Preventive Services Task Force (USPSTF) recommends that adults 55 to 80 years of age who are asymptomatic, current smokers or those who have quit smoking within the past 15 years, with tobacco-smoking histories of at least 30 pack-years, undergo annual LDCT (grade B) [5]. With this recommendation, nongrandfathered commercial insurers must cover LDCT in this population without any outof-pocket cost requirement to reduce financial barriers to access effective preventive services [6]. Currently, the only CMS-approved lung cancer screening registry is the Lung Cancer Screening Registry (LCSR) administered by the ACR [7]. The LCSR registers practices that provide LDCT and collects standardized information regarding those individuals who undergo lung cancer screening at these registered practices. The LCSR also facilitates reimbursement of LDCT services among Medicare patients for these registered providers [8]. Although some of the financial barriers to screening have been reduced, geographic access to services, including proximity of at-risk populations to screening facilities, represents a potential barrier. We aimed to assess the relationship between the availability of lung cancer screening facilities and the size of the at-risk population as well as state-level clinically relevant epidemiologic and demographic variables.
METHODS Data Sources Primary Outcome. The publicly available list of screening facilities participating in the LCSR was accessed on November 18, 2016, from the ACR [9]. Facility number by state, the primary outcome, was used as a proxy for the availability of lung cancer screening facilities in each state. Additionally, we normalized the number of facilities by state by the number of screening-eligible individuals, defined later.
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Analysis The location and distribution of screening facilities by state were graphically represented using QGIS version 2.18, an open-source geographic information system application that provides data viewing and analysis [17]. We calculated the nearest neighbor index within each state to investigate state-specific facility location clustering and dispersion patterns. If the index is less than 1, the pattern exhibits clustering; an index greater than 1 indicates dispersion. The magnitude in either direction indicates the degree of clustering or dispersal. We used BRFSS sampling weights and stratum indicators to adjust for the complex sampling design. We first used descriptive statistics to describe the sample’s characteristics. Continuous data were summarized using means and SDs; categorical data were summarized using weighted percentages. We performed multivariate linear regression models to further examine the influence of these covariates on state-level screening facility number. We specifically controlled for the screening-eligible population in the model. We chose to use nonnormalized screening facility number rather than facility number normalized to screening-eligible population to enable explicit estimation of the independent effect of the rate of screening-eligible individuals per 100,000 compared with other covariates. All statistical analyses were performed using Stata version 11 (StataCorp, College Station, Texas). RESULTS As of November 18, 2016, 2,423 facilities participated in the LCSR (Table 1), with a median number of 32 facilities per state (interquartile range, 13-76), with the largest number in Florida (n ¼ 198) and the smallest number in the District of Columbia and Montana (n ¼ 3). When adjusted by the rate of screeningeligible individuals per 100,000, the median population-normalized facility number was 15.7 (interquartile range, 10.7-19.3). Figure 1 graphically represents the location and distribution of lung cancer screening facilities by state-specific rates of screening-eligible individuals. Figure 2 depicts screening facility location and distribution by nearest neighbor index. Seventy-one percent of states had significant facility clustering, whereas 12% demonstrated significant dispersal. Of these states with dispersed facilities, 60% were western states (Utah, Wyoming, and Montana). When evaluating the independent effects of state-level covariates on the availability of lung cancer screening 1390
services, we demonstrated a positive independent effect (coefficient ¼ 12.87; 95% confidence interval [CI], 10.93 to 14.8) between state-level number of screening facilities and the rate of screening-eligible individuals per 100,000 (Table 2). There were no significant correlations between facility number and state-specific lung cancer death rates, smoking prevalence, demographic characteristics, physician supply, or Medicare expenditure, although there was a trend toward a positive correlation between lung cancer incidence rates (coefficient ¼ 1.25; 95% CI, 0.15 to 2.65; P ¼ .08) and facility number and a trend toward a negative correlation between the proportion of the population in poverty (coefficient ¼ 2.14; 95% CI, 4.48 to 0.19; P ¼ .07).
