PeerJ (Nov 2024)

Developing a quality indicator system for evaluating internet plus home care nursing services based on the SERVQUAL model: a Delphi-analytic hierarchy process study

  • Lei Ye,
  • Shulan Yang,
  • Biyan Jiang,
  • Caixia Liu,
  • Xiaoqing Jin,
  • Polun Chang

DOI
https://doi.org/10.7717/peerj.18281
Journal volume & issue
Vol. 12
p. e18281

Abstract

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Background In the context of global population aging and the rapid development of information technology, the demand for Internet Plus Home Care Nursing (Internet+ HCN) services have been on the rise, especially in China. Internet+ HCN services have the potential to maximize existing human resources to counter the shortage of medical healthcare services. However, at present, Internet+ HCN services are difficult to scale due to the lack of standardized service quality governance. Quality indicators for service evaluation of Internet+ HCN services are under-defined. Objective To develop a quality indicator system for evaluating Internet+ HCN services, and to shed theoretical light on assessing mHealth service quality from a user experience perspective. Methods An initial quality indicator system was established based on scenarios related to Internet+ HCN services. The Delphi Method was applied to modify the indicators according to experts’ opinions, and the analytic hierarchy process (AHP) was applied to calculate the indicator weight. Finally, a quality indicator system for evaluating Internet+ HCN services was developed based on the SERVQUAL model. Results Altogether, 17 experts from relevant fields such as nursing education, clinical nursing, health management, and health informatics were consulted through email surveys. The response rates in both rounds of Delphi and the AHP were 100%. The average expert authority coefficients were 0.912 and 0.925 respectively in the two rounds of Delphi. Kendall’s W, indicating variation coefficients, ranged from 0.262 to 0.265. Finally, a quality indicator system for evaluating Internet+ HCN services, comprising five primary indicators and 15 secondary indicators, was developed. Primary indicators and their AHP generated the following weights: assurance (0.245), reliability (0.240), tangibles (0.192), responsiveness (0.190), and empathy (0.132). Conclusions By measuring the services quality gap between user expectations and perceptions, the proposed SERVQUAL model-based quality indicator system shows potential in improving the quality of Internet+ HCN services through the perspective of user experiences.

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