Literature DB >> 25002002

Non-visit-based cancer screening using a novel population management system.

Steven J Atlas1, Adrian H Zai2, Jeffrey M Ashburner2, Yuchiao Chang2, Sanja Percac-Lima2, Douglas E Levy2, Henry C Chueh2, Richard W Grant2.   

Abstract

BACKGROUND: Advances in information technology (IT) now permit population-based preventive screening, but the best methods remain uncertain. We evaluated whether involving primary care providers (PCPs) in a visit-independent population management IT application led to more effective cancer screening.
METHODS: We conducted a cluster-randomized trial involving 18 primary care practice sites and 169 PCPs from June 15, 2011, to June 14, 2012. Participants included adults eligible for breast, cervical, and/or colorectal cancer screening. In practices randomized to the intervention group, PCPs reviewed real-time rosters of their patients overdue for screening and provided individualized contact (via a letter, practice delegate, or patient navigator) or deferred screening (temporarily or permanently). In practices randomized to the comparison group, overdue patients were automatically sent reminder letters and transferred to practice delegate lists for follow-up. Intervention patients without PCP action within 8 weeks defaulted to the automated control version. The primary outcome was adjusted average cancer screening completion rates over 1-year follow-up, accounting for clustering by physician or practice.
RESULTS: Baseline cancer screening rates (80.8% vs 80.3%) were similar among patients in the intervention (n = 51,071) and comparison group (n = 52,799). Most intervention providers used the IT application (88 of 101, 87%) and users reviewed 7984 patients overdue for at least 1 cancer screening (73% sent reminder letter, 6% referred directly to a practice delegate or patient navigator, and 21% deferred screening). In addition, 6128 letters were automatically sent to patients in the intervention group (total of 12,002 letters vs 16,378 letters in comparison practices; P < .001). Adjusted average cancer screening rates did not differ among intervention and comparison practices for all cancers combined (81.6% vs 81.4%; P = .84) nor breast (82.7% vs 82.7%; P = .96), cervical (84.1% vs 84.7%; P = .60), or colorectal cancer (77.8% vs 76.2%; P = .33).
CONCLUSIONS: Involving PCPs in a visit-independent population management IT application resulted in similar cancer screening rates compared with an automated reminder system, but fewer patients were sent reminder letters. This suggests that PCPs were able to identify and exclude from contact patients who would have received automated reminder letters but not undergone screening. © Copyright 2014 by the American Board of Family Medicine.

Entities:  

Keywords:  Cancer Screening; Prevention; Primary Health Care

Mesh:

Year:  2014        PMID: 25002002     DOI: 10.3122/jabfm.2014.04.130319

Source DB:  PubMed          Journal:  J Am Board Fam Med        ISSN: 1557-2625            Impact factor:   2.657


  9 in total

1.  Effect of Combined Patient Decision Aid and Patient Navigation vs Usual Care for Colorectal Cancer Screening in a Vulnerable Patient Population: A Randomized Clinical Trial.

Authors:  Daniel S Reuland; Alison T Brenner; Richard Hoffman; Andrew McWilliams; Robert L Rhyne; Christina Getrich; Hazel Tapp; Mark A Weaver; Danelle Callan; Laura Cubillos; Brisa Urquieta de Hernandez; Michael P Pignone
Journal:  JAMA Intern Med       Date:  2017-07-01       Impact factor: 21.873

2.  Evaluation of Interventions Intended to Increase Colorectal Cancer Screening Rates in the United States: A Systematic Review and Meta-analysis.

Authors:  Michael K Dougherty; Alison T Brenner; Seth D Crockett; Shivani Gupta; Stephanie B Wheeler; Manny Coker-Schwimmer; Laura Cubillos; Teri Malo; Daniel S Reuland
Journal:  JAMA Intern Med       Date:  2018-12-01       Impact factor: 21.873

3.  Building Equity Improvement into Quality Improvement: Reducing Socioeconomic Disparities in Colorectal Cancer Screening as Part of Population Health Management.

Authors:  Seth A Berkowitz; Sanja Percac-Lima; Jeffrey M Ashburner; Yuchiao Chang; Adrian H Zai; Wei He; Richard W Grant; Steven J Atlas
Journal:  J Gen Intern Med       Date:  2015-02-13       Impact factor: 5.128

Review 4.  Interventions targeted at women to encourage the uptake of cervical screening.

Authors:  Helen Staley; Aslam Shiraz; Norman Shreeve; Andrew Bryant; Pierre Pl Martin-Hirsch; Ketankumar Gajjar
Journal:  Cochrane Database Syst Rev       Date:  2021-09-06

5.  Non-Communicable Disease Preventive Screening by HIV Care Model.

Authors:  Corinne M Rhodes; Yuchiao Chang; Susan Regan; Virginia A Triant
Journal:  PLoS One       Date:  2017-01-06       Impact factor: 3.240

6.  Patient navigation for lung cancer screening among current smokers in community health centers a randomized controlled trial.

Authors:  Sanja Percac-Lima; Jeffrey M Ashburner; Nancy A Rigotti; Elyse R Park; Yuchiao Chang; Salome Kuchukhidze; Steven J Atlas
Journal:  Cancer Med       Date:  2018-02-21       Impact factor: 4.452

7.  Satisfaction With Health Care Among Patients Navigated for Preventive Cancer Screening.

Authors:  Emilia A Hermann; Jeffrey M Ashburner; Steven J Atlas; Yuchiao Chang; Sanja Percac-Lima
Journal:  J Patient Exp       Date:  2018-01-17

8.  Impact of Patient Navigation on Population-Based Breast Screening: a Systematic Review and Meta-analysis of Randomized Clinical Trials.

Authors:  Lu Tian; Lei Huang; Jie Liu; Xia Li; Aisha Ajmal; Maryam Ajmal; Yunjin Yao; Li Tian
Journal:  J Gen Intern Med       Date:  2022-06-01       Impact factor: 6.473

9.  Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study.

Authors:  Stijn Van de Velde; Tiina Kortteisto; David Spitaels; Gro Jamtvedt; Pavel Roshanov; Ilkka Kunnamo; Bert Aertgeerts; Per Olav Vandvik; Signe Flottorp
Journal:  JMIR Res Protoc       Date:  2018-06-11
  9 in total

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