Personalized Risk-based Follow-up of Cervical Cancer Screening in Practice (PREDICT), Randomized Control Trial
Phase: NA
Conditions: Cervical Cancer Screening
Sponsor: Massachusetts General Hospital

 
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Version 1, June 27, 2024] 
 
 
 
 
 
 
 
PREDICT (Personalized Risk-based Follow-up of Cervical Cancer Screening in Practice), RCT 
NCT#: TBA 
Detailed Protocol version: February 18, 2025 
 
 

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Institutional Review Board 
Intervention/Interaction Detailed Protocol 
 
 
Principal Investigator: 
Jennifer S. Haas, MD & Steven Atlas, MD 
 
Project Title: 
PREDICT (Personalized Risk-based Follow-up of Cervical Cancer 
Screening in Practice), RCT 
 
Version Date: 
February 18, 2025 
 
 
Version Name/Number: 
1 
 
 
For Intervention/Interaction studies, submit a Detailed Protocol that includes the following sections.  If 
information in a particular section is not applicable, omit and include the other relevant information.   
 
1. 
 Background and Significance 
Cervical cancer remains a public health burden, particularly for underserved populations. 
Cervical cancer mortality in the United States (US) has declined over the past 20 years due 
largely to improved preventive care and treatment of precancerous lesions.1 Today, cervical 
cancer is highly preventable when detected early and managed appropriately. Nevertheless, it 
continues to be a significant public health concern in the US with 13,960 new cervical cancer 
cases diagnosed and 4,310 cervical cancer deaths.2 In addition, an estimated 196,000 cases of 
high-grade cervical pre-cancer are diagnosed each year.3 Cervical cancer is most often 
diagnosed in under-screened individuals or after a failure to follow up on abnormal screening 
results.1-3 Racial/ ethnic and socioeconomic disparities in cervical cancer screening, incidence, 
and mortality persist in the US.2,4 Even among individuals who receive screening, the benefits 
are only realized if coupled with timely and appropriate surveillance and diagnostic evaluation. 
Our work shows that unfortunately many individuals with an abnormal cervical cancer screening 
result do not receive timely follow-up.5-8  
Evolution of cervical cancer screening and management (CCSM). The 2018 US Preventive 
Services Task Force (USPSTF) screening guidelines recommend 3 strategies to screen for 
cervical cancer (Papanicolaou [Pap] test alone (with option of reflex human papilloma virus 
[HPV] testing), Pap/ HPV co-testing, and HPV alone).9 In 2019, the American Society for 
Colposcopy and Cervical Pathology (ASCCP) revised guidelines for managing abnormal 
cervical cancer screening results.10 The 2019 guidelines reflect the principle of “equal 
management for equal risks.”11 Algorithms for these guidelines were developed through 
analyses of 1.5 million observations from the Kaiser Permanente Northern California cohort, a 
system with strong implementation infrastructure that may not be generalizable to other 
settings.11 The 2019 guidelines use information from a patient’s current and prior screening and 
surveillance history to make follow-up recommendations based on their risk of developing 
cervical squamous intraepithelial neoplasia grade 3 or more severe diagnoses (CIN 3+) in the 
future. Risk-based guidelines are explicitly designed to maximize benefits of cancer prevention 
while minimizing harms of over-testing and over-treatment.10,12 The ASCCP guidelines establish 
clinical action thresholds recommending immediate colposcopy/ treatment or surveillance 

