Instrumentation & Measurement Magazine 24-6 - 91

Fig. 2. DTC diagnostic apps-application fields taxonomy.
Concerning DTC diagnostic
apps, most papers
in the literature deal with
the evaluation of multiple
apps, sometimes according
to arbitrary selection criteria.
The cost of these apps is
rarely reported (and is very
variable, generally ranging
from $1 to $200), and almost
nobody highlights the risk
that free apps may sell users'
data. In fact, diagnostic
apps collect great amounts
of personal data, including
parameters of clinical interest,
and this information
could be used by third parties
if access were somehow
allowed. Therefore, privacy
and data protection issues
should be properly taken
into consideration when
waived from FDA approval (as well as the majority of wearable
devices). It is true that regulations should not hinder the
technological development (with a consequent deceleration
of digital health adoption), even more if it has the potential to
support the healthcare system, but there is an undeniable necessity
to regulate all these new devices with the purpose to
homogenize their performance evaluation and to provide customers
with safe, complete, and comparable information.
Assessment of New Health-related
Devices Performance: What Kind of
Methodology?
The literature clearly evidences the lack of a commonly
accepted protocol for testing wearable devices, and each researcher
prefers to develop her/his own methodology and
dataset to prove a certain hypothesis. Consequently, there
is a huge variety of very specific testing protocols, providing
uneven and barely comparable data [7]. Both free-living
conditions and the performing of different activities (e.g.,
running, cycling, jogging, and weightlifting) are considered.
Even the choice of the reference apparatus is not uniform,
since some consider a gold standard instrument (e.g., electrocardiograph
for HR), while others compare the results with
another wearable device considered more accurate (e.g., a
chest-strap device to validate a wrist-worn one). Also, the
sample size of the tested population affects the results, but
this is rarely taken into account; the dimension of the statistical
sample varies in a range of 1-120 units, with different
significance, considering subjects with different characteristics
(young or adult, but also older people and even children,
healthy, sick or hospitalised patients), resulting in highly inhomogeneous
data that is irregular from a statistical point
of view.
September 2021
addressing these apps in the literature. Sometimes the performance
is evaluated by multiple experts, while other times the
app result is compared with a reference diagnosis procedure.
The performance is usually expressed in terms of a percentage
of true positives (meaning correct diagnosis), sensitivity
(the ratio between true positives and the total number of positives),
and/or specificity (the ratio between true negatives and
the total number of negatives). The accuracy rates vary a lot: up
to 80% for appropriate triage advice and 33% for self-care suggestions
in symptom checkers, and also, " frequently inaccurate
advice " are qualitatively reported [1].
Sometimes the users' opinions on the app are reported, but
there are no studies that consider the actual users' outcomes;
occasionally, it is said that younger aged users and those with
greater familiarity with the Internet can help in handling the
apps and interpreting their results. Moreover, the researchers
often did not identify the considered apps by name, thus impeding
the public to obtain useful information in the selection
of which app to adopt. Several studies underline privacyand
security- related issues, since some apps do not properly
consider informed consent, privacy and confidentiality policies,
and possible conflicts of interest; the safety of data and
the confidentiality of medical information should be always
ensured, also with encryption techniques and suitable information
technology (IT) infrastructures [15]. An overview of
the methodology aspects considered for wearable devices and
diagnostic apps characterization is reported in Table 1.
Uneven Data and Lack of Metrological
Parameters
Since the performance assessment is carried out without a
common standard, using considerably varying methodologies,
sparse results are obtained. Different researchers consider
IEEE Instrumentation & Measurement Magazine
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