Alarm Fatigue: Using Alarm Data from a Patient Data Monitoring System on an Intensive Care Unit to Improve the Alarm Management.

Excessive numbers of clinical alarms reduce the awareness of caregivers. Frequent alarms, many of which are non-actionable, can lead to cognitive overload, stress, and desensitization to alarms, called "Alarm Fatigue", which can severely impact patient safety. Due to the multifactorial nature of excessive alarming quantitative data about many facets of alarm generation and management are required in order to tackle the problem efficiently and effectively. Since there is no system available which would provide said data, we set out to develop one in the form of a data warehouse based on a thorough understanding of clinicians' needs. The developed system answers the users' needs in terms of readily providing them information on a daily basis, but also serves as a data source for further research. Further work is needed to include alarm sources from outside the patient monitoring infrastructure.

Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation.

BACKGROUND: Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes. OBJECTIVE: This study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia. METHODS: A randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit-based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles. RESULTS: From the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. CONCLUSIONS: EDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.

An Online Differential Cost Estimator Tool to Support Cost Planning of Demographic and Health Surveys Using Mobile Electronic Device or Paper and Pen Methods: A Function of Sample Size.

The use of mobile devices for a house to house interview-administered survey data collection is becoming a practice along with the paper-based data collection tools. Though the electronic data capture mechanism is supposed to improve the efficiency of the data collection mechanism and the quality of the data, there is limited evidence on the cost-effectiveness of the technologies. This project aims to develop an online pre-implementation survey cost estimator to support the planning and decision of implementing agency. Scalable costs with sample size were estimated using parametric cost estimating technique. In this article, we used Introduction, State of the art, Concept, Implementation, Lessons Learned (ISCIL) format to present the overall development process of this online cost estimator.

Alarm Fatigue: Causes and Effects.

The term "Alarm fatigue" is commonly used to describe the effect which a high number of alarms can have on caregivers: Frequent alarms, many of which are avoidable, can lead to inadequate responses, severely impacting patient safety. In the first step of a long-term effort to address this problem, both the direct and indirect impact of alarms, as well as possible causes of unnecessary alarms were focused. Models of these causes and impacts were developed using a scoping review which included guided interviews with experts from medical informatics, clinicians and medical device manufacturers. These models can provide the methodical grounds for the definition of targeted interventions and the assessment of their effects.