Introduction
Cancer is the second leading cause of death in the United States (1), and colorectal
cancer (CRC) is the second leading cause of cancer death among cancers that affect
both men and women (2). There is strong evidence that screening for CRC reduces incidence
and mortality rates from the disease either by detecting cancer early, when treatments
are more effective, or by preventing CRC through removal of precancerous polyps (3).
The US Preventive Services Task Force recommends CRC screening for people at average
risk (aged 50–75 y), using either stool-based tests (ie, fecal immunochemical test
[FIT], fecal occult blood test [FOBT], multi-targeted stool DNA test [FIT-DNA]) or
tests that directly visualize the colon (ie, colonoscopy, sigmoidoscopy, or computed
tomographic colonography [CTC]) (3). Despite availability of these tests, a significant
proportion of Americans remain unscreened; in 2016, only 67.3% of age-appropriate
men and women were up to date with screening (4).
Although mortality rates from CRC have declined over time (5), disparities in incidence
and mortality rates continue. In 2014, the most recent year for which data were available,
the incidence of CRC among African Americans was 44.1 cases per 100,000, the highest
rate among racial/ethnic groups (2). Similarly, the mortality rate of CRC among African
Americans was 18.5 cases per 100,000, compared with 13.8 per 100,000 for whites (2).
Disparities in incidence and mortality rates by socioeconomic factors, insurance status,
and geographic areas are also well documented (6–8). With regard to CRC screening,
disparities in screening persist with lower rates among people with low annual household
income, with low educational attainment, and who are Hispanic/Latino (9). The National
Colorectal Cancer Roundtable set an ambitious national target of 80% for CRC screening
in the United States by 2018 (http://nccrt.org/).
The Colorectal Cancer Control Program (CRCCP), funded by the Centers for Disease Control
and Prevention (CDC), aims to increase CRC screening rates among medically underserved
populations (www.cdc.gov/cancer/crccp/index.htm). The CRCCP funds 23 states, 6 universities,
and 1 tribal organization (Figure 1) to partner with health care systems and implement
evidence-based interventions (EBIs) recommended by the Community Preventive Services
Task Force in the Guide to Community Preventive Services (Community Guide) (10). CDC
is leading a comprehensive, multiple methods evaluation to address a range of process,
outcome, and cost-related questions. In this article, we present evaluation results
for the CRCCP’s first program year (PY1), July 2015 through June 2016. Data were collected
from October 2015 through April 2017.
Figure 1
Map Showing Grantees of CDC’s Colorectal Cancer Control Program, Program Year 1, July
2015 through June 2016. Abbreviation: CDC, Centers for Disease Control and Prevention.
There are 22 state grantees (Alabama State Department of Health, Arkansas Department
of Health, California Department of Public Health, Colorado Department of Public Health
and Environment, Delaware Department of Health and Social Services, District of Columbia
Department of Health, Florida Department of Health, Idaho Department of Health and
Welfare, Iowa Department of Public Health, Kentucky Cabinet for Health and Family
Services, Louisiana State University Health Sciences Center, Mary Hitchcock Memorial
Hospital [NH], Maryland Department of Health and Mental Hygiene, Massachusetts Department
of Public Health, Michigan Department of Community Health, Minnesota Department of
Health, Montana Department of Public Health and Human Services, Nevada Division of
Public and Behavioral Health, New York State Department of Health, Oregon Health Authority,
Rhode Island Department of Health, South Dakota Department of Health), 7 university
grantees (University of Chicago, University of Puerto Rico, University of South Carolina,
University of Wisconsin, Virginia Department of Health, Washington State Department
of Health, West Virginia University), and 1 tribal grantee (Great Plains Tribal Chairmen's
Health Board).
Purpose and Objectives
CDC first funded the CRCCP from 2009 through 2015. In this earlier iteration, 22 states
and 4 tribal grantees received funds to provide direct CRC screening services to low-income,
uninsured, or underinsured populations known to have low CRC screening rates (11).
Grantees contracted with primary care and gastroenterological providers to deliver
recommended CRC screening tests. To a lesser degree, grantees implemented Community
Guide–recommended EBIs with the goal of increasing population-level screening rates.
Evaluation of this program focused on monitoring patient-level clinical service delivery,
the types of EBIs implemented (12,13), costs (14,15), and changes in state-wide screening
rates using data from the Behavioral Risk Factor Surveillance System (BRFSS). Evaluators
found that program reach was insufficient to detect impact at the state level.
In response to the findings, CDC redesigned the CRCCP model and funded a new 5-year
grant period beginning in 2015. Under the new model, grantees partner with primary
care clinics to implement EBIs as well as supporting activities (SAs) such as health
information technology (HIT) improvements to support population management for cancer
screening. In contrast to the first CRCCP iteration in which the focus was primarily
on individuals, changing to a health systems model increases public health impact
because reach is extended (16). Grantees use public health data to identify and recruit
primary care clinics serving low-income, high-need populations in their states. Under
this new model, the clinic is the defined measurement unit, with clinic-level screening
rates representing the primary outcome. CDC is conducting a comprehensive evaluation
of the CRCCP to examine program processes, outcomes, and costs. The evaluation aims
to support program improvement, strengthen accountability, and ensure sound policy
decision making. In this article, we address 3 overarching evaluation questions:
How many people are reached through the program?
