Data Entry

According to Jennings and Staggers (12), "fundamental to successful performance measurement and other data-driven initiatives is information system support" (p. 25). While the healthcare industry is behind others in information system support, the availability of such systems is changing. Many organizations are integrating clinical databases and designing electronic patient records. Healthcare continues to lag behind, however, which places a strain on the system when trying to measure outcomes. Healthcare professionals often resort to manual data collection and then request non clinical personnel to enter the values. While this approach is efficient, it is danger-prone in terms of data integrity. It also eliminates the need for clinicians to learn more about information systems. As a consequence, many healthcare professionals are not up to date with basic computer applications. Continuing education and systems designed for direct data entry will help alleviate this frustration.

Data Analysis

The approach to data analysis should be determined prior to data collection and includes consideration of the specific questions being answered as well as the levels of measurement used in the data collection process. Statistical consultation is necessary to accurately perform the analysis and interpret the results. Typically, the sample characteristics are analyzed using descriptive statistics including frequency distributions, means, and standard deviations. Analyzing demographic variables, such as age, gender, and educational level descriptively provides valuable insights into the sample's attributes. Further descriptive statistics are used to analyze the specific study variables. Finally, inferential statistics are employed to investigate for relationships or comparisons. Statistical procedures such analysis of variance and regression analysis allow researchers to test hypotheses. Findings from the data analysis should be interpreted in light of current clinical practice and prior research.

Data Reporting