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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">9100846</journal-id><journal-id journal-id-type="pubmed-jr-id">1173</journal-id><journal-id journal-id-type="nlm-ta">Cancer Causes Control</journal-id><journal-id journal-id-type="iso-abbrev">Cancer Causes Control</journal-id><journal-title-group><journal-title>Cancer causes &#x00026; control : CCC</journal-title></journal-title-group><issn pub-type="ppub">0957-5243</issn><issn pub-type="epub">1573-7225</issn></journal-meta><article-meta><article-id pub-id-type="pmid">31187351</article-id><article-id pub-id-type="pmc">6684105</article-id><article-id pub-id-type="doi">10.1007/s10552-019-01190-2</article-id><article-id pub-id-type="manuscript">HHSPA1043920</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>The effect of delivery structure on costs, screening and health
promotional services in state level National Breast and Cervical Cancer Early
Detection Programs</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Trogdon</surname><given-names>Justin G.</given-names></name><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-5484-7870</contrib-id><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><name><surname>Ekwueme</surname><given-names>Donatus U.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Subramanian</surname><given-names>Sujha</given-names></name><xref ref-type="aff" rid="A3">3</xref></contrib><contrib contrib-type="author"><name><surname>Miller</surname><given-names>Jacqueline W.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Wong</surname><given-names>Faye L.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib></contrib-group><aff id="A1"><label>1</label>Department of Health Policy and Management, Gillings School
of Global Public Health and the Lineberger Comprehensive Cancer Center, University
of North Carolina at Chapel Hill, 135 Dauer Dr., CB-7411, Chapel Hill, NC 27599,
USA</aff><aff id="A2"><label>2</label>Division of Cancer Prevention and Control, Centers for
Disease Control and Prevention (CDC), Atlanta, USA</aff><aff id="A3"><label>3</label>RTI International, Waltham, USA</aff><author-notes><corresp id="CR1">Justin G. Trogdon, <email>justintrogdon@unc.edu</email>, Donatus
U. Ekwueme, <email>dce3@cdc.gov</email>, Sujha Subramanian,
<email>ssubramanian@rti.org</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>1</day><month>8</month><year>2019</year></pub-date><pub-date pub-type="epub"><day>11</day><month>6</month><year>2019</year></pub-date><pub-date pub-type="ppub"><month>8</month><year>2019</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>2</month><year>2020</year></pub-date><volume>30</volume><issue>8</issue><fpage>813</fpage><lpage>818</lpage><!--elocation-id from pubmed: 10.1007/s10552-019-01190-2--><abstract id="ABS1"><sec id="S1"><title>Purpose</title><p id="P1">We estimated the costs and effectiveness of state programs in the
National Breast and Cervical Cancer Early Detection Program (NBCCEDP) based
on the type of delivery structure.</p></sec><sec id="S2"><title>Methods</title><p id="P2">Programs were classified into three delivery structures: (1)
centralized, (2) decentralized, and (3) mixed. Centralized programs offer
clinical services in satellite offices, but all other program activities are
performed centrally. Decentralized programs contract with other entities to
fully manage and provide screening and diagnostic services and other program
activities. Programs with mixed service delivery structures have both
centralized and decentralized features. Programmatic costs were averaged
over a 3 year period (2006&#x02013;2007, 2008&#x02013;2009, and
2009&#x02013;2010). Effectiveness was defined in terms of the average number
of women served over the 3 years. We report costs per woman served by
program activity and delivery structure and incremental cost effectiveness
by program structure and by breast/cervical services.</p></sec><sec id="S3"><title>Results</title><p id="P3">Average costs per woman served were lowest for mixed program
structures (breast=$225, cervical = $216) compared to decentralized (breast
= cervical = $276) and centralized program structures (breast = $259,
cervical = $251). Compared with decentralized programs, for each additional
woman served, centralized programs saved costs of $281 (breast) and $284
(cervical). Compared with decentralized programs, for each additional woman
served, mixed programs added an additional $109 cost for breast but saved
$1,777 for cervical cancer.</p></sec><sec id="S4"><title>Conclusions</title><p id="P4">Mixed program structures were associated with the lowest screening
and diagnostic costs per woman served and had generally favorable
incremental costs relative to the other program structures.</p></sec></abstract><kwd-group><kwd>Cost effectiveness</kwd><kwd>Cancer screening</kwd><kwd>Breast</kwd><kwd>Cervical</kwd></kwd-group></article-meta></front><body><sec id="S5"><title>Introduction</title><p id="P5">As the largest cancer-screening program in the United States, the National
Breast and Cervical Cancer Early Detection Program (NBCCEDP) serves as a learning
laboratory for other national cancer and non-cancer prevention and control programs.
