Using Artificial Intelligence to Reduce Global Healthcare Costs through Discovery and Development of Nutritional Interventions

doi:10.15520/ijnd.v10i09.3082

Impact of interventions to reduce overnutrition on healthcare costs related to obesity and type 2 diabetes: a systematic review

Nutrition Reviews ◽

10.1093/nutrit/nuz070 ◽

2019 ◽

Vol 78 (5) ◽

pp. 412-435

Author(s):

Michaela Olm ◽

Renée G Stark ◽

Nathanael Beck ◽

Christina Röger ◽

Reiner Leidl

Keyword(s):

Systematic Review ◽

Type 2 Diabetes ◽

Economic Evaluation ◽

Healthcare Costs ◽

Health Economic Evaluation ◽

Economic Modeling ◽

Community Dwelling ◽

Nutritional Interventions ◽

Healthcare Needs

Abstract Context In recent decades, obesity and type 2 diabetes mellitus (T2DM) have both become global epidemics associated with substantial healthcare needs and costs. Objective The aim of this review was to critically assess nutritional interventions for their impact on healthcare costs to community-dwelling individuals regarding T2DM or obesity or both, specifically using CHEERS (Consolidated Health Economic Evaluation Reporting Standards) criteria to assess the economic components of the evidence. Data Sources Searches were executed in Embase, EconLit, AgEcon, PubMed, and Web of Science databases. Study Selection Studies were included if they had a nutritional perspective, reported an economic evaluation that included healthcare costs, and focused on obesity or T2DM or both. Studies were excluded if they examined clinical nutritional preparations, dietary supplements, industrially modified dietary components, micronutrient deficiencies, or undernutrition; if they did not report the isolated impact of nutrition in complex or lifestyle interventions; or if they were conducted in animals or attempted to transfer findings from animals to humans. Data Extraction A systematic review was performed according to PRISMA guidelines. Using predefined search terms, 21 studies evaluating food habit interventions or taxation of unhealthy foods and beverages were extracted and evaluated using CHEERS criteria. Results Overall, these studies showed that nutrition interventions and taxation approaches could lead to cost savings and improved health outcomes when compared with current practice. All of the included studies used external sources and economic modeling or risk estimations with population-attributable risks to calculate economic outcomes. Conclusions Most evidence supported taxation approaches. The effect of nutritional interventions has not been adequately assessed. Controlled studies to directly measure economic impacts are warranted.

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Patient apprehensions about the use of artificial intelligence in healthcare

npj Digital Medicine ◽

10.1038/s41746-021-00509-1 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Jordan P. Richardson ◽

Cambray Smith ◽

Susan Curtis ◽

Sara Watson ◽

Xuan Zhu ◽

...

Keyword(s):

Artificial Intelligence ◽

Data Security ◽

Healthcare Costs ◽

Patient Choice ◽

Medical Community ◽

Patient Acceptance ◽

Data Source ◽

Patient Concerns ◽

Applications Of Ai

AbstractWhile there is significant enthusiasm in the medical community about the use of artificial intelligence (AI) technologies in healthcare, few research studies have sought to assess patient perspectives on these technologies. We conducted 15 focus groups examining patient views of diverse applications of AI in healthcare. Our results indicate that patients have multiple concerns, including concerns related to the safety of AI, threats to patient choice, potential increases in healthcare costs, data-source bias, and data security. We also found that patient acceptance of AI is contingent on mitigating these possible harms. Our results highlight an array of patient concerns that may limit enthusiasm for applications of AI in healthcare. Proactively addressing these concerns is critical for the flourishing of ethical innovation and ensuring the long-term success of AI applications in healthcare.

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Legal Urgency on Designing The Legislation for The Use of Artificial Intelligence in Indonesian Medical Practice

Jurnal Penelitian Hukum De Jure ◽

10.30641/dejure.2021.v21.541-550 ◽

2021 ◽

Vol 21 (4) ◽

pp. 541

Author(s):

Hary Abdul Hakim ◽

Chrisna Bagus Edhita Praja ◽

Hardianto Djanggih

Keyword(s):

Artificial Intelligence ◽

Medical Practice ◽

Healthcare Costs ◽

Descriptive Analysis ◽

High Accuracy ◽

Health Law ◽

Disease Treatment ◽

Medical Practices ◽

Medical Diagnoses ◽

Legal Documents

Artificial intelligence (AI) offers the potential for a great improvement in patient care, both in diagnose and disease treatment, and a consequential reduction in healthcare costs, a part of opportunities and challenge are ahead. The use of AI in medicine was significantly developed in some countries. Indonesia as a modern country also has a great change in promoting the use of AI. The study aims to propose on designing the legislation for the use of AI in Indonesian medical practices. The method used in this research is normative juridical approaches with descriptive analysis. The data used are primary legal material namely the Indonesian Penal Code and Law No. 36 of 2009 on Health Law. Meanwhile, the secondary legal material used are books, journals, and other legal documents. The results show that designing the new legislation as the guidance and basis for the use of AI shall give a good impact on the development of health services as practices among other countries. Moreover, Health Act 2009 clearly supported the use of advance technology’s product in medicine. Yet, the application of AI facilitates interpretation follows with high accuracy and speed for medical diagnoses.