DISCUSSION We demonstrated state-level variability in lung cancer screening facility number when normalized to the rate of screening-eligible individuals as well as variability in facility clustering. Appropriately, the number of lung cancer screening facilities correlated with the estimated number of individuals eligible for screening by state; however, the frequency of screening facilities was not associated with lung cancer incidence and death rates, smoking prevalence, or other state-level demographic variables. Equitable and efficient use of proven preventive services requires reduction of a host of barriers to access. The Patient Protection and Affordable Care Act expanded the number of insured individuals to decrease the lack of insurance coverage as a barrier to care. Furthermore, cost of care even for those insured limits use of these services, therefore, the Affordable Care Act concomitantly eliminated out-of-pocket cost sharing for high-value preventive services for those with commercial insurance. With regard to lung cancer screening, Medicare has similarly extended coverage with no cost sharing as long as patients participate in an approved registry. Having eliminated cost to the patient and lack of reimbursement to the practice as barriers to screening, access to services may still be limited by geographic availability. For example, western states demonstrated significant lung screening service dispersal, likely mirroring a metropolitan area or population distribution that should reduce geographic limitations on access; however, individuals who live in more remote locations may have to travel farther to access these screening services compared with those who live more centrally. Conversely, states with highly clustered services but large geographic areas may similarly restrict Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
Table 1. Lung screening service availability and clinically relevant epidemiologic and demographic factors, by state
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Access to Lung Cancer Screening Services
State
Facility Number
Rate of ScreeningEligible Individuals per 100,000
PopulationNormalized Facility Number*
Lung Cancer Incidence Rate†
Lung Cancer Death Rate†
Poverty (%)
Insured (%)
Unemployed (%)
Black (%)
Latino (%)
Physician Supply‡
Medicare Expenditure§
Nearest Neighbor Index
Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware DC Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire
32 6 22 12 97 49 38 13 3 198 65 10 16 76 67 39 32 80 30 19 54 47 93 59 21 43 3 30 16 11
2.98 0.35 3.66 2.01 12.74 2.54 1.69 0.63 0.32 12.61 5.52 0.57 0.70 7.28 4 1.69 1.54 3.15 3.05 0.85 2.94 3.04 6.32 2.84 1.82 4.03 0.66 0.92 1.55 0.70
10.73 16.98 5.99 5.94 7.60 19.26 22.39 20.48 9.17 15.69 11.76 17.41 22.72 10.42 16.74 23.00 20.66 25.32 9.82 22.22 18.33 15.42 14.70 20.73 11.50 10.65 4.54 32.50 10.29 15.51
66.7 54.7 48.4 78.7 42.6 42.2 62.3 69.1 55.3 58.8 64 49.3 46.9 63.2 71.6 62 61.8 93.4 68 74.8 56.6 62.6 62.4 56.6 75.2 73.7 58 60.1 60.1 64.8
54.7 47.3 35.3 60.4 32.1 29.9 37.7 47.6 42.7 42.6 46.4 32.3 36.2 45.9 54.3 46.8 44.2 69.5 53.8 55.1 41.1 41.6 47.9 39 58.6 54.8 37.6 42.8 45.5 42.1
34.48 21.73 33 36.26 29.79 21.21 22.72 22.75 25.9 31.08 32.13 22.91 26.92 26.01 28.84 21.87 25.58 28.97 34.3 28.26 20 22.11 26.79 19.65 42.39 26.73 26.87 23.72 29.41 18.53
86.66 86.36 85.5 86.81 88.12 88.62 92.03 90 90.9 82.91 82.14 91.11 85.71 90.37 88.05 92.7 86.2 92.64 83.8 90.69 90.37 93.51 89.28 93.45 82.22 87.7 87.5 87.71 85.22 90.69