The NBCCEDP&#x02019;s organizational structure is complex; CDC funds states,
tribes/tribal organizations, and US territories across the US and each
grantee&#x02019;s program has established a unique screening delivery system to serve
their population of eligible women. Each of these programs uses one of the following
three different service delivery mechanisms in their respective jurisdictions: (1)
centralized, (2) decentralized, and (3) mixed [<xref rid="R1" ref-type="bibr">1</xref>]. Centralized programs offer clinical services in satellite offices,
which may include local health departments that are not independent entities from
the state health departments, but all other program activities are performed
centrally (e.g., tracking and case management service). Decentralized programs, on
the other hand, contract with local and regional health departments, primary care
clinics (e.g., community health centers), private hospitals, or other healthcare
facilities to fully manage and provide screening and diagnostic services and other
program activities.</p><p id="P6">Programs with mixed service delivery structures have both centralized and
decentralized features [<xref rid="R2" ref-type="bibr">2</xref>.] There is a great
deal of variation among states with a mixed delivery structures and this variation
depends upon the needs and capacity at the health department. Various activities of
the program may be managed at the state health department while other activities are
managed at district level or even in the providers&#x02019; offices. For example,
some state health departments do their program enrollment through the provider
offices, but have patient navigation and the billing controlled centrally at the
state health department. Other programs contract with providers directly for
clinical services such as Federally Qualified Health Centers.</p><p id="P7">NBCCEDP grantees selected their program structures for specific reasons and
the delivery structure was not arbitrary or randomly assigned. The delivery
structure for each grantee is based on the infrastructure of their health department
system. States that function through health districts were more likely to have a
decentralized program whereas states with internal infrastructure may centralize the
entire program in the state health department.</p><p id="P8">In recent years, attention has been given to the estimated costs and effects
of these delivery structures for cancer screening, diagnostic follow-up, and other
program services. Because program resources reach only a fraction of eligible women,
all other things equal, service delivery mechanisms that provide efficient
allocation of resources are clearly desirable. Such service delivery mechanisms
should enable programs to screen and serve optimal numbers of eligible populations.
Currently, there is no information describing how the three service delivery
structures used by NBCCEDP grantees impact costs and effectiveness. In this study,
we assessed the costs and effectiveness of various delivery structures used to
deliver screening, diagnostic, and other program services in the NBCCEDP and
examined how different types of service delivery structures affect the number of
women served.</p></sec><sec id="S6"><title>Methods</title><sec id="S7"><title>Cost assessment tool</title><p id="P9">To collect economic costs related to the NBCCEDP, we used a customized
cost assessment tool (CAT). The development and testing of the CAT has been
described previously [<xref rid="R1" ref-type="bibr">1</xref>, <xref rid="R3" ref-type="bibr">3</xref>]. In brief, the CAT collected activity-based
economic cost data from the programmatic perspective, regardless of the funding
source used to pay those costs. A detailed protocol was used to guide the data
collection at each of the 68 grantees funded at the time of data collection.</p><p id="P10">In the CAT, grantees reported costs for items such as staff time,
materials purchased, and screening costs. For each line item, grantees were
provided space to list up to three activities for which the resource was used.
