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The design of healthcare facilities significantly affects patient outcomes, well-being, and environmental sustainability. With growing concerns over climate change and resource scarcity, there is an increasing demand to incorporate eco-friendly building concepts and healing design principles into hospital design in India. This review synthesizes recent research to explore the application of these approaches in the Indian healthcare context. Eco-friendly healthcare facilities emphasize energy efficiency, water conservation, waste management, use of renewable energy sources, and eco-friendly building materials. These sustainable practices offer environmental and economic benefits such as reduced operational costs, diminished ecological impact, and improved patient experiences. Healing architecture principles, including day lighting, natural ventilation, healing gardens, and the integration of natural elements, aim to create therapeutic environments that promote patient recovery and well-being. Studies from Indian hospitals that have implemented green design practices and healing architecture elements demonstrate the feasibility and positive outcomes of these strategies. The review examines the challenges and barriers to implementing green hospitals and healing architecture in India, such as resource constraints, regulatory compliance, and lack of awareness. Evaluation frameworks like GRIHA (Green Rating for Integrated Habitat Assessment) are discussed as tools for assessing and enhancing environmental sustainability in Indian hospital infrastructure. By integrating recent research with best practices, this review provides an understanding of green hospitals and healing architecture in the Indian context, highlighting their significance in creating sustainable, patient-centered healthcare facilities that prioritize both environmental stewardship and patient recovery. [ABSTRACT FROM AUTHOR]

Patient safety, which is both an overarching principle and a key factor in determining the quality of healthcare, continues to be a priority in healthcare systems on a global scale. A cross-sectional study in accredited Indian hospitals aimed to evaluate the HSOPSC V-2 (Hospital Survey on Patient Safety Culture). 1,603 healthcare professionals participated, assessing psychometric features using confirmatory factor analysis in SMART PLS 4. The average composite positive response rate was 64.8%. High positive responses (79%) were seen in 'teamwork', 'communication about error', and 'hospital management support for patient safety'. However, 'staffing and work pace' (30%), 'response to error' (50%), 'communication openness', and 'reporting patient safety events' (both 59%) had lower positive responses, indicating room for improvement. Findings suggest I-HOSPSC 2.0's content validity, reliability, and construct validity in measuring patient safety culture in Indian hospitals. It can aid administrators in assessing safety culture and improving patient safety and treatment efficacy. Notably, this is the inaugural HSOPSC V-2 validation research in the Indian healthcare context. Future research should explore the tool's psychometric properties based on care setting levels due to substantial differences between public and private healthcare setups in India. [ABSTRACT FROM AUTHOR]

The integration of Artificial Intelligence (AI) technologies in Indian healthcare is set to revolutionize drug related problem (DRP) management, ensuring patient safety and optimizing healthcare outcomes. AI-driven drug discovery will enable precision medicine by tailoring treatments to individual patient profiles, genetics, and environmental factors. Medication management will be greatly improved through AI-powered applications that track and monitor patients' medication schedules, reducing adverse reactions and enhancing treatment effectiveness. AI algorithms will play a vital role in identifying potential drug interactions and safety concerns, offering real-time alerts to healthcare providers. Personalized drug prescriptions and dosage recommendations will minimize medication errors and maximize treatment efficacy. Healthcare chatbots will empower patients with accurate information, enabling them to actively manage their health and make informed decisions. AI-driven data analytics will facilitate population health management, guiding evidence-based decision-making to address public health concerns effectively. Remote healthcare services powered by AI-driven telemedicine platforms will bridge the gap between underserved populations and healthcare facilities, providing equitable access to quality care. Despite the transformative potential, challenges such as data privacy, regulatory compliance, and integration with existing healthcare infrastructure must be addressed responsibly. By embracing AI technologies collaboratively, Indian healthcare will enter an era of enhanced DRP management, leading to improved patient safety, optimized healthcare outcomes, and a more efficient and equitable healthcare system. [ABSTRACT FROM AUTHOR]

