Data collection and analysis methods generate the evaluation outcome and recommendations from the full range of personnel:

Information system management and technical staff,
Users working in a finance and operations capacity,
Users working in a medical, clinical and nursing capacity, and
Users working in a research capacity.

Data Collection

Data Collection

Quantitative Method

Built-in questionnaires pose predefined questions that provide detailed data on the system's characteristics, use, and impact, with:

  • Likert scales,
  • Two-item scale,
  • Open-ended questions, and
  • Data entry of quantitative measures.
Qualitative Methods

Some factors must be assessed using qualitative methods:

  • Document review: technical, financial and administrative documents, system and training documentation,
  • System review: system testing, performance and usage monitoring, helpdesk logs, and
  • Focus groups and interviews: built-in interview guides.

Data Analysis

Data Analysis

Quantitative Data Analysis

The toolset safeguards and stores all content from the completed surveys. Statistical measures are produced incorporating the specific variables:

  • Nominal variables: number and percentage of personnel per category, mean, mode; and
  • Ordinal variables: minimum, maximum, range, median and quartiles.

Multiple answers and filtered questions are handled.

Weighing mechanisms are applied to compensate for over- and under-representation.

Statistical tests and procedures are performed on individual and groups of variables.

Graphical outputs are produced.

Qualitative Data Analysis

Interviews and focus groups are transcribed and analyzed by:

  • Building matrices with categorized data;
  • Producing displays such as flowcharts and graphs;
  • Tabulating frequencies and exploring relationships;
  • Situating information within a historical perspective.

The data from both documentation and system reviews is merged and the overall analysis explains the system’s use and impact.