Iraqi Health Tech Startup Opportunities Unlocked by Generative AI

It is becoming more and more obvious that AI is set to achieve great things in healthcare. From saving costs by automating time-consuming desk work to showing life-saving warnings about patient health, most would agree generative AI has many much-needed use cases in healthcare. Furthermore, as we navigate through 2024, the AI in healthcare market is witnessing remarkable growth, with a projected increase from USD 22.45 billion in 2023 to USD 208.2 billion in 2030 (Global AI in Healthcare, 2023). In Iraq, where the healthcare sector is ripe for digital transformation, AI presents a unique opportunity to leapfrog traditional healthcare models. By harnessing the power of AI, Iraqi healthcare startups can address the pressing challenges of the current system, including the manual management of patient records and the need for more efficient care delivery.

In this article, we will try to address some interesting dynamics and opportunities and use cases related to AI in healthcare tech, specifically those related to the Iraqi ecosystem.

AI Enables Tech Leapfrogging:

There have been many instances where a developing country could make use of the latest version of a piece of technology without having to adopt the steps in between. For example, some developing countries have leapfrogged traditional landline telephone infrastructure and moved directly to mobile networks and smartphones. This is known as “Technological Leapfrogging.”

There is potential for a similar thing to happen in Iraqi healthcare tech through AI. For instance, the vast majority of patient healthcare data in Iraqi public hospitals are stored in handwritten format. This has been a huge blocker for improving the quality of care because it could not be measured at scale.

The inability to measure healthcare quality at scale presents a significant barrier to enhancing care because it obscures our understanding of performance across the healthcare spectrum. Without scalable, standardized measures, pinpointing areas for improvement, allocating resources effectively, and enacting data-driven policy changes become challenging tasks. Classic electronic medical record systems currently used in most developed countries also have their drawbacks. They are infamous for consuming too much time from the medical staff.

Thanks to AI, we are now seeing a wave of electronic medical record systems where many of these time-consuming aspects are automated through AI. By using these newer systems, doctors, nurses, and other members of the hospital staff can use their time to provide medical care instead of inputting information into digital systems.

By using such AI-powered systems, Iraq and other countries that have predominantly handwritten medical records can skip the time-consuming drawbacks of the previous generation of medical software, which is a major factor in blocking adoption, and they can benefit from all of the advantages of digitizing patient data.

No Entrenched Competition Means a Level Playing Field for Startups:

For most industries and in most regions around the world, some large providers have succeeded in providing value for general use cases in their industry and their region. These are known as “incumbents”.

Under typical conditions, a startup would have to provide value that out-competes the incumbent for their industry and region. However, whenever there is a significant technological breakthrough, this drastically changes as incumbents can struggle to satisfy the use cases. Startups, on the other hand, are much more agile and are able to innovate. This was observed with the World Wide Web, mobile technology, and the cloud. We are now seeing it happen with AI.

AI-focused Healthcare startups can build systems that are AI-first, as opposed to the incumbents’ systems, where AI is usually an afterthought.

This unlocks a unique and interesting opportunity for Iraqi startups. Firstly, there is a new type of demand that is not handled by incumbents locally. Secondly, reaching product-market fit locally unlocks the opportunity for easier deployment for regions with similar healthcare systems, that is, neighboring countries, and even for global markets.

Examples of AI Use Cases in Healthcare:

Doctor Assistant AI: This is a broad and exciting category where AI can help doctors have more efficient medical interviews by taking down notes, suggesting questions, offering insights mid-interview, establishing a differential diagnosis, and even suggesting treatment plans. Especially since this technology is in its early phases, it is very important that it is used as a tool to increase efficiency and not as an alternative for a qualified medical professional’s opinion.

Clinical Condition Monitoring AI: A lot of data is gathered relating to all the steps being taken to manage patients, from entering a healthcare facility to the time they are discharged. By monitoring this data as it is generated, AI can generate time-critical and life-saving insights that, unfortunately, are otherwise frequently missed. These warnings can be issued to medical professionals so that they are corrected as soon as possible.

Patient Education AI: Once clinical conclusions are made by professionals, an important and continuous process of patient education begins. AI can help by interacting with patients to keep them always best informed about their conditions. This not only helps them make better choices about their health but also builds more trust in the healthcare process.

Medical Administrative AI: Many newly hired medical professionals are surprised by the amount of administrative and office tasks involved in their work. Form-filling and data entry are especially time-consuming. AI excels in handling this type of task, and it has the potential to be smart enough to handle edge cases or at least delegate responsibility when needed. This category also includes AI helping with healthcare facility-level tasks such as revenue cycle management and making use of analytics to optimize healthcare costs and resource allocation.

Other Use Cases: Mental health assistance, helping patients with medication adhesion, and finding the best healthcare providers for a specific patient are great examples of the many opportunities unlocked by this new technology.

While much of the Iraqi patient's clinical information ends up documented in the English language, Iraqi patients speak the Iraqi dialect of Arabic. As multiple AI use cases involve listening to what these patients are saying, one could see a challenge and an opportunity to develop AI models related to this language. These can be large language models, but they also could be speech models, multi-modal models, etc.

Recently, the most impressive AI functionalities have been powered by generative AI, at least in terms of public attention and press. Unfortunately, generative AI is susceptible to “hallucinations”. Not only does it make mistakes, but many times it is confident about its output when generating such mistakes. This could be very dangerous in a healthcare setting where people’s lives and well-being are at stake. Hence, startups implementing AI solutions in healthcare need to do so with a large focus on safety and accuracy.

One of the better approaches to do so is to base the responses generated by AI on real-world peer-reviewed references and data from well-established entities. These can include medical associations and societies, scientific book publishers, and online medical reference platforms.

These systems typically handle a lot of information. As medical information tends to be sensitive, it is extra important to ensure data safety, be transparent about its usage, and comply with relevant regulations.

Many of the state-of-the-art AI systems are developed and trained on data that has major underlying biases, such as those relating to ethnicities and gender. Since medical management can be affected by such variables, it is important to explore ways in which the population using a technology is well-represented in the data used to build that technology.

The users of this new technology will include not only medical professionals but also patients. Patients, of course, come from all socioeconomic classes of the country.

Not only do people need to be comfortable with getting and interacting with services digitally, but they also need to have at least a basic understanding of the abilities and limitations of the AI features that they interact with.

That being said, AI has the potential to make interaction with technology much easier and more intuitive. Furthermore, the Iraqi population has clearly been adopting more and more digital products and services.

Hence, startups in this space just need to put relatively more effort into making the user experience intuitive, clear, and practical.

In conclusion, this technology has a lot of potential to revolutionize the way things are done in the medical space. By prioritizing safety, accuracy, and ethical considerations while remaining informed about AI's capabilities, healthcare providers can unlock its full potential to revolutionize healthcare delivery and ultimately benefit humanity as a whole.