Email UpdatesThis artifact provides patient-centered, evidence-based preventive health information directly to patients between the ages of 35-70 who are identified as overweight or obese to: 1) raise awareness that they may have one or more risk factor(s) for prediabetes or Type 2 diabetes, 2) provide educational materials that explain how overweight/obesity and other personal/family factors increase their risk for developing diabetes and ways to reduce their risk, and 3) encourage them to talk to their primary care clinician about being screened for prediabetes and type 2 diabetes.
The artifact represents the first part of the U.S. Preventive Services Task Force (USPSTF) Prediabetes and Type 2 Diabetes: Screening recommendation.
Artifact Creation and Usage
This artifact was developed by MITRE software engineers and clinical informaticists, in collaboration with clinical subject matter experts and leaders from the USPSTF.
Additional information about MITRE's health expertise is available here.
Additional information about the USPSTF's preventive health expertise is available here.
If you would like further information, would like to give us feedback, or have any questions about this artifact, please contact us at ClinicalDecisionSupport@ahrq.hhs.gov.
| Recommendation is copyrighted by USPSTF and administered by AHRQ |
| This CDS logic is expressed using Health Level Seven International (HL7) Clinical Quality Language (CQL) and the HL7 Fast Healthcare Interoperability Resources (FHIR) data model. All value sets referenced in the logic are published on the Value Set Authority Center (VSAC). Additional details about these resources can be accessed via the following URLs: CQL: https://ecqi.healthit.gov/cql FHIR DSTU2: https://www.hl7.org/fhir/DSTU2/index.html FHIR R4: https://hl7.org/fhir/R4/index.html VSAC: https://vsac.nlm.nih.gov/ |
Structured code that is interpretable by a computer (includes data elements, value sets, logic)
Identifies patients who are overweight or obese and, through the intervention text presented to patients, provides preventive health recommendations to:
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| This artifact is intended for use in a broad population of adults (aged 35-70, or younger in certain populations) who are overweight or obese. |
This CDS artifact is designed to be implemented in a patient-facing information technology (IT) system (e.g., a patient portal or health and wellness app) to deliver preventive health recommendations outside of a traditional encounter with a clinician. Organizations that might consider implementing this logic range from a large self-insured healthcare organization that seeks to provide health and wellness resources to their employees and patients, to a healthcare innovator that culls patient data from numerous sources (e.g., electronic health records, claims, pharmacy-based management systems, biometric devices, patient-reported data) to provide personalized wellness information via a mobile app. It is intended for use by patients to provide patient-centered, evidence-based information on preventive treatment options to consider based on that patient’s individual health history and risk factors. The patient is provided with user-friendly notifications, educational materials, and tools in lay language to facilitate patient action and encourage collaborative decision-making between the patient and their clinician and caregiver(s) to determine the most appropriate treatment or care choice. |
| This artifact represents the first half of the USPSTF recommendation: This artifact represents the first half of the USPSTF Prediabetes and Type 2 Diabetes: Screening recommendation (which identifies individuals who meet criteria to be screened for prediabetes and Type 2 DM). The second half of the recommendations (which encourages consideration of counseling if screening results are abnormal) is represented by a distinct artifact, Prediabetes and Type 2 Diabetes: Counseling. The CDS Connect team opted to develop two distinct artifacts from the one recommendation to simplify the logic and enable organizations to select portions of the recommendation that align with their organization's need. |
Implementation consideration: The patient notifications included in the structured CQL expression of this artifact are general, enabling implementing organizations to expand upon and personalize the interventions based on their unique needs and patient population. Information provided to the patient translates the preventive care recommendation into lay language and provides additional resources in a user-friendly format and method. This user-friendly information facilitates patient action through the provision of vetted resources, and in the case of the customized piloted CDS, an opportunity to provide personalized motivational messaging and logistical support for appointments and followup. Additional information and resources: CQL Services, an open source, publicly available tool that facilitates integration of CQL code with a health IT system, was used during the pilot implementation of this artifact. CQL Services is available here. |
Derived from USPSTF guideline Prediabetes and Type 2 Diabetes: Screening
US Preventive Services Task Force. Screening for Prediabetes and Type 2 Diabetes: US Preventive Services Task Force Recommendation Statement. JAMA. 2021;326(8):736–743. doi:10.1001/jama.2021.12531
https://jamanetwork.com/journals/jama/fullarticle/2783414
Jonas DE, Crotty K, Yun JDY, et al. Screening for Prediabetes and Type 2 Diabetes: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2021;326(8):744–760. doi:10.1001/jama.2021.10403
https://jamanetwork.com/journals/jama/fullarticle/2783415
The USPSTF recommends screening for prediabetes and type 2 diabetes in adults aged 35 to 70 years who have overweight or obesity. Clinicians should offer or refer patients with prediabetes to effective preventive interventions.
