ACCQUIREnet

As part of the regular clinical workflow, each team takes care of the patient, documents the patient encounter in the electronic health record (EHR), and also (if the patient is due for outcome measurement) records the outcomes in the CleftCap database. 

Local data analyses may be performed by each participating site at any time. 

Periodically (usually semi-annually), the data must be aggregated from each site to permit specific analyses such as benchmarking and generation of performance reports. Duke University functions as the statistical support center for this process. Secure means of transfer is specified in the IRB protocol and data-transfer agreements with participating sites and may include secure-FTP or university-approved cloud storage system such as Box or OneDrive.

Once data are received by Duke, the data are stored in a secure enclave, which is approved for storage of PHI. The data are reformatted from the raw schema used in the CleftCap project template and transformed into a format more suitable for data analysis, using a project-specific extension to the PCORnet® Common Data Model. It is in this phase that records linkage and enrichment are possible (e.g., EHR, epidemiologic surveillance data from birth-defects monitoring programs, socioeconomic data from Census.gov, payor data from CMS and insurance carriers, etc.). Data-quality checks are performed along various steps in this pipeline. Finally, the data are stored in a secure database (CleftBASE), which is utilized for the analytical queries.

Analysis includes calculation of network benchmarks for each outcome measure. Team-specific performance reports (or quality-improvement [QI] reports) will be made available to each participating team. These reports are private and confidential — each team will only see its own performance, relative to the network benchmark, and will not be able to know the performance of any other team. For now, these reports are static reports, but a longer-term aim is to create a dynamic dashboard so that teams may explore their team’s data in different ways.

Research aims are handled similarly to QI reports: The statistical team will analyze the data in CleftBASE according to the specific aims and formal, a priori statistical analysis plan. De-identified results tables are sent to the principal investigator. (Any participant in ACCQUIREnet may be an investigator.)

A long-term aim and milestone for the network is to curate a de-identified multi-site dataset that would be made available to each participating site. This “participant use file” (PUF) is modeled after the successful practice of the American College of Surgeons (ACS) National Surgical Quality-Improvement Program (NSQIP®) and similar features in AHRQ HCUP databases. By going this extra step and publishing a de-identified multi-site dataset, participating sites would be able to perform even more analyses that might exceed the capacity of the statistical support center to handle. In this manner, our long-term vision is to make the data even more accessible for every participating center. A signed user agreement guides usage of the PUF. The PUF is only available to participating sites in ACCQUIREnet and may not be re-distributed.

Who Controls the Data?

Since ACCQUIREnet is a distributed data network, each participating team remains in full control of its own data. There is no lock-in: every team director has the ability to export and download that site’s data at any point in time. Each participating site is allowed to analyze its own data in any way it deems fit (in accordance with the IRB protocol). 

Of course, for security and privacy reasons, multi-site data aggregation and analysis will only be performed by the statistical support center at Duke. Any participant in ACCQUIREnet may volunteer to be an investigator; as such, he or she would develop the specific aims and statistical analysis plan with the Duke statisticians. The statisticians would then perform the analysis and send the results to the investigator, and they would work together in the writing of the manuscript. In this manner, data security is not compromised, but every participant has the ability to work on specific areas of interest.

What About Authorship?

The core tenet of ACCQUIREnet is collaboration, not competition. Presently, we propose that any participant can propose and lead a scientific inquiry and may be first or senior author on any academic publication that results from that work. The core research team and statistical support team at Duke will also be named authors on the papers, as will any other collaborators who meet the ICMJE criteria for authorship. Certain platform papers may include all participants, listed by name wherever possible, or using the network byline “on behalf of ACCQUIREnet” where necessary according to the journal’s restrictions. Each manuscript will also include boilerplate acknowledgment statements to meet the licensing requirements of REDCap®, CLEFT-Q™ and FACE-Q™, ICHOM, and others.

What Is the Governance Structure for ACCQUIREnet?

ACCQUIREnet is a collaborative network, and every participating site may contribute to the network’s standards, areas of focus, and priorities. Every participant may pose research questions, for which he or she may serve as first or senior author. Sustaining such a network requires dedicated effort, and Duke University is serving as the network coordinating center and as the statistical support center for data analysis. Furthermore, ACCQUIREnet has a stewardship committee to assist with governance. 