Each activity was selected from the following options: management, screening,
case management, tracking and follow-up assessment, public education and
outreach, professional education, coalition and partnership building, quality
assurance and improvement, and surveillance and evaluation. For example, hours
reported for a registered nurse may have been allocated to case management,
professional education and quality assurance and improvement. Further, in the
CAT, grantees were also required to report the relative focus of each activity
on breast or cervical cancer in their programs.</p><p id="P11">We used the CAT to collect cost data for the 2006&#x02013;2007,
2008&#x02013;2009, and 2009&#x02013;2010 program fiscal years. Grantee activities
and costs supported by all funding sources, including CDC, the state, and other
organizations, were collected in the CAT and reported in this study. Five
grantees (California, Hawaii, Maine, Michigan, and Minnesota) provided cost data
for 2007&#x02013;2008 rather than for 2009&#x02013;2010. Because we analyzed
average annual costs (see <xref rid="S9" ref-type="sec">Statistical
Analysis</xref> below), we retained these grantee&#x02019;s programs in the
analysis.</p><p id="P12">To ensure the accuracy of data collected with the CAT, we performed a
series of data quality checks. We verified that all CAT modules were fully and
accurately completed. We reviewed the submitted data to determine whether
grantees reported their actual total expenditures for clinical (screening and
diagnostic) procedures rather than their rates per procedure. We checked to
ensure that grantees did not double-report cost data across modules. We also
compared data across fiscal years to identify large, potentially erroneous,
changes in reported costs. For grantees with incomplete or potentially
inaccurate data, we resolved inconsistencies via e-mail and telephone calls and,
in some cases, through revisions in the CAT.</p><p id="P13">Our final analysis sample included 147 program-years. We excluded tribes
and territories because our preliminary analysis indicated that their cost
structures were very different from those of the state programs. We also
excluded six program-years in which total costs differed by more than 10% from
adjusted annual funding due to data quality concerns. These six program-years
represented 1 year of data from each of six different states: five of those
program-years were the first year of data collection (2006&#x02013;2007) and one
program-year was 2008&#x02013;2009.</p></sec><sec id="S8"><title>Women served</title><p id="P14">Data on the numbers of women served were obtained from CDC&#x02019;s
Minimum Data Elements (MDE) and the CAT. The MDE collects patient-level clinical
data that are associated with federal NBCCEDP funds, whereas the CAT collected
clinical data on women screened with non-federal funds and in-kind
contributions. The total number of women served included all women who were
screened or who received diagnostic follow-up using either federal or
non-federal funds.</p></sec><sec id="S9"><title>Statistical analysis</title><p id="P15">Program costs and the number of women served were averaged over time at
the grantee level before analysis to obtain statistics for a representative
year. Program costs for each activity were calculated by pooling all
expenditures allocated to that activity. Activity costs per woman served were
calculated by dividing activity costs by the number of women served. All costs
in this analysis are presented in 2010 dollars. We report median activity costs
per woman served by program delivery structure. We test the null hypothesis that
delivery structure is independent of costs using a nonpara-metric
<italic>k</italic> sample test on the equality of medians in unpaired data
(Stata command &#x0201c;medians&#x0201d;; Stata Version 14.0, College Station,
TX).</p><p id="P16">We examined the pseudo-incremental cost effectiveness of program
delivery structure, defined as the difference in cost between two delivery
structures divided by the difference in the number of women served. In cases in
which a program structure is more expensive (higher cost) but also more
effective (greater number of women served), incremental cost effectiveness can
