4.2 Underpinning theory
Several theories and models have been used to inform this chapter that are essential foundations for successful digital health implementation. The underpinning theories can be applied to lead successful digital health initiatives to gain the value and benefits anticipated. Table 4.1 shows some of the key theories relevant to this chapter.
Table 4.1: Key theories
| Domain | Theory or framework | Description |
|---|---|---|
| Evaluation of healthcare information systems | Technology, People, Organisations and Macroenvironmental factors (TPOM) Evaluation Framework
(Cresswell et al., 2020) |
The TPOM framework (Cresswell et al., 2020) is a robust analytical model for evaluating healthcare information systems. Its strength lies in its comprehensive approach, encapsulating dimensions described in previous models and necessary to understand the complexities of technology adoption and implementation in healthcare settings. By considering technology, people, organisations and macroenvironmental factors, the framework offers a holistic view that enables practitioners to delve into the complex dynamics at play within healthcare IT initiatives (Cresswell et al., 2020). |
| Innovation diffusion and complexity | Non-adoption, Abandonment and Challenges to the Scale-Up, Spread and Sustainability (NASSS) Framework
(Greenhalgh & Abimbola, 2019) |
The NASSS framework, developed by Greenhalgh and Abimbola (2019), is a model designed to analyse the complexity of technological innovations within healthcare settings. It consists of seven domains: the illness context, the technology, the organisation, the adopter system, the embedding and adaptation process, the interactional workability and the wider context. By examining these domains, the NASSS framework helps researchers and practitioners understand why some healthcare technologies succeed while others fail, considering the intricate interplay of social, technical and organisational factors.
The NASSS framework supports those working in digital information technology to predict and evaluate technologies in health and social care settings. When applied, the framework adds to the value proposition through improved system design and identifies technologies that may have limited scope for success and widespread adoption and, importantly, how we can learn from program failures. |
| Evaluation of health information systems and technology | Human, organisation and technology fit (HOT-fit) model
(Yusof et al., 2008) |
The HOT-fit model proposed by Yusof et al. (2008) is a conceptual framework used to evaluate the alignment or fit between humans, organisations and technology within an information system context. The model emphasises the importance of ensuring compatibility between these three elements to achieve successful information system implementation and outcomes.
Applying this model improves how health and information technologies align to the organisation, the people and the context, ensuring a ‘fit’ that aligns with the organisation’s work, purpose and function. |
| User acceptance, adoption, and usability | Technology acceptance model (TAM) (Davis, 1989) | TAM has been widely used in research and practice to evaluate and predict users’ acceptance and usage of various technologies, including software applications, websites and online platforms, mobile apps and information systems within organisations.
Since Davis (1989) first described TAM, it has been extended and adapted to various contexts and technologies. Applying this model allows us to quantify how well the technology supports and meets the requirements of users through measurement of perceived ease of use and perceived usefulness. While there are some criticisms of the framework, it remains well regarded, as it provides a useful and informative tool to establish acceptance and usefulness in health and social care settings. |