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intervals (1, 3 or 5-years) based on the estimated risk of CIN3+ associated with a person’s 
current and historical CCSM results.10 The complexity of these evidence-based guidelines make 
it challenging for practitioners to implement in practice. Furthermore, while women with 
adequate prior screening can stop screening at age 65, many women may not meet exit 
criteria13 and “inappropriate exit” may contribute to rising cervical cancer rates and higher stage 
disease in this age group.14,15 Roughly 20% of US cervical cancer cases currently occur in 
women older than 65 years, and primarily affect Black and Hispanic individuals.2 
Complexity of implementing of cervical cancer management in clinical practice. The need 
to estimate the risk of developing CIN3+ in the future to determine the appropriate management 
strategy is complicated and error-prone to implement in clinical practice. The ASCCP guidelines 
contain hundreds of algorithms to address permutations of age, comorbidity and prior/ current 
cervical cancer screening history. While the ASCCP has created a phone app to enable 
practitioners to manually enter results and see the recommended next step, this approach is not 
feasible for busy primary care practitioners (PCPs) and isn’t scalable to manage 
populations.16,17 Cervical screening tests/ procedures are often not captured as coded data in 
electronic health records (EHRs),18 so they cannot easily be used for risk estimation. Patients 
who experience barriers to access, including those who identify as Black or Hispanic, those with 
incomes at or below the poverty threshold, and the uninsured may not receive the full benefits of 
risk based-management because their prior screening history may be unknown to their current 
clinical team.6,19,20 Preliminary analysis of our data from Population-based Research to Optimize 
the Screening Process (PROSPR) finds that more than a third of patients who received care in 
3 diverse healthcare systems, including sites participating in this proposed project, had an 
unknown cervical cancer screening history prior to the patient’s index abnormal test during the 
study period (unpublished data). As the ASCCP guidelines are a harbinger of other 
personalized, risk-based algorithms for cancer screening and management, developing systems 
and strategies to implement these complex guidelines in practice are critical. 
Clinical decision support (CDS) is critical to the implementation of cervical screening 
guidelines. Recognizing the complexity of implementing the CCSM guidelines in clinical 
practice, the Centers for Disease Control and Prevention’s (CDC) Division of Cancer Prevention 
and Control has developed a CDS tool that provides CCSM guidance using several standard 
health interoperability standards including Fast Healthcare Interoperability Resources (FHIR).21 
This tool is open-source, and the execution of the ~2000 clinical permutations has been 
validated. 21 The CDS tool provides practitioners with CCSM recommendations based on the 
current guidelines from USPSTF and the ASCCP. 
While the CDC’s CCSM CDS tool transforms USPSTF and ASCCP guidelines into shared, 
interoperable, and executable algorithms, use in clinical practice requires integration into local 
infrastructure, most notably the availability of coded data for cervical screening and diagnostic 
results. We have created and validated coded algorithms to convert text CCSM results into 
coded data,8,18 allowing us to integrate the CDS tool. Embedding this open source, interoperable 
CDS tool in clinical practice settings will support disseminating guideline-recommended care; 
yet without evaluation of additional strategies it is unlikely that an informatics solution alone will 
result in timely care for diverse patients in a variety of health care settings.5,8 
Multilevel barriers to risk-based management recommendations. Responsibility for 
comprehensive screening and follow-up falls to the ordering practitioner, typically a PCP. 
Unfortunately, few PCPs/ primary care practices have systems to implement personalized risk 
assessment or promote follow-up.16,22 PCPs face the challenge managing populations of 
patients and coordinating care with involved specialists. The transition from screening to 
diagnostic evaluation often requires a transfer of role/ responsibility between primary and 

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specialist care.23,24 For example, colposcopy should follow “high risk” abnormal Pap or HPV 
screening results to detect early cervical cancers and to detect and treat precancerous lesions 
before they progress to cancer.10  
Patient barriers often begin with not being informed about how and when they will be notified of 
test results. Patients may not understand the importance of a result or have difficulty negotiating 
the process for obtaining recommended follow-up. Patient barriers such as language, literacy, 
financial resources, anxiety, logistical challenges such as transportation and scheduling, and 
knowledge and beliefs about tests and treatments have been shown to result in delays in follow-
up of abnormal screening results.25-28  
While patients and practitioners may take individual responsibility, effective CCSM requires 
that the patient and PCP function effectively with practice staff and relevant specialists who 
together comprise a care team. The World Health Organization defines a team as “a 
distinguishable set of two or more people who interact dynamically, interdependently and 
adaptively towards a common and valued goal, who have been assigned specific roles or 
functions to perform, with specialized and complementary knowledge and roles, and act as a 
collective unit.”29 Effective team function can benefit the patient (improved outcomes and 
satisfaction), PCP and specialist (greater role clarity and job satisfaction), and health system 
(efficient resource use).30 Individuals and care teams function within the context of a health 
system, with unique leadership, culture and policies. Systems include infrastructure to support 
care through health information technology (IT), which can help or hinder the individual and 
team functions. Systems adopt various approaches to measure and incentivize care that may 
directly or indirectly influence the follow-up of abnormal screening results.31  
Summary and potential impact of proposed study. Cancer screening and management 
guidelines are moving from a “one size fits all” approach to one that is tailored to an individual. 
CCSM is the first example of a guideline that incorporates longitudinal screening history to 
personalize risk assessment. While a personalized approach offers the promise of enhancing 
the balance of benefits vs. harms of screening and management, this ideal can only be realized 
through strong systems to support care delivery. Without IT tools that integrate personalized 
algorithms with care delivery, more errors of judgement may occur if practitioners and patients 
are confused about appropriate next steps. We hypothesize that delivering risk based CCSM to 
all eligible individuals will require: 1) using a generalizable CDS tool that is validated and open 
source to implement the ASCCP recommendations; 2) leveraging a system level health IT 
platform to present risk-based, personalized recommendations; and 3) offering a stepped care 
approach that individually engages patients and PCPs; and 4) enhances team-functioning, with 
increasing intensity over time (Figure 1). Accordingly, we propose to develop, implement, and 
rigorously test PREDICT (Personalized Risk-based Follow-up of Cervical Cancer Screening 
in Practice) within 4 primary care practice networks. 