There is an increasing emphasis on digital health. However, success of digital health depends on voluntary adoption, which requires good product–market fit for a wide range of users. A national-level survey through snowball sampling was conducted from November 2020 to March 2021 among all MBBS doctors willing to participate. A total of 1010 doctors from different sectors, locations, qualifications with wide range of experience and patient load participated. Doctors from across the board felt going digital would entail long learning curves, additional workload, more screen time and that they do not improve overall quality of care. Majority feel digital solutions do not help in increasing net revenue and consequently prefer free-of-cost digital solutions. Among those willing to pay, onetime investment for hardware/equipment (38%) followed by annual subscription for software licenses (34%) are the preferred modalities. Seventy-four percent of doctors expressed not being comfortable with government providing digital solutions or controlling the data. In order to make the findings more practical and relevant, digital health adoption curve and market intelligence grid have been proposed. Digital health companies can use the adoption curve to understand how adoption can fluctuate with cost, ease of use and data policy. The grid can help companies identify the requirements of their target segment of doctors and therefore achieve better product–market fit. [ABSTRACT FROM AUTHOR]

Background Emergency abdominal surgeries pose significant challenges, especially in the Indian population, due to comorbidities, delayed presentations, and limited resources. Accurately predicting morbidity and mortality is crucial for timely interventions and improved patient care. The neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein-to-albumin ratio (CAR) have shown potential as prognostic markers, balancing inflammation and nutritional status. Aim The study aims to evaluate the predictive efficacy of NLR and CAR with regard to postoperative morbidity and mortality in patients undergoing emergency abdominal surgery, thereby contributing to better risk stratification and management strategies. Patients and methods A prospective observational study was conducted in a tertiary teaching hospital in northern Karnataka from August 2022 to June 2024, involving 102 patients undergoing emergency abdominal surgeries. The sample size (71) was calculated using G*Power software, targeting a 95% power with a 5% significance level. The inclusion criterion was patients aged over 18 years undergoing emergency abdominal surgeries; those who were immunocompromised, on steroid therapy, having malignancies, undergoing radiotherapy, or having chronic liver diseases were excluded from the study. Patients coming into the surgical inpatient department (IPD) with an acute abdomen requiring emergency abdominal surgeries as an emergency were preoperatively assessed using complete blood count (CBC), CRP, and serum albumin tests. NLR and CAR were evaluated preoperatively and at 24 and 48 hours postoperatively. The outcome measures included surgical site infection rates, hospital stay duration, and outcome in the form of recovery or death. SPSS version 20 was used for statistical analyses. Results The study included 102 patients whose mean age was 43.7 ± 18.9 years; 74 of the participants (72.5%) were male. The most common procedures were exploratory laparotomy (64 patients; 62.7%) and appendicectomy (32 patients; 31.4%). A significant increase in CAR levels was observed on postoperative days 1 and 2 compared to baseline (p < 0.05). Preoperative NLR ≥ 8 was significantly associated with higher mortality (65% vs. 50%, p < 0.01). Preoperative albumin > 3.2 g/dL was associated with better outcomes (recovery in 54 patients; 65.9%) compared to < 3.2 g/dL (15 patients; 75% mortality). This study showed that NLR and CAR are valuable predictors of postoperative outcomes, with CAR indicating the risk for surgical site infections (SSI) and NLR predicting mortality. Conclusion The preoperative NLR had a significant association with mortality among the patients. Hence the NLR can be a good marker for the worst outcome and CAR during the postoperative period can be considered as a marker to detect the risk of SSI. NLR and CAR are simple, inexpensive tests readily available from routine blood investigations. The utility of NLR and CAR as valuable prognostic markers in the perioperative assessment of patients undergoing emergency abdominal surgery could enhance the prediction of patient outcomes and guide more effective management strategies to improve patient outcomes in high-risk emergency abdominal surgery., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. BLDE (DU)'s Shri B M Patil Medical College, Hospital and Research Centre issued approval BLDE (DU)/IEC/668/2022-23. The Ethical Committee of this University met on Friday, 26th August 2022 at 3.30 p.m. in the Department of Pharmacology scrutinizes the Synopsis of Post Graduate Student of BLDE (DU)'s Shri B.M.Patil Medical College Hospital & Research Centre from ethical clearance point of view. After scrutiny, the following original/corrected and revised version synopsis of the thesis/ research projects has been accorded ethical clearance. Title: "The Role of the Neutrophil: Lymphocyte Ratio (NLR) and the C-Reactive Protein:Albumin Ratio (CAR) In Predicting Morbidity and Mortality Following Emergency Abdominal Surgeries". Name of the Student/Principal Investigator: Dr Shrihari V. Name of the Guide: Dr. Ramakanth Baloorkar. Professor, Dept. of Surgery. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Shrihari et al.)

