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.

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