19.33 11.81 11.59 17.58 11.95 9.58 12.38 11.66 18.63 13.81 14.28 8.66 9.18 10.63 12.93 7.81 9.77 17.64 16.9 12.55 11.22 12.03 13.31 7.73 21.11 12.83 10.62 8.77 12.5 10.69
25.33 5 4.54 14.28 6.93 4.25 10.61 20.33 44.54 15.52 30.19 0.93 0.69 14.43 8.95 2.91 5.97 8.08 30.98 0.97 28.87 6.94 13.63 5.17 37.77 11.22 0.5 4.56 8.86 1.13
3.4 6.36 26.57 5.71 34.69 17.96 13.27 7.33 8.63 22.67 8.11 10.44 10 14.68 5.47 4.68 9.42 2.5 3.23 13.25 8.55 9.72 4.22 4.1 1.4 3.68 3.43 8.42 23.86 2
206 255.6 234 198.1 262.5 273.2 337.8 266.8 849.3 257.2 220.9 296.5 189.6 271.5 222.6 211 214.2 225.1 240.9 313.8 370.6 432.4 271.9 282.9 184.7 260.4 229.5 226 197.4 300.3
$9,887.66 $8,213.33 $9,464.51 $9,307.84 $8,531.57 $9,157.91 $9,004.67 $9,560.28 $8,247.27 $10,298.46 $9,370.97 $6,535.37 $9,189.77 $9,614.56 $9,431.58 $9,073.08 $9,913.07 $9,258.16 $10,300.84 $8,491.39 $9,535.89 $9,001.54 $9,458.63 $8,411.85 $10,267.82 $9,427.52 $8,490.20 $9,781.99 $9,554.72 $8,954.63
0.43jj 0.63 0.25jj 0.57jj 0.36jj 0.42jj 0.8¶ 0.71 3.36jj 0.22jj 0.68jj 0.55jj 0.65jj 0.66jj 0.81jj 0.87jj 0.73jj 0.57jj 0.52jj 0.54jj 0.5jj 0.8¶ 0.6jj 0.84¶ 0.77 0.53jj 3.73jj 0.89 0.08jj 1.19
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Table 1. Continued
Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
State
Facility Number
Rate of ScreeningEligible Individuals per 100,000
PopulationNormalized Facility Number*
Lung Cancer Incidence Rate†
Lung Cancer Death Rate†
Poverty (%)
Insured (%)
Unemployed (%)
Black (%)
Latino (%)
Physician Supply‡
Medicare Expenditure§
Nearest Neighbor Index
New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming
85 9 115 91 7 124 21 22 133 18 36 13 80 173 10 6 80 48 15 52 4
4.19 1.27 9.91 6.08 0.37 7.48 2.62 2.36 7.82 0.51 2.97 0.48 4.38 11.02 0.65 0.36 4.28 3.48 1.39 3.25 0.31
20.28 7.08 11.60 14.95 18.63 16.56 8.00 9.30 16.99 34.94 12.10 26.57 18.24 15.69 15.32 16.36 18.65 13.77 10.78 15.99 12.70
57.5 39.6 59.5 68.5 56.4 67.4 68.7 55.6 64.3 69.9 64.4 59.4 74.1 52.7 26.1 59.1 58.2 55 79.1 59 38.7
38.6 30.5 39.6 49.1 41 51.3 56.8 42.2 45.1 50.5 49.3 40.9 56.4 38.7 18.7 42.5 43.3 39.9 56.9 42.5 35.9
22.76 36.92 29.56 32.43 20 27.85 30.76 27.64 23.19 25.31 32.23 22.8 33.66 31.57 19.04 22.5 23.39 21.52 32.72 22.27 21.57
88.12 88.88 89.53 84.19 91.3 91.08 85.59 90.47 91.31 91.17 85.52 92.3 86.27 76.04 87.95 95 88.84 89.59 91.52 92.69 83.33
11.51 13.96 13.36 14.83 7.82 12.25 15.25 12.69 11.16 14.7 15.78 8.07 17.15 12.34 6.62 10.5 10 10.85 18.64 9.55 10
13.3 2.38 16.26 21.61 2.43 11.97 7.45 2.22 10.42 5.58 26.31 1.07 16.17 12.34 1.09 0.55 19.23 3.52 3.72 5.61 0.94
18.34 44.44 17.39 7.41 2.69 2.75 8.22 10.31 5.7 12.05 4.21 2.61 3.03 34.93 12.04 1.1 8.07 9.95 1.08 5.28 8.8
290.1 235.3 353.8 244 237 279.8 201.8 291.3 306.4 346.5 223.1 231.4 247.1 213.3 207.5 337.7 255.9 268.7 246.7 254.9 196.7
$9,467.34 $7,983.15 $8,597.49 $9,075.11 $9,419.42 $9,394.39 $9,961.87 $7,906.94 $9,246.61 $8,524.63 $9,733.01 $9,284.06 $9,580.76 $10,156.71 $9,779.76 $8,238.74 $9,089.89 $8,332.85 $8,825.58 $8,572.58 $9,230.26
0.52jj 1.21 0.38jj 0.51jj 7.39jj 0.65jj 0.8 0.72¶ 0.65jj 0.9 0.47jj 0.59jj 0.38jj 0.33jj 1.44jj 1.52¶ 0.42jj 0.54jj 0.75 0.6jj 2.24jj
*Number of facilities/screening-eligible rate. † Age-adjusted rates per 100,000. ‡ Number of active physicians per 100,000. § Medicare standardized risk-adjusted per capita costs. jj Statistically significant (P < .01). ¶ Statistically significant (P < .05).
