Improving Data Integrity in Public Health: A Case Study of an Outbreak Management System in Nigeria.

The completeness and accuracy of data in the Nigerian health care system is a challenge. Studies have shown that the data quality, and by extension data integrity, has been suboptimal and thus poses a barrier to strengthening service delivery. This article showcases how the design process sparked the concept for an intervention to improve the integrity of public health data being collected in Nigeria.In collaboration with the Nigerian Institute of Medical Research (NIMR) and Lifebank, the Co-creation Hub team conducted formative research with the coronavirus disease (COVID-19) test center managers at NIMR. The insights informed the development of the features for an outbreak management system. These features were refined through an iterative process of development and continuous feedback from the end users.NIMR reported an improvement in its data collection process and data integrity. They reported that (1) almost all data collection by the test center was now automated, thereby minimizing the proportion of inaccurate and repeat entry in comparison to data collected in other parts of the same center; (2) the auto-validation feature of the system ensured that all required fields of a patient's information were completed and verified, thereby ensuring 100% data completeness; and (3) the validation and verification feature ensured that patients' contact information was validated.The integration of this intervention into the current health information system ensures an improvement in the accuracy and validity of health care data being collected and stored.

Is Remote Learning as Effective as In-Person Learning for Contouring Education? A Prospective Comparison of Face-to-Face versus Online Delivery of the Anatomy and Radiology Contouring Bootcamp.

PURPOSE: The Anatomy and Radiology Contouring (ARC) Bootcamp was a face-to-face (F2F) intervention providing integrated education for radiation oncology (RO) residents and medical physicists. To increase access, we launched an online offering in 2019. We evaluated the effect of the online course on participants' knowledge acquisition, contouring skills, and self-confidence by comparing it with the F2F course. METHODS AND MATERIALS: Using modules, the online course offers content similar to that of the F2F comparator. Participants from the 2019 F2F and the 2019-2020 online course completed pre- and postevaluations assessing anatomy and radiology knowledge, contouring skills, self-confidence, and course satisfaction. RESULTS: There were 180 individuals enrolled (F2F: n = 40; online: n = 140); 57 participants (F2F: n = 30; online: n = 27) completed both evaluations. The online course had a wider geographic participation (19 countries) than F2F (4 countries). F2F had primarily RO resident participation (80%), compared with online (41%). Both cohorts demonstrated similar improvements in self-confidence pertaining to anatomy and radiology knowledge, contouring skills, and interpreting radiology images (all P < .001). Both the online (mean ± SD improvement: 6.6 ± 6.7 on a 40-point scale; P < .001) and F2F (3.7 ± 5.7; P = .002) groups showed anatomy and radiology knowledge improvement. Only the F2F group demonstrated improvement with the contouring assessment (F2F: 0.10 ± 0.17 on a 1-point Dice scale; P = .004; online: 0.07 ± 0.16; P = .076). Both cohorts perceived the course as a positive experience (F2F: 4.8 ± 0.4 on a 5-point scale; online: 4.5 ± 0.6), stated it would improve their professional practice (F2F: 4.6 ± 0.5; online: 4.2 ± 0.8), and said they would recommend it to others (F2F: 4.8 ± 0.4; online: 4.4 ± 0.6). CONCLUSIONS: The online ARC Bootcamp demonstrated improved self-confidence, knowledge scores, and high satisfaction levels among participants. The offering had lower completion rates but was more accessible to geographic regions, provided a flexible learning experience, and allowed for ongoing education during the COVID-19 pandemic.