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A. INNOVATION AND SCIENTIFIC PREMISE 
Our scientific premise builds from conceptual 
models,32-36 guideline-recommended CCSM, a 
disseminable informatics approach, and our 
prior work both on cancer screening and the 
implementation of pragmatic trials in care 
settings. We will evaluate the effectiveness and 
implementation of our intervention, including: 1) 
visit-based delivery of CCSM reminders to 
patients and practitioners; and 2) population 
outreach and practitioner support for scheduling 
follow-up care. We will deploy the intervention 
across distinct primary care networks and patient 
populations. 
Our intervention content and strategy of 
leveraging technology to generate multiple 
approaches to outreach and engagement is 
innovative. We will evaluate methods of 
delivering guideline-recommended care, comparing visit- and population-based approaches. To 
maximize engagement, we will useinnovative health IT to integrate with patients’ EHR records.8  
Our intervention delivery is highly scalable. By using an open source CDS tool, our 
approach is broadly disseminable. We propose to integrate the CDC CCSM tool using national 
data standards (described in Section C4), endorsed by the 21st Century Cures Act Final Rule 
to support seamless and secure access, exchange, and use of electronic health data.37  
 
2. 
Specific Aims and Objectives  
 
Specific Aim 1: To evaluate the effectiveness of the multilevel system, team and 
individual components of PREDICT vs. standard care by conducting a 3-arm cluster 
randomized controlled trial of individuals who are due for cervical cancer screening and 
management. 
Specific Aim 2: Guided by Evaluation (RE-AIM QuEST) and Determination (CFIR) 
frameworks, we will assess the reach, adoption, implementation and maintenance of 
PREDICT. To evaluate the implementation of PREDICT within the 4 networks and to inform and 
facilitate the dissemination of the intervention beyond the participating networks. 
 
 
3. 
General Description of Study Design 
 
PREDICT components include: 1) system redesign to deliver CCSM recommendations to a 
population of eligible individuals (build and integration of system already approved in MGB 
Protocol#2024P000973 2) support individual patient and practitioner engagement, and 3) 
enhances team coordination through an efficient “stepped care” approach. This will be 
compared to standard care by the patient’s care team using a 3-arm, pragmatic randomized 
design (with randomization at the clinic level) that will allow us to examine the marginal and 
cumulative effectiveness of the intervention components. 
Step 1: Automated Practitioner Functionality
 
Updated health prevention reminders 
 
Adding problem list terms 
 
Actionable “smart sets” for ordering followup 
testing/referrals 

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The study will be conducted in four primary care networks that are part of Mass General 
Brigham [MGB]: two affiliated with academic medical centers (Brigham and Women’s Hospital 
[BWH] and Massachusetts General Hospital [MGH]), and two affiliated with community hospitals 
(Newton Wellesley Hospital [NWH] and North Shore Medical Center [NSMC]): (Table 1) 
 
 
We will perform a 3-arm cluster RCT with randomization done at the primary care practice-level, 
across the 4 participating practice networks. We have chosen this level of randomization to 
reduce the risk of cross-arm contamination; it would also be logistically complicated for the 
practices to have different patients randomized to different intervention components. Patients 
followed by gynecologists will receive 
intervention components based on the 
randomization to the patient’s PCP 
practice. Randomization will be stratified 
based on: (1) primary care network, (2) 
practice size (e.g., number of women 21-
70 years), and (3) percent insured by 
Medicaid or dual eligible. Prior RCTs with 
randomization at the practice level have 
resulted in good balance of patient and 
practitioner characteristics across arms.8,38-
42 The 3-arm design is summarized in Figure 2 and will allow us to compare “standard care” 
(Arm 1) to two intervention arms that represent the sequential addition of: only the systems level 
components that provide visit-based reminders to individual patients and practitioners (Arm 2), 
and the addition of the team-level population outreach and practitioner support (Arm 3). Given 
our stepped care approach, this randomization scheme will allow us to compare the cumulative 
addition of each level of intervention to standard care as well as the marginal effect of each 
additional level to the prior group. 
 
