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Referral is a dynamic process, in which a health worker at one level of the health system, having insufficient resources (drugs, equipment, skills) to manage a clinical condition, seeks the help of a better or differently resourced facility at the same or higher level to assist in. Health care systems of every country are designed in such a way to encourage patients to first attempt to get care at the primary level and then to approach a higher level of care according to the need. This protocol minimizes the costs for the caretaker/patients. However, in most of the countries, patients often bypass primary care facilities and directly go to the higher center thereby, increasing the burden on higher level facilities, the picture is not very different in India also. Health care system in India is plugged by: overpopulation, lack of expert clinicians, skewed distribution of physicians, lack of motivation among existing health care personnel and an ineffective referral mechanism. Due to failure of conventional paper-based referral systems in our country, we can introduce an e-referral system in the era of internet. It is evident from our experiences, that this artificial intelligence enabled e-referral system has many advantages over the traditional paper-based referral system. It will aid health workers for timely management of cases. Most importantly, it will streamline the existing unorganized referral process. Although, for effective e-Referral system, there should be a collaborative platform where easy search and discovery for health care providers is possible and help in decision making. e- Referral should be incorporated in our health system to strengthen it by bridging the access gap may be through Public Private Partnership model. [ABSTRACT FROM AUTHOR]

In this paper, we have described the health care problem (maldistribution of doctors) in India. Later, we have introduced the concept of artificial intelligence and we have described this technology with various examples, how it is rapidly changing the health care scenario across the world. We have also described the various advantages of artificial intelligence technology. At the end of the paper, we have raised some serious concerns regarding complete replacement of human based health care technology with artificial intelligence technology. Lastly, we concluded that we have to use artificial intelligent technology to prevent human sufferings/health care problems with proper caution. [ABSTRACT FROM AUTHOR]

Background: Patient education is an essential component of improving public health as it empowers individuals with the knowledge and skills necessary for making informed decisions about their health and well-being. Primary care physicians play a crucial role in patients' education as they are the first contact between the patients and the healthcare system. However, they may not get adequate time to prepare educational material for their patients. An artificial intelligence-based writer like ChatGPT can help write the material for physicians. Aim: This study aimed to ascertain the capability of ChatGPT for generating patients' educational materials for common public health issues in India. Materials and Methods: This observational study was conducted on the internet using the free research version of ChatGPT, a conversational artificial intelligence that can generate human-like text output. We conversed with the program with the question - "prepare a patients' education material for X in India." In the X, we used the following words or phrases -- "air pollution," "malnutrition," "maternal and child health," "mental health," "noncommunicable diseases," "road traffic accidents," "tuberculosis," and "water-borne diseases." The textual response in the conversation was collected and stored for further analysis. The text was analyzed for readability, grammatical errors, and text similarity. Result: We generated a total of eight educational documents with a median of 26 (Q1-Q3: 21.5-34) sentences with a median of 349 (Q1-Q3: 329-450.5) words. The median Flesch Reading Ease Score was 48.2 (Q1-Q3: 39-50.65). It indicates that the text can be understood by a college student. The text was grammatically correct with very few (seven errors in 3415 words) errors. The text was very clear in the majority (8 out of 9) of documents with a median score of 85 (Q1-Q3: 82.5-85) in 100. The overall text similarity index was 18% (Q1-Q3: 7.5-26). Conclusion: The research version of the ChatGPT (January 30, 2023 version) is capable of generating patients' educational materials for common public health issues in India with a difficulty level ideal for college students with high grammatical accuracy. However, the text similarity should be checked before using it. Primary care physicians can take the help of ChatGPT for generating text for materials used for patients' education. [ABSTRACT FROM AUTHOR]

Automated clinical decision support systems (CDSS) are knowledge-based systems that provide patient-specific information and data to clinicians at the proper time for enhancing the clinical workflow of hospital organizations. Nowadays, it is adopted by most of the health care professionals for clinical decision-making that helps to reduce the adverse clinical care events occurring during the treatment. In this article, we present a recent literature review on the adoption of computer-based CDSSs in the area of health care based on qualitative and quantitative techniques, published between 2007 and 2022. For this purpose, we searched Google Scholar and identified different adoption factors by using textual analysis from the included publications. We then ranked the different factors based on the total number of occurrences and represented them as a conceptual framework. A total of 14 different adoption factors were found from 13 studies, among them the usefulness of the system is the most prominent factor that influences the adoption of CDSS to a great extent. This literature review and the framework could be helpful to researchers and healthcare professionals working in the field of technology adoption, providing an overall idea of factors and techniques in this field of research. We have also mentioned the limitations and future research gaps of different studies, which will help the researchers to take an initiation towards these types of research. We also conducted a case study on adoption of fully automatic digital blood pressure monitor and identified that "usefulness" and "ease of use" could influence the adoption of fully automatic digital blood pressure monitor system. [ABSTRACT FROM AUTHOR]

