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The Abdur Razzaque Ansari Memorial Weavers Hospital (ARAM) came into effect on 7 April 1996, and is dedicated to the people of Jharkhand and weavers. To deal with the issues of inequity in healthcare services, ARAM was founded for the extension of affordable healthcare services to the needy in and around the area of Jharkhand. Visualised by a great social worker and legend Abdur Razzaque Ansari, it has been successfully run by his eldest son Mr Sayeed Ahmad Ansari for 28 years. This research uses mainly a case-study approach through secondary data from the hospital website and other websites citing ARAM and its functions. Consent to use data for the study was obtained from Mr. Sayeed Ahmad Ansari. Primary information was collected through the patients who availed facilities from the hospital. They were interviewed through a semi-structured questionnaire each taking 30-40 minutes. Taken over by Medanta Group on 8 July 2015 (earlier being managed by Apollo Hospitals Group for 20 years), it is the first super speciality community hospital in Eastern India. Treating over 50,000 patients yearly with state-of-the-art medical equipment and providing discounts to lower-income groups, people from the weaver’s community, freedom fighters and members of ICSI have intrigued people from these sections for affordable treatment and facilities in and near Jharkhand. With a 200 bed-capacity, nine different disciplines and 12 departments spread across the city of Ranchi, the hospital caters to a massive population at a much-subsidised rate. Reaching out to rural villages through free medical camps and awareness campaigns, the hospital showcases how a successful model of healthcare cooperative can be replicated accordingly in similar developing and underdeveloped regions.

Medication management is a complex process, at high risk of error with life threatening consequences. The focus should be on devising strategies to avoid errors and make the process self-reliable by ensuring prevention of errors and/or error detection at subsequent stages. The purpose of this paper is to use failure mode effect analysis (FMEA), a systematic proactive tool, to identify the likelihood and the causes for the process to fail at various steps and prioritise them to devise risk reduction strategies to improve patient safety.

The study was designed as an observational analytical study of medication management process in the inpatient area of a multi-speciality hospital in Gurgaon, Haryana, India. A team was made to study the complex process of medication management in the hospital. FMEA tool was used. Corrective actions were developed based on the prioritised failure modes which were implemented and monitored.

The percentage distribution of medication errors as per the observation made by the team was found to be maximum of transcription errors (37 per cent) followed by administration errors (29 per cent) indicating the need to identify the causes and effects of their occurrence. In all, 11 failure modes were identified out of which major five were prioritised based on the risk priority number (RPN). The process was repeated after corrective actions were taken which resulted in about 40 per cent (average) and around 60 per cent reduction in the RPN of prioritised failure modes.

FMEA is a time consuming process and requires a multidisciplinary team which has good understanding of the process being analysed. FMEA only helps in identifying the possibilities of a process to fail, it does not eliminate them, additional efforts are required to develop action plans and implement them. Frank discussion and agreement among the team members is required not only for successfully conducing FMEA but also for implementing the corrective actions.

FMEA is an effective proactive risk-assessment tool and is a continuous process which can be continued in phases. The corrective actions taken resulted in reduction in RPN, subjected to further evaluation and usage by others depending on the facility type.

The application of the tool helped the hospital in identifying failures in medication management process, thereby prioritising and correcting them leading to improvement.

The purpose of this paper is to examine healthcare organizations for the improvements in their existing services (incremental innovation) as well as for the new service developments (radical innovation) initiated through the utilization of resources and co-producing behavior.

The paper uses an SEM approach to analyze the responses obtained from 257 medical administrators of 50 hospitals registered with National Accreditation Board for Hospitals and Healthcare Providers.

The results reflect a positive and significant impact that is more driven by internal resources and is found to be stronger for incremental innovation in healthcare. The study also posits that resource utilization in conjunction with co-production activities has greater potential to bring innovation that is likely to succeed and stay inimitable.

The paper outlines scope for future research and suggests inclusion of other service sectors, geographical locations and performance indicators to attain a better understanding of the constructs examined.

The paper outlines implications for policy makers concerned with healthcare. Providers of health services ought to develop a proactive customer-oriented approach so as to deliver value through service innovations. Integrating customer co-production processes may further augment the overall quality of care.

Empirical studies integrating the resource-oriented view of innovation along with firms’ co-production and collaborative mechanisms are majorly lacking. The study bridges this gap and suggests ways to bring innovation in health services, a pivotal need for health institutions of an emerging economy like India.

The Healthcare sector is one of the important sectors of the Service Industry. It is believed that in this sector, the customer server relationship is very critical, and even the slightest gap in the people quality may have a huge impact on the delivered service quality. Some of these enablers are doctors, nursing staff and support staff. Furthermore, the nonpeople quality enablers such as diagnostic services, facilities, hygiene levels and so on are also likely to impact the delivered service quality. It was also felt that the degree of impact each enabler has on the service quality could vary. Therefore there is a need for structured and deep analysis. The paper attempts to identify, analyze and prioritize the enablers that impact the delivered service quality.