 
4. 
Subject Selection 
 
Inclusion criteria:  
Individuals who:  
1) have a cervix and are 21-70 years old. The inclusion of those up to age 70 is intended to 
identify individuals whose prior history does not meet screening exit criteria,13 and would 
warrant surveillance or diagnostic care even though women with adequate prior screening can 
stop at age 65. 
2) receive care at a participating primary care practice (i.e. PCP team visit within the past 3 
years),  
3) have had a Pap and/ or HPV test within the past 3.5 years, and  
4) have a CCSM result that suggests a 5-year risk of developing CIN3+ that warrants 
surveillance at 1 or 3 years, diagnostic colposcopy, or treatment (Figure 3) 

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Personalized individual 
risk will be assessed by 
applying algorithms 
based on CDC’s CDS 
tool.. The need for follow-
up will be determined by 
the lack of an appropriate 
clinical test, diagnostic 
procedure or treatment 
as documented in the 
EHR within the specified time. Since the Pap and/ or HPV tests used by the CDS tool were 
done by an MGB-affiliated provider, we anticipate that most follow-up will also occur with the 
MGB system. 
 
Exclusion criteria: Individuals who: 1) were diagnosed with cervical cancer/ CIN3+ prior to the 
most recent screening Pap or HPV test; 2) have had their cervix removed; or 3) are not English 
or Spanish-speaking.  
 
This trial is testing a “care enhancement.” We are requesting a waiver of informed consent given 
the large number of subjects distributed over 47 primary care practices. Randomization will be 
done at the practice level and individual patients will not be approached for recruitment. The 
outcomes for the main trial will be assessed using data from the electronic health record. 
 
(See Study Procedures section 6 for more information) 
 
5. 
Subject Enrollment 
 
The trial is testing a “care enhancement” and is minimal risk; we are requesting a HIPPA waiver 
given the large number of subjects distributed over 47 primary care practices.The HIPAA waiver 
is for the data collection to meet the aims of the research, not just for recruitment. Due to the 
way our IT system is configured, we anticipate that we could review up to 20,000 patient charts 
study-wide. Not all of the patient charts reviewed will be deemed eligible. All patients will remain 
under the care of their primary care team and the intervention components will be delivered in 
addition to those individuals who are overdue for follow-up. PCPs and specialists will not 
perform recruitment; this will be done centrally through the automated population based 
system that applies the 2019 ASCCP guidelines to Pap or HPV results for eligible patients 
in participating PCP practices 
 
6. 
STUDY PROCEDURES 
Control Arm (Standard Care only) patients will receive the usual care provided by their PCP, 
practice, and/or specialist. For eligible women 21-65 years, reminders to perform routine 
cervical cancer screening are set at a default of 3 years across MGB and can be manually 
modified by a practitioner to 1 or 5 years (or no testing) based on clinical judgement. Pap/ HPV 
results are returned to the ordering practitioner in the lab results section of each patient’s EHR 
and in an “In-basket” (i.e., all results of any type, normal or abnormal, are sent into this queue). 
The interpretation of the results and notification of the patient is at the discretion of the 
practitioner. Since the ASCCP guidelines are currently only available on an app that is not 
linked to EHR data, few practitioners manually obtain the required information and input it into 
Figure 3: Summary of Risk-Based Clinical Action Thresholds 

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the app to determine the patient’s risk. From the “in-basket”, the ordering practitioner may 
choose, at their discretion, to send a letter to the patient, document a phone call, and/ or order 
additional testing. If the ordering practitioner is not the PCP, the PCP often does not receive any 
additional information (i.e., at the discretion of the ordering practitioner).  
Though individual practices may have standard procedures to communicate and manage 
results, this process is highly variable and there are no systems in place beyond the initial result 
communication.  
Intervention Arm Components. PREDICT will include multilevel components that address 
individual (patient, practitioner), team, and system-level barriers These will be tested using the 
3-arm design that allows assessment of the sequential addition of these components. This 
design will also evaluate changing the responsibility for “opportunistic” follow-up, typically by the 
practitioner or patient at the time of a visit, to a systematic, multilevel approach, examining the 
cumulative and marginal effects of each subsequent level of intervention. In addition to the 
multilevel components, the individual- and team-level engagement algorithm will take a “stepped 
care” approach with increasing level of intensity of engagement  
Step 1 will start 90 days before the date an individual is due for follow-up (“due date”), at the 
time of enrollment, based on the patient’s personalized risk score (Figure 4). For example, Step 
1 for a patient with a 5-year CIN 3+ risk of 0.6% in a practice randomized to an intervention arm 
would automatically have a 1-year surveillance follow-up reminder set in the EHR. In these 
intervention practices, practitioners could access this information when in the patient’s EHR or 
when the patient views the reminder in their patient portal. For practices randomized to Arm 3, 
Step 2 would begin with a patient being sent a 
reminder letter, 90 day prior to the due date via the 
patient portal or mailed if no portal account 
(Outreach 1). If needed, four weeks later a phone 
call from the outreach coordinator reminds 
patients of the follow-up date if scheduled or helps 
establish follow-up (Outreach 2). The coordinator 
could also place an order for a referral and send a 
reminder to the practitioner to sign it if appropriate. 
The study database will include have been made, 
and the outcome of those efforts. 
Figure 