What EBI/SA activities are implemented by CRCCP grantees?
Does the CRCCP contribute to improved screening rates in participating clinics?
Intervention Approach
In 2010, CDC and the Health Resources and Services Administration (HRSA) commissioned
the National Academy of Medicine to convene experts and examine the integration of
public health and primary care (17). The premise of the study was that capacity in
both public health and primary care could be expanded, and meaningful improvements
in population health, including disparity reduction, could be achieved through effective
integration. The resulting report identified CRC screening as an area for collaboration
between public health and primary care, given the potential alignment in the goals
of the CDC’s CRCCP and HRSA’s federally qualified health centers (FQHCs). CRCCP’s
priority population is served by FQHCs, and CRC screening rates in these clinics are
often low. The national CRC screening rate in 2016 for FQHCs was 39.9% (18). In addition,
HRSA recognized the importance of CRC screening and had recently introduced a new
quality measure for CRC screening that FQHCs were required to report annually. These
circumstances offered the opportunity for FQHCs and local public health agencies to
collaborate and achieve greater increases in screening.
Along with public health and primary care integration, several tenets of effective
public health implementation also support the CRCCP model (19). These include focusing
on defined, high-need populations in which disease burden is highest; establishing
partnerships to support implementation; implementing sustainable health system changes;
using evidence-based strategies to maximize scarce public health resources; encouraging
innovation in adaptation of EBIs/SAs; conducting ongoing, systematic monitoring and
evaluation; and using data for program improvement and performance management.
The program logic model (Figure 2) reflects the activities, outputs, and short-term
outcomes for the CRCCP. Along with health system clinics, grantees partner with organizations
in their states such as primary care associations, the American Cancer Society, and
organizations that can assist with implementation, evaluation, or both. Grantees are
required to implement 2 or more EBIs identified in the Community Guide in each clinic
(Table 1). CDC prioritizes 4 EBIs including patient reminders, provider reminders,
provider assessment and feedback, and reducing structural barriers. Two SAs (ie, small
media, patient navigation) can be implemented alongside the priority EBIs, and grantees
are encouraged to conduct provider education and community outreach to link priority
population members to clinical services. Grantees use HIT to integrate EBIs at the
systems level (eg, provider receives an automated reminder via the electronic health
record [EHR] while seeing a patient) and address issues that interfere with accurate
screening rate measurement (eg, entering screening information in incorrect EHR fields)
(20).
Figure 2
Program Logic Model Showing Activities and Outcomes of the Colorectal Cancer Control
Program, Program Year 1, Centers for Disease Control and Prevention, July 2015 through
June 2016. Abbreviations: CRC, colorectal cancer; EBIs, evidence-based interventions;
SAs, supporting activities.
The CRCCP logic model defines grantee activities that lead to short and intermediate
outcomes. To increase health system CRC screening rates, CRCCP grantees conduct several
activities. Grantees partner with health systems, clinics, and others. Grantees implement
up to 4 priority EBIs including providing patient and provider reminders, giving provider
assessment and feedback, and reducing structural barriers. Grantees implement up to
2 SAs, small media and patient navigation. To help connect community members to screening
services, grantees facilitate community–clinical linkages through targeted outreach,
use community health workers, and link community members to medical homes. Finally,
grantees deliver professional development training to health system clinics and provide
support for improving information technology, including for electronic health record
systems. These activities lead to several short-term outcomes including working partnerships,
implemented EBIs and SAs in clinics, screened priority patient populations, improved
provider knowledge of CRC screening and quality standards, and health system or clinic
data that are used. These short-term outcomes contribute to the intermediate outcome
of increased health system/clinic CRC screening rates.
Table 1
Evidence-Based Interventions and Supporting Activities Used by Grantees, Program Year
1, CDC Colorectal Cancer Control Program, July 2015–June 2016
[CATEGORY NAME]
Definitiona
Evidence-Based Interventions
Patient reminders
Patient reminders or recalls are text-based (ie, letter, postcard, e-mail) or telephone
messages advising people that they are due (reminder) or overdue (recall) for screening.
Reminder messages may be general to address an overall priority population or tailored
to specific individuals.
Provider reminders
Reminders inform health care providers it is time for a patient’s cancer screening
test (reminder) or that the patient is overdue for screening (recall). The reminders
can be provided in different ways, such as patient charts or by e-mail.
Provider assessment and feedback
Provider assessment and feedback interventions both evaluate provider performance
in offering and/or delivering screening to patients (assessment) and present providers
with information about their performance in providing screening services (feedback).
Feedback may describe the performance of a group of providers or an individual provider
and may be compared with a goal or standard.
Reducing structural barriers
Structural barriers are noneconomic burdens or obstacles that impede access to screening.
Interventions designed to reduce these barriers may facilitate access to cancer screening
services by reducing time or distance between service delivery settings and target
populations, modifying hours of service to meet patient needs, offering services in
alternative or nonclinical settings, or eliminating or simplifying administrative
procedures and other obstacles.
