Journal of registry management最新文献

After reading the article and completing the quiz, the participants will be able to: Understand why a Merkel cell patient registry was implementedDescribe the advantages of a rare tumor registryDescribe the method for implementation of the Merkel Cell Carcinoma (MCC) Patient Registry.

After reading the educational posters and completing the quiz, participants will be able to: Describe how changes in access to medical care due to COVID-19 likely affect cancer incidence ratesUnderstand how state-specific patient claims databases can be leveraged to get an early picture of the impact of COVID-19 on cancer rates.

Introduction: Central cancer registries are responsible for managing appropriate research contacts and record releases. Do not contact (DNC) flags are used by some registries to indicate patients who should not be contacted or included in research. Longitudinal changes in DNC coding practices and definitions may result in a lack of code standardization and inaccurately include or exclude individuals from research.

Purpose: We performed a comprehensive manual review of DNC cases in the Utah Cancer Registry to inform updates to standardization of DNC code definitions, and use of DNC codes for exclusion/inclusion in research.

Methods: We identified 858 cases with a current or prior DNC flag in the SEER Data Management System (SEER*DMS) or a research database, with cancers diagnosed from 1957-2021. We reviewed scanned images of correspondence with cases and physicians, incident forms, and comments in SEER*DMS and research databases. We evaluated whether there was evidence to support the current DNC code, a different DNC code, or insufficient evidence for any code.

Results: Of the 755 cases that had a current DNC flag and reason code in SEER*DMS, the distribution was as follows: 58%, Patient requested no contact; 20%, Physician denied; 13%, Patient is not aware they have cancer; 4%, Patient is mentally disabled [sic]; 4%, Other; and 1%, Unknown. In 5% of these cases, we found evidence supporting a different DNC reason code. Among cases included because of a prior DNC flag in SEER*DMS (n = 10) or a DNC flag in a research database (ie, cases with no current DNC flag or reason code in SEER*DMS, n = 93), we found evidence supporting the addition of a SEER*DMS DNC flag and reason code in 50% and 40% of cases, respectively. We identified DNC reason codes with outdated terminology (Patient is mentally disabled) and codes that may not accurately reflect patient research preferences (Physician denied without asking the patient). To address this, we identified new reason codes, retired old reason codes, and updated current reason code definitions and research handlings.

Conclusion: The time and resource investment in manual review allowed us to identify and, in most cases, resolve discordance in DNC flags and reason codes, adding reason codes when they were missing. This process was valuable because it informed recommended changes to DNC code definitions and research handlings that will ensure more appropriate inclusion and exclusion of cancer cases in research.

Objectives: We aim to assess external and internal attributes and operations of the Centers for Disease Control and Prevention (CDC)'s National Program of Cancer Registries (NPCR) central cancer registries by their consistency in meeting national data quality standards.

Methods: The NPCR 2017 Program Evaluation Instrument (PEI) data were used to assess registry operational attributes, including adoption of electronic reporting, compliance with reporting, staffing, and software used among 46 NPCR registries. These factors were stratified by (1) registries that met the NPCR 12-month standards for all years 2014-2017; (2) registries that met the NPCR 12-month standards at least once in 2014-2017 and met the NPCR 24-month standards for all years 2014-2017; and (3) registries that did not meet the NPCR 24-month standards for all years 2014-2017. Statistical tests helped identify significant differences among registries that consistently, sometimes, or seldom/never achieved data standards.

Results: Registries that always met the standards had a higher level of electronic reporting and a higher compliance with reporting among hospitals than registries that sometimes or seldom/never met the standards. Although not a statistically significant finding, the same registries also had a higher proportion of staffing positions filled, a higher proportion of certified tumor registrars, and more quality assurance and information technology staff.

Conclusions: This information may be used to understand the importance of various factors and characteristics, including the adoption of electronic reporting, that may be associated with a registry's ability to consistently meet NPCR standards. The findings may be helpful in identifying best practices for processing high-quality cancer data.

Introduction: Integration of screening data into routine cancer surveillance systems can create more robust data systems to inform cancer prevention and control activities. Currently, state central cancer registries do not routinely collect breast and cervical cancer screening data as part of state cancer surveillance activities. Florida conducted a pilot study involving: (1) linkage of breast and cervical cancer screening data from the Florida Breast and Cervical Cancer Early Detection Program (FBCCEDP) from 2009 to 2021 to the Florida Cancer Data System (FCDS) database to capture screening data for matched cancer cases in the FCDS; and (2) evaluation of the feasibility of developing a population-based breast and cervical cancer screening surveillance system by capturing electronic screening data from private health care providers.

Methods: In 2018, the FCDS worked with the Florida Department of Health to identify data partners for the 5-year cancer screening pilot project funded by the Centers for Disease Control and Prevention. Engagement of project partners required extensive review of available screening data; data standards and formatting; data transmission schedules and methods; and processing procedures. The FCDS developed a database to integrate multiple source data sets into a single database whereby linkage to the central cancer registry could be performed.

Results: The FCDS worked with Suncoast Health Systems, a clinical practice in the Hillsborough region of Florida, and the FBCCEDP to evaluate data availability, standardization of data sets, and data submission schedules for the pilot project. Extensive meetings and data reviews were conducted with both partners in the first phase of the project. The FCDS developed automated data processing procedures to integrate the data into a single cancer screening database and then linked records to the central cancer registry data set.

Discussion: Registry collaboration with the FBCCEDP and Suncoast team on data quality and standardization has produced positive results. The project required extensive review of data and produced many lessons learned for development of a cancer screening surveillance system. Our pilot project depended on partnership building, commitment to data quality, and consistency in data submission practices.