Almost half (49%) of the United States population has prediabetes or type 2 diabetes. Type 2 diabetes has many associated comorbidities and is the seventh leading cause of death in the United States. It is also the most expensive chronic condition in the nation. Identifying patients with prediabetes allows for early intervention to prevent or delay the onset of type 2 diabetes. The objective of this quality improvement project was to develop and implement a screening algorithm in the primary care setting using the Prediabetes Risk Test and point of care HemoglobinA1c testing to improve identification of patients with prediabetes and increase referrals to lifestyle intervention. Over the 12-week implementation period, fifteen patients were identified as having prediabetes, three agreed to a referral to lifestyle intervention, and one was started on metformin. This was a marked increase compared to two prior recent years. The algorithm was feasible and effective at improving identification of prediabetes, in addition to improving staff and provider knowledge and retention. Future studies should include a broader patient population in a variety of locations with longitudinal follow-up. Updating the Prediabetes Risk Test to specify physical activity for future studies may also be beneficial.
","abstract_html":"<p>Almost half (49%) of the United States population has prediabetes or type 2 diabetes. Type 2 diabetes has many associated comorbidities and is the seventh leading cause of death in the United States. It is also the most expensive chronic condition in the nation. Identifying patients with prediabetes allows for early intervention to prevent or delay the onset of type 2 diabetes. The objective of this quality improvement project was to develop and implement a screening algorithm in the primary care setting using the Prediabetes Risk Test and point of care HemoglobinA1c testing to improve identification of patients with prediabetes and increase referrals to lifestyle intervention. Over the 12-week implementation period, fifteen patients were identified as having prediabetes, three agreed to a referral to lifestyle intervention, and one was started on metformin. This was a marked increase compared to two prior recent years. The algorithm was feasible and effective at improving identification of prediabetes, in addition to improving staff and provider knowledge and retention. Future studies should include a broader patient population in a variety of locations with longitudinal follow-up. Updating the Prediabetes Risk Test to specify physical activity for future studies may also be beneficial.</p>","abstract_has_math":false,"creators":["Masoud, Katherine"],"institution":null,"degree_name":"Doctor of Nursing Practice (DNP)","degree_level":"Open Access Thesis","degree_discipline":"Yale University School of Nursing","degree_department":null,"school":null,"contributors":["Neesha Ramchandani"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-01T08:00:00Z","date_published":"2023-01-01T08:00:00Z","updated_at":"2026-07-24T06:16:14Z","subjects":["Point of care, Prediabetes, Risk test, Screening algorithm"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://elischolar.library.yale.edu/ysndt/1157","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Neesha Ramchandani"]},{"key":"dc:creator","label":"Author","values":["Masoud, Katherine"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Yale University School of Nursing"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Nursing Practice (DNP)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Point of care, Prediabetes, Risk test, Screening algorithm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://elischolar.library.yale.edu/ysndt/1157"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Almost half (49%) of the United States population has prediabetes or type 2 diabetes. Type 2 diabetes has many associated comorbidities and is the seventh leading cause of death in the United States. It is also the most expensive chronic condition in the nation. Identifying patients with prediabetes allows for early intervention to prevent or delay the onset of type 2 diabetes. The objective of this quality improvement project was to develop and implement a screening algorithm in the primary care setting using the Prediabetes Risk Test and point of care HemoglobinA1c testing to improve identification of patients with prediabetes and increase referrals to lifestyle intervention. Over the 12-week implementation period, fifteen patients were identified as having prediabetes, three agreed to a referral to lifestyle intervention, and one was started on metformin. This was a marked increase compared to two prior recent years. The algorithm was feasible and effective at improving identification of prediabetes, in addition to improving staff and provider knowledge and retention. Future studies should include a broader patient population in a variety of locations with longitudinal follow-up. Updating the Prediabetes Risk Test to specify physical activity for future studies may also be beneficial.
"]},{"key":"dc:title","label":"Title","values":["Implementing A Prediabetes Screening Algorithm To Improve Identification And Referrals In Primary Care"]}]}],"canonical_facts":{"dc:contributor":["Neesha Ramchandani"],"dc:creator":["Masoud, Katherine"],"dc:description.abstract":["Almost half (49%) of the United States population has prediabetes or type 2 diabetes. Type 2 diabetes has many associated comorbidities and is the seventh leading cause of death in the United States. It is also the most expensive chronic condition in the nation. Identifying patients with prediabetes allows for early intervention to prevent or delay the onset of type 2 diabetes. The objective of this quality improvement project was to develop and implement a screening algorithm in the primary care setting using the Prediabetes Risk Test and point of care HemoglobinA1c testing to improve identification of patients with prediabetes and increase referrals to lifestyle intervention. Over the 12-week implementation period, fifteen patients were identified as having prediabetes, three agreed to a referral to lifestyle intervention, and one was started on metformin. This was a marked increase compared to two prior recent years. The algorithm was feasible and effective at improving identification of prediabetes, in addition to improving staff and provider knowledge and retention. Future studies should include a broader patient population in a variety of locations with longitudinal follow-up. Updating the Prediabetes Risk Test to specify physical activity for future studies may also be beneficial.
"],"dc:identifier":["https://elischolar.library.yale.edu/ysndt/1157"],"dc:subject":["Point of care, Prediabetes, Risk test, Screening algorithm"],"dc:title":["Implementing A Prediabetes Screening Algorithm To Improve Identification And Referrals In Primary Care"],"thesis:degree_discipline":["Yale University School of Nursing"],"thesis:degree_level":["Open Access Thesis"],"thesis:degree_name":["Doctor of Nursing Practice (DNP)"]},"updated_at":"2026-07-24T06:16:14Z"}