Evidence map›Paper›PMID 35607984›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2022

Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery.

Silvia Moler-Zapata, Richard Grieve, David Lugo-Palacios, A Hutchings, R Silverwood, Luke Keele, Tommaso Kircheis, David Cromwell, Neil Smart, Robert Hinchliffe and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 2 countries.

Silvia Moler-ZapataDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0003-4733-5601
Richard GrieveDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-8899-1301
David Lugo-PalaciosDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
A HutchingsDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
R SilverwoodUniversity College London, London, UK.
Luke KeeleUniversity of Pennsylvania, Philadelphia, USA.ORCID 0000-0002-3859-2713
Tommaso KircheisDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
David CromwellDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
Neil SmartCollege of Medicine and Health, University of Exeter, Exeter, UK.
Robert HinchliffeBristol Surgical Trials Centre, University of Bristol, Bristol, UK.
Stephen O'NeillDepartment of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.
London School of Hygiene & Tropical Medicine · GBRoyal College of Surgeons of England · GBUniversity College London · GBUniversity of Bristol · GBUniversity of Exeter · GBUniversity of Pennsylvania · US

Funding

Medical Research Council MR/T025212/1
6 · The paper itself

Abstract

backgroundElectronic health records (EHRs) offer opportunities for comparative effectiveness research to inform decision making. However, to provide useful evidence, these studies must address confounding and treatment effect heterogeneity according to unmeasured prognostic factors. Local instrumental variable (LIV) methods can help studies address these challenges, but have yet to be applied to EHR data. This article critically examines a LIV approach to evaluate the cost-effectiveness of emergency surgery (ES) for common acute conditions from EHRs.

methodsThis article uses hospital episodes statistics (HES) data for emergency hospital admissions with acute appendicitis, diverticular disease, and abdominal wall hernia to 175 acute hospitals in England from 2010 to 2019. For each emergency admission, the instrumental variable for ES receipt was each hospital's ES rate in the year preceding the emergency admission. The LIV approach provided individual-level estimates of the incremental quality-adjusted life-years, costs and net monetary benefit of ES, which were aggregated to the overall population and subpopulations of interest, and contrasted with those from traditional IV and risk-adjustment approaches.

resultsThe study included 268,144 (appendicitis), 138,869 (diverticular disease), and 106,432 (hernia) patients. The instrument was found to be strong and to minimize covariate imbalance. For diverticular disease, the results differed by method; although the traditional approaches reported that, overall, ES was not cost-effective, the LIV approach reported that ES was cost-effective but with wide statistical uncertainty. For all 3 conditions, the LIV approach found heterogeneity in the cost-effectiveness estimates across population subgroups: in particular, ES was not cost-effective for patients with severe levels of frailty.

conclusionsEHRs can be combined with LIV methods to provide evidence on the cost-effectiveness of routinely provided interventions, while fully recognizing heterogeneity. HIGHLIGHTS: This article addresses the confounding and heterogeneity that arise when assessing the comparative effectiveness from electronic health records (EHR) data, by applying a local instrumental variable (LIV) approach to evaluate the cost-effectiveness of emergency surgery (ES) versus alternative strategies, for patients with common acute conditions (appendicitis, diverticular disease, and abdominal wall hernia).The instrumental variable, the hospital's tendency to operate, was found to be strongly associated with ES receipt and to minimize imbalances in baseline characteristics between the comparison groups.The LIV approach found that, for each condition, there was heterogeneity in the estimates of cost-effectiveness according to baseline characteristics.The study illustrates how an LIV approach can be applied to EHR data to provide cost-effectiveness estimates that recognize heterogeneity and can be used to inform decision making as well as to generate hypotheses for further research.

Indexed as

AppendicitisDiverticular DiseasesHernia, AbdominalAcute DiseaseCost-Benefit AnalysisElectronic Health RecordsHumanscost-effectiveness analysisemergency surgeryheterogeneous treatment effectsinstrumental variablepersonalized medicine

Identifiers

PMID35607984
PMCPMC9583279
OpenAlexW4282927688

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.