Literature DB >> 27573987

Improving the Understanding of Publicly Reported Healthcare-Associated Infection (HAI) Data.

Max Masnick1, Daniel J Morgan2, Mark D Macek3, John D Sorkin4, Jessica P Brown1, Penny Rheingans5, Anthony D Harris1.   

Abstract

OBJECTIVE Hospital-acquired infection (HAI) data are reported to the public on the Centers for Medicare and Medicaid Services (CMS) Hospital Compare website. We previously found that public understanding of these data is poor. Our objective was to develop an improved method for presenting HAI data that could be used on the CMS website. DESIGN Randomized controlled trial comparing understanding of data presented using the current CMS presentation strategy versus a new strategy. SETTING A 760-bed tertiary referral hospital. PARTICIPANTS A total of 61 patients were randomly selected within 24 hours of admission. INTERVENTION Participants were shown HAI data as presented on the CMS Hospital Compare website (control arm) or data formatted using a new method (experimental arm). RESULTS No statistically significant demographic differences were identified between study arms. Although 47% percent of participants said a website for comparing hospitals would have been helpful, only 10% had ever used such a website. Participants viewing data using the new presentation strategy compared hospitals correctly 56% of the time, compared with 32% in the control arm (P=.0002). CONCLUSIONS Understanding of HAI data increased significantly with the new data presentation method compared to the method currently used on the CMS Hospital Compare website. Many participants expressed interest in a website for comparing hospitals. Improved methods for presenting CMS HAI data, such as the one assessed here, should be adopted to increase public understanding. Infect Control Hosp Epidemiol 2016;1-6.

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Year:  2016        PMID: 27573987      PMCID: PMC6849396          DOI: 10.1017/ice.2016.180

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  3 in total

Review 1.  Evidence-based risk communication: a systematic review.

Authors:  Daniella A Zipkin; Craig A Umscheid; Nancy L Keating; Elizabeth Allen; KoKo Aung; Rebecca Beyth; Scott Kaatz; Devin M Mann; Jeremy B Sussman; Deborah Korenstein; Connie Schardt; Avishek Nagi; Richard Sloane; David A Feldstein
Journal:  Ann Intern Med       Date:  2014-08-19       Impact factor: 25.391

2.  Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website.

Authors:  Max Masnick; Daniel J Morgan; John D Sorkin; Elizabeth Kim; Jessica P Brown; Penny Rheingans; Anthony D Harris
Journal:  Infect Control Hosp Epidemiol       Date:  2015-11-23       Impact factor: 3.254

3.  Visual representation of statistical information improves diagnostic inferences in doctors and their patients.

Authors:  Rocio Garcia-Retamero; Ulrich Hoffrage
Journal:  Soc Sci Med       Date:  2013-02-08       Impact factor: 4.634

  3 in total
  1 in total

1.  How do pregnant women use quality measures when choosing their obstetric provider?

Authors:  Rebecca A Gourevitch; Ateev Mehrotra; Grace Galvin; Melinda Karp; Avery Plough; Neel T Shah
Journal:  Birth       Date:  2017-01-26       Impact factor: 3.689

  1 in total

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