Speech and Language Explanatory Case Study

Speech and Language Explanatory Case Study

Introduction

Broad Intent of Research
An analyzation of Electronic Health Reporting (EHR) interface design for Speech and Language Pathologists (SLP) by comparing two interface platforms, Therapy Corner and TheraSpeech.

Study Analyzation
How cognitive system engineering and usability methods can be used to construct EHR interface designs to minimize cognitive task load inhibitors.

Methodology

Three Stages of Research Approach

Qualitative Measurement

Implement analysis and measurement.

Interface Construction

Interface construction and usability methods to convert HTA functions into an interface design.

Functionality Assessment

Research into functions, tasks, and goals of SLPs.

Design and Procedures

Functionality Questionnaire Functional and task-related analysis consisted of a functionality questionnaire and secondary domain-specific empirical research. The questionnaire consisted of questions related to demographic, functional, and technical interaction. Secondary Empirical Sources A significant source of information comes from the American Speech-Language-Hearing Association (ASHA). Other sources of research stem from peer-reviewed scientific journals dealing with SLP perspectives on processes and procedures. Qualitative Questionnaire The System Usability Scale (SUS) questionnaire measures computer systems usability and ease-of-use, becoming a reliable tool for usability evaluations.
  • Made up of ten questions that alter between positive and negative tones, tonal switching prevents users from scoring in a biased manner and compels them to think about what the question is asking.
  • Answers are in the form of a 5-point Likert Scale (1=highly do not agree, 5=highly agree). 
  • Provides sample scores for statistical measurement, in this case study a within-in subject paired t-test method is used. 

Treatment of Data

Hierarchical Analysis Feedback from the functionality questionnaire and empirical research provided support to implement a Hierarchical Task Analysis (HTA), and helped form a better understanding of SLP functions by:
  • Decomposing tasks and goals result into HTA plans which are used towards hierarchically and procedurally presenting information.
  • Allowing procedural knowledge to be captured using systems engineering methods in both tabular and hierarchical formats.
Hierarchical Task Analysis results are converted into user flow charts depicting user engagement process according to research findings.

HTA Plans
Tabular and hierarchical visual formats display traceable task completion engagement. All tasks were recorded using VitTech’s CORE Software System.

Results

A statistical measurement of SUS scores using a paired t-test answered the research question resulting in significant findings. 
  • Level of confidence was 95%, or a significance level of .05 (α=.05).The
  • The t-distribution graph region of acceptance is  [-2.3646:2.3646] and the t-value equated to -3.67, which falls outside of the distribution region.
  • The p-value equated to 0.007964, which is smaller than .05, therefore the null hypothesis is rejected.
Participant Information A participation request was sent to a group of SLPs that resulted in 8 participants with varying degrees of education and work backgrounds.  All participants met the following prerequisites:
  • Higher Education Degree
  • SLP Work Experience
  • Experience with EHR Systems

Interface visual comparison

The displays show the differences between interface designs. Theraspeech’s design is not a full representation due to the amount of work involved in a complete website overhaul would require a significant amount of time and further analysis. The functions are set to allow a user to execute a set number of objectives in a controlled space. 

Discussion

This explanatory case study looked at the effects of applying HTA to EHR interface design to decrease task loads on SLPs carrying out reporting responsibilities by utilizing Human Factors Integration (HFI).
  • Beginning with an understanding of the process and people 
  • Then the development of an interface model
  • Finally assessing domain expert engagement
Determined that the application of HTA within the design process of TheraSpeech’s interface significantly improved SLPs engagement over Therapy Corner’s interface engagement.

Recommendations

Further analysis into cognitive functions, human error, and further interface testing would be beneficial by conducting the following:
  • Cognitive Work Analysis (CWA)
    • work domain analysis 
    • control task analysis
    • strategies analysis 
    • social organization 
    • cooperation analysis
    • worker competencies analysis
  • Systematic Human Error Reduction and Prediction Approach (SHERPA)
  • Nielson’s 10 Heuristics analysis
  • Link analysis
Comprehensive testing techniques and software provides feedback on how well the interface performs. Techniques such as user trials, walkthrough analysis, and questionnaires allow qualitative participant feedback Software testing such as eye-gazing, time trials, performance loading, and integration testing can provide quantitative feedback on interface engagement

Conclusion

This explanatory case study analyzed two interfaces to measure the significance of applying HFI into SLP interface design with the ultimate goal of reducing task loads and decreasing errors. The application of cognitive system engineering to interface design can significantly improve SLPs’ EHR functions and be part of a larger HFI endeavor.  As described by Bentley et al. (2021), Human Factors is a design discipline concerned with human work that involves systems, people, and machines to improve human performance and well-being. This research accomplishes these goals by providing an improved manner of designing human-machine interface EHR systems and improve the lives of SLPs and their patients.

Contact

Explanatory studies like this one can contribute to the improvement of engagement with clients and stakeholders. Lets connect on how I can help accomplish that.