Supporting Activities
Small media
Small media include videos and printed materials such as letters, brochures, and newsletters.
These materials can be used to inform and motivate people to be screened for cancer.
They can provide information tailored to specific individuals or targeted to general
audiences.
Patient navigation
Patient navigation is a strategy aimed at reducing disparities by helping patients
overcome barriers to health care. For purposes of the CRCCP, patient navigation is
defined as individualized assistance offered to patients to help overcome health care
system barriers and facilitate timely access to quality screening and follow-up, as
well as initiation of treatment services for people diagnosed with cancer. Patient
navigation includes assessment of patient barriers, patient education, resolution
of barriers, and patient tracking and follow-up. Patient navigators may be professional
(eg, nurse) or lay workers.
Professional development/provider education
Professional development/provider education are interventions directed at health care
staff and providers to increase their knowledge and to change attitudes and practices
in addressing cancer screening. Activities may include distribution of provider education
materials, including screening recommendations, and/or continuing medical education
opportunities.
Community health workers
Community health workers are lay health educators with a deep understanding of the
community and are often from the community being served. Community health workers
work in community settings in collaboration with a health promotion program, clinic,
or hospital to educate people about cancer screening, promote cancer screening, and
provide peer support to people referred to cancer screening.
Abbreviations: CDC, Centers for Disease Control and Prevention; CRCCP, Colorectal
Cancer Control Program.
a
Based on definitions from The Guide to Community Preventive Services.
Evaluation Methods
Using CDC’s Framework for Program Evaluation (21), we developed a comprehensive evaluation
to assess processes and outcomes for the 5-year program period. The 6-step framework
includes 1) engaging stakeholders, 2) describing the program, 3) focusing the evaluation
design, 4) gathering credible evidence, 5) justifying conclusions, and 6) ensuring
use and sharing lessons learned. Stakeholders, including CRCCP grantees, CDC staff,
and health care experts, provided guidance throughout the evaluation planning process.
The program logic model helped to describe the program and focus the evaluation design.
In developing the evaluation plan, evaluators specified key questions and selected
appropriate methods to address them. The multiple methods evaluation includes an annual
grantee survey (Office of Management and Budget [OMB] control no. 0920–1074), a clinic-level
data set (OMB control no. 0920–1074), case studies, cost studies, and use of secondary
data (eg, financial reports). The description of methods centers on the collection,
reporting, and analysis of clinic-level data presented in this article.
For the clinic data set, we developed a detailed data dictionary including record
identification numbers, health system and clinic characteristics, patient population
characteristics, screening rate measures, monitoring and quality improvement activities,
and EBIs/SAs. Five grantees reviewed and provided feedback on the data dictionary.
To support consistent and accurate reporting of clinic-level CRC screening rates,
we developed Guide for Measuring Cancer Screening Rates in Health Systems Clinics
(www.cdc.gov/cancer/crccp/guidance_measuring_crc_screening_rates.htm). The guide provides
information for calculating and validating CRC screening rates using chart review–generated
or EHR-generated rates. Grantees use 1 of the following 4 nationally recognized screening
rate measures: 1) National Committee for Quality Assurance’s Healthcare Effectiveness
Data and Information Set (HEDIS) (www.ncqa.org/hedis-quality-measurement), 2) HRSA’s
Uniform Data System (UDS) (https://bphc.hrsa.gov/datareporting/), 3) Indian Health
Service’s Government Performance and Results Act (www.ihs.gov/crs/gprareporting/),
or 4) the National Quality Forum’s endorsed measure (www.qualityforum.org/Measures_Reports_Tools.aspx).
Each measure has specifications for the numerator and denominator used to calculate
the screening rate. The 4 options are provided to accommodate varying reporting requirements
of grantees’ clinic partners (eg, FQHCs must report UDS screening rates to HRSA).
For any given clinic, grantees must specify at baseline their selected CRC screening
rate measure and 12-month measurement period (eg, calendar year). This same screening
rate measure and measurement period must be used consistently for annual reporting.
We encourage grantees to validate EHR-calculated screening rates using the chart review
methods outlined in the guidance and, when appropriate, to partner with HIT experts
to improve EHR data systems for monitoring and reporting CRC screening rates.
Baseline data are collected at the time a clinic is recruited for CRCCP participation.
Annual data are reported each September following the end of the program year (July–June).
This reporting provides CDC a longitudinal data set to examine EBI/SA implementation
over time and assess changes in CRC screening rates. We developed spreadsheet-based
forms, one each for clinic baseline and annual data. Grantees may use these forms
to collect data directly from clinics or send the forms to clinic staff to complete
and return. The forms incorporate validation features such as specified data ranges
and drop-down response boxes (eg, primary CRC screening test type). The data collection
tools were pilot-tested with 5 grantees for clarity, feasibility, and functionality.
Grantees use a web-based data reporting system, Clinic Baseline and Annual Reporting
Systems (CBARS), developed by CDC’s data contractor, Information Management Services
(IMS), to report clinic data to CDC. CBARS has built-in features to improve data quality
including identifying missing data fields, flagging errors, and assessing discrepancies
between historical and current responses. Data fields (eg, changes in clinic population
size) can be updated at any time. Grantees were trained on the data variables, forms,
and CBARS through CDC-led webinars. We provide on-going technical assistance to grantees
and maintain a summary of frequently asked questions for use by grantees.