Background: According to the renowned and Oscar award-winning American actor and film director Marlon Brando, "privacy is not something that I am merely entitled to, it is an absolute prerequisite." Privacy threats and data breaches occur daily, and countries are mitigating the consequences caused by privacy and data breaches. The Indian healthcare industry is one of the largest and rapidly developing industry. Overall, healthcare management is changing from disease-centric into patient-centric systems. Healthcare data analysis also plays a crucial role in healthcare management, and the privacy of patient records must receive equal attention. Purpose: This paper mainly presents the utility and privacy factors of the Indian healthcare data and discusses the utility aspect and privacy problems concerning Indian healthcare systems. It defines policies that reform Indian healthcare systems. The case study of the NITI Aayog report is presented to explain how reformation occurs in Indian healthcare systems. Findings: It is found that there have been numerous research studies conducted on Indian healthcare data across all dimensions; however, privacy problems in healthcare, specifically in India, are caused by prevalent complacency, culture, politics, budget limitations, large population, and existing infrastructures. This paper reviews the Indian healthcare system and the applications that drive it. Additionally, the paper also maps that how privacy issues are happening in every healthcare sector in India. Originality/Value: To understand these factors and gain insights, understanding Indian healthcare systems first is crucial. To the best of our knowledge, we found no recent papers that thoroughly reviewed the Indian healthcare system and its privacy issues. The paper is original in terms of its overview of the healthcare system and privacy issues. Social Implications: Privacy has been the most ignored part of the Indian healthcare system. With India being a country with a population of 130 billion, much healthcare data are generated every day. The chances of data breaches and other privacy violations on such sensitive data cannot be avoided as they cause severe concerns for individuals. This paper segregates the healthcare system's advances and lists the privacy that needs to be addressed first. [ABSTRACT FROM AUTHOR]

Background: According to the renowned and Oscar award-winning American actor and film director Marlon Brando, “privacy is not something that I am merely entitled to, it is an absolute prerequisite.” Privacy threats and data breaches occur daily, and countries are mitigating the consequences caused by privacy and data breaches. The Indian healthcare industry is one of the largest and rapidly developing industry. Overall, healthcare management is changing from disease-centric into patient-centric systems. Healthcare data analysis also plays a crucial role in healthcare management, and the privacy of patient records must receive equal attention. Purpose: This paper mainly presents the utility and privacy factors of the Indian healthcare data and discusses the utility aspect and privacy problems concerning Indian healthcare systems. It defines policies that reform Indian healthcare systems. The case study of the NITI Aayog report is presented to explain how reformation occurs in Indian healthcare systems. Findings: It is found that there have been numerous research studies conducted on Indian healthcare data across all dimensions; however, privacy problems in healthcare, specifically in India, are caused by prevalent complacency, culture, politics, budget limitations, large population, and existing infrastructures. This paper reviews the Indian healthcare system and the applications that drive it. Additionally, the paper also maps that how privacy issues are happening in every healthcare sector in India. Originality/Value: To understand these factors and gain insights, understanding Indian healthcare systems first is crucial. To the best of our knowledge, we found no recent papers that thoroughly reviewed the Indian healthcare system and its privacy issues. The paper is original in terms of its overview of the healthcare system and privacy issues. Social Implications: Privacy has been the most ignored part of the Indian healthcare system. With India being a country with a population of 130 billion, much healthcare data are generated every day. The chances of data breaches and other privacy violations on such sensitive data cannot be avoided as they cause severe concerns for individuals. This paper segregates the healthcare system’s advances and lists the privacy that needs to be addressed first.

