Indonesia Artificial Intelligence in Healthcare Market Report 2022 to 2030

Indonesia Artificial Intelligence (AI) in Healthcare Market Analysis

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Indonesia's Artificial Intelligence (AI) In Healthcare Market is projected to grow from $0.04 Bn in 2022 to $0.82 Bn by 2030, registering a CAGR of 45.22% during the forecast period of 2022-30. The market will be driven by more investments in AI technology by healthcare providers and a rise in professionals with expertise in the technology. The market is segmented by healthcare components & by healthcare applications. Some of the major players include IBM Watson Health, Philips Healthcare, Alodokter & Asa Ren Pte Ltd.

ID: IN10IDDH003 CATEGORY: Digital Health GEOGRAPHY: Indonesia AUTHOR: Vidhi Upadhyay

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Indonesia Artificial Intelligence (AI) In Healthcare Market Executive Summary

Indonesia's Artificial Intelligence (AI) In Healthcare Market is projected to grow from $0.04 Bn in 2022 to $0.82 Bn by 2030, registering a CAGR of 45.22% during the forecast period of 2022-30. Healthcare is a major priority in Indonesia, and the central and regional governments are working to construct and upgrade healthcare facilities. In public and private hospitals in Indonesia, there were 1.4 beds per 1,000 people, compared to the global average of 7.3 beds. Furthermore, national healthcare spending as a percentage of GDP remains at 0.9 per cent, far below the average benchmark of 5 per cent. In Indonesia, the most common NCDs (noncommunicable diseases) are hypertension, heart disease, bronchial asthma, chronic renal failure, diabetes, stroke, and cancer.

Mayapada Hospital in Jakarta has incorporated an artificial intelligence (AI) system to analyse medical images and aid in the diagnosis of diseases such as tuberculosis. Another hospital in Surabaya has incorporated an artificial intelligence (AI) system to anticipate patient health outcomes and assist healthcare professionals in developing personalised treatment plans. The adoption and use of AI in healthcare in Indonesia are still in their early stages, but AI has the potential to significantly improve care delivery in the country. As more healthcare professionals invest in AI and more professionals gain expertise in the technology, the use of AI in healthcare in Indonesia is expected to grow over the next few years.

indonesia artificial intelligence in healthcare market

Market Dynamics

Market Growth Drivers

In August 2022, The Indonesia Health Ministry launched the Indonesia Health Services platform in Jakarta, as part of the nation's healthcare technology transformation pillar. With Indonesia's population rapidly growing, there is an increasing need for superior and more personalised healthcare services. The growing use of digital systems such as electronic health records (EHRs) generates an increasing amount of healthcare data that can be processed using AI algorithms. This information can be used to spot patterns and trends, as well as to build predictive models that can help improve patient outcomes. AI technology advancements, such as machine learning and natural language processing, will make it easier for healthcare providers to develop and implement AI systems in their organisations.

Market Restraints

Many Indonesians have no access to healthcare. Indonesia, a country of 17,508 islands, has only 10,205 Community Health Centres (known as puskemas), with only 4,119 offering in-patient services. 15 of Indonesia's 34 provinces continue to provide subpar public services, with less than 70% compliance with national standards. Furthermore, insurance penetration is expected to be around 2% of GDP in 2020. These two situations highlight the low level of healthcare provided throughout Indonesia, as well as the limited availability of medical care, which is impeding the improvement of the quality of healthcare received by Indonesians. According to the Health Ministry, Indonesia still lacks approximately 3,941 Obstetrics and Gynaecology doctors. Unfortunately, approximately 300 pregnant women per 100,000 live births in the country die. Lack of expertise, high cost of AI technology implementation and other regulatory barriers are expected to slow down the adoption of AI in healthcare.

Competitive Landscape

Key Players

IBM Watson Health
Philips Healthcare
GE Healthcare
Siemens Healthineers
Microsoft Healthcare
Amazon Web Services (AWS) Healthcare
Google Healthcare
NVIDIA Healthcare
Prodia Widyahusada (IDN)
PJB Digital (IDN)
Alodokter (IDN)
Asa Ren Pte Ltd (IDN)

Notable Insights

In March 2023, Alni, a chat-based virtual assistant for doctors, has been launched by Alodokter, an Indonesia-based digital health platform. Ali employs conversational AI to prescreen patients via a series of questions and then makes prediagnosis recommendations to Alodokter's telemedicine doctors.

March 2023, Predictmedix Announced the Completion of a 1600-Person Clinical Study in Indonesia for Safe Entry's Medical Device Regulatory Approval

In February 2023, Mayapada Hospital incorporated artificial intelligence to improve Indonesia's healthcare infrastructure.

November 2022, G42 Healthcare, a foremost Abu Dhabi-based AI health-tech company, has entered into an MOU with Indonesia's health tech DNA company, Asa Ren Pte Ltd, as part of its commitment to enhance its clinical genomics functionality and collaborate with global leaders in the domain.

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 Healthcare Market Segmentation

Artificial Intelligence (AI) in Healthcare Market is segmented as mentioned below:

By Healthcare Component (Revenue, USD Billion):

Software Solutions
Hardware
Services

By Healthcare Applications (Revenue, USD Billion):

Robot-Assisted Suregery
Virtual Assistants
Administrative Workflow Assistants
Connected Machines
Diagnosis
Clinical Trials
Fraud Detection
Cybersecurity
Dosage Error Reduction

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.