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Intervention components in Arm 3 will differ for individuals recommended for 3-year surveillance 
and for individuals 65 years and older who have prior abnormalities that would warrant 
additional surveillance or diagnostic management. In Arm 3, individuals recommended for 3-
year surveillance will only receive Outreach 1 reminder letters (the study will have insufficient 
resources to make phone calls). Since individuals 65 years and older who have prior 
abnormalities that would warrant additional surveillance or diagnostic management are more 
likely to have other comorbid conditions that may affect recommended follow-up, study 
coordinators will message practitioners prior to performing patient outreach 
 
 
7. 
Risks and Discomforts 
 
The potential risks to subjects include loss of confidentiality of healthcare data. Study staff will 
follow careful protocols to minimize these risks. The co-investigators will emphasize the 
importance of maintaining confidentiality in training all study staff. All study data will be coded 
with unique study identification numbers. Electronic data will be stored within the MGB firewalls, 
will be password protected, and will be protected by anti-virus software. Only study staff will 
have access to study data on shared file areas.  
 
8. 
Benefits 
 
While a personalized approach offers the promise of enhancing the balance of benefits vs. 
harms of screening and management, this ideal can only be realized through strong systems to 
support care delivery. Without IT tools that integrate personalized algorithms with care delivery, 
more errors of judgement may occur if practitioners and patients are confused about appropriate 
next steps.  
 
Participants in practices randomly assigned to the intervention arms may benefit by receiving a 
timely follow-up of their abnormal cancer screening test results. Patients in control practices will 
receive usual care under the direction of their primary care provider. If the intervention is 
effective, more timely follow-up of abnormal cancer screening test results could lead to earlier 
detection, treatment, and cure of the cancers studied in this proposal. In the future, all patients 
could benefit from the knowledge produced by this study through the dissemination of similar 
care systems. 
 
 
9. 
Statistical Analysis 
 
Our primary analysis will be intention-to-treat (ITT). All eligible, enrolled patients will be part of 
the ITT cohort. We expect that a small number of patients may change primary care practices 
within our systems. These individuals will be evaluated according to their initial practice’s 
intervention status. The primary analysis model will be a random effects logistic regression, 
implemented through the SAS Glimmix procedure. Timely follow-up (yes/no) will be the patient-
level outcome and random effects for practice and practitioner will allow for exchangeable 
correlation between patients within the same practice and patients seen by the same 
practitioner. The primary fixed predictors will be 2 indicator variables representing the 2 
intervention arms and we will use a global likelihood ratio test to compare the 3 study arms. 

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Results will be presented as adjusted follow-up rates, with 95% confidence intervals, calculated 
using marginal standardization. Secondary analyses will model time-to-follow-up, using a 
clustered proportional hazards regression to examine whether follow-up occurs as quickly as 
possible.  
Sample Size/Power. Our primary goal is to enroll 7,500 high risk patients. This design will 
provide 90% power to detect an 8.4% improvement in the follow-up rate for an intervention arm 
compared to our control  
 
10.   Monitoring and Quality Assurance 
 
The PI will be responsible for monitoring and assuring the validity and integrity of the data and 
adherence to the IRB-approved protocol. Although we do not anticipate any direct adverse 
events from this study, we will promptly report any such adverse events to the IRB and halt the 
study until such potential adverse effects are addressed. Applicable DF/HCC policy (REGIST-
101) will be followed. Summary accrual information will be reported for 24 months. 
 
11. Data and Research Material Sharing 
 
A) Sending Data/Materials to Research Collaborators outside Mass General 
Brigham 
 
All work with patient data will take place behind the MGB firewall. No data will be sent to 
external collaborators. 
 
B) Receiving Data/Materials from Research Collaborators outside Mass 
General Brigham 
 
All work with patient data will take place behind the MGB firewall. No data will be sent to 
external collaborators. 
 
12. Privacy and Confidentiality 
 
☒ Study procedures will be conducted in a private setting. 
☒ Only data and/or specimens necessary for the conduct of the study will be collected. 
☒ Data collected (paper and/or electronic) will be maintained in a secure location with appropriate 
protections such as password protection, encryption, physical security measures (locked 
files/areas) 
☐ Specimens collected will be maintained in a secure location with appropriate protections (e.g. 
locked storage spaces, laboratory areas) 
☒ Data and specimens will only be shared with individuals who are members of the IRB-approved 
research team or approved for sharing as described in this IRB protocol. 
☒  Data and/or specimens requiring transportation from one location or electronic space to 
another will be transported only in a secure manner (e.g. encrypted files, password protection, 
using chain-of-custody procedures, etc.) 

