Raspberry Pi-Based Data Archival System for Electroencephalogram Signals From the SedLine Root Device.

BACKGROUND: The retrospective analysis of electroencephalogram (EEG) signals acquired from patients under general anesthesia is crucial in understanding the patient's unconscious brain's state. However, the creation of such database is often tedious and cumbersome and involves human labor. Hence, we developed a Raspberry Pi-based system for archiving EEG signals recorded from patients under anesthesia in operating rooms (ORs) with minimal human involvement. METHODS: Using this system, we archived patient EEG signals from over 500 unique surgeries at the Emory University Orthopaedics and Spine Hospital, Atlanta, for about 18 months. For this, we developed a software package that runs on a Raspberry Pi and archives patient EEG signals from a SedLine Root EEG Monitor (Masimo) to a secure Health Insurance Portability and Accountability Act (HIPAA) compliant cloud storage. The OR number corresponding to each surgery was archived along with the EEG signal to facilitate retrospective EEG analysis. We retrospectively processed the archived EEG signals and performed signal quality checks. We also proposed a formula to compute the proportion of true EEG signal and calculated the corresponding statistics. Further, we curated and interleaved patient medical record information with the corresponding EEG signals. RESULTS: We retrospectively processed the EEG signals to demonstrate a statistically significant negative correlation between the relative alpha power (8-12 Hz) of the EEG signal captured under anesthesia and the patient's age. CONCLUSIONS: Our system is a standalone EEG archiver developed using low cost and readily available hardware. We demonstrated that one could create a large-scale EEG database with minimal human involvement. Moreover, we showed that the captured EEG signal is of good quality for retrospective analysis and combined the EEG signal with the patient medical records. This project's software has been released under an open-source license to enable others to use and contribute.

Use of webQDA software on qualitative nursing research: an experience report.

OBJECTIVES: to report the user experience of the webQDA software in the support of qualitative data analysis about health literacy of older adults. METHODS: quasi-experimental research developed from January 2014 to January 2015, with 118 older adults, all of whom were interviewed to assess the level of health literacy. Interviews were carried out before and after four educational interventions, according to Freire's method named Culture Circle. The interviews were transcribed and entered in the software, which highlighted the analytical categories. RESULTS: the systems of sources, interpretative encoding and questioning of the data available in the software allowed the construction of three categories for the literacy levels and four categories for their dimensions. FINAL CONSIDERATIONS: We concluded that the webQDA software enables the structured encoding of qualitative materials, ensuring faster and effective management of data with systematization and analytical transparency.

Qualitative Data Management and Analysis within a Data Repository.

Data repositories can support secure data management for multi-institutional and geographically dispersed research teams. Primarily designed to provide secure access, storage, and sharing of quantitative data, limited focus has been given to the unique considerations of data repositories for qualitative research. We share our experiences of using a data repository in a large qualitative nursing research study. Over a 27-month period, data collected by this 15-member team from 83 participants included photos, audio recordings and transcripts of interviews, and field notes. The data repository supported the secure collection, storage, and management of over 1,800 files with data. However, challenges were introduced during analysis that required negotiations about the structure and processes of the data repository. We discuss strengths and limitations of data repositories, and introduce practical strategies for developing a data management plan for qualitative research, which is supported through a data repository.

Use of webQDA software on qualitative nursing research: an experience report / Uso del software webQDA en investigación cualitativa en enfermería: reporte de experiencia / Uso do software webQDA na pesquisa qualitativa em enfermagem: relato de experiência

ABSTRACT Objectives: to report the user experience of the webQDA software in the support of qualitative data analysis about health literacy of older adults. Methods: quasi-experimental research developed from January 2014 to January 2015, with 118 older adults, all of whom were interviewed to assess the level of health literacy. Interviews were carried out before and after four educational interventions, according to Freire's method named Culture Circle. The interviews were transcribed and entered in the software, which highlighted the analytical categories. Results: the systems of sources, interpretative encoding and questioning of the data available in the software allowed the construction of three categories for the literacy levels and four categories for their dimensions. Final considerations: We concluded that the webQDA software enables the structured encoding of qualitative materials, ensuring faster and effective management of data with systematization and analytical transparency.

RESUMEN Objetivos: relatar la experiencia con la utilización del software webQDA como base al análisis de los datos cualitativos sobre literacidad en salud de ancianos. Métodos: investigación cuasiexperimental realizada en el período de enero de 2014 a enero de 2015, en la cual participaron 118 ancianos mediante entrevistas para evaluar el nivel de literacidad en salud. Se realizaron entrevistas antes y después de cuatro intervenciones educativas, de acuerdo con el método problematizador freireano titulado Círculo de Cultura. Se transcribieron las entrevistas y las insertaron en el software, lo que permitió obtener las categorías analíticas. Resultados: los sistemas de fuentes, de codificación interpretativa y de cuestionamiento de los datos disponibles en el software permitieron elaborar tres categorías sobre los niveles de literacidad y cuatro categorías sobre sus dimensiones. Consideraciones finales: Se concluyó que el software webQDA permite la codificación estructurada de los materiales cualitativos, lo que promueve una gestión más rápida y eficaz de los datos a partir de la sistematización y transparencia analítica.

RESUMO Objetivos: relatar a experiência de uso do software webQDA no apoio à análise dos dados qualitativos acerca do letramento em saúde de idosos. Métodos: pesquisa quase experimental desenvolvida no período de janeiro de 2014 a janeiro de 2015, com 118 idosos, os quais foram entrevistados para avaliar o nível de letramento em saúde. Foram realizadas entrevistas antes e após quatro intervenções educativas, segundo o método problematizador freireano denominado Círculo de Cultura. As entrevistas foram transcritas e inseridas no software, o que permitiu evidenciar as categorias analíticas. Resultados: os sistemas de fontes, codificação interpretativa e questionamento dos dados disponíveis no software permitiram a construção de três categorias para os níveis do letramento e de quatro categorias para as suas dimensões. Considerações finais: Conclui-se que o software webQDA permite a codificação estruturada dos materiais qualitativos, assegurando gestão mais rápida e eficaz dos dados a partir da sistematização e transparência analítica.

The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database.

There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models.

Improving Childhood Lead Poisoning Surveillance and Data Management in Arizona Through an Evaluation of the Transition to a New Surveillance System.

The Arizona Childhood Lead Poisoning Prevention Program (CLPPP) worked with internal teams to identify opportunities for improvement in data quality and data management processes during the transition of lead poisoning surveillance into Arizona's communicable disease surveillance system. A pretransition review led to the determination of key strategies based on feasibility to implement and potential for impact on program operations. The strategies included standardizing reporting methods, automating data processing, and centralizing data management. The Childhood Lead Poisoning Prevention Program evaluated pre- and posttransition data management processes to determine whether improved efficiency was achieved. To evaluate the key strategies, indicators regarding data flow, data capture, and surveillance capacity were used. The key strategies were successful in improving data quality and efficiency. In addition, the implementation of these strategies has increased engagement among reporters, expanded surveillance capacity, and established a foundation to better understand lead poisoning challenges affecting Arizonan children.