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AI in primary care – What are we trying to solve and for whom?

The healthcare industry is continuously called to face an increasing number of problems. Chronical illnesses, comorbidity and an increasingly ageing population put a strain on the healthcare system’s resources. On the other side, patients expect quicker and easier access to healthcare, with increasing quality of patient experience. So how can healthcare providers hit these critical points at once? Manage their resources, give critical patients the attention they need, while maintaining quick access for the remaining patients?

The vision of transforming primary care, in the long run, finds everyone on board: create more channels by providing the right tools and solutions, to both healthcare professionals and patients. Patients with the help of relevant solutions should be taking over part of the responsibility for their condition. While the vision in itself is complex, the way towards it creates a lot more turmoil.

But we are far too often starting from the wrong end – rushing to hack and crack the code, but would a hack solve the problem in the long run? Let’s first take a step back and give it a thought. Digital transformation is about delivering value to the end-user. To deliver value, we need to identify where we deliver it and how, in order to create tools that are actually being used and get a long-term improvement. Hence, in an attempt to reach this transparency, the two main questions are raised: what are we trying to solve and for whom?

The incoming patient flow is often processed as follows: Patient queues are manually managed by nurses or medical administrators. They, in turn, make a preliminary medical assessment and either advise the patients some self-care or assign them to a healthcare service of a certain category (e.g. GP, test lab, specialist depending on specific practice set-up). Every medical professional along the way needs to gather the history and symptoms anew and in turn, patients re-tell their story to every professional along the way. As this flow is currently overloading and stretching healthcare resources and patients alike, what are the needs to be addressed, in order to create value with an automated solution for patients and healthcare professionals alike?

Healthcare professionals as end-users

1) Signpost patients in a smart way

The critical success factor in this part is not to provide an irrevocable one-dimensional diagnosis but to assess the severity of each patient’s situation and effectively signpost them to the right care path. If, for example, the solution detects a urinary tract infection, why not skip the administrative fuss and send the patient directly to a professional that can provide the right prescription?

2) Patient insight before the first interaction

While getting general information from patients is crucial, insight into the specific patient case in point is necessary. Before the medical professional meets the patient for the first time, he or she would like to know beforehand why the patient is seeking help at this point in time. As we hear from our customers, clinics could dare to offer a lot more self-booking appointments, if only doctors could avoid the “I just don’t feel well” comment coming along with it.

3) Continuity of patient handover

Efficient documentation is also a top-priority need: Any information should easily be transferred from the automatic tool to the human being handling it. Seamless incorporation of the digi-physical flow is a critical point that needs to be covered if we want to create value for the end-users and save them time and effort in the long run. The information-gathering process, that is currently conducted over and over, could be done once in an automated way and complemented with further insights along the care chain.

Critical success factors

If the needs listed above are the what the tool needs to solve, the critical success factors are the how it needs to be solved. Before we even start developing any automated tool, our development must take into account patient safety, decision making transparency and it must complement the healthcare flow – not replace it. These three critical factors will in turn influence the considerations of which technology the solution should be optimally built on.

Webinar AI in primary care - Untangling the buzzwords The AI application the healthcare of here and now seems ready for, is diagnostic tools. But how are these solutions built and what challenges can they uptake? In this webinar, Anastacia Simonchik and Andreas Larsson break down AI in primary care. Watch the webinar

Patients as end-users

When it comes to patients as end-users, one of the most critical aspects is to keep them and their attention within any new tool and channel. Apart from building a simple, user-friendly solution, let’s take a look at the needs of the patients. What is important for them when they contact primary care?

1) A high level of trust in the process and result

Contrary perhaps to one’s first instinct, t’s not medical complexity that creates trust in such a solution – it’s simplicity and ease of use. The clearer the communication is between the solution and the patient, the more the patient will trust the process and the result itself. The critical questions here are how simple to understand the questions are and how relevant to each case they are, as perceived by the patient. Patients will feel much more confident if they are met by 10 questions – but relevant to that particular case, rather than 100 medically exhaustive questions which make them feel hesitant whether they got the meaning of half of them correctly.

2) Accessibility and control

Patients would like to get in touch with medical professionals for advice or a consultation when it suits them best. However, wanting accessibility to healthcare does not always equal needing medical care provided by a physical person. We’ve seen that it’s enough for the patient to initiate the contact by e.g. sending a message and know that it’s in the hands of medical professionals from now on – even if the communication is not face-to-face or synchronous, it is perceived to be taking place.

3) Acknowledgement of the patient’s knowledge and actions

A lot of patients today research their symptoms and conditions before they contact their healthcare provider. These patients perceive any step that is not taking into account their action as a delay or waste. There is simply the need that their knowledge and actions are taken into account and applied to their case. Consequently, any attempt at automating first primary care contact should utilise or aim at utilising the patient’s knowledge of his or her condition.

Responding to the needs

Working with digital innovation means that there is always a question of priorities, choices and limitations. However, we have seen many times over that focusing on solving the user problems is the key to success. Innovating the first patient contact requires delivering on the needs and demands of both medical personnel and patients. We identified 3 pillars around which we wanted to build our technology: Patient-friendly communication, medical context awareness and integration in the digi-physical flow. But how does it go from idea to practice? How do these factors come into development in such a solution? Which technology and data is suitable to cover these specific needs? Find out here!

Stay tuned for our next AI post, where we attempt to answer these questions and scope the relevant technological approaches within AI! Follow us on Twitter to get the news first.

Anastacia Simonchik

Anastacia Simonchik

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