The enablers have been identified through literature review and inputs from experts in the healthcare fraternity. The authors have explored different decision-making tools such as analytic hierarchy process (AHP), analytic network process (ANP), stepwise weight assessment ratio analysis, Hybrid Model and DEMATEL (Decision-Making Trial and Evaluation Laboratory) for the analysis of data in this paper. Based on the strengths of the approach and careful considerations by focus group discussions, DEMATEL was chosen as the best option. It is simple, unique, sparingly used in the healthcare sector, effective in prioritizing and gives meaningful insights on importance, cause and effect factors. DEMATEL approach converts the complex problem with interrelated factors into a clear structure that makes simple interrelationships among factors in the form of cause and effects digraph, and hence, the authors chose to use it. A case study in one of the hospitals has also been conducted to demonstrate the applicability of the developed index. The case study very strongly validates the developed index.

This research paper has found that there are people quality enablers such as the doctor, nursing staff, support staff and nonpeople quality enablers such as facilities, diagnostic services and hygiene levels maintenance, which impact the delivered service quality. It also concludes that the delivered service quality depends not only on the quality but also on the availability of these enablers. The inputs received from the experts have been run through the DEMATEL methodology and importance computed for each. The top five priority enablers are Quality of Doctor, Availability of Doctor, Quality of Support Staff, Quality of Nursing Staff and Availability of Support Staff.

The weights of the enablers have been obtained using the DEMATEL tool. These weights have been calculated using the inputs from 22 experts, which meets the statistical requirement (Skulmoski, 2007). However, a larger group of experts can be reached, and based on the inputs received from them, the tool can be revalidated for repeatability and reproducibility. Using Fuzzy DEMATEL can also be explored for further analysis.

The proposed framework to assess the service quality level of a healthcare organization is based on a sound approach of DEMATEL. The service index arrived, thereafter, can be used to rate the delivered service quality by any healthcare organization. It can be used to compare the similar type of healthcare organizations across locations. This Index can facilitate improvements in the healthcare organization through internal and external benchmarking. It also helps the organization to know the gaps, understand the root cause, improve upon them and become the best in class. This Index uses the inputs from the end customers to calculate the rating, which makes it more reliable and accurate. The overall scores obtained from the Index can provide the ranking to the healthcare providing organizations and options to customers to choose from best. The service quality index can be used by an organization to continuously monitor their delivered service quality scores and improve them to become the best in class. The research paper highlights the significant role played by the people quality and its strong impact/contribution on the delivered service quality. Hence, it is believed that it will encourage the healthcare organizations to prioritize the improvement and upgrade of the people quality over the nonpeople quality aspect.

Putting people and nonpeople quality enablers in one single model and assigning weights to them using the DEMATEL approach is a new application in healthcare. Developing an Index to measure the delivered service quality in the healthcare sector is also different and new.

Need for preventive health care: To comprehend the contribution of preventive health care in improving the health quotient. Sri Sathya Sai Sanjeevani Hospital (SSSSH) and its initiative is an apt example of the wonder which preventive care can bring in the context of rural health. Community participation: The case can be instrumental in showing the pathway to encourage community involvement in mainstream health by promoting the holistic model of SSSSH that understands mothers and children's health profile and needs, especially in the unreached rural segments of an emerging economy like India. Importance of healthy childhood: World Health Organization (WHO) promotes the school health programme to prevent health risks among children by inculcating healthy behaviours during childhood. The successful SSSSH model proves that it is implementable by integrating comprehensive health education modules in the existing institutions for medical care.

The challenge of a healthy childhood is inadequate availability and accessibility of quality care. Non-awareness of the parents is also a significant reason for the children who miss the benefit of a happy childhood. While much is planned by the Government and some part of it being executed, this case highlights the effectiveness of the maternal and child health programme executed by the Sri Sathya Sai Sanjeevani Hospital (SSSSH). This initiative fulfills the dire need of ensuring the preventive healthcare component leading to safe motherhood and safe birth of healthy children. Further, the case is also the culmination of pin-pointed innovative awareness activities such as school health screening and the Divine Mother and Child Health Program (DMCHP). It opens up the discussion on the current model of health care followed by SSSSH, Raipur, and its impact in the local areas to decide on its expansion across the country for nationwide implementation.

Bachelors in Business Administration, MBA, Executive MBA, Post Graduate Diploma in Healthcare Management

Teaching notes are available for educators only.

CSS 2: Built Environment.

The purpose of this paper is to examine the effect of patient participation on patient satisfaction and the subsequent effect on patient behavior outcomes

The research employs self-administered survey method to test hypotheses. The convenience sampling approach is used to collected data from 410 patients in metropolitan cities of India. The data are analyzed using SmartPLS to test the proposed model.

The results shows patient participation is positively related to behaviour outcomes and patient confidence and satisfaction mediate the effect of patient participation on adherence.

The study was limited to a small sample which may somewhat limit generalization of the findings. However, the findings, based on primary data, are insightful. Second, the current study was cross-sectional in nature, whereas a longitudinal study could had measured changes in perceptions over an extended time period.

The results provide interesting insights about the significance of patient participation in positive behavior outcome. These insights will enable health care professionals and government to formulate a suitable policy through which to encourage patient participation in health treatment regimes.

The paper demonstrates the influence of patient participation on behavior. There has been little research on this aspect in the Indian context to date, so this study offers an important guideline to the health care industry in relation to introducing customer empowerment into health care regimes.

This paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise.

It is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers.

The developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information.

The architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.