Kenya Artificial Intelligence (AI) in Diagnostics Market Report 2022 to 2030

Kenya Artificial Intelligence (AI) in Diagnostics Market Analysis

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Kenya Artificial Intelligence (AI) in the diagnostics market is projected to grow from $xx Bn in 2022 to $xx Bn by 2030, registering a CAGR xx% during the forecast period of 2022-2030. The market will be driven by a constantly rising population, a rising disease burden, and a high demand for more effective and accurate diagnostic devices. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, iSono Health, Siemens Healthineers

ID: IN10KEDH002 CATEGORY: Digital Health GEOGRAPHY: Kenya AUTHOR: Vidhi Upadhyay

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Kenya Artificial Intelligence (AI) in Diagnostics Market Executive Summary

The Kenya Artificial Intelligence (AI) in the diagnostics market is projected to grow from $xx Bn in 2022 to $xx Bn by 2030, registering a CAGR of xx% during the forecast period of 2022 - 2030. The public sector provides more than half of Kenya's healthcare services, through the Ministry of Health (MOH), other government-funded entities, and donor countries such as the United States. These services are complemented by those provided in hospitals and clinics run by private corporations, non-governmental organizations (NGOs), and faith-based groups such as the Kenyan Episcopal Conference, the Christian Health Association of Kenya, and the Kenyan Red Cross. Kenya has a higher overall CVD death rate (13.8%) compared to the majority of African countries.

While AI in diagnostics acceptance and utilization in Kenya is in its initial phases, there are encouraging signals of growth. AI has the potential to greatly enhance healthcare outcomes in Kenya with continuous investment and research. The Government of Kenya's (GOK) ongoing efforts to assist cancer management include the Managed Equipment Service (MES), through which level four and five hospitals have been equipped with varied hi-tech diagnostic equipment such as X-ray, CT-SCAN, ultrasound, and mammography machines to enhance cancer diagnosis in the counties.

Market Dynamics

Market Growth Drivers

The Kenya Medical Research Institute (KEMRI) and the Kenya Health Information System (KHIS) are two efforts developed by the government to foster healthcare innovation. Kenya's population is quickly rising, which has increased the demand for healthcare services. AI in diagnostics can assist healthcare practitioners in more efficiently and accurately diagnosing and treating illnesses, potentially improving patient outcomes. Technological advancements have enabled the development of increasingly complex AI algorithms and systems that can evaluate medical data and pictures more correctly and effectively.

Market Restraints

In Kenya, where more than 43% of the population is impoverished, health concerns include high maternal and infant mortality rates as well as a high burden of infectious illnesses such as HIV, TB, and malaria. Kenya's infrastructure is underdeveloped, which may impede the adoption and use of AI in diagnostics. Certain locations may lack consistent internet connectivity, limiting access to online diagnostic tools. AI in diagnostics may be costly to develop and execute, making access to these technologies challenging for healthcare professionals and patients. In Kenya, there is currently a restricted regulatory system for AI in diagnostics, which might raise concerns about the safety and efficacy of these technologies. This can make it more challenging for healthcare practitioners and patients to engage in and use these technologies.

Competitive Landscape

Key Players

IBM Watson Health
iSono Health
Siemens Healthineers
Philips Healthcare
GE Healthcare
Google Health
AliveCor, Inc.
Abdul Latif Jameel Health
Lunit Inc.

Notable Deals

January 2023, Abdul Latif Jameel Health collaborates with iSono Health to use AI to revolutionize breast care. Abdul Latif Jameel Health will market the ATUSA scanner throughout the Middle East and North Africa, as well as African markets such as Kenya, under the terms of the deal.

Healthcare Policies and Regulatory Landscape and Reimbursement Scenario

The Ministry of Health (MOH) is the major authority in charge of supervising Kenya's healthcare industry. Its function in artificial intelligence diagnostics and reimbursement is to offer regulatory supervision and guarantee that AI-based diagnostic systems fulfill the required safety and effectiveness criteria. The MOH is also in charge of establishing reimbursement rules and guidelines for AI diagnostics. National Health Insurance Fund (NHIF) is a government body that offers Kenyan people health insurance coverage. Its purpose in AI diagnostics is to guarantee that AI-based diagnostic technologies are reimbursed by insurance companies, allowing individuals to utilize and afford them.

1. Executive Summary
1.1 Digital Health Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Digital Health Policy in Country
1.6 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Market Size (With Excel and Methodology)
2.2 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

Artificial Intelligence (AI) in Diagnostics Market Segmentation

By Component Outlook Type (Revenue, USD Billion):
- Software
- Hardware
- Services

By Diagnosis Outlook Type (Revenue, USD Billion):
- Cardiology
- Oncology
- Pathology
- Radiology
- Chest and Lung
- Neurology
- Others

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

Analyzing historical proprietary data collected from multiple projects.
Regularly updating our existing data sets with new findings and trends.
Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

Searching through academic conferences, published research, citations, and social media platforms
Collecting and compiling diverse data to build a comprehensive and detailed database
Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
Continuously refreshing our database to ensure that the information remains current and reliable.
Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

Merging historical data from secondary research with real-time data from primary research.
Conducting thorough data validation and cleansing to remove inconsistencies and errors.
Organizing data into a structured format that is easily accessible and usable for various applications.
Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.