ArticleJournal of management policy and practice2024
Assessing Resources Devoted to Electronic Reporting and Automation Among Central Cancer Registries Meeting National Program of Cancer Registries (NPCR) Quality Standards.
Article in Journal of management policy and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The Centers for Disease Control and Prevention (CDC) has emphasized a need for data modernization initiatives (DMIs) to improve the quality and timeliness of cancer surveillance data. To guide such DMI efforts, we need data on the resources required to generate high-quality data. Twenty-one central cancer registries (CCRs) collected data from July 2020 to June 2021. We explored the potential relationship between resources for (1) electronic reporting and automation and (2) the quality of CCR data. We then compared activity-based costs of registries that always (n = 8), sometimes (n = 6), or seldom/never (n = 7) met data quality standards for completeness, timeliness, duplicate rate, and missing values. We found the registries that consistently met data quality standards used more resources on setting up processes to acquire data, training staff, and processing data. Compared to high-quality registries, registries that seldom/never met quality standards spent the most on case finding/data abstraction of non-hospital records. This study provides key findings for resource use, which can guide advancements when implementing electronic reporting and automation to improve CCR operations.
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Registered trials
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.