Recruitment in healthcare, with a human touch
Some of the issues encountered while concepting and designing the first marketplace for healthcare recruitment in Ro
How we started
When we first sketched the MEDIjobs architecture, we started from the main problems faced by the recruitment market in the medical field (medical specialists as candidates, on the one hand, and the clinics looking for staff, on the other) and we tried to understand why the current solutions were not effective.
Starting June 2016, we reiterated the business model, while constantly staying in touch with users, listening to their opinions and trying to relate to their problems.
What did we find out? What were the problems of the HR industry and of the medical recruitment industry in particular, and how did we respond to them?
What we found out
Recruitment in healthcare is not a very enjoyable experience, neither for candidates, nor for companies, but rather an outdated, time consuming and unfriendly process.
For candidates, what should be a journey full of discoveries about them and the world they’ll be entering as professionals, is often translated into a long and tedious journey.
People don’t want to send resumes and letters of intent, they long to be understood. And companies want to hire a person who resonates with their values and culture.
But now more than ever, the balance of power is tilted towards the candidates. In the medical field, where good doctors are highly sought after and highly rated, this is all the more visible.
If they want to stay relevant, companies should understand that the future of recruitment is digital (even for harder “portable” industries such as healthcare) and in personalised services.
Our solution
At MEDIJobs we turned the process of looking for a job or a candidate in a simple, efficient and friendly one.

How?
By transferring it almost entirely online (which translates into accessibility time and resource savings), and by personalising and humanising this digital process.
In august 2016 we launched MEDIRecruit, the most advanced recruitment solution in the medical field up until that moment, the only product that accelerates engagement and provides clinics with relevant candidates.
Through MEDIrecruit, almost the entire process is done online: the clinic receives directly into its account a shortlist of candidates that meets its unique requirements, consisting of 3 to 5 applicants selected by an algorithm from a special database of over 10,000 medical specialists.
For the next step, candidates and employers are allowed to set up their own interviews, using a digital calendar available on the platform.
Bias in HR and how to overcome it
From large corporations like Deloitte, to startups such as GapJumpers, companies have realised that when working with people and their careers, you have walk blindfolded.
So they began to remove from CVs data such as age, background, and socio-economic background to focus only on the talent and skills of the applicant.
Why this change?
We, humans, are naturally prone to preconceptions, and this damages our ability to keep ourselves impartial in critical situations.
To navigate into everyday life with ease, we learned to recognise certain patterns and apply them automatically to situations we believe that are similar. Although this method helps us make quicker decisions, it can also make us apply labels without thinking too much.
At MEDIjobs we tried to translate the aspect of diversity directly into the final product.
Thus, companies are not shown details that could help evaluate the candidates in a biased way (such as age or even picture), leaving the experience to speak for itself.
A lot of studies show that we are inclined to catalog a man with a good physical appearance as being better or more competent from a professional point of view, and ideally we should eliminate any preconceptions in the pre-screening stage, so showing the candidate’s picture in the first step was not an option.

Auction based medical recruiting
In April 2017 we launched to test a new product: MEDIjobs All Stars, a service that connects the most experienced medical professionals with companies that want to increase their team’s performance, through an auction-based system, where each week, companies can make salary offers to these specialists.
In time, the solution aims to gather enough information in order to build a machine learning algorithm that automates all the interactions created within the platform.
