Evidence map›Paper›PMID 28729232›Full record

ArticleJMIR cancer2017

Development, Feasibility, and Small-Scale Implementation of a Web-Based Prognostic Tool-Surveillance, Epidemiology, and End Results Cancer Survival Calculator.

Michelle Henton, Bridget Gaglio, Laurie Cynkin, Eric J Feuer, Borsika A Rabin

Abstract read
In one paragraph

Article in JMIR cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. Review
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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

5 authors.

Michelle HentonClinical Effectiveness and Decision Science, Patient-Centered Outcomes Research Institute, Washington, DC, United States.ORCID http://orcid.org/0000-0003-3649-1510
Bridget GaglioClinical Effectiveness and Decision Science, Patient-Centered Outcomes Research Institute, Washington, DC, United States.ORCID http://orcid.org/0000-0003-1020-3066
Laurie CynkinOffice of Advocacy Relations, Office of the Director, National Cancer Institute, Bethesda, MD, United States.ORCID http://orcid.org/0000-0002-7648-4289
Eric J FeuerStatistical Research and Applications Branch, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, United States.ORCID http://orcid.org/0000-0003-4842-7751
Borsika A RabinDepartment of Family Medicine and Public Health, School of Medicine, University of California San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0001-9837-7866

Funding

Training and DevelopmentP20CA137219 · NCI · KAISER FOUNDATION RESEARCH INSTITUTE · PI DEARING, JAMES WILLIAM · 2008 to 2012
$7.8M
NCI NIH HHS P20 CA137219
6 · The paper itself

Abstract

backgroundPopulation datasets and the Internet are playing an ever-growing role in the way cancer information is made available to providers, patients, and their caregivers. The Surveillance, Epidemiology, and End Results Cancer Survival Calculator (SEER*CSC) is a Web-based cancer prognostic tool that uses SEER data, a large population dataset, to provide physicians with highly valid, evidence-based prognostic estimates for increasing shared decision-making and improving patient-provider communication of complex health information.

objectiveThe aim of this study was to develop, test, and implement SEER*CSC.

methodsAn iterative approach was used to develop the SEER*CSC. Based on input from cancer patient advocacy groups and physicians, an initial version of the tool was developed. Next, providers from 4 health care delivery systems were recruited to do formal usability testing of SEER*CSC. A revised version of SEER*CSC was then implemented in two health care delivery sites using a real-world clinical implementation approach, and usage data were collected. Post-implementation follow-up interviews were conducted with site champions. Finally, patients from two cancer advocacy groups participated in usability testing.

resultsOverall feedback of SEER*CSC from both providers and patients was positive, with providers noting that the tool was professional and reliable, and patients finding it to be informational and helpful to use when discussing their diagnosis with their provider. However, use during the small-scale implementation was low. Reasons for low usage included time to enter data, not having treatment options in the tool, and the tool not being incorporated into the electronic health record (EHR). Patients found the language in its current version to be too complex.

conclusionsThe implementation and usability results showed that participants were enthusiastic about the use and features of SEER*CSC, but sustained implementation in a real-world clinical setting faced significant challenges. As a result of these findings, SEER*CSC is being redesigned with more accessible language for a public facing release. Meta-tools, which put different tools in context of each other, are needed to assist in understanding the strengths and limitations of various tools and their place in the clinical decision-making pathway. The continued development and eventual release of prognostic tools should include feedback from multidisciplinary health care teams, various stakeholder groups, patients, and caregivers.

Indexed as

clinical decision-makingcommunicationInternetneoplasmspatient care team

Identifiers

PMID28729232
PMCPMC5544898

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.