The clinic data can be divided into 3 categories: clinic characteristics, process
implementation, and CRC screening rates. Clinic characteristics include clinic type,
clinic size based on screening-eligible (ages 50–75 y) patient count, percentage of
uninsured patients, primary CRC screening test type used by the clinic, availability
of free fecal testing kits for patients, patient-centered medical home recognition,
and rurality based on the US Department of Agriculture’s rural–urban continuum codes
(22).
Process implementation variables include several related to EBI and SA activities.
At baseline, grantees report whether each EBI/SA is in place before CRCCP implementation,
regardless of the quality, reach, or level of functionality. Annually, grantees report
whether the EBI/SA is in place at end of program year and whether CRCCP resources
were used during the program year toward the EBI/SA. We define CRCCP resources as
funds, staff time, materials, or contracts used to contribute to planning, developing,
implementing, monitoring, evaluating, or improving an EBI/SA. If an EBI/SA was reported
as not in place at the end of the program year, grantees report whether planning activities
to implement the EBI/SA in the future were conducted. Analyzing these data allows
CDC to assess whether CRCCP resources were used to implement a new EBI/SA in the program
year (ie, EBI/SA was not in place at baseline), enhance an existing EBI/SA (ie, the
EBI was in place at baseline and CRCCP resources were used to improve the EBI’s implementation
during the program year), or plan for future implementation of the EBI/SA.
Other process implementation variables include the existence of a CRC screening policy
and CRC clinic champion. A champion is an individual who takes a leadership role in
a public health effort. Other variables include frequency of monitoring the CRC screening
rate and frequency of implementation support provided to the clinic. Implementation
support is defined as onsite or other (eg, telephone) contacts with the clinic to
support and improve implementation activities for EBIs/SAs and CRC screening data
quality.
The third category, CRC screening rates, includes the 12-month measurement period,
screening rate measure used, numerator and denominator to calculate the screening
rate, and if chart review is used, the percentage of charts extracted. Grantees also
report a screening rate target for the upcoming program year.
We used descriptive analyses to summarize clinic characteristics and process implementation.
We calculated a weighted average of baseline and annual screening rates across clinics,
where weights were the clinic screen-eligible patient counts, the screening rate denominators
reported at baseline and again at the end of PY1. Screening rate change was calculated
as the difference between the weighted baseline screening rate and weighted PY1 screening
rate. We calculated the number of patients screened at each clinic by multiplying
the clinic screening rate by the respective screen-eligible patient count. Weighted
screening rates and screened patient counts were determined by clinic characteristics
(eg, rurality, size) and by process implementation status (eg, number of EBIs supported
by CRCCP resources). All data analyses were conducted using SAS software, version
9.3 (SAS Institute Inc).
Results
In PY1, 29 of the 30 CRCCP grantees reported data for at least 1 clinic; 1 grantee
did not recruit any clinics in PY1. A baseline and annual record was reported for
each of 418 clinics. We excluded 5 clinics because grantees had terminated the partnership
before the end of PY1, leaving a total of 413 clinics for analysis. Grantees reported
baseline and PY1 annual screening rate data for 387 of the 413 (93.7%) clinics.
The 413 clinics represent 3,438 providers serving a CRC screening-eligible population
of 722,925 patients. The recruited clinics represent 140 unique health systems. Of
the 413 clinics, most were FQHCs or Community Health Centers (CHCs) (71.9%); certified
patient centered medical homes (73.1%); and located in metro areas (72.4%). The clinics
varied in size, with 27.4% of clinics serving fewer than 500 patients; 36.8% serving
between 500 and 1,500 patients; and 35.8% serving more than 1,500 patients (Table
2). The proportion of uninsured patients within clinics also varied; 30.8% of clinics
reported large uninsured patient populations (more than 20%). More than half (52.5%)
used FIT/FOBT as their primary CRC screening test, and 28.8% had access to free fecal
test kits. At baseline, many clinics had at least one EBI (87.9%) or SA (72.6%) already
in place.
Table 2
Characteristics of Participating Primary Care Clinics (N = 413), Program Year 1, CDC
Colorectal Cancer Control Program, July 2015–June 2016
Clinic Characteristic
Percentage of Clinicsa (No.)
