A computer science conundrum that could transform healthcare Premium

Discover how solving the P vs NP problem could revolutionize healthcare and various other fields, offering unprecedented solutions.

In the 17th century, a Dutch draper named Anton van Leeuwenhoek used a small handmade microscope to peer into a world previously unseen by the human eye. Thus he discovered microorganisms and gave rise to the field of microbiology. It offered solutions to challenges in healthcare that until then had seemed intractable.

Today, we face a new set of complex problems in healthcare that seem more intractable than others before for their inherent complexity and the constraints they threaten to impose on resources.

It so happens that an unsolved problem in computer science, simply called the P versus NP problem, could hold the key to these modern-day conundra. While it may sound like a cryptic puzzle reserved for computer science mavens, its implications stretch beyond algorithms and data structures, rippling through diverse fields including healthcare. But what exactly is this puzzle, and how could its resolution unlock a new era in medical science?

Let’s start with a simple arithmetic example. Say you’re asked to multiply 17 with 19. With some time, you’d arrive at the answer: 323. This is a ‘P’ problem: you can solve it reasonably quickly. (‘P’ stands for polynomial time.) Suppose you’re presented with 323 and asked to identify the two prime numbers multiplied to get this. In this case, you will have to take the trial and error route until you arrive at 17 and 19. This is an ‘NP’ problem: it takes longer to solve, but once you have the solution, you can verify it quickly. (‘NP’ here is nondeterministic polynomial time.)

Healthcare is filled with complex problems. Consider scheduling in a hospital: assigning doctors and nurses to shifts, booking operating theatres for surgeries, and organising patient appointments. It is an intricate puzzle that requires considering various factors — staff availability, urgency of medical cases, etc. — and potential changes such as emergency cases and cancellations.

The P vs NP question is this: could there be a shortcut to solve ‘NP’ problems as quickly as ‘P’ problems? Because the implication is that if P equals NP, we could quickly find the optimal solution to these scheduling problems, thus significantly improving patient care.

The implications of resolving this question are profound and wide-reaching, including for healthcare.