Grade B (see Appendix Table 1 for what the USPSTF Grades mean and suggestions for practice, available here)
| See full recommendation report for details regarding the Level of Certainty, available here. |
| Artifact decision notes are outlined in Appendix A of the implementation guide attached to this artifact. |
| The pilot organization ran this logic every night as a batch report. Other implementers may opt for a different triggering event. |
Patient is >=35 years old AND <=70 years old
AND BMI >=25kg/m2, MOST RECENT VALUE
OR Patient is >=18 years old and <35 years old
AND BMI >=25kg/m2, MOST RECENT VALUE
AND one of more of the following:
Family history of diabetes
OR polycystic ovary syndrome
OR race = African American; American Indian or Alaskan Native; or Native Hawaiian or Pacific Islander
OR ethnicity = Hispanic or Latino
OR Patient is >=18 years old and <=70 years old
AND BMI >=23kg/m2, MOST RECENT VALUE
AND race = Asian American
OR Patient is >=18 years old and <=70 years old
AND gestational diabetes
Pregnancy (active)
OR pregnancy observation within the past 42 weeks (final, amended)
OR diabetes mellitus with the past 12 months (active, relapse)
OR prediabetes within the past 12 months (active, relapse)
OR impaired fasting glucose (IFG) within the past 12 months (active, relapse)
OR impaired glucose tolerance (IGT) within the past 12 months (active, relapse)
OR hemoglobin A1C test result, MOST RECENT VALUE within the past 3 years (final, amended)
OR fasting plasma glucose test result, MOST RECENT VALUE within the past 3 years (final, amended)
OR glucose tolerance test result, MOST RECENT VALUE within the past 3 years (final, amended)
Display notification to patient: You may be at risk for (in other words, more likely to get) prediabetes and type 2 diabetes based on risk factors you may have. Many factors increase a person’s risk for high blood sugar including: being 35 years or older; being overweight; having a parent, brother or sister with diabetes; or if you are a woman with a history of diabetes while pregnant (gestational diabetes) or polycystic ovarian syndrome (a condition where the ovaries produce higher-than-normal amounts of certain hormones). If you are African American, Hispanic, Alaskan Native, American Indian, Asian American, or Native Hawaiian/Pacific Islander you may also be more likely to have high blood sugar at an age under 35. Experts (i.e., the US Preventive Services Task Force) recommend blood tests to measure blood sugar levels if you are at increased risk. If the tests show you have high blood sugar (prediabetes), there are steps you can take to help lower your blood sugar and prevent diabetes. Recommendation: Contact your primary care clinician to schedule an appointment and ask about being tested for high blood sugar and diabetes. Here are some links to resources you may want to review:
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This artifact was tested by b.well® Connected Health over an 8-week period from June 2019 - August 2019, along with 4 other artifacts listed below (and published on the CDS Connect Repository).