Clinic type
Community health center/federally qualified health center
71.9 (297)
Health system/hospital owned
15.7 (65)
Private/physician owned
6.1 (25)
Other primary care facility
6.3 (26)
Patient-centered medical home recognized
Yes
73.1 (302)
No
24.7 (102)
Unknown
2.2 (9)
Ruralityb
Metro
72.4 (299)
Urban
20.1 (83)
Rural
5.8 (24)
Unknown
1.7 (7)
Clinic size (no. of patients)c
Small (<500)
27.4 (113)
Medium (500–1,500)
36.8 (152)
Large (>1,500)
35.8 (148)
Uninsured patient population status (%)
Low (<5)
35.4 (146)
Medium (5–20)
28.1 (116)
High (>20)
30.8 (127)
Unknown
5.8 (24)
Primary colorectal cancer test type
FIT/FOBT
52.5 (217)
Colonoscopy referral
32.2 (133)
Varies by provider
12.3 (51)
Unknown
2.9 (12)
Free fecal testing kits
Yes
28.8 (119)
No
64.7 (267)
Unknown
6.5 (27)
Number of evidence-based interventions in place at baseline
0
12.1 (50)
1
20.1 (83)
2
16.9 (70)
3
30.3 (125)
4
20.6 (85)
Number of supporting activities in place at baseline
0
27.4 (113)
1
27.8 (115)
2
22.8 (94)
3
21.8 (90)
4
0.2 (1)
Abbreviations: CDC, Centers for Disease Control and Prevention; FIT/FOBT, fecal immunochemical
test/fecal occult blood test.
a
Percentages are unweighted and may not sum to 100% because of rounding.
b
Based on US Department of Agriculture’s rural–urban continuum codes.
c
Based on count of eligible patients aged 50 to 75 years.
During PY1, grantees used CRCCP resources to implement new or to enhance EBIs in 95.2%
of clinics. Patient reminder activities were supported most frequently (73.1%), followed
by provider assessment and feedback (64.9%), reducing structural barriers (53.0%),
and provider reminders (47.7%) (Table 3). All 4 EBIs were more often enhanced than
implemented as a new activity. CRCCP resources were used less often to plan future
EBI activities.
Table 3
Status of Process Implementation (Evidence-Based Interventions and Supporting Activities)
Performed by Primary Care Clinics (N = 413), Program Year 1a, CDC Colorectal Cancer
Control Program, July 2015–June 2016
Activity
Clinics Using CRCCP Resourcesb
Implemented New Activity
Enhanced Existing Activity
Planning-Only Activity
Unknown
% (No.)
Evidence-based interventions
95.2 (393)
—
—
—
—
Patient reminders
73.1 (302)
29.5 (89)
54.3 (164)
12.9 (39)
3.3 (10)
Provider reminders
47.7 (197)
20.3 (40)
64.0 (126)
8.6 (17)
7.1 (14)
Provider assessment and feedback
64.9 (268)
30.2 (81)
51.9 (139)
10.8 (29)
7.1 (19)
Reducing structural barriers
53.0 (219)
29.2 (64)
38.8 (85)
30.1 (66)
1.8 (4)
Supporting activities
86.4 (357)
—
—
—
—
Provider education
57.6 (238)
35.7 (85)
42.4 (101)
19.8 (47)
2.1 (5)
Small media
69.0 (285)
43.2 (123)
42.8 (122)
10.2 (29)
3.9 (11)
Community health workers
11.6 (48)
27.1 (13)
25.0 (12)
47.9 (23)
0
Patient navigators
43.8 (181)
19.3 (35)
31.5 (57)
48.6 (88)
0.6 (1)
Abbreviations: CDC, Centers for Disease Control and Prevention; CRCCP, Colorectal
Cancer Control Program.
a
Percentage estimates are unweighted and may not sum to 100% because of rounding.
b
Clinics could use CRCCP resources to implement, enhance or plan for the chosen activity.
CRCCP resources were used toward SAs in 86.4% of clinics. Resources were used to support
small media most frequently (69.0%), followed by provider education (57.6%) (Table
3). Only 11.6% of clinics used resources for supporting community health workers.
However, nearly half of the clinics conducted planning activities for future implementation
of community health workers (47.9%) and patient navigators (48.6%). Provider education
was more often enhanced than newly implemented (42.4% vs 35.7%), as were patient navigators
(31.5% vs 19.3%).
Most clinics reported having a CRC screening champion (78.7%) and a CRC screening
policy (72.6%) in place at the end of PY1 (Table 4). Most clinics received implementation
support from the CRCCP grantees on a weekly (12.3%) or monthly (77.7%) basis. Clinics
monitored CRC screening rates at different intervals, including monthly (63.4%) or
quarterly/semi-annually/annually (34.5%). Most clinics (73.1%) performed screening
rate validation using chart review or other methods as part of CRCCP implementation.
Table 4
Other Program Implementation Factors in Participating Clinics (N = 413), Program Year
1, CDC Colorectal Cancer Control Program, July 2015–June 2016
Other Program Element
Percentage of Clinicsa (No.)
Colorectal cancer screening champion
Yes
78.7 (325)
No
18.9 (78)
Unknown
2.4 (10)
Colorectal cancer screening policy
Yes
72.6 (300)
No
25.7 (106)
Unknown
1.7 (7)
Frequency of implementation support
Weekly
12.3 (51)
Monthly
77.7 (321)
Quarterly, semi-annually, or annually
9.9 (41)
Frequency of screening rate monitoring
Monthly
63.4 (262)
Quarterly, semi-annually, or annually
34.5 (151)
Performs screening rate validation
Yes
73.1 (302)
No
18.9 (78)
Unknown
8.0 (33)
Abbreviation: CDC, Centers for Disease Control and Prevention.
a
Percentage estimates are unweighted; do not necessarily sum to 100% because of rounding.
