
Effective requirements elicitation and validation are crucial for developing healthcare applications that genuinely meet the needs of end users. This study investigates the role of healthcare professionals in these processes and explores the application of openEHR archetypes to enhance stakeholder engagement. A comprehensive literature review identified significant gaps in the participation of domain experts throughout the software development lifecycle. A thematic analysis of survey responses from healthcare professionals revealed vital challenges they face with existing software applications. Statistical analyses confirmed the limited involvement of these professionals, while interviews with software engineers provided insights into the practical implications of integrating archetypes into development processes. Based on these findings, a set of good practices is proposed to facilitate effective requirements elicitation and validation through the active involvement of healthcare professionals. Utilizing openEHR archetypes, these practices aim to bridge the gap between technical specifications and clinical needs, ultimately leading to the development of more user-centered healthcare software solutions. This study highlights the importance of fostering collaboration between developers and domain experts to enhance the quality and usability of healthcare applications, paving the way for improved patient outcomes and operational efficiency.
openEHR archetypes, requirements elicitation, Electrical engineering. Electronics. Nuclear engineering, Healthcare software development, software engineering, TK1-9971
openEHR archetypes, requirements elicitation, Electrical engineering. Electronics. Nuclear engineering, Healthcare software development, software engineering, TK1-9971
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