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☒   All electronic communication with participants will comply with Mass General Brigham secure 
communication policies. 
☒ Identifiers will be coded or removed as soon as feasible and access to files linking identifiers 
with coded data or specimens will be limited to the minimal necessary members of the research 
team required to conduct the research. 
☒ All staff are trained on and will follow the Mass General Brigham policies and procedures for 
maintaining appropriate confidentiality of research data and specimens. 
☒ The PI will ensure that all staff implement and follow any Research Information Service Office 
(RISO) requirements for this research. 
☐ Additional privacy and/or confidentiality protections 
 
 
13.   References 
1. 
Deshmukh AA, Suk R, Shiels MS, et al. Incidence Trends and Burden of Human Papillomavirus-
Associated Cancers Among Women in the United States, 2001-2017. J Natl Cancer Inst. Jun 1 
2021;113(6):792-796. doi:10.1093/jnci/djaa128 
2. 
Cancer Stat Facts: Cervical Cancer. May 7, 2023. Accessed May 7, 2023. 
https://seer.cancer.gov/statfacts/html/cervix.html 
3. 
McClung NM, Gargano JW, Park IU, et al. Estimated Number of Cases of High-Grade Cervical 
Lesions Diagnosed Among Women - United States, 2008 and 2016. MMWR Morb Mortal Wkly Rep. Apr 
19 2019;68(15):337-343. doi:10.15585/mmwr.mm6815a1 
4. 
Qin J, Holt HK, Richards TB, Saraiya M, Sawaya GF. Use Trends and Recent Expenditures for 
Cervical Cancer Screening-Associated Services in Medicare Fee-for-Service Beneficiaries Older Than 65 
Years. JAMA Intern Med. Jan 1 2023;183(1):11-20. doi:10.1001/jamainternmed.2022.5261 
5. 
Tosteson AN, Beaber EF, Tiro J, et al. Variation in Screening Abnormality Rates and Follow-Up of 
Breast, Cervical and Colorectal Cancer Screening within the PROSPR Consortium. J Gen Intern Med. Apr 
2016;31(4):372-9. doi:10.1007/s11606-015-3552-7 
6. 
Spencer JC, Kim JJ, Tiro JA, et al. Racial and Ethnic Disparities in Cervical Cancer Screening from 
Three US Healthcare Settings. Am J Prev Med. May 3 2023;doi:10.1016/j.amepre.2023.04.016 
7. 
Feldman S, Lykken JM, Haas JS, et al. Factors associated with timely colposcopy following an 
abnormal cervical cancer test result. Prev Med. Nov 2022;164:107307. 
doi:10.1016/j.ypmed.2022.107307 
8. 
Haas JS, Atlas SJ, Wright A, et al. Multilevel follow-up of cancer screening (mFOCUS): Protocol 
for a multilevel intervention to improve the follow-up of abnormal cancer screening test results. 
Contemp Clin Trials. Aug 8 2021;109:106533. doi:10.1016/j.cct.2021.106533 
9. 
Force USPST, Curry SJ, Krist AH, et al. Screening for Cervical Cancer: US Preventive Services Task 
Force Recommendation Statement. JAMA. Aug 21 2018;320(7):674-686. doi:10.1001/jama.2018.10897 
10. 
Perkins RB, Guido RS, Castle PE, et al. 2019 ASCCP Risk-Based Management Consensus 
Guidelines for Abnormal Cervical Cancer Screening Tests and Cancer Precursors. J Low Genit Tract Dis. 
Apr 2020;24(2):102-131. doi:10.1097/LGT.0000000000000525 
11. 
Cheung LC, Egemen D, Chen X, et al. 2019 ASCCP Risk-Based Management Consensus 
Guidelines: Methods for Risk Estimation, Recommended Management, and Validation. J Low Genit Tract 
Dis. Apr 2020;24(2):90-101. doi:10.1097/LGT.0000000000000528 
12. 
Egemen D, Cheung LC, Chen X, et al. Risk Estimates Supporting the 2019 ASCCP Risk-Based 
Management Consensus Guidelines. J Low Genit Tract Dis. Apr 2020;24(2):132-143. 
doi:10.1097/LGT.0000000000000529 