Table 5 provides screening rates overall and by key clinic characteristics at baseline
and PY1, as well as screening rate changes from baseline to PY1 for the 387 clinics
reporting baseline and PY1 screening rates. A total of 640,086 patients were eligible
for screening at baseline, and 631,634 patients were eligible at the end of PY1. The
average screening rate increased during PY1 by 4.4 percentage points from baseline
(42.9%) to PY1 (47.3%). The total number of patients up to date with CRC screening
was 274,694 at baseline and 298,790 at the end of PY1, an increase of 24,096 patients,
which represents 3.8% of the baseline eligible patient counts.
Table 5
Colorectal Cancer Screening–Eligible Patient Population Counts and Weighted Screening
Counts, Changes From Baseline to Program Year 1a (N = 387), CDC Colorectal Cancer
Control Program, July 2015–June 2016
Characteristic
No. of Clinics
Baseline Screening–Eligible Patient Counts
PY1 Screening-Eligible Patient Counts
Baseline SRb (%)
Baseline Screened Patient Counts
PY1 SRb (%)
PY1 Screened Patient Counts
Changec in SR
Change in Screened Patient Countsd (%e)
Overall
387
640,086
631,634
42.9
274,694
47.3
298,790
4.4
24,096 (3.8)
Clinic type
FQHC/CHC
284
373,405
372,878
36.5
136,469
41.9
156,417
5.4
19,948 (5.3)
Health system/hospital
58
180,498
176,541
58.9
106,368
61.5
108,554
2.6
2,186 (1.2)
Private/physician owned
22
48,868
44,416
42.3
20,688
41.5
18,417
−0.8
−2,271 (−4.6)
Other primary care facility
23
37,315
37,799
29.9
11,170
40.7
15,402
10.8
4,232 (11.3)
Rurality
f
Metro
280
493,124
491,916
43.8
216,209
47.7
234,610
3.9
18,400 (3.7)
Urban
77
112,765
107,890
41.9
47,256
47.8
51,586
5.9
4,330 (3.8)
Rural
23
21,833
18,529
38.3
8,363
50.3
9,313
12.0
949 (4.3)
Unknown
7
12,363
13,300
23.2
2,865
24.7
3,281
1.5
416 (3.4)
Clinic size (no. of patients)
Small (<500)
103
31,108
35,387
28.0
8,701
29.2
10,328
1.2
1,627 (5.2)
Medium (500–1,500)
142
125,523
126,694
32.7
40,990
40.4
51,179
7.7
10,189 (8.1)
Large (>1,500)
142
483,455
469,553
46.5
225,003
50.5
237,283
4.0
12,280 (2.5)
Uninsured patient population status (%)
Low (<5)
140
305,362
303,681
48.4
147,748
51.5
156,460
3.1
8,712 (2.9)
Medium (5–20)
113
165,359
160,929
39.1
64,664
46.0
74,072
6.9
9,408 (5.7)
High (>20)
113
139,007
143,942
38.7
53,825
41.4
59,556
2.7
5,731 (4.1)
Unknown
21
30,358
23,082
27.9
8,457
37.7
8,702
9.8
245 (0.8)
Primary CRC test type
FIT/FOBT
212
249,597
249,057
32.7
81,634
39.0
97,028
6.3
15,395 (6.2)
Colonoscopy
118
317,712
311,704
52.4
166,565
55.1
171,617
2.7
5,053 (1.6)
Varies by provider
47
60,829
51,697
39.1
23,765
43.6
22,529
4.5
−1,236 (−2.0)
Unknown
10
11,947
19,177
22.9
2,730
39.7
7,615
16.8
4,885 (40.9)
Free fecal testing kits
Yes
117
176,019
167,969
35.5
62,563
42.2
70,800
6.7
8,237 (4.7)
No
247
411,856
415,706
44.7
184,044
48.3
200,812
3.6
16,768 (4.1)
Unknown
23
52,211
47,959
53.8
28,087
56.7
27,178
2.9
−909 (−1.7)
Number EBIs supported with CRCCP during PY1
0
19
30,249
31,748
48.4
14630
48.6
15,434
0.2
805 (2.7)
1
109
230,943
233,202
50.6
116898
52.1
121,432
1.5
4,533 (2.0)
2
66
113,239
113,127
38.8
43943
43.1
48,779
4.3
4,836 (4.3)
3
82
95,580
99,989
42.4
40549
50.4
50,363
8.0
9,814 (10.3)
4
111
170,075
153,569
34.5
58674
40.9
62,782
6.4
4,108 (2.4)
CRC screening champion
Yes
301
523,200
521,724
43.1
225,517
48.0
250,475
4.9
24,957 (4.8)
No
76
95,419
89,567
39.8
38,011
40.5
36,270
0.7
−1,742 (−1.8)
Unknown
10
21,467
20,344
52.0
11,166
59.2
12,046
7.2
880 (4.1)
CRC screening policy
Yes
294
456,376
447,686
42.2
192,603
47.7
213,766
5.5
21,163 (4.6)
No
89
181,604
181,350
45.1
81,913
46.6
84,553
1.5
2,640 (1.5)
Unknown
4
2,105
2,598
8.5
179
18.1
471
9.6
292 (13.9)
Abbreviations: CDC, Centers for Disease Control and Prevention; CRC, colorectal cancer;
CRCCP, Colorectal Cancer Control Program; EBIs, evidence-based interventions; FIT/FOBT,
fecal immunochemical test/fecal occult blood test; FQHC/CHC, federally qualified health
center/community health center; PY1, program year 1.
