Supplementary File – Unmet Clinical Needs
Appendix: Modifications made to the process and their respective rationale
Category
AIM Modification
Rationale
Mindset
To train a multidisciplinary team of
engineers, designers, business graduates and
clinicians with an intention to form start-up
companies that solve a clinically validated
need with a solution that fits the Indian
healthcare system.
Innovative solutions for unmet needs require to reach the patient in
order to reduce the burden of the problem and by developing the
solution through a start-up company increases the chances for
commercialization of the product to bring it into the market.
Team
Structure
Clinical fellows are internal to the hospital
facilitating the clinical immersion.
In India, the ecosystem for MedTech innovation is still in its infancy
and most clinicians do not recognize this space to be a sustainable
career options. Many clinicians do not wish to take the risk of
jeopardizing their clinical careers while exploring medical device
development through a fellowship program. But, these clinicians are
invaluable as they can provide integrated observations that cannot be
obtained by shadowing.
Pre Immersion
Three week classroom training before
immersion that includes in-depth
understanding of the process from selecting a
focus area to commercialization of a product.
Additionally, it includes basic clinical
background in the focus area and ethics.
It is critical that the observations are performed while keeping in
mind the information that will be required in different stages of the
process. This instruction is important as it helps avoid future
situations in which the team must backtrack due to lack of
information.
Clinical
Observation
The team records negative outcomes only
and documents the information collected into
a 15 parameter observation docket: date/time
venue, a detailed account of the observation (
100-150 words), the negative outcome, the
problem statement, the need statement,
criticality of the need as felt by the clinician,
frequency of the negative outcome as seen by
clinician, criticality of the need as felt by the
observer, frequency of the negative outcome
as seen by the observer, the best available
solution, cost of the existing solution,
incidence/prevalence data, patient pathway,
and any relevant insights.
Observers often record observations in which they see a potential for
something to go wrong but nothing actually goes wrong. These
observers jump straight to potential solutions without fully
considering the pre-existing landscape. To avoid this, we train the
team to record observations where there was a negative outcome seen
so that a solution is created for a problem that actually exists. In
addition, there is a huge shortage of epidemiological, cost, and
demographical data that is accurate and reliable. Such data is needed
for the filtering process. For most needs such information is not easily
available and this affects the filtering process. To tackle this issue we
train the team to collect information from clinicians as the
observation takes place and carry out voice of customer studies to get
some data that can be used later to make calculated extrapolations or
check the reliability of available data.
Needs
Filtering
A set of filtering parameters designed to
identify unmet needs that have high
criticality and frequency. These needs must
also have a high market impact if addressed,
moderate predicate competition, moderate
technical complexity, low regulatory hurdles
and a good buyer environment.
We designed 4 sets of filtering levels that evaluate needs using a prestructured scoring system and a standard weighting formula. This
filtering system takes into account all the parameters that need to be
favorable for the solution to increase the chance of its development
and implementation into our healthcare system. On arriving at the top
10 needs, the teams are trained to select their top 2-3 needs based on
an in-depth stakeholder and business model understanding.