The study discusses the need and importance of frugal innovation in Indian medical devices industry in the backdrop of present healthcare infrastructure and need to expand it beyond top 20 cities. Medical devices have a widespread role, but are usually underutilized due to many factors, most important being affordability and limited market penetration. In order to ensure their optimal utilization, they need to be tailored to the needs of Tier 2 cities and beyond, which present lucrative opportunity and high market potential. The study discusses various frugal innovations and their contribution in revolutionizing the Indian healthcare sector, but the need is to promote their accessibility, awareness and availability. It concludes by recommending few initiatives to bridge the massive healthcare gap by promoting widespread adoption and usage of frugally engineered medical devices. [ABSTRACT FROM AUTHOR]

The current Indian Healthcare system is in need of a radical reinvention. In India, increase in income levels, aging population, rising health awareness and changing attitude towards preventive healthcare is expected to boost healthcare services demand in future. The massive growth of the volume, velocity, and variety of digital health data creates both manageability issues and opportunities for greater patient insights. Finding a way to successfully manage Big Insights to eventually "predict, personalize, and prevent" could lead to early detection of potential problems, which means healthier people, as well as fewer complications and admissions. This paper provides an overview of Big Data, applicability of it in Healthcare system, opportunities that it hold to improve Indian healthcare, challenges in this journey, some of the work in progress and a future outlook on how Big Data Analytics can help lower healthcare costs in India while providing better health care access to the priceless human resources. [ABSTRACT FROM AUTHOR]

Indian healthcare is fast growing and with significant chunk of it being in small, fragmented, informal sector; Artificial Intelligence (AI) is pegged as a magical tool for a better healthcare system. There is an inclination to merely mimic the US approach in the on-going policy making and legislative exercises, which can have serious fallouts for Indian healthcare. India needs a different approach to suite her unique requirements. In this regard, each of the five stages in AI development lifecycle has been analyzed in the light of current on-ground realities. These boil down to three fold challenges of how to increase adoption of digital health, prevent data silos and create maximum value from data. Availability of quality data for value addition without barriers and restrictions is the common denominator for leveraging the full potential of AI. This requires liberal policies enabling secondary use of data in developing countries with rapidly growing healthcare sector akin to India. This has to be carefully balanced with data privacy and security. Restrictive healthcare data policies and laws can slow down adoption of digitization, perpetuate status-quo, be biased towards the incumbent players, cause Industry stagnation and thus will do more harm than good. It is therefore the data policies that will make or break AI in Indian healthcare. [ABSTRACT FROM AUTHOR]

Internet of things (IoT) plays a significant role in offering a wide range of benefits to the healthcare supply chain. It improves the quality of patient care, reduces the cost of medical procedures, maintaining flawless operations and supports clinical decisions. Despite strong policy interest and vast potential benefits of IoT in the healthcare supply chain, the actual adoption rate is relatively low and it's in the nascent stage in developing countries like India. The objective of this paper is to identify and analyze the potential barriers which would restrain the healthcare industry from adopting IoT. Based on the review of the literature and brainstorming with experts from industry and academia, 14 barriers were identified for IoT adoption. The contextual relationship between the identified barriers was developed using interpretive structural modeling and the obtained results were used as input to fuzzy MICMAC analysis to determine the driving and dependence power of the IoT adoption barriers. From the result, Legal and regulatory standards, Lack of IT Infrastructure are major barriers influencing the adoption of IoT in the healthcare supply chain. The findings will support the decision-makers to understand the contextual relationship between the IoT adoption barriers in the Indian healthcare supply chain., (© 2021 John Wiley & Sons Ltd.)