Electronic vs. Paper-Based Data Collection

This week’s content focused on metric tools. Steps for identifying, selecting, and using a metric tool were presented. The terms reliability and validity were also discussed. Phase 2 of the Case Study was also presented. Based on the information you reviewed answer the following discussion prompts. Note: You can use your own experience in searching and identifying tools for your DNP capstone project or MSN Collaborative Project in the first question of the discussion as well. Compare and contrast the different types of metric tools (e.g., surveys, chart review, etc) that can be used to collect information. Include in your discussion the role of technology in metric tool selection and use (e.g., online survey software vs. paper and pencil collection). Briefly describe the importance of reliability and validity in relation to data collection and analysis of outcomes. What is the documented reliability (state the value) of the tool the clinicians selected for the project discussed in the case study? Based on this value what do you conclude about the tool? Describe why it is necessary to code the collected data prior to statistical analysis. Provide an example of coding translation for one of the demographic data points listed in the case study. Note: Please read and follow all directions. Electronic vs. Paper-Based Data Collection

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Part 1. Compare and contrast the different types of metric tools (e.g., surveys, chart review, etc) that can be used to collect information. Include in your discussion the role of technology in metric tool selection and use (e.g., online survey software vs. paper and pencil collection).

There are a range of metric tools available to nurse researchers for collecting information. The first type is retrospective review of records and charts that is effective in estimating the general impact, frequency and nature of an event. However, it is likely to underestimate events and unlikely to provide valid data that can analyze root causes. Secondly, surveys that can evaluate frequency of events to include active errors, and improve understanding of the contributing factors, latent causes, and root causes. Thirdly, direct observation that can similarly evaluate frequency of events to include active errors, and improve understanding of the contributing factors, latent causes, and root causes. Fourthly, incident reports that can only improve understanding of the contributing factors, latent causes, and root causes (Michel, n.d.).

The discussed tools can either be applied through traditional paper-based systems or electronic devises. Although electronic systems are steadily improving and gaining popularity, there are occasions where paper-based systems are preferable. Still, electronic-based systems have the advantage of being easy to use, not requiring printing, easy enumerator training, secure, immediate digitalization, and better quality control. However, paper-based systems also enjoy some advantages that include cheaper to manage, and not requiring technical knowledge (SurveyCTO, 2020).

Part 2. Briefly describe the importance of reliability and validity in relation to data collection and analysis of outcomes.

Reliability and validity are important concepts. Reliability looks at the consistency of measure while validity looks at the accuracy of measure. In fact, reliability looks at the extent to which the results can be reproduced if the study is repeated under similar conditions while validity looks at the extent to which the results measure what they are intended to measure (Mackey & Gass, 2015).

Part 3. What is the documented reliability (state the value) of the tool the clinicians selected for the project discussed in the case study? Based on this value what do you conclude about the tool?

The reliability of a tool can be calculated and reliability coefficients presented with values ranging from 0.00 to 1.00 to indicate the amount of errors. Reliability coefficient values approaching 0.00 indicate much error while values approaching 1.00 indicate no error (Pokorski, 2018). Electronic vs. Paper-Based Data Collection

Part 4. Describe why it is necessary to code the collected data prior to statistical analysis. Provide an example of coding translation for one of the demographic data points listed in the case study.

Coding refers to assigning numerical labels to non-numerical information with the intention of represent important themes in the data. Coding data helps in converting non-numerical information into numerical data so as to facilitate measurement comparisons (Pokorski, 2018).  For instance, when dealing with information on gender, the responses will either be male or female. These responses can be coded as 1 for male and 2 for female.

References

Mackey, A., & Gass, S. M. (2015). Second language research: methodology and design. London: Routledge.

Michel, P. (n.d.). Strengths and weaknesses of available methods for assessing the nature and scale of harm caused by the health system: literature review. Retrieved from https://www.who.int/patientsafety/research/P_Michel_Report_Final_version.pdf

Pokorski, M. (2018). Current concepts in medical research and practice: advances in experimental medicine and biology. Cham: Springer International Publishing AG.

SurveyCTO (2020). Electronic vs. paper-based data collection. Retrieved from https://www.surveycto.com/best-practices/capi-vs-papi/ Electronic vs. Paper-Based Data Collection