Fig 1. Distribution of lung cancer screening facilities and the rate of lung cancer screening-eligible individuals per 100,000 by state.
geographic access, such as California or Texas, because of travel distance or duration. Conducting these analyses is beyond the scope of the current study but represent key areas for future work. That the availability of screening services correlates strongly with the number of screening-eligible individuals, for whom practice reimbursement is ensured,
may suggest response to market forces and local demand. Nonetheless, opportunity to align lung screening availability with relevant clinical variables, such as state-level lung cancer deaths, or other population risk factors, such as smoking prevalence, remains as a public health consideration. Smoking trends continue to shift from cities, where most facilities are located, to rural areas
Fig 2. Distribution of lung cancer screening facilities and state-specific nearest neighbor index, a measure of site clustering or dispersal. If the index is less than 1, the pattern exhibits clustering; an index greater than 1 indicates dispersion. Journal of the American College of Radiology Health Services Research and Policy n Charkhchi, Kolenic, Carlos
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Table 2. Correlates of screening site availability and state-specific clinically relevant epidemiologic and demographic characteristics Facility Number
Coefficient
95% Confidence Interval
P
Rate eligible per 100,000 Lung incidence Lung death Physician supply Poverty Insured Unemployed Black Latino Medicare expenditure Smoking prevalence
12.871 1.255 0.741 0.006 2.144 1.349 0.176 0.044 0.212 0.003 0.667
10.939 to 14.803 0.150 to 2.658 2.827 to 1.345 0.083 to 0.096 4.481 to 0.192 3.618 to 0.920 4.211 to 3.858 0.821 to 0.909 0.726 to 1.152 0.006 to 0.013 1.402 to 2.737
<.01 .08 .48 .89 .07 .24 .93 .92 .65 .46 .52
[18,19], increasing the challenge of optimizing screening facility distribution. Changes in smoking prevalence raise the need for further investigation on how resources should be allocated geographically [20]. From analogous studies of breast cancer screening, geographic access increases the use of screening mammography and potentially decreases stage at diagnosis [21,22]. Having geographic access to a facility alone insufficiently guarantees access to screening. Full implementation of lung cancer screening requires increasing screening capacity per facility, particularly in areas with currently constrained care delivery. Smieliauskas et al [23] estimated that lung cancer screening implementation would increase imaging procedures by 4% across the United States, representing a significant workforce issue and likely to result in disparities to access lung cancer screening. Manpower constraints can limit temporal service availability with office closures and limited hours. We demonstrated no correlation between physician supply as measured by the total number of active physicians per 100,000 individuals and the number of screening facilities. The LCSR gives the physical locations of screening facilities, not the hours that service is provided, another measure of access. Although the physical structures exist to render services, the low supply of radiologists in some states may represent a limiting factor. A key limitation of this brief report is the inability to precisely define the distribution of the population considered at risk, particularly of those with the risk profile specified by the USPSTF and Medicare as eligible for LDCT coverage, as the BRFSS has insufficient data to define those with at least a 30-pack-year smoking history or those who have quit within the past 15 years. We likely underestimated the number of 1394
screening-eligible individuals, which, however, would further bias toward the observed correlation between facility availability and the rate of screening-eligible individuals. As with all self-reported data, BRFSS responses are subject to recall bias, similar to the bias encountered when clinically implementing a lung screening program and ascertaining smoking status. Nevertheless, we derived the most representative state population estimates of screening-eligible individuals by using the BRFSS. Using the BRFSS to estimate the screening-eligible population precludes evaluation of county-level contributors of geographic access and limits analyses to state-specific variables. This latter focus may underestimate the geographic availability of screening services, particularly for those who reside in border communities straddling more than one state. Similarly, it is beyond the scope of our analyses to measure travel distances and durations to the nearest screening facility, particularly for individuals who live in these border communities. However, we are able to describe the relationship of state-specific variables. The LCSR itself presents only the geographic locations of screening sites, not an estimate of relative use or the potential clinical impact of actual use among screeningeligible individuals. However, we used the LSCR as a source of screening service availability. It is beyond the scope of the study to assess actual screening use at these facilities and the impact on lung cancer mortality reduction.
