Reduction in Clinical Variance Using Targeted Design Changes in Computerized Provider Order Entry Order (CPOE) Sets

Brian Jacobs458 enrolled

Overview

Selective redesign of order sets using different ways to frame the order and physician decision-making in a computerized provider order entry system could increase adherence to evidence-based care and reduce population-specific variance.

Variance in ordering of care can be characterized as the lack of uniform use of specific treatments by clinicians for a given medical condition. Unwarranted variance in healthcare has been associated with prolonged length of stay, diminished health and increased cost. Practice variation in the management of asthma can be significant and few investigators have evaluated strategies to reduce this variation. We hypothesized that selective redesign of order sets using different ways to frame the order and physician decision-making in a computerized provider order entry system could increase adherence to evidence-based care and reduce population-specific variance.

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

HEALTH_SERVICES_RESEARCH

Masking

NONE

Enrollment

458

Conditions

Asthma Exacerbation

Interventions

Evidence Based Intervention to order setOTHER

The order set was altered to include evidence based care items

Eligibility

Sex: ALL

Medical Language ↔ Plain English

Inclusion Criteria: * All patients admitted using an acute asthma exacerbation order set. Exclusion Criteria: * Patients who did not have either an admission or discharge diagnosis of asthma exacerbation. * In addition, patients admitted to the intensive care unit directly or transferred to the intensive care unit within 24-hours were excluded from analysis. * Finally, patients were excluded from analysis if asthma was not the presenting problem.

Locations (1)

Cincinnati Children's Hospital Medical Center

Cincinnati, Ohio, United States

Outcomes

Primary Outcomes

Reduced variation from in evidence-based care through integrating evidence into the clinician workflow in the EMR system.

Time frame: 2 years

Data from ClinicalTrials.gov

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