Background: There is a constant search across the globe for optimal healthcare solutions with affordability, accessibility, availability, and quality of healthcare services being the burning issue for mankind. The pandemic has further necessitated the need of use of the Telemedicine platform to address healthcare issues which are also non Covid related. Though Telemedicine has been in use for over two decades in India, there have been various challenges and adoption issues which have not yet made the technology an effective solution to address the current healthcare issues. There has been phenomenal growth in the Information and Communication Technology (ICT) over the last decade and its utilization in the healthcare field. Methods: Internet research on the various adoption strategies by healthcare providers coupled with our own experience for using this technology along with guidelines provided by the information and communication technology providers. The Telemedicine Guidelines of 2020 released by the Ministry of Health and Family welfare, India, provides a framework for the implementation of healthcare delivery through this technology. Results: This paper mentions our telemedicine experience in governmental and private institutes and highlights the implementation challenges of this technology and some solutions that made a difference in the execution. However, we discuss to a larger extent the possible challenges and barriers in the implementation of this technology in India. Conclusion: Despite successful work in the field of telemedicine, it is yet to become an integral part of healthcare system because challenges related to adaptability of healthcare users and lack of proper training to fast growing technologies. The future is going to compel the usage of this kind of technology and it is essential for setting up infrastructure and having trained personnel to man these departments to encash the full potential of the telemedicine technology. [ABSTRACT FROM AUTHOR]

The article focuses on the Indo-United Kingdom (UK) collaboration in mental health, highlighting the growth of the initiative from a pilot involving 2 National Health Service (NHS) organizations to over 20 organizations across England and Wales. Topics include developing a long-term sustainable partnership; recent advances in clinical research in India and the UK; and strengths and challenges of the UK-India partnership in mental health.

Oral cancer constitutes around 2.1% and it is the sixth-most common malignancy worldwide and the third-most common type of malignancy in India. The purpose of this systematic review is to find the prediction of survival rate among oral cancer patients using artificial intelligence (AI) and its forms like machine learning. Suitable articles were identified by searching PubMed, Trip database, Cochrane, and Google Scholar host databases. The search was done with the help of PIO analysis where the population stands for oral cancer patients, the intervention given here were AI and its subsets and the outcome were diagnosis and survival prediction of oral cancer. The screening of the titles and abstracts was done, and only those articles that fulfilled the eligibility criteria were selected. The search resulted in 451 articles, of which only six articles that fulfilled the criteria were included. The studies showed that AI models were able to predict the 5-year survival rate among oral cancer patients. The accuracy of the decision tree classifier, logistic regression, and boosted decision tree models were 76%, 60%, and 88.7%, respectively. Modern age diagnosed people tend to have a longer survival rate than those diagnosed in the past. The limitation was that these studies were created using retrospective cohorts, but for validation, they must be compared with prospective cohorts. These studies are important for identification and survival prediction, which will contribute to future advancements, change in the treatment plan, and reduce health-care problems. [ABSTRACT FROM AUTHOR]

Purpose: Big data is the new gold, especially in health care. Advances in collecting and processing electronic medical records (EMR) coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Ophthalmology has been an area of focus where results have shown to be promising. The objective of this study was to determine whether the EMR at a multi-tier ophthalmology network in India can contribute to the management of patient care, through studying how climatic and socio-demographic factors relate to eye disorders and visual impairment in the State of Telangana.Methods: The study was designed by merging a dataset obtained from the Telangana State Development Society to an existing EMR of approximately 1 million patients, who presented themselves with different eye symptoms and diagnosed with several diseases from the years (2011-2019). The dataset obtained included weather and climatic variables to be tested alongside eye disorders. AI creative featuring techniques have been used to narrow down the variables most affected by climatic and demographic factors, with the application of the Cynefin Framework as a guide to simplify and structure the dataset for analysis.Results: Our findings revealed a high presence of cataract in the state of Telangana, mostly in rural areas and throughout the different weather seasons in India. Males tend to be the most affected as per the number of visits to the clinic, while home makers make the most visit to the hospital, in addition to employees, students, and laborers. While cataract is most dominant in the older age population, diseases such as astigmatism, conjunctivitis, and emmetropia, are more present in the younger age population.Conclusion: The study appeared useful for taking preventive measures in the future to manage the treatment of patients who present themselves with eye disorders in Telangana. The use of clinical big datasets helps to identify the burden of ocular disorders in the population. The overlaying of meteorological data on the clinical presentation of patients from a geographic region lends insight into the complex interaction of environmental factors on the prevalence of ocular disorders in them. [ABSTRACT FROM AUTHOR]