Evidence map›Paper›PMID 35802837›Full record

ArticleJCO clinical cancer informatics2022

Supporting Structured Data Capture for Patients With Cancer: An Initiative of the University of Wisconsin Carbone Cancer Center Survivorship Program to Improve Capture of Malignant Diagnosis and Cancer Staging Data.

Hamid Emamekhoo, Cibele B Carroll, Chelsea Stietz, Jeffrey B Pier, Michael D Lavitschke, Daniel Mulkerin, Mary E Sesto, Amye J Tevaarwerk

Open access · greenAbstract read
In one paragraph

Article in JCO clinical cancer informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Developing the multidisciplinary and multispecialty workforce and the systems needed to sustain high-quality care from diagnosis through long-term survivorship.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

8 authors at 5 institutions in 1 country.

Hamid EmamekhooUniversity of Wisconsin, Madison, WI.ORCID 0000-0002-8506-8703
Cibele B CarrollCarbone Cancer Center, Madison, WI.ORCID 0000-0003-2681-0928
Chelsea StietzUW Health, Madison, WI.
Jeffrey B PierUW Health, Madison, WI.
Michael D LavitschkeUW Health, Madison, WI.
Daniel MulkerinUniversity of Rochester, Rochester, NY.
Mary E SestoUniversity of Wisconsin, Madison, WI.
Amye J TevaarwerkMayo Clinic, Rochester, MN.ORCID 0000-0002-8087-5119
University of Wisconsin Health · USUniversity of Wisconsin–Madison · USMayo Clinic in Arizona · USUniversity of Rochester · USUniversity of Wisconsin Carbone Cancer Center · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Justine Yang Bruce · 1985 to 2026
$142.6M
University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NCI NIH HHS P30 CA014520
6 · The paper itself

Abstract

purposeStructured data elements within electronic health records are health-related information that can be entered, stored, and extracted in an organized manner at later time points. Tracking outcomes for cancer survivors is also enabled by structured data. We sought to increase structured data capture within oncology practices at multiple sites sharing the same electronic health records.

methodsApplying engineering approaches and the Plan-Do-Study-Act cycle, we launched dual quality improvement initiatives to ensure that a malignant diagnosis and stage were captured as structured data. Intervention: Close Visit Validation (CVV) requires providers to satisfy certain criteria before closing ambulatory encounters. CVV may be used to track open clinical encounters and chart delinquencies to encourage optimal clinical workflows. We added two cancer-specific required criteria at the time of closing encounters in oncology clinics: (1) the presence of at least one malignant diagnosis on the Problem List and (2) staging all the malignant diagnoses on the Problem List when appropriate.

resultsSix months before the CVV implementation, the percentage of encounters with a malignant diagnosis on the Problem List at the time of the encounter was 65%, whereas the percentage of encounters with a staged diagnosis was 32%. Three months after cancer-specific CVV implementation, the percentages were 85% and 75%, respectively. Rates had increased to 90% and 88% more than 2 years after implementation.

conclusionOncologist performance improved after the implementation of cancer-specific CVV criteria, with persistently high percentages of relevant malignant diagnoses and cancer stage structured data capture 2 years after the intervention.

Indexed as

NeoplasmsSurvivorshipHumansNeoplasm StagingUniversitiesWisconsin

Identifiers

PMID35802837
PMCPMC9296185
OpenAlexW4284959046

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.