be calculated; this provides the cost effectiveness of one program structure
relative to another. Activity costs were allocated to breast and cervical
cancer-specific costs using the allocation for each activity reported in the
CAT. We then aggregated the within-program averages for overall program costs
and women served by delivery structure. Average and incremental cost
effectiveness ratios were calculated using these delivery structure totals.</p></sec><sec id="S10"><title>Sensitivity analyses</title><p id="P17">We performed two sensitivity analyses related to our inclusion and
exclusion criteria. First, we conducted the analysis excluding the program-years
representing 2007&#x02013;2008 instead of 2008&#x02013;2009 (CA, HI, ME, MI, and
MN). Second, we conducted the analysis including the program-years in which
total costs differed by more than 10% from adjusted annual funding.</p></sec></sec><sec id="S11"><title>Results</title><p id="P18">Across the 51 state programs (including Washington DC), ten were
centralized, 17 were decentralized, and 24 were mixed (<xref rid="F1" ref-type="fig">Fig. 1</xref>). <xref rid="F2" ref-type="fig">Figure 2</xref> reports median
costs per woman served for each activity by program structure. Screening and
diagnostic services had the highest median costs per woman served (from $131.84 for
mixed programs to $152.57 for centralized programs). The next highest median costs
per woman served was for program management (from $14.98 for mixed programs to
$32.99 for decentralized programs) and patient support/case management (from $10.88
for centralized programs to $30.71 decentralized programs). Differences in median
costs per woman served were largest for these activities and were significantly
different from screening and diagnostic services (p = 0.012) and program management
(p = 0.012). Decentralized programs spent the most on program management. Mixed
programs&#x02019; median screening and diagnostic service costs per woman served were
approximately $20 lower than centralized and decentralized programs.</p><p id="P19"><xref rid="T1" ref-type="table">Table 1</xref> presents the results of the
pseudo-incremental cost-effectiveness analysis. Centralized programs are reported
first because they served the smallest number of women, followed by the
decentralized programs, and then the mixed programs. Compared with a base of
centralized programs, decentralized programs incurred costs of $281 for each
additional woman served for breast cancer and $284 for each additional woman served
for cervical cancer. Compared with decentralized programs, mixed programs added an
additional $109 for each additional woman served for breast cancer but saved $1,777
for each additional woman served for cervical cancer. In both sensitivity analyses
(excluding the 2007&#x02013;2008 program-years and including the program-years in
which total costs differed by more than 10% from adjusted annual funding) the
results for average and incremental cost effectiveness were nearly identical to
those reported <xref rid="T1" ref-type="table">Table 1</xref>, with estimates within
a few dollars of the original analytic sample (available upon request).</p></sec><sec id="S12"><title>Discussion</title><p id="P20">Our results indicate that program delivery structure was associated with the
cost and effectiveness of services provided by NBCCEDP grantee programs. Mixed
program structures were the most common among NBCCEDP grantees and they had the
lowest screening and diagnostic costs per woman served. This is important, as
programs were required to spend at least 60% of their funds on these activities
during the time of this study. Screening and diagnostic costs were approximately
five times higher than costs per woman served for the next highest cost activity
(program management).</p><p id="P21">Programs with mixed structures served the most number of women annually. For
breast cancer screening services, these program s also had the highest total costs.
However, for cervical cancer screening services, programs with mixed structures
actually served more women than decentralized programs at a lower cost.</p><p id="P22">These results could reflect the fact that a mixed program structure allows
programs to specialize on specific activities for which they are the most efficient.
