Overview of Changes

Att 5- Table of changes from OMB No. 0920-0909_ 2021_11-30-20_FINAL.docx

CDC Diabetes Prevention Recognition Program (DPRP)

Overview of Changes

OMB: 0920-0909

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Overview of Data Collection Changes from 2018 Diabetes Prevention Recognition Program (DPRP) Standards

(OMB No. 0920-0909, exp. 02/28/2021) for 2021 DPRP Standards (revision)

Type of Change

Rationale

Detailed Description of Change(s)

Affected Form(s)

  1. Collect additional organizational information from applicant organizations

  1. Improve CDC’s ability to better understand delivery platform structure

  2. Will allow CDC to link Coach ID to evaluation data to further assess performance

  3. Will allow CDC to ensure Coaches are trained by a CDC-approved training entity holding a Memorandum of Understanding (MOU) with CDC

  1. Drop down questions per delivery mode (intensity of live coach interaction per session; how curriculum is delivered; how/when weight and physical activity [PA] minutes are collected via virtual programs; and participant module delivery options)

  2. Coach ID (organization-assigned unique identifier that does not contain PII)

  3. Coach Training Entity (Includes all CDC-approved entities holding MOUs)



DPRP Application Form

  1. Collect Gender information in addition to currently-collected Sex-at-birth information

Will allow for CDC to offer a more gender-inclusive variable, as requested by key stakeholders; recent research shows greater odds of being diagnosed with type 2 diabetes based on gender identity

  1. Gender (described as how you identify) – Male/Female/Other/Not reported

DPRP Evaluation Data

  1. Collect class cohort-level information

Will allow CDC to evaluate outcomes by annual participant cohorts; further allows organizations to better understand their data submissions and evaluation timelines by a specific annual group of participants

Add variable: Class ID (organization-assigned unique identifier that represents one, yearlong group of participants at a time and does not contain PII)

DPRP Evaluation Data

  1. Collect coach identifier by class cohort

Will allow CDC to link Coach ID to evaluation data to further assess cohort performance for quality improvement; further allows CDC-recognized organizations to better understand participant outcomes by Coach characteristics such as place trained and type of training received

Add variable: Coach ID (organization-assigned unique identifier that does not contain PII)

DPRP Evaluation Data

  1. Remove session level variable

Will help minimize data collection burden on CDC-recognized organizations by eliminating a session variable per each participant per session (min. of 22 in the yearlong intervention); session ID data analysis has not been found to yield useful information compared to all other participant variables collected

Remove variable: Session ID

(numbering of ordered sessions as delivered within the yearlong lifestyle change program)

DPRP Evaluation Data

  1. Revise ENROLL-HC variable; break into two variables

DPRP data indicated that organizations and participants did not understand the previous collapsed variable. The 2018 ENROLL variable included both people who had referred participants to the intervention and participants’ motivations for having enrolled in the intervention, making it difficult to draw appropriate conclusions from these data. Information on healthcare provider referrals (ENROLL-HC) is needed by key National DPP stakeholders and is also used as a metric for an agency-wide priority under CDC’s Strategic Framework.

Add Enrollment Motivation (new): Organizations will identify the main motivation which led the participant to enroll in the yearlong program.


Revise Enrollment Source (revised): Organizations will identify whether a healthcare professional was the source which led the participant to enroll in the yearlong program.

DPRP Evaluation Data

  1. Collect pre- and post-outcome data for CDC recognition

Literature reviews indicate that a 0.2% reduction in hemoglobin A1C (HbA1C) in persons with prediabetes corresponds to a 30 to 40% reduction in type 2 diabetes incidence, similar to a 5% reduction in body weight. Therefore, we are proposing to allow HbA1c reporting as an additional (optional) means for organizations to achieve full recognition.

Add optional variable: Hemoglobin A1C; HbA1C (pre-intervention and post-yearlong-intervention to assess improvement in prediabetes HbA1C level as an alternative to weight loss for those organizations interested in this option); HbA1C value per participant must be collected and submitted prior to final data submission for that year; must be included in last session record.

DPRP Evaluation Data

NOTE: None of these changes alter the critical elements of the lifestyle change program shown to prevent or delay type 2 diabetes in research studies –participant eligibility requirements, lifestyle program intensity and duration, participant weight loss (at least 5% of body weight), documentation of physical activity minutes (with a goal of 150 minutes per week), and documentation of required attendance throughout the entire 12-month intervention.

  1. Diabetes Prevention Program Research Group, Reduction in the Incidence of Type 2 Diabetes with Lifestyle Intervention or Metformin. February 7, 2002, N Engl J Med 2002; 346:393-403; doi: 10.1056/NEJMoa012512.

  2. Caceres, Billy A., Jackman. Kasey B., Edmondson, Donald, Bockting, Walter O. “Assessing gender identity differences in cardiovascular disease in US adults: an analysis of data from the 2014–2017 BRFSS.” J Behav Med (2020) 43:329–338.

  3. Zhang X, Gregg EW, Williamson DF, Barker LE, Thomas W, Bullard KM, Imperatore G, Williams DE, Albright AL. A1C level and future risk of diabetes: a systematic review. Diabetes Care. 2010 Jul;33(7):1665-73. doi: 10.2337/dc09-1939.

  4. Zhuo X, Zhang P, Selvin E, Hoerger TJ, Ackermann RT, Li R, Bullard KM, Gregg EW. Alternative HbA1c cutoffs to identify high-risk adults for diabetes prevention: a cost-effectiveness perspective. Am J Prev Med. 2012 Apr;42(4):374-81. doi: 10.1016/ j.amepre.2012.01.003.

  5. Leong A, Daya N, Porneala B, Devlin JJ, Shiffman D, McPhaul MJ, Selvin E, Meigs JB. Prediction of Type 2 Diabetes by Hemoglobin A1c in Two Community-Based Cohorts. Diabetes Care. 2018 Jan;41(1):60-68. doi: 10.2337/dc17-0607. Epub 2017 Oct 26.

  6. Selvin E, Steffes MW, Zhu H, Matsushita K, Wagenknecht L, Pankow J, Coresh J, Brancati FL. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med. 2010 Mar 4;362(9):800-11; doi: 10.1056/NEJMoa0908359.

  7. DeJesus RS, Breitkopf CR, Rutten LJ, Jacobson DJ, Wilson PM, Sauver JS. Incidence Rate of Prediabetes Progression to Diabetes: Modeling an Optimum Target Group for Intervention. Popul Health Manag. 2017 Jun;20(3):216-223; doi: 10.1089/pop.2016.0067. Epub 2016 Sep 30.

  8. Pavithra Vijayakumar, Annika Hoyer, Robert G. Nelson, Ralph Brinks, and Meda E. Pavkov. Estimation of chronic kidney disease incidence from prevalence and mortality data in American Indians with type 2 diabetes. PLoS One. 2017; 12(2): e0171027. Published online 2017 Feb 6; doi: 10.1371/journal.pone.0171027.

  9. Toro-Ramos, T., Michaelides, A., Anton, M., Karim, Z., Kang-Oh, L., Argyrou, C., Loukaidou, E., Charitou, M., Sze, W., Miller, J. “Mobile Delivery of the Diabetes Prevention Program in People With Prediabetes: Randomized Controlled Trial.” JMIR mHealth and uHealth (http://mhealth.jmir.org), 08.07.2020.

  10. Daftarian, Z., Bowen, P. “Improving outcomes in patients with prediabetes through a lifestyle modification program.” Journal of the American Association of Nurse Practitioners: March 2020 - Volume 32 - Issue 3 - p 244-25.



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