ArticleMedical care2018
Leveraging Linkage of Cohort Studies With Administrative Claims Data to Identify Individuals With Cancer.
Article in Medical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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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.
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.
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Who cites it
30 citing papers in PubMed.
- Cancer Risk With Advanced Therapies in Patients With Inflammatory Bowel Diseases: An Administrative Claims-Based Study.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2026Article
- Comparing Trends in Telemedicine Use and Geographic Disparities in Utilization Among Patients With Cancer in the United States.JCO oncology practice · 2026Article
- Rurality and Use of Metastasis-Directed Therapies for Medicare Beneficiaries with Metastatic Colon Cancer: A Retrospective Cohort Study.Annals of surgical oncology · 2026Article
- Changes in patient-sharing patterns after oncologist departures in rural and urban settings: a Medicare cohort study.Applied network science · 2026Article
- Small-Area Lung Cancer Incidence and Mortality: Cross-Sectional Population-Based Study Using Hospital Discharge and Death Registration Data.JMIR public health and surveillance · 2025Article
- Computational definition of medical exclusion and feasibility of excluding people not eligible for French population-based colorectal cancer screening from the French medico-administrative database.BMC medical informatics and decision making · 2025Review
- Antidepressant Use Trajectories and Risk of Discontinuation After Adolescents and Young Adult Cancer Diagnosis.Pharmacoepidemiology and drug safety · 2025Article
- Travel burden and bypassing closest site for surgical cancer treatment for urban and rural oncology patients.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2025Article
- Cross-State Travel for Cancer Care and Implications for Telehealth Reciprocity.JAMA network open · 2025Article
- Article
- Associations Between Oncology Outreach and Patient-Sharing Measures of Care Coordination.Cancer medicine · 2024Article
- Surgeon and Care Team Network Measures and Timely Breast Cancer Treatment.JAMA network open · 2024Article
- The Association Between Oncology Outreach and Timely Treatment for Rural Patients with Breast Cancer: A Claims-Based Approach.Annals of surgical oncology · 2024Article
- Characterizing the Traveling Oncology Workforce and Its Influence on Patient Travel Burden: A Claims-Based Approach.JCO oncology practice · 2024Article
- Comparison of US Oncologist Rurality by Practice Setting and Patients Served.JAMA network open · 2024Article
- Association of rurality, socioeconomic status, and race with pancreatic cancer surgical treatment and survival.Journal of the National Cancer Institute · 2023Article
- Association of rurality with utilization of palliative care and hospice among Medicare beneficiaries who died from pancreatic cancer: A cohort study.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2023Article
- Rural Disparities in Lung Cancer-directed Surgery: A Medicare Cohort Study.Annals of surgery · 2023Article
- Novel Algorithm for the Estimation of Cancer Incidence Using Claims Data in Japan: A Feasibility Study.JCO global oncology · 2023Article
- Use of a Novel Network-Based Linchpin Score to Characterize Accessibility to the Oncology Physician Workforce in the United States.JAMA network open · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundIn an effort to overcome quality and cost constraints inherent in population-based research, diverse data sources are increasingly being combined. In this paper, we describe the performance of a Medicare claims-based incident cancer identification algorithm in comparison with observational cohort data from the Nurses' Health Study (NHS).
methodsNHS-Medicare linked participants' claims data were analyzed using 4 versions of a cancer identification algorithm across 3 cancer sites (breast, colorectal, and lung). The algorithms evaluated included an update of the original Setoguchi algorithm, and 3 other versions that differed in the data used for prevalent cancer exclusions.
resultsThe algorithm that yielded the highest positive predictive value (PPV) (0.52-0.82) and κ statistic (0.62-0.87) in identifying incident cancer cases utilized both Medicare claims and observational cohort data (NHS) to remove prevalent cases. The algorithm that only used NHS data to inform the removal of prevalent cancer cases performed nearly equivalently in statistical performance (PPV, 0.50-0.79; κ, 0.61-0.85), whereas the version that used only claims to inform the removal of prevalent cancer cases performed substantially worse (PPV, 0.42-0.60; κ, 0.54-0.70), in comparison with the dual data source-informed algorithm.
conclusionsOur findings suggest claims-based algorithms identify incident cancer with variable reliability when measured against an observational cohort study reference standard. Self-reported baseline information available in cohort studies is more effective in removing prevalent cancer cases than are claims data algorithms. Use of claims-based algorithms should be tailored to the research question at hand and the nature of available observational cohort data.
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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.