Mass General Brigham Institutional Review Board 
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13. 
Mills JM, Morgan JR, Dhaliwal A, Perkins RB. Eligibility for cervical cancer screening exit: 
Comparison of a national and safety net cohort. Gynecol Oncol. Aug 2021;162(2):308-314. 
doi:10.1016/j.ygyno.2021.05.035 
14. 
Feldman S, Cook E, Davis M, et al. Cervical Cancer Incidence Among Elderly Women in 
Massachusetts Compared With Younger Women. J Low Genit Tract Dis. Oct 2018;22(4):314-317. 
doi:10.1097/LGT.0000000000000435 
15. 
Cooley JJP, Maguire FB, Morris CR, et al. Cervical Cancer Stage at Diagnosis and Survival among 
Women >/=65 Years in California. Cancer Epidemiol Biomarkers Prev. Jan 9 2023;32(1):91-97. 
doi:10.1158/1055-9965.EPI-22-0793 
16. 
Schapira MM, Sprague BL, Klabunde CN, et al. Inadequate Systems to Support Breast and 
Cervical Cancer Screening in Primary Care Practice. J Gen Intern Med. Oct 2016;31(10):1148-55. 
doi:10.1007/s11606-016-3726-y 
17. 
Conrad SK, Dahman B, Kumar A, Hylton J, Isaacs C. Adherence to the American Society for 
Colposcopy and Cervical Pathology guidelines: an observational study. Obstet Gynecol Sci. Jan 
2022;65(1):84-93. doi:10.5468/ogs.21247 
18. 
Diamond CJ, Laurentiev J, Yang J, et al. Natural Language Processing to Identify Abnormal Breast, 
Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-
up. Stud Health Technol Inform. Jun 6 2022;290:433-437. doi:10.3233/SHTI220112 
19. 
Spencer JC, Noel L, Shokar NK, Pignone MP. Understanding the role of access in Hispanic cancer 
screening disparities. Cancer. May 15 2023;129(10):1569-1578. doi:10.1002/cncr.34696 
20. 
Suk R, Hong YR, Rajan SS, Xie Z, Zhu Y, Spencer JC. Assessment of US Preventive Services Task 
Force Guideline-Concordant Cervical Cancer Screening Rates and Reasons for Underscreening by Age, 
Race and Ethnicity, Sexual Orientation, Rurality, and Insurance, 2005 to 2019. JAMA Netw Open. Jan 4 
2022;5(1):e2143582. doi:10.1001/jamanetworkopen.2021.43582 
21. 
Saraiya M, Colbert J, Bhat GL, et al. Computable Guidelines and Clinical Decision Support for 
Cervical Cancer Screening and Management to Improve Outcomes and Health Equity. J Womens Health 
(Larchmt). Apr 2022;31(4):462-468. doi:10.1089/jwh.2022.0100 
22. 
Atlas SJ, Tosteson ANA, Burdick TE, et al. Primary Care Practitioner Perceptions on the Follow-up 
of Abnormal Cancer Screening Test Results. JAMA Netw Open. Sep 1 2022;5(9):e2234194. 
doi:10.1001/jamanetworkopen.2022.34194 
23. 
Zapka JG, Taplin SH, Solberg LI, Manos MM. A framework for improving the quality of cancer 
care: the case of breast and cervical cancer screening. Cancer Epidemiol Biomarkers Prev. Jan 
2003;12(1):4-13.  
24. 
Beaber EF, Kim JJ, Schapira MM, et al. Unifying screening processes within the PROSPR 
consortium: a conceptual model for breast, cervical, and colorectal cancer screening. J Natl Cancer Inst. 
Jun 2015;107(6):djv120. doi:10.1093/jnci/djv120 
25. 
Eggleston KS, Coker AL, Das IP, Cordray ST, Luchok KJ. Understanding barriers for adherence to 
follow-up care for abnormal pap tests. J Womens Health (Larchmt). Apr 2007;16(3):311-30. 
doi:10.1089/jwh.2006.0161 
26. 
Wujcik D, Fair AM. Barriers to diagnostic resolution after abnormal mammography: a review of 
the literature. Cancer Nurs. Sep-Oct 2008;31(5):E16-30. doi:10.1097/01.NCC.0000305764.96732.45 
27. 
Ramachandran A, Freund KM, Bak SM, Heeren TC, Chen CA, Battaglia TA. Multiple barriers delay 
care among women with abnormal cancer screening despite patient navigation. J Womens Health 
(Larchmt). Jan 2015;24(1):30-6. doi:10.1089/jwh.2014.4869 
28. 
Percac-Lima S, Aldrich LS, Gamba GB, Bearse AM, Atlas SJ. Barriers to follow-up of an abnormal 
Pap smear in Latina women referred for colposcopy. J Gen Intern Med. Nov 2010;25(11):1198-204. 
doi:10.1007/s11606-010-1450-6 