M any mixed programs do not have local health departments that can deliver screening
services. Thus, the most common activities to be outsourced are direct screening and
follow-up services and billing support. There is heterogeneity across programs in
the decision on which activities to keep within the program and which to
decentralize.</p><p id="P23">We excluded tribes and territories from our analysis. Previous cost analyses
of the NBCCEDP have also excluded cost data from tribes and territories for several
reasons [<xref rid="R1" ref-type="bibr">1</xref>, <xref rid="R2" ref-type="bibr">2</xref>, <xref rid="R4" ref-type="bibr">4</xref>]. First, there are
significant demographic and cultural differences between states, tribes, and
territories [<xref rid="R5" ref-type="bibr">5</xref>]. Second, organizational
factors that impact delivery of screening services are different among tribe and
territory grantees of the NBCCEDP as compared to the states [<xref rid="R6" ref-type="bibr">6</xref>]. Lastly, including data from smaller tribe and
territory grantees created instability in national estimates.</p><p id="P24">Our results give some understanding of the relative costs of these program
structures. However, we have a small number of programs for some structures (e.g.,
only ten centralized program s). Furthermore, costs and the number of women served
depend on many factors not included in this analysis. These include the population
of eligible women in the catchment area, availability and costs of clinical and
program staff, and other characteristics specific to the program &#x02018;s target
population [<xref rid="R2" ref-type="bibr">2</xref>, <xref rid="R7" ref-type="bibr">7</xref>&#x02013;<xref rid="R9" ref-type="bibr">9</xref>].</p><p id="P25">In addition, NBCCEDP grantees selected their program structures for specific
reasons, and the delivery structure was not arbitrary or randomly assigned. The
choice of delivery structure may be associated with other factors that affect cost
effectiveness, creating confounding of the measured association. For example, the
NBCCEDP has been shown to exhibit economies of scale, in which the average cost per
woman served decreases as the number of women served increases [10]. If larger
programs tend to choose a mixed delivery structure, this could lead to lower costs
per woman served. Therefore, caution should be used in interpreting the results of
this study.</p></sec><sec id="S13"><title>Conclusion</title><p id="P26">A key decision for disease prevention and control programs is how to
structure the delivery of health services. In the NBCCEDP, delivery structure was
associated with average and incremental cost effectiveness of the state programs. In
particular, a mixed delivery structure was associated with lower costs per woman
served. The results are suggestive that a mixed structure, in which programs perform
activities in which they have a comparative advantage and outsource all other
activities, may be a promising approach to improve the efficiency of the programs.
Programs would need to ensure that such a structure is feasible and appropriate
given their own context.</p></sec></body><back><ack id="S14"><title>Acknowledgments</title><p id="P27">The authors thank Wesley Crouse for his assistance in data collection.</p><p id="P28"><bold>Funding</bold> This study was funded by Contract No. 200-2002-00575 TO
06 and 200-2008-27958 TO 9 from the Centers for Disease Control and Prevention
(CDC). The findings and conclusions in this report are those of the authors and do
not necessarily represent the official position of the CDC.</p></ack><fn-group><fn fn-type="COI-statement" id="FN1"><p id="P29"><bold>Conflict of interest</bold> All authors declare that they have no
conflict of interest.</p></fn><fn id="FN2"><p id="P30"><bold>Publisher&#x02019;s Note</bold> Springer Nature remains neutral
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<volume>17</volume>:<fpage>321</fpage>&#x02013;<lpage>330</lpage><pub-id pub-id-type="pmid">24326873</pub-id></mixed-citation></ref></ref-list></back><floats-group><fig id="F1" orientation="portrait" position="float"><label>Fig. 1</label><caption><p id="P31">NBCCEDP delivery structure</p></caption><graphic xlink:href="nihms-1043920-f0001"/></fig><fig id="F2" orientation="portrait" position="float"><label>Fig. 2</label><caption><p id="P32">Median cost per woman served by program component and delivery structure
(2010$) (The distribution of cost per program component excludes in-kind