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Health Care Bot using Artificial Intelligence for Self-Diagnosis

International Journal for Modern Trends in Science and Technology - RTT2020 ◽

10.46501/ijmtst061230 ◽

2020 ◽

Vol 6 (12) ◽

pp. 156-160

Author(s):

Chandan Patra

Keyword(s):

Artificial Intelligence ◽

Health Care ◽

Healthcare Costs ◽

Good Life ◽

Medical Knowledge ◽

Healthcare Services ◽

Health Issues ◽

The Real ◽

The Right

Healthcare bot is a technology that makes interaction between man and machine possible by using Artificial Intelligence with the support of dialog flow. Now a day people tend to seek knowledge or information from internet that concern with health through online healthcare services. To lead a good life healthcare is very much important. But it is very difficult to obtain the consultation with the doctor in case of any health issues. The basic aim of this system is to bridge the vocabulary gap between the doctors by giving self-diagnosis from the comfort of one’s place. The proposed idea is to create a medical bot using Artificial Intelligence that can diagnose the disease and provide basic details about the disease before consulting a doctor. To reduce the healthcare costs and improve accessibility to medical knowledge the medical bot is built. Certain bots act as a medical reference books, which helps the patient know more about their disease and helps to improve their health. The user can achieve the real benefit of a bot only when it can diagnose all kind of disease and provide necessary information. Hence, people will have an idea about their health and have the right protection.

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Improving Global Healthcare and Reducing Costs Using Second-Generation Artificial Intelligence-Based Digital Pills: A Market Disruptor

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18020811 ◽

2021 ◽

Vol 18 (2) ◽

pp. 811

Author(s):

Yaron Ilan

Keyword(s):

Artificial Intelligence ◽

Global Health ◽

Generic Drug ◽

Healthcare Costs ◽

Second Generation ◽

Insurance Companies ◽

Single Subject ◽

Loss Of Response ◽

Drug Companies ◽

Chronic Medications

Background and Aims: Improving global health requires making current and future drugs more effective and affordable. While healthcare systems around the world are faced with increasing costs, branded and generic drug companies are facing the challenge of creating market differentiators. Two of the problems associated with the partial or complete loss of response to chronic medications are a lack of adherence and compensatory responses to chronic drug administration, which leads to tolerance and loss of effectiveness. Approach and Results: First-generation artificial intelligence (AI) systems do not address these needs and suffer from a low adoption rate by patients and clinicians. Second-generation AI systems are focused on a single subject and on improving patients’ clinical outcomes. The digital pill, which combines a personalized second-generation AI system with a branded or generic drug, improves the patient response to drugs by increasing adherence and overcoming the loss of response to chronic medications. By improving the effectiveness of drugs, the digital pill reduces healthcare costs and increases end-user adoption. The digital pill also provides a market differentiator for branded and generic drug companies. Conclusions: Implementing the use of a digital pill is expected to reduce healthcare costs, providing advantages for all the players in the healthcare system including patients, clinicians, healthcare authorities, insurance companies, and drug manufacturers. The described business model for the digital pill is based on distributing the savings across all stakeholders, thereby enabling improved global health.

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AI Health Care Chatbot

International Journal for Modern Trends in Science and Technology - RTT2020 ◽

10.46501/ijmtst061241 ◽

2020 ◽

Vol 6 (12) ◽

pp. 219-224

Author(s):

Sumit

Keyword(s):

Artificial Intelligence ◽

Health Care ◽

Healthcare Costs ◽

Good Life ◽

Medical Knowledge ◽

Healthcare Services ◽

Health Issues ◽

The Real ◽

The Right

Healthcare bot is a technology that makes interaction between man and machine possible by using Artificial Intelligence with the support of dialog flow. Now a day people tend to seek knowledge or information from internet that concern with health through online healthcare services. To lead a good life healthcare is very much important. But it is very difficult to obtain the consultation with the doctor in case of any health issues. The basic aim of this system is to bridge the vocabulary gap between the doctors by giving self-diagnosis from the comfort of one’s place. The proposed idea is to create a medical chatbot using Artificial Intelligence that can diagnose the disease and provide basic details about the disease before consulting a doctor. To reduce the healthcare costs and improve accessibility to medical knowledge the medical bot is built. Certain bots act as a medical reference books, which helps the patient know more about their disease and helps to improve their health. The user can achieve the real benefit of a bot only when it can diagnose all kind of disease and provide necessary information. Hence, people will have an idea about their health and have the right protection.

Download Full-text