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Indication alerts to improve problem list documentation.
Grauer, Anne; Kneifati-Hayek, Jerard; Reuland, Brian; Applebaum, Jo R; Adelman, Jason S; Green, Robert A; Lisak-Phillips, Jeanette; Liebovitz, David; Byrd, Thomas F; Kansal, Preeti; Wilkes, Cheryl; Falck, Suzanne; Larson, Connie; Shilka, John; VanDril, Elizabeth; Schiff, Gordon D; Galanter, William L; Lambert, Bruce L.
Afiliación
  • Grauer A; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Kneifati-Hayek J; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Reuland B; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Applebaum JR; Department of Quality and Patient Safety, New York-Presbyterian Hospital, New York City, New York, USA.
  • Adelman JS; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Green RA; Department of Quality and Patient Safety, New York-Presbyterian Hospital, New York City, New York, USA.
  • Lisak-Phillips J; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Liebovitz D; Department of Quality and Patient Safety, New York-Presbyterian Hospital, New York City, New York, USA.
  • Byrd TF; Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
  • Kansal P; Department of Medicine, Northwestern University, Chicago, Illinois, USA.
  • Wilkes C; Department of Medicine, Northwestern University, Chicago, Illinois, USA.
  • Falck S; Department of Medicine, Northwestern University, Chicago, Illinois, USA.
  • Larson C; Department of Medicine, Northwestern University, Chicago, Illinois, USA.
  • Shilka J; Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA.
  • VanDril E; Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Schiff GD; Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Galanter WL; Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA.
  • Lambert BL; Brigham and Women's Hospital Center for Patient Safety Research, Harvard Medical School Center for Primary Care, Boston, Massachusetts, USA.
J Am Med Inform Assoc ; 29(5): 909-917, 2022 04 13.
Article en En | MEDLINE | ID: mdl-34957491
ABSTRACT

BACKGROUND:

Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication.

METHODS:

We analyzed medication orders from 2 healthcare systems that used an innovative indication alert. We collected data at site 1 between December 2018 and January 2020, and at site 2 between May and June 2021. We reviewed random samples of 100 charts from each site that had problems added in response to the alert. Outcomes were (1) alert yield, the proportion of triggered alerts that led to a problem added and (2) problem accuracy, the proportion of problems placed that were accurate by chart review.

RESULTS:

Alerts were triggered 131 134, and 6178 times at sites 1 and 2, respectively, resulting in a yield of 109 055 (83.2%) and 2874 (46.5%), P< .001. Orders were abandoned, for example, not completed, in 11.1% and 9.6% of orders, respectively, P<.001. Of the 100 sample problems, reviewers deemed 88% ± 3% and 91% ± 3% to be accurate, respectively, P = .65, with a mean of 90% ± 2%.

CONCLUSIONS:

Indication alerts triggered by medication orders initiated in the absence of a justifying diagnosis were useful for populating problem lists, with yields of 83.2% and 46.5% at 2 healthcare systems. Problems were placed with a reasonable level of accuracy, with 90% ± 2% of problems deemed accurate based on chart review.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas / Sistemas de Entrada de Órdenes Médicas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Sistemas de Apoyo a Decisiones Clínicas / Sistemas de Entrada de Órdenes Médicas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos