How to Lose (and Regain) 3.6 Billion Euros

This chapter imagines a conversation between two senior civil servants when they realize that the Irish government has lost 3.6 billion euros through a spreadsheet error. The Assistant Secretary of the Department of Finance reports to the General Secretary that the accountant was not sure how to classify a loan to the Housing Finance Agency (HFA) from the National Treasury Management Agency (NTMA). They had assumed that it might be adjusted for elsewhere in the General Government Debt calculations, but it was not. As such, the government debt appears twice in the national accounts, once as an asset for the NTMA and once as a liability for the HFA. The General Secretary then asks why the data entry error was not picked up. The Assistant Secretary answers that everybody assumed that somebody else had dealt with it. The accounts got returned, nobody spotted the mistake, and everyone moved onto to other tasks.

Cohort profile: the Alberta Prostate Cancer Research Initiative (APCaRI) Registry and Biorepository facilitates technology translation to the clinic through the use of linked, longitudinal clinical and patient-reported data and biospecimens from men in Alberta, Canada

PurposeThe Alberta Prostate Cancer Research Initiative (APCaRI) Registry and Biorepository was established in 2014 by the APCaRI to facilitate the collection of clinical and patient-reported data, biospecimen, to measure prostate cancer outcomes and to support the development and clinical translation of innovative technologies to better diagnose and predict outcomes for patients with prostate cancer.ParticipantsMen suspected with prostate cancer and referred to Urology centres in Alberta were enrolled in the APCaRI 01 study, while men with a prior prostate cancer diagnosis participated in the APCaRI 03 study from 1 July 2014 to 30 June 2019. The APCaRI Registry and Biorepository links biospecimens and data from a wide representation of patients drawn from an Alberta population of more than 4 million.Findings to dateFrom 1 July 2014 to 30 June 2019, total APCaRI 01 and 03 study recruitment was 3754 men; 142 (4%) of these men withdrew in full, 65 men (2%) withdrew biospecimens and 123 men (3%) died of any cause. Over this same time, 8677 patient-reported outcome measure (PROM) surveys and 7368 biospecimens were collected and are available from the registry and biorepository, respectively. The data entry error rate was 0.8% and 0.95% for critical and non-critical values, respectively, and 1.8% for patient-reported surveys.Future plansThe APCaRI Registry and Biorepository will collect longitudinal data and PROM surveys until 2024, patient outcomes up to 25 years after recruitment and biospecimen storage for up to 25 years. The APCaRI cohorts will continue to provide data and samples to researchers conducting retrospective studies. The richness of the data and biospecimens will complement many different research questions, ultimately to improve the quality of care for men with prostate cancer.

Measles Data Reporting in the District Health Information System: A Case Study of Gombe State

BACKGROUND: The District Health Information System (DHIS2) is a modular, cloud-based data management system designed for use in integrated health information systems. In Nigeria, it serves as the repository for routine health data, including measles. A first dose of measles is given routinely in most countries, however, for a country to include a second dose of measles in the routine immunization schedule, it must meet certain criteria set by the World Health Organization (WHO). Unfortunately, Nigeria falls into the category of countries that haven’t met the criteria. Despite this, MCV2 data can be seen on the DHIS2 platform. Data from DHIS2 also shows that Gombe State has the highest number of health facilities that reported MCV2 data at least once from 2015 to 2017. The aim of the study was to determine the reasons for the MCV2 reporting on DHIS2 platform for Gombe State. METHOD: We conducted a cross-sectional study among health workers in selected health facilities and LGA RI Officers at the LGA level in Gombe State. Health facility registers were reviewed, and data consistency was ascertained. We reviewed and conducted secondary data analysis of MCV2 data for Gombe State from January 2015 to December 2017. RESULTS: Of the 22 health facilities assessed, 14 health facilities (12 public and 2 private) reported offering MCV2 during the health facility-level interviews. At the LGA level, 5 LGAs out of the 11 LGAs reported during the LGA-level interviews that a second dose of measles is part of the RI schedule in their respective LGAs. For the 6 LGAs that reported not offering a second dose of measles as part of the RI schedule, 3 LGAs identified data entry error as the possible reason for having MCV2 data in the DHSI2 platform while the remaining 3 LGAs reported that the MCV2 data in the DHIS2 platform can be attributed to recording children who didn’t receive a first dose of measles at 9 months but received at 18–23 months as second dose of measles. CONCLUSION: Data entry error and knowledge gap on how to record measles data were identified factors responsible for MCV2 data on the DHIS2 platform. There is a need for targeted interventions towards improving the quality of RI data in Nigeria.

An analysis of aircraft maintenance incidents using psychological and cognitive engineering knowledge

The aim of the current analysis is to complement existing studies of aircraft maintenance incidents by providing finer and more detailed explanations for their causes in terms of task and error types. A total of 109 aircraft maintenance incidents were analyzed with respect to knowledge and concepts from psychology and cognitive engineering. The skill, rule and knowledge-based framework by Rasmussen (1983) was used to identify the main task types involved in the incidents. Error types such as post-completion error, prospective memory failure and data-entry error were used as part of the analysis. System usability and the occurrence of interruptions, distractions and multitasking were also adopted as important factors in the analysis. Results suggest that more than 60% of the incidents involved rule-based performance. Almost 50% of the rule-based incidents can be explained in terms of the errors types and factors identified. This analysis provides a starting point for practitioners to discuss aircraft maintenance incidents using theoretically grounded concepts.

Web-Based Survey Software for Academic Research

The features of Datacurious, a web-based survey software program designed specifically for academic research, are examined in this article. Web-based data collection has been deemed an effective, reliable, and safe method of data collection, while also saving researchers time, effort, and cost and reducing data entry error. Recent developments in web-based survey software systems allow data be collected through relatively simple, easy-to-use interfaces, making the technology accessible to researchers with little to no technical expertise. Datacurious, available online at www.datacurious.com, utilizes an intuitive and user-friendly interface with broad capabilities in its survey designer. Programming enables researchers to adhere to ethical guidelines for surveying human subjects. Technical features of datacurious ensure survey participant privacy and confidentiality and provide options for informed consent, incentive, and debriefing pages. Datacurious also allows researchers to control entry to online surveys. Providing a flexible and robust web-based survey platform, datacurious accords to web design standards in survey design, while being responsive to the needs of the academic research community.

ERRATUM

In the article entitled "Neurologic History and Examination Results and Their Relationship to Human Immunodeficiency Virus Type 1 Serostatus in Hemophilic Subjects: Results from the Hemophilia Growth and Development Study" by James F. Bale, Jr, MD et al that appeared in the April 1993 issue of Pediatrics (1993;91:736-741) an error was made in the entry of the baseline data. This data entry error relates to the number of HIV-1 positive subjects who had non-hemophilia-related decreases in muscle bulk. This change and its effect on the statistical analysis are summarized below: See Table in the PDF File