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Implementing a Prediabetes Screening Algorithm to Improve Identification and Referrals in Primary Care- [electronic resource]
Implementing a Prediabetes Screening Algorithm to Improve Identification and Referrals in Primary Care- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214100504
- ISBN
- 9798380011259
- DDC
- 610.73
- 서명/저자
- Implementing a Prediabetes Screening Algorithm to Improve Identification and Referrals in Primary Care - [electronic resource]
- 발행사항
- [S.l.]: : Yale University., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(83 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-02, Section: B.
- 주기사항
- Advisor: Ramchandani, Neesha.
- 학위논문주기
- Thesis (D.N.P.)--Yale University, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Almost 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.
- 일반주제명
- Nursing.
- 일반주제명
- Health care management.
- 키워드
- Prediabetes
- 키워드
- Risk test
- 키워드
- Population
- 키워드
- Primary care
- 기타저자
- Yale University Yale University School of Nursing
- 기본자료저록
- Dissertations Abstracts International. 85-02B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520240214100504
■006m o d
■007cr#unu||||||||
■020 ▼a9798380011259
■035 ▼a(MiAaPQ)AAI30493274
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a610.73
■1001 ▼aMasoud, Katherine.
■24510▼aImplementing a Prediabetes Screening Algorithm to Improve Identification and Referrals in Primary Care▼h[electronic resource]
■260 ▼a[S.l.]:▼bYale University. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(83 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-02, Section: B.
■500 ▼aAdvisor: Ramchandani, Neesha.
■5021 ▼aThesis (D.N.P.)--Yale University, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aAlmost 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.
■590 ▼aSchool code: 0265.
■650 4▼aNursing.
■650 4▼aHealth care management.
■653 ▼aPrediabetes
■653 ▼aRisk test
■653 ▼aScreening algorithm
■653 ▼aPopulation
■653 ▼aPrimary care
■690 ▼a0569
■690 ▼a0769
■71020▼aYale University▼bYale University School of Nursing.
■7730 ▼tDissertations Abstracts International▼g85-02B.
■773 ▼tDissertation Abstract International
■790 ▼a0265
■791 ▼aD.N.P.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16932480▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
