The formation of patient trust and its transference to online health services: the case of a Dutch online patient portal for rehabilitation care.

BACKGROUND: Trust is widely recognized as a crucial factor in successful physician-patient communication and patient engagement in treatment. However, with the rise of eHealth technologies, such as online patient portals, the role of trust and the factors that influence it need to be reconsidered. In this study, we aim to identify the factors that contribute to trust in an eHealth service and we aim to identify the consequences of trust in an eHealth service in terms of use. METHODS: The Patient Trust Assessment Tool was provided to new outpatients of a rehabilitation center in the Netherlands, that were expected to use the center's online patient portal. Via this tool, we assessed five trust-related factors. This data was supplemented by questions about demographics (age, gender, rehabilitation treatment) and data about use (number of sessions, total time spent in sessions), derived from data logs. Data was analyzed via Partial Least Squares Structural Equation Modelling. RESULTS: In total, 93 patients participated in the study. Out of these participants, 61 used the portal at least once. The measurement model was considered good. Trust in the organization was found to affect trust in the care team (ß = .63), trust in the care team affected trust in the treatment (ß = .60). Both, trust in the care team and trust in the treatment influenced trust in the technology (ß = .42 and .30, respectively). Trust in the technology affected the holistic concept trust in the service (ß = .78). This holistic trust in the service finally, did not affect use. CONCLUSIONS: This study shows that the formation of this trust is not unidimensional, but consists of different, separate factors (trust in the care organization, trust in the care team and trust in the treatment). Trust transfer does take place from offline to online health services. However, trust in the service does not directly affect the use of the eHealth technology.

Identifying the Value of an eHealth Intervention Aimed at Cognitive Impairments: Observational Study in Different Contexts and Service Models.

BACKGROUND: Value is one of the central concepts in health care, but it is vague within the field of summative eHealth evaluations. Moreover, the role of context in explaining the value is underexplored, and there is no explicit framework guiding the evaluation of the value of eHealth interventions. Hence, different studies conceptualize and operationalize value in different ways, ranging from measuring outcomes such as clinical efficacy or behavior change of patients or professionals to measuring the perceptions of various stakeholders or in economic terms. OBJECTIVE: The objective of our study is to identify contextual factors that determine similarities and differences in the value of an eHealth intervention between two contexts. We also aim to reflect on and contribute to the discussion about the specification, assessment, and relativity of the "value" concept in the evaluation of eHealth interventions. METHODS: The study concerned a 6-month eHealth intervention targeted at elderly patients (n=107) diagnosed with cognitive impairment in Italy and Sweden. The intervention introduced a case manager role and an eHealth platform to provide remote monitoring and coaching services to the patients. A model for evaluating the value of eHealth interventions was designed as monetary and nonmonetary benefits and sacrifices, based on the value conceptualizations in eHealth and marketing literature. The data was collected using the Mini-Mental State Examination (MMSE), the clock drawing test, and the 5-level EQ-5D (EQ-5D-5L). Semistructured interviews were conducted with patients and health care professionals. Monetary data was collected from the health care and technology providers. RESULTS: The value of an eHealth intervention applied to similar types of populations but differed in different contexts. In Sweden, patients improved cognitive performance (MMSE mean 0.85, SD 1.62, P<.001), reduced anxiety (EQ-5D-5L mean 0.16, SD 0.54, P=.046), perceived their health better (EQ-5D-5L VAS scale mean 2.6, SD 9.7, P=.035), and both patients and health care professionals were satisfied with the care. However, the Swedish service model demonstrated an increased cost, higher workload for health care professionals, and the intervention was not cost-efficient. In Italy, the patients were satisfied with the care received, and the health care professionals felt empowered and had an acceptable workload. Moreover, the intervention was cost-effective. However, clinical efficacy and quality of life improvements have not been observed. We identified 6 factors that influence the value of eHealth intervention in a particular context: (1) service delivery design of the intervention (process of delivery), (2) organizational setup of the intervention (ie, organizational structure and professionals involved), (3) cost of different treatments, (4) hourly rates of staff for delivering the intervention, (5) lifestyle habits of the population (eg, how physically active they were in their daily life and if they were living alone or with family), and (6) local preferences on the quality of patient care. CONCLUSIONS: Value in the assessments of eHealth interventions need to be considered beyond economic terms, perceptions, or behavior changes. To obtain a holistic view of the value created, it needs to be operationalized into monetary and nonmonetary outcomes, categorizing these into benefits and sacrifices.

Designing eHealth that Matters via a Multidisciplinary Requirements Development Approach.

BACKGROUND: Requirements development is a crucial part of eHealth design. It entails all the activities devoted to requirements identification, the communication of requirements to other developers, and their evaluation. Currently, a requirements development approach geared towards the specifics of the eHealth domain is lacking. This is likely to result in a mismatch between the developed technology and end user characteristics, physical surroundings, and the organizational context of use. It also makes it hard to judge the quality of eHealth design, since it makes it difficult to gear evaluations of eHealth to the main goals it is supposed to serve. OBJECTIVE: In order to facilitate the creation of eHealth that matters, we present a practical, multidisciplinary requirements development approach which is embedded in a holistic design approach for eHealth (the Center for eHealth Research roadmap) that incorporates both human-centered design and business modeling. METHODS: Our requirements development approach consists of five phases. In the first, preparatory, phase the project team is composed and the overall goal(s) of the eHealth intervention are decided upon. Second, primary end users and other stakeholders are identified by means of audience segmentation techniques and our stakeholder identification method. Third, the designated context of use is mapped and end users are profiled by means of requirements elicitation methods (eg, interviews, focus groups, or observations). Fourth, stakeholder values and eHealth intervention requirements are distilled from data transcripts, which leads to phase five, in which requirements are communicated to other developers using a requirements notation template we developed specifically for the context of eHealth technologies. RESULTS: The end result of our requirements development approach for eHealth interventions is a design document which includes functional and non-functional requirements, a list of stakeholder values, and end user profiles in the form of personas (fictitious end users, representative of a primary end user group). CONCLUSIONS: The requirements development approach presented in this article enables eHealth developers to apply a systematic and multi-disciplinary approach towards the creation of requirements. The cooperation between health, engineering, and social sciences creates a situation in which a mismatch between design, end users, and the organizational context can be avoided. Furthermore, we suggest to evaluate eHealth on a feature-specific level in order to learn exactly why such a technology does or does not live up to its expectations.