Evidence map›Paper›PMID 29845468›Full record

ArticleJournal of general internal medicine2018

Impact of Cost Display on Ordering Patterns for Hospital Laboratory and Imaging Services.

Mark T Silvestri, Xiao Xu, Theodore Long, Tasce Bongiovanni, Steven L Bernstein, Sarwat I Chaudhry, Julia I Silvestri, Marilyn Stolar, Erich J Greene, James D Dziura and 2 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of general internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Testing wisely: toward more efficient laboratory utilization.Proceedings (Baylor University. Medical Center) · 2024
    Article
  5. Huisarts en wetenschap · 2022
    Article
  6. Article
  7. Article
  8. Laboratory Demand Management Strategies-An Overview.Diagnostics (Basel, Switzerland) · 2021
    Review
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Mark T SilvestriRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA. mark.silvestri@yale.edu.
Xiao XuDepartment of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, New Haven, CT, USA.
Theodore LongRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Tasce BongiovanniRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Steven L BernsteinRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Sarwat I ChaudhryRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Julia I SilvestriZearn Math, New York, NY, USA.
Marilyn StolarYale Center for Analytical Sciences, Yale School of Public Health, New Haven, CT, USA.
Erich J GreeneYale Center for Analytical Sciences, Yale School of Public Health, New Haven, CT, USA.
James D DziuraDepartment of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA.
Cary P GrossRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Harlan M KrumholzRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, CT, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
6 · The paper itself

Abstract

backgroundPhysicians "purchase" many health care services on behalf of patients yet remain largely unaware of the costs of these services. Electronic health record (EHR) cost displays may facilitate cost-conscious ordering of health services.

objectiveTo determine whether displaying hospital lab and imaging order costs is associated with changes in the number and costs of orders placed.

designQuasi-experimental study.

participantsAll patients with inpatient or observation encounters across a multi-site health system from April 2013 to October 2015.

interventionDisplay of order costs, based on Medicare fee schedules, in the EHR for 1032 lab tests and 1329 imaging tests. MAIN MEASURES: Outcomes for both lab and imaging orders were (1) whether an order was placed during a hospital encounter, (2) whether an order was placed on a given patient-day, (3) number of orders placed per patient-day, and (4) cost of orders placed per patient-day. KEY

resultsDuring the lab and imaging study periods, there were 248,214 and 258,267 encounters, respectively. Cost display implementation was associated with a decreased odds of any lab or imaging being ordered during the encounter (lab adjusted odds ratio [AOR] = 0.97, p = .01; imaging AOR = 0.97, p < .001), a decreased odds of any lab or imaging being ordered on a given patient-day (lab AOR = 0.95, p < .001; imaging AOR = 0.97, p < .001), a decreased number of lab or imaging orders on patient-days with orders (lab adjusted count ratio = 0.93, p < .001; imaging adjusted count ratio = 0.98, p < .001), and a decreased cost of lab orders and increased cost of imaging orders on patient-days with orders (lab adjusted cost ratio = 0.93, p < .001; imaging adjusted cost ratio = 1.02, p = .003). Overall, the intervention was associated with an 8.5 and 1.7% reduction in lab and imaging costs per patient-day, respectively.

conclusionsDisplaying costs within EHR ordering screens was associated with decreases in the number and costs of lab and imaging orders.

Indexed as

Fees and ChargesAcademic Medical CentersClinical Laboratory TechniquesDiagnostic ImagingFemaleHospitalizationHumansMalePractice Patterns, Physicians'cost displayelectronic health recordphysician ordering patterns

Identifiers

PMID29845468
PMCPMC6082197

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.