- Healthful Diet and Physical Activity for CVD Prevention in Adults with Cardiovascular Risk Factors
- Abnormal Blood Glucose and Type 2 Diabetes Mellitus: Part 2, Counseling
- Statin Use for the Primary Prevention of CVD in Adults: Patient-Facing CDS Intervention
- CMS's Million Hearts® Model Longitudinal ASCVD Risk Assessment Tool for Baseline 10-Year ASCVD Risk
b.well offers a platform with personalized health management resources targeted to consumers to help them self-manage the entire healthcare process. AHRQ and MITRE would like to thank b.well for their partnership on the pilot. The collaborative effort provided a valuable opportunity to test the CQL CDS expression and learn from the implementation process and end user experiences. High-level details are outlined below. Detailed information on the pilot implementation can be found in the CDS Connect Pilot Report: Preventive Health CDS Interventions document posted within this artifact.
| 1. What went well? | ||||||||||
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| 2. What did not go well? | ||||||||||
| · The pilot technical team did not have prior experience with the standards used (e.g., Fast Healthcare Interoperability Resources [FHIR], CDS Hooks, and Clinical Quality Language [CQL]), which extended the technical integration time and efforts. | ||||||||||
| · Data mapping consumed almost 25 percent of the pilot partner’s technical resource hours (80 hours) and an additional 20 hours of clinical and data/analytics resource time. | ||||||||||
| · Some required data was simply not available. Given more time, the pilot partner could have enhanced existing capabilities to obtain the required data directly from the end users. | ||||||||||
| 3. What would you do differently? | ||||||||||
| · Initiate the pilot partnership no later than March to allow more time for integration and testing efforts, as well as end user engagement. | ||||||||||
| · If more time was available, consider implementing the CDS using the FHIR Release 4 (R4) in addition to FHIR Draft Standard for Trial Use 2 (DSTU2). | ||||||||||
| 4. What enhancements were suggested by the pilot partner? | ||||||||||
| · Allow the calculation of an “inferred” diagnosis or potential “at risk” status for end users without a confirmed diagnosis, based on other available data. This would enable reaching a larger population of end users and providing them with education that may be valuable. The CDS Connect team opted not to implement this enhancement since expansion of the target population would diverge from the USPSTF recommendation. | ||||||||||
| · If time had allowed, it would have been helpful to obtain end user input on the educational materials prior to implementing them. Instead, the pilot partner used health literacy and health communication best practices when developing the educational content. | ||||||||||
| · It would have been helpful to survey a larger number of end users, and to provide the survey to the user directly after the intervention. This would allow more conclusive analysis of the survey results; however, the project team was required to follow Paperwork Reduction Act requirements which limited the number of survey recipients to 9 or less | ||||||||||
| · Provision of more detailed information from CDS Hooks, to provide information such as the specific user data that qualified that user for the CDS intervention. This information could be used for both testing purposes as well as personalization of the intervention text. | ||||||||||
| 5. What were the key takeaways/lessons learned from the pilot experience? | ||||||||||
| · Aggregating data from multiple sources provides a rich source of clinical information, but also presents challenges when using the data to satisfy CDS logic requirements. This is primarily due to the lack of standards employed by each data source (e.g., claims, electronic health systems, pharmacy benefits management systems, reference laboratories, and patient-generated health data). Much of the data were not linked to a standard clinical terminology code, and many of the required FHIR attributes were missing (e.g., “status,” “verificationStatus,” “onsetDateTime,” “valueQuantity”). | ||||||||||
| · Data mapping to account for the issues listed above is a resource-intensive process that also requires knowledgeable clinical informatics expertise. The mapping efforts can impact the integration timeline. | ||||||||||
| · The experience of the pilot technical team with FHIR and other evolving standards should be considered during the technical evaluation and planning stages. | ||||||||||
| · Patient-facing CDS pilots should consider a pilot partner with consumer/patient-facing experience and expertise and should ensure a pilot timeframe that allows end user personalization and engagement opportunities to be realized. |