contributions. * indicate cost categories that are statistically significantly
different across delivery structures at the 95% CI based on a nonparametric
<italic>k</italic> sample test on the equality of medians in unpaired
data)</p></caption><graphic xlink:href="nihms-1043920-f0002"/></fig><table-wrap id="T1" position="float" orientation="landscape"><label>Table 1</label><caption><p id="P33">Average annual program costs and women served in the NBCCEDP by program
structure (2010 $)</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th align="left" valign="top" rowspan="1" colspan="1"/><th colspan="4" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Breast cancer screening</th><th colspan="4" align="left" valign="top" style="border-bottom: solid 1px" rowspan="1">Cervical cancer screening</th></tr><tr><th align="left" valign="top" rowspan="1" colspan="1">Program structure</th><th align="left" valign="top" rowspan="1" colspan="1">Program costs<sup><xref rid="TFN1" ref-type="table-fn">a</xref></sup></th><th align="left" valign="top" rowspan="1" colspan="1">Women Served</th><th align="left" valign="top" rowspan="1" colspan="1">Average cost effectiveness</th><th align="left" valign="top" rowspan="1" colspan="1">Incremental cost effectiveness</th><th align="left" valign="top" rowspan="1" colspan="1">Program costs<sup><xref rid="TFN1" ref-type="table-fn">a</xref></sup></th><th align="left" valign="top" rowspan="1" colspan="1">Women Served</th><th align="left" valign="top" rowspan="1" colspan="1">Average cost effectiveness</th><th align="left" valign="top" rowspan="1" colspan="1">Incremental cost effectiveness</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Centralized<sup><xref rid="TFN2" ref-type="table-fn">b</xref></sup> (<italic>n</italic> =
10)</td><td align="right" valign="top" rowspan="1" colspan="1">13,849,647</td><td align="right" valign="top" rowspan="1" colspan="1">53,405</td><td align="left" valign="top" rowspan="1" colspan="1">259</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">11,304,013</td><td align="right" valign="top" rowspan="1" colspan="1">44,968</td><td align="left" valign="top" rowspan="1" colspan="1">251</td><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Decentralized (<italic>n</italic> = 17)</td><td align="right" valign="top" rowspan="1" colspan="1">68,142,747</td><td align="right" valign="top" rowspan="1" colspan="1">246,671</td><td align="left" valign="top" rowspan="1" colspan="1">276</td><td align="left" valign="top" rowspan="1" colspan="1">281</td><td align="right" valign="top" rowspan="1" colspan="1">52,015,555</td><td align="right" valign="top" rowspan="1" colspan="1">188,408</td><td align="left" valign="top" rowspan="1" colspan="1">276</td><td align="left" valign="top" rowspan="1" colspan="1">284</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Mixed (<italic>n</italic> = 24)</td><td align="right" valign="top" rowspan="1" colspan="1">79,933,843</td><td align="right" valign="top" rowspan="1" colspan="1">355,285</td><td align="left" valign="top" rowspan="1" colspan="1">225</td><td align="left" valign="top" rowspan="1" colspan="1">109</td><td align="right" valign="top" rowspan="1" colspan="1">41,864,842</td><td align="right" valign="top" rowspan="1" colspan="1">194,120</td><td align="left" valign="top" rowspan="1" colspan="1">216</td><td align="left" valign="top" rowspan="1" colspan="1">&#x02212;1,777</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Total</td><td align="right" valign="top" rowspan="1" colspan="1">161,926,236</td><td align="right" valign="top" rowspan="1" colspan="1">655,361</td><td align="left" valign="top" rowspan="1" colspan="1">247</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">105,184,410</td><td align="right" valign="top" rowspan="1" colspan="1">427,496</td><td align="left" valign="top" rowspan="1" colspan="1">246</td><td align="left" valign="top" rowspan="1" colspan="1"/></tr></tbody></table><table-wrap-foot><fn id="TFN1"><label>a</label><p id="P34">In-kind contributions are not included due to the inability to
validate the quality of those variables</p></fn><fn id="TFN2"><label>b</label><p id="P35">Centralized: DE, ME, MS, NV, OK, OR, TN, VT, WV, WY. Decentralized:
GA, HI, IL, IA, KY, MD, MA, MI, MT, NJ, NY, NC, OH, PA, TX, WA, WI. Mixed:
AL, AK, AZ, AR, CA, CO, DC, CT, FL, ID, IN, KS, LA, MN, MO, NE, NH, NM, ND,
RI, SC, SD, UT, VA</p></fn></table-wrap-foot></table-wrap></floats-group></article>