a
Restricted to clinics that provided both baseline and PY1 screening rates.
b
Screening rate averages were weighted by screening eligible patient counts.
c
Change was calculated as the percentage point difference between baseline screening
rate and PY1 screening rate.
d
Change was calculated as the difference between PY1 screened patient counts and baseline
screened patient counts.
e
Change in number of patients from baseline to PY1 as percentage of baseline eligible
patient counts.
f
Based on US Department of Agriculture’s rural–urban continuum codes.
Baseline screening rates varied by clinic type. Health system/hospital clinics had
a higher baseline screening rate (58.9%) than FQHCs/CHCs (36.5%), private/physician
owned clinics (42.3%) or other primary care facilities (29.9%). During PY1, FQHCs/CHCs
and other primary care facilities observed a larger increase in screening rates (5.4
and 10.8 percentage points, respectively), than health system/hospital clinics and
private/physician owned clinics (2.6 and −0.8 percentage points, respectively).
Although rural clinics had the lowest average baseline screening rate at 38.3%, their
screening rate during PY1 increased by 12.0 percentage points, higher than those of
metro or urban clinics. The baseline screening rate was highest among large clinics
(46.5%), followed by medium clinics (32.7%) and small clinics (28.0%). The average
screening rate increase during PY1 was greatest among medium-sized clinics (7.7 percentage
points) compared small and large clinics (1.2 and 4.0 percentage points, respectively).
Baseline screening rates and screening rate increases also varied by the proportion
of clinic patients that were uninsured. Among clinics reporting their uninsured patient
population, the baseline screening rate was lowest (38.7%) among clinics with a high
uninsured patient population (more than 20%). However, clinics with 5% to 20% uninsured
patients had the largest percent increase in screening (6.9 percentage points) during
PY1. Among clinics reporting primary screening test type, clinics using FIT/FOBT observed
greater screening rate increases (6.3 percentage points) than those clinics primarily
using colonoscopy (2.7 percentage points). Clinics that reported having free fecal
testing kits available for patients observed greater screening rate increases than
those without (6.7 vs 3.6 percentage points).
Although PY1 screening rates varied by the number of EBIs newly implemented or enhanced
in PY1, the highest screening rate increases were observed among clinics newly implementing
or enhancing 3 or 4 EBIs (8.0 and 6.4 percentage points, respectively). Among clinics
reporting their status of CRC screening champion or CRC screening policy in place
at the end of PY1, clinics with a champion or screening policy reported greater increases
in screening rates (4.9 and 5.5 percentage points, respectively) than clinics without
them (0.7 and 1.5 percentage points, respectively).
Implications for Public Health
With the goal of increasing CRC screening and reducing disparities, the CRCCP integrates
public health and primary care, implementing evidence-based strategies in clinics
to achieve sustainable health systems change. Early results from our PY1 evaluation,
including changes in screening rates, suggest the CRCCP is working; program reach
was measurable and substantial, clinics enhanced EBIs in place or implemented new
ones in clinics, and we observed an increase in the overall average screening rate.
Our data suggest that the CRCCP is reaching its intended population. At baseline,
the screening rate was low, at only 42.9%, and nearly three-quarters of the 413 clinics
were FQHCs/CHCs. Of interest, 92.5% of clinics were located in metro or urban areas.
Baseline screening rates were lowest in rural clinics, and evidence indicates that
death rates for CRC are highest among people living in rural, nonmetropolitan areas
(23); therefore, expansion of the program to rural areas is important. The diversity
observed in other clinic characteristics such as clinic size (patients aged 50–75
y) and percentage of uninsured patients was expected, given the varied and unique
contexts in which grantees are operating. Reach will continue to expand as additional
clinics participate in years 2 through 5.
Consistent with the new model, grantees committed CRCCP resources during PY1 toward
EBI implementation in 95% of all participating clinics. However, less than 50% of
clinics used CRCCP resources for provider reminders in PY1. Provider reminders can
increase screening rates by a median of 15.3% (24). If reminders are integrated into
an electronic health system, the activity is sustainable. Consequently, grantees could
prioritize provider reminders for clinics where implementation is poor or not yet
instituted.
Among the 387 clinics for which screening rate changes were calculated, 50.0% had
either 3 or 4 EBIs in place at the end of the first program year. Using multiple EBIs
that combine different approaches to increase community demand and access to cancer
screening leads to greater effects (25). Grantees could be encouraged to newly implement
or improve EBIs consistent with this finding. Interestingly, large numbers of clinics
had EBIs in place at baseline, therefore, grantees more often expended CRCCP resources
to enhance implementation of existing EBIs than establish new ones. That resources
were used toward these existing EBIs suggests the potential importance of public health
intervention to improve and scale up implementation of these activities. A case study
is under way that will help us understand the ways in which EBIs are enhanced.