Which Teams Have Joined ACCQUIREnet?

As of February 2025, the following sites have joined or are in the process of joining ACCQUIREnet:

• Arnold Palmer Hospital for Children — Orlando Health (Orlando, FL)
• Boston Children’s Hospital — Harvard University (Boston, MA)
• Brenner Children’s Hospital — Wake Forest University (Winston-Salem, NC)
• Children’s Hospital Colorado (CHCO) — University of Colorado (Aurora, CO)
• Children’s Memorial Hermann Hospital — University of Texas at Houston (Houston, TX)
• Duke Children’s Hospital — Duke University (Durham, NC)
• Indiana University Health (Indianapolis, IN)
• Joe DiMaggio Children’s Hospital (Hollywood, FL)
• Johns Hopkins All Children’s Hospital — Johns Hopkins University (St. Petersburg, FL)
• Maine Medical Center (Portland, ME)
• Nicklaus Children’s Hospital (Miami, FL)
• St. Louis Children’s Hospital — Washington University (St. Louis, MO)

Additionally, ACCQUIREnet enjoys fruitful collaboration with other networks and sites that collect ICHOM and CLEFT-Q™/FACE-Q™ data, including McMaster University, Toronto SickKids, Erasmus, and Karolinska.

Does It Cost Money to Participate in ACCQUIREnet?

No. Joining ACCQUIREnet is free, and presently the project team has no plans on charging for participation. A network this size does require money to be sustained, and so far this money comes from institutional (Duke University) and grant funding.

ACCQUIREnet is indebted to many domain experts who have generously shared their time and expertise over the years. ACCQUIREnet has been strongly inspired by Americleft, European Reference Network (ERN), EUROCRAN, ICHOM, NSQIP-Pediatric, Solutions for Patient Safety, and PCORnet®.

The principal investigator (Alexander Allori) would like to express his sincere appreciation to the following individuals:

• Jeffrey Marcus, MD, who has not only been my most influential clinical mentor, colleague, and friend, but who also scribbled on a Post-It® note: "Help me with this project. Figure out how to analyze cleft outcomes." That led to Project CHEER, CLP360°, and the rest is history.
• David Fitzsimons, PhD, who first invited me to join the ACPA Data Standards Committee in 2014, shared with me his experience building his own database, and teaching me a million things about cleft-related speech.
• John Meara, MD, DDS, MBA, for hearing about my early work in CLP360° and inviting me to be one of the co-directors of the ICHOM Standard Set working group. Without him, there would have been no Standard Set.
• Anne Klassen, PhD, and Karen Wong-Riff, MD, PhD, who kindly shared their CLEFT-Q™ and FACE-Q™ instruments, which constitute a substantial portion of the outcome metrics in our project.
• Elizabeth Heitman, PhD, who introduced me to the field of health-technology assessment. What started as a simple master's thesis has set the course for the rest of my academic career.
• Amy Abernethy, MD, PhD, who showed me how learning health systems can be utilized to study the effectiveness and quality of healthcare interventions. This led to the development of the "EQUIP model," which I have used as the underlying structure for ACCQUIREnet.
• Hayden Bosworth, PhD, who provided valuable instruction on dissemination and implementation science research methods.
• Keith Marsolo, PhD, who generously shared his insights and experiences gained from his pioneering work on PCORnet®. His contributions have been instrumental in shaping the informatical design choices that we made for ACCQUIREnet.
• Leslie Curtis, PhD, who welcomed me to the Department of Population Health Sciences and facilitated numerous introductions, expanding my network and knowledge.
• Kevin Weinfurt, PhD, who offered expert advice on the proper use of patient-reported outcome measures, ensuring that my research aligns with best practices.
• Miguel Hernán, MD, DrPH, ScM, whose brief but encouraging words gave me a much-needed boost of confidence. The task of developing and applying causal inference methods in surgery has been tough, and I deeply respect his vision, approach, and enthusiasm.

There were many more people and organizations that have helped along the way, and I thank you. Specifically, to all my students and resident trainees over the years, thank you for your hard work, enthusiasm, and company on this journey.