CONCLUSION Despite heterogeneity in lung cancer screening service distribution and the tendency toward facility clustering for the vast majority of states, encouragingly, the number of screening facilities in each state correlated with the rate of screening-eligible individuals per 100,000, a measure Journal of the American College of Radiology Volume 14 n Number 11 n November 2017
of the at-risk population. However, there remains a need to evaluate the extent to which geographic clustering or dispersal affects service access. The lack of correlation with other variables such as state-specific lung cancer mortality or smoking prevalence presents an opportunity to align service provision with clinically relevant epidemiologic factors.
TAKE-HOME POINTS -
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At the state level, the number of lung cancer screening facilities correlates with the rate of screening-eligible individuals per 100,000, a measure of the at-risk population. Despite correlation of the number of screening facilities with the size of the at-risk population, the geographic distribution of the screening sites may still result in disparities to screening access. The potential mismatch in screening facility distribution with other clinically relevant epidemiologic factors, such as lung cancer mortality and smoking prevalence, remains a public health opportunity.
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8. American College of Radiology. Lung Cancer Screening Registry. Available at: https://www.acr.org/Quality-Safety/National-RadiologyData-Registry/Lung-Cancer-Screening-Registry. Accessed February 13, 2017. 9. American College of Radiology. LCSR registrants as of June 26, 2017. Available at: https://www.acr.org/w/media/ACR/Documents/PDF/ QualitySafety/NRDR/Lung-Cancer-Screening-Practice-Registry/Listof-LCSR-Participants.pdf. Accessed February 13, 2017. 10. Centers for Disease Control and Prevention. Methodologic changes in the Behavioral Risk Factor Surveillance System in 2011 and potential effects on prevalence estimates. Available at: https://www. cdc.gov/mmwr/preview/mmwrhtml/mm6122a3.htm. Accessed July 13, 2017. 11. Centers for Disease Control and Prevention. About the Behavioral Risk Factor Surveillance System (BRFSS). Available at: https://www. cdc.gov/brfss/about/about_brfss.htm. Accessed July 13, 2017. 12. Pierannunzi C, Hu SS, Balluz L. A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS) 2004–2011. BMC Med Res Methodol 2013;13:1. 13. US Cancer Statistics Working Group. United States cancer statistics: 1999-2013 incidence and mortality web-based report. Atlanta, Georgia: US Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute; 2013. 14. Centers for Disease Control and Prevention. Map of current cigarette use among adults. Available at: https://www.cdc.gov/statesystem/ cigaretteuseadult.html. Accessed February 13, 2017. 15. Center for Workforce Studies. 2015 State Physician Workforce Data Book. Washington, District of Columbia: American Association of Medical Colleges; 2015. 16. Centers for Medicare and Medicaid Services. Geographic variation public use files. Available at: https://www.cms.gov/Research-StatisticsData-and-Systems/Statistics-Trends-and-Reports/Medicare-GeographicVariation/GV_PUF.html. Accessed April 11, 2017. 17. QGIS - The leading open source desktop GIS. Available at: http://www.qgis.org/en/site/about/index.html. Accessed February 2, 2017. 18. Liu L, Edland S, Myers MG, Hofstetter CR, Al-Delaimy WK. Smoking prevalence in urban and rural populations: findings from California between 2001 and 2012. Am J Drug Alcohol Abuse 2016;2990:1-10. 19. Aloise-Young PA, Wayman JC, Edwards RW. Prevalence of cigarette smoking among rural adolescents in the United States. Subst Use Misuse 2002;37:613-30. 20. Dwyer-Lindgren L, Mokdad AH, Srebotnjak T, Flaxman AD, Hansen GM, Murray CJ. Cigarette smoking prevalence in US counties: 1996-2012. Popul Health Metr 2014;12:5. 21. Khan-Gates JA, Ersek JL, Eberth JM, Adams SA, Pruitt SL. Geographic access to mammography and its relationship to breast cancer screening and stage at diagnosis: a systematic review. Womens Health Iss 2015;25:482-93. 22. Elkin EB, Ishill NM, Snow JG, et al. Geographic access and the use of screening mammography. Med Care 2010;48:349-56. 23. Smieliauskas F, MacMahon H, Salgia R, Shih Y-CT. Geographic variation in radiologist capacity and widespread implementation of lung cancer CT screening. J Med Screen 2014;21:207-15.
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