Grantees complemented EBI implementation with extensive SAs; CRCCP resources were
used for SAs in more than 80% of clinics. Small media, which was used most often,
can be distributed with patient reminders by community health workers and patient
navigators to strengthen those strategies. Among the 181 clinics where CRCCP resources
were used toward patient navigators, nearly 50% used them for planning rather than
implementation, suggesting that new patient navigator programs may be started in PY2.
Evidence indicates that patient navigation increases CRC screening (26–28).
In the first program year, the overall screening rate increased by 4.4 percentage
points. The CRCCP’s PY1 overall screening rate of 47.3% is much lower than the commonly
cited 67.3% from the 2016 BRFSS. These results again confirm that grantees are working
with clinics serving the intended populations and also indicate the significant gap
in CRC screening rates between those reached by the CRCCP and the US population overall.
Among FQHCs/CHCs participating in the CRCCP, the screening rate increased by 5.4 percentage
points in PY1, compared with 1.6 percentage points for FQHCs nationally during 2015–2016
(https://bphc.hrsa.gov/uds/datacenter.aspx?year=2015). Given that PY1 included several
or more months dedicated to program start-up (eg, grantees putting contracts in place,
hiring staff), the time for EBI/SA implementation was limited. Consequently, we may
observe more substantial increases in screening rates going forward as interventions
are in place for a longer period. At the same time, given that 52.5% of clinics primarily
used FIT/FOBT tests, there is a challenge of ensuring annual rescreening to maintain
current levels.
The screening rate changes observed during the CRCCP PY1 varied by clinic characteristics
and other process implementation factors. For instance, clinics with champions and
screening policies had higher screening rate increases than those without a champion
or policy. Many public health studies have established that champions contribute to
improved outcomes (29). Screening policies may be associated with more organized screening
approaches in which higher screening rates are likely. Of note, clinics with 3 or
more EBIs in place at the end of PY1 had higher screening rate increases than clinics
with fewer EBIs, suggesting a possible dose effect. This is similar to what the Community
Guide has reported (25). Longitudinal data will allow CDC to examine trends and better
assess factors associated with screening rate changes.
The evaluation of federally funded programs in multiple US states is challenging,
given the complexity and diversity of programs and strategic implementation in the
unique environment of individual states. CDC’s evaluation approach addresses these
challenges by working closely with grantees to collect clinic-level process and outcome
data. Involving stakeholders, developing strong data collection and reporting systems,
and communicating frequently with grantees have helped CDC institute a strong evaluation
and better understand contextual factors that affect the data interpretation. Most
importantly, the evaluation design allows CDC to track implementation progress and
outcomes in a more timely fashion and make programmatic adjustments as needed.
We noted some limitations of this PY1 evaluation. First, some interventions were in
place for less than a year, given the time needed to start programs. Second, EHRs
often needed improvements to produce accurate screening rates at the population level,
leaving room for further improvements in the accuracy and reliability of screening
rate measurement. Technical assistance provided to clinics played a crucial role in
improving their capacity to report quality data. Third, given real-world program implementation,
we cannot isolate the effects of factors, such as temporal trends in CRC screening,
on clinic screening rates. However, future years of longitudinal data will help identify
factors associated with screening rate changes. Finally, improvement of screening
delivery was beyond the scope of this evaluation.
Other aspects of our evaluation are under way. CDC is completing qualitative case
studies with a subset of grantees to learn more about implementation, including how
EBIs/SAs are selected and prioritized. An economic study of program implementation
with 11 of the CRCCP grantees is in progress. The study will provide valuable information
about costs and return on investment of the chosen EBIs. Sustainability of public
health activities is essential to achieving long-term health outcomes. Therefore,
CDC is examining whether the CRCCP model leads to sustained process and outcomes after
CRCCP resources end. In particular, we are assessing whether EBIs/SAs become institutionalized
health systems changes within the partner clinics without having to rely on CRCCP
resources. When intervention sustainability is achieved, grantees could redirect CRCCP
resources to additional clinic sites, leading to expanded reach and impact of the
program.
The CRCCP shows promise, as evidenced by PY1 results. Grantees have collaborated with
more than 400 clinics, integrating public health interventions in primary care settings
by implementing EBIs/SAs and increasing CRC screening rates. The frequency of implementation
support provided to clinics, screening rate monitoring, and screening rate validation
suggest substantial engagement between grantees and clinics and may reflect a high
intensity of CRCCP process implementation contributing to outcomes. We anticipate
increasing reach over time as EBIs are sustained, allowing program resources to be
shifted to additional clinics. Rural clinics, where screening rates were especially
low, are an area for expansion. Early evaluation results suggest that several factors
may support greater screening rate increases including implementing multiple EBIs,
making free FOBT/FIT kits available, engaging a clinic champion, and having a CRC
screening policy in place. CDC’s support may also improve EHR data capture to achieve
more accurate measurement of screening outcomes. Integrating evidence-based public
health activities in primary care settings can help achieve needed increases in CRC
screening among underserved populations.