Mass General Brigham Institutional Review Board 
Intervention/Interaction Detailed Protocol 
 
Version 2024.02.07 
 
Page 13 of 14 
29. 
Kohn LT, Corrigan JM, Donaldson MS. To Err is Human. Building a Safer Health System. 1999.  
30. 
Bodenheimer T, Ghorob A, Willard-Grace R, Grumbach K. The 10 building blocks of high-
performing primary care. Ann Fam Med. Mar-Apr 2014;12(2):166-71. doi:10.1370/afm.1616 
31. 
National Committee for Quality Assurance (NCQA). HEDIS and Performance Measurement. 
NCQA. 2015. http://www.ncqa.org/HEDISQualityMeasurement.aspx 
32. 
Glasgow RE, Harden SM, Gaglio B, et al. RE-AIM Planning and Evaluation Framework: Adapting 
to New Science and Practice With a 20-Year Review. Front Public Health. 2019;7:64. 
doi:10.3389/fpubh.2019.00064 
33. 
Glasgow RE, McKay HG, Piette JD, Reynolds KD. The RE-AIM framework for evaluating 
interventions: what can it tell us about approaches to chronic illness management? Patient Educ Couns. 
Aug 2001;44(2):119-27. doi:10.1016/s0738-3991(00)00186-5 
34. 
Damschroder LJ, Reardon CM, Widerquist MAO, Lowery J. The updated Consolidated 
Framework for Implementation Research based on user feedback. Implement Sci. Oct 29 2022;17(1):75. 
doi:10.1186/s13012-022-01245-0 
35. 
Damschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use 
with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. 
Implement Sci. Jan 22 2022;17(1):7. doi:10.1186/s13012-021-01181-5 
36. 
Damschroder LJ, Lowery JC. Evaluation of a large-scale weight management program using the 
consolidated framework for implementation research (CFIR). Implement Sci. May 10 2013;8:51. 
doi:10.1186/1748-5908-8-51 
37. 
ONC’s Cures Act Final Rule. HealthIT.gov. Accessed May 13, 2023. 
https://www.healthit.gov/topic/oncs-cures-act-final-
rule#:~:text=ONC's%20Cures%20Act%20Final%20Rule%20supports%20seamless%20and%20secure%20a
ccess,secure%20access%20to%20health%20information. 
38. 
Atlas SJ, Zai AH, Ashburner JM, et al. Non-visit-based cancer screening using a novel population 
management system. Randomized Controlled Trial 
Research Support, Non-U.S. Gov't 
Research Support, U.S. Gov't, P.H.S. Journal of the American Board of Family Medicine : JABFM. Jul-Aug 
2014;27(4):474-85. doi:10.3122/jabfm.2014.04.130319 
39. 
Atlas SJ, Grant RW, Lester WT, et al. A cluster-randomized trial of a primary care informatics-
based system for breast cancer screening. Comparative Study 
Multicenter Study 
Randomized Controlled Trial 
Research Support, N.I.H., Extramural 
Research Support, Non-U.S. Gov't. Journal of general internal medicine. Feb 2011;26(2):154-61. 
doi:10.1007/s11606-010-1500-0 
40. 
Atlas SJ, Ashburner JM, Chang Y, Lester WT, Barry MJ, Grant RW. Population-based breast 
cancer screening in a primary care network. Randomized Controlled Trial 
Research Support, N.I.H., Extramural 
Research Support, Non-U.S. Gov't 
Research Support, U.S. Gov't, P.H.S. The American journal of managed care. Dec 2012;18(12):821-9.  
41. 
Haas JS, Linder JA, Park ER, et al. Proactive tobacco cessation outreach to smokers of low 
socioeconomic status: a randomized clinical trial. Randomized Controlled Trial 
Research Support, N.I.H., Extramural 
Research Support, Non-U.S. Gov't. JAMA Intern Med. Feb 2015;175(2):218-26. 
doi:10.1001/jamainternmed.2014.6674 

Mass General Brigham Institutional Review Board 
Intervention/Interaction Detailed Protocol 
 
Version 2024.02.07 
 
Page 14 of 14 
42. 
Linder JA, Rigotti NA, Schneider LI, et al. Clinician characteristics and use of novel electronic 
health record functionality in primary care. Comparative Study 
Research Support, N.I.H., Extramural 
Research Support, U.S. Gov't, P.H.S. Journal of the American Medical Informatics Association : JAMIA. 
Dec 2011;18 Suppl 1:i87-90. doi:10.1136/amiajnl-2011-000330