Evidence map›Paper›PMID 31564812›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2019

Identification of cancer patients using claims data from health insurance systems: A real-world comparative study.

Hongrui Tian, Ruiping Xu, Fenglei Li, Chuanhai Guo, Lixin Zhang, Zhen Liu, Mengfei Liu, Yaqi Pan, Zhonghu He, Yang Ke

Abstract read
In one paragraph

Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  4. Challenge and future of cancer screening in China: Insights from esophageal cancer screening practice.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023
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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

10 authors.

Hongrui TianKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Ruiping XuAnyang Cancer Hospital, Anyang 455000, China.
Fenglei LiHua County People's Hospital, Anyang 456400, China.
Chuanhai GuoKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Lixin ZhangAnyang Cancer Hospital, Anyang 455000, China.
Zhen LiuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Mengfei LiuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Yaqi PanKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Zhonghu HeKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Yang KeKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China.

methodsWe chose Hua County, Henan Province as the study site, and randomly selected 300 and 1,200 qualified inpatient electronic medical records (EMRs) as well as the New Rural Cooperative Medical Scheme (NCMS) claims records for cancer patients in Hua County People's Hospital (HCPH) and Anyang Cancer Hospital (ACH) in 2017. Diagnostic information for NCMS claims was evaluated on an individual level, and sensitivity and positive predictive value (PPV) were calculated taking the EMRs as the gold standard.

resultsThe sensitivity of NCMS was 95.2% (93.8%-96.3%) and 92.0% (88.3%-94.8%) in ACH and HCPH, respectively. The PPV of the NCMS was 97.8% (96.7%-98.5%) in ACH and 89.0% (84.9%-92.3%) in HCPH. Overall, the weighted and combined sensitivity and PPV of NCMS in Hua County was 93.1% and 92.1%, respectively. Significantly higher sensitivity and PPV in identifying patients with common cancers than non-common cancers were detected in HCPH and ACH separately (P<0.01).

conclusionsIdentification of cancer patients by use of the NCMS is accurate on individual level, and it is therefore feasible to conduct claims-based cancer surveillance in areas not covered by cancer registries in China.

Indexed as

cancer surveillanceclaims dataNCMSpositive predictive valuesensitivity

Identifiers

PMID31564812
PMCPMC6736657

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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.