Impact of Pandemic on Women Health Indicators in a Tertiary Health Centre of Bihar

BACKGROUND This study was conducted to analyse the impact of pandemic on healthcare, evaluate the negative psychological behaviour towards health professionals and study the effect of Covid-19 infection on hospital avoiding attitude of female patients. METHODS This was a case-control study conducted in Department of Obstetrics and Gynaecology at Patna Medical College and Hospital, Patna, Bihar. Study period was from 01st April 2020 to 30th September 2020. All the patients except Covid-19 positive cases, coming to Gynaecology Outpatient Department (GOPD), antenatal care (ANC) and labour room emergency (LRE) were included in the study. Patients who were seen from April 2019 to September 2019, total of 20,961 were in ‟pre Covid-19ˮ control group, while patients seen from April 2020 to September 2020, a total of 8,859 were in ‟during Covid-19” case group. Records of all health parameters for patients were reviewed, and then divided into two groups as patient input indicators and healthcare efficiency indicators. Number of patients visiting GOPD, ANC and admitted in LRE comprised patient input indicators (implying hospital avoiding attitude) while delivery rate, dilation and evacuation (D & E) rate, stillbirth rate and mortality rate comprised healthcare efficiency indicators. RESULTS Overall patients visiting the hospital dropped down from 21,361 to 8859 (by 58.5 %); GOPD patients reduced by 74 % while total ANC patients reduced by 44 %; and total LRE admissions reduced by 35.3 %. CONCLUSIONS Despite increased health professionals (workdays) per patient in LRE, mortality rate and still birth rate increased by 60.2 % and 23 % respectively indicating worsening of efficiency which is direct hidden negative psychological impact of pandemic immediately calling for the need of positive counselling and proper psychiatric care of both the health professionals and patients. KEY WORDS Covid-19, Pandemic, Still Birth Rate

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Purpose-With increased demand and restricted healthcare resources, it becomes important to take a step back and evaluate the efficiency of healthcare delivery. The present study aims to evaluate the health system efficiency of India by benchmarking it against its peers in BRICS countries and against OECD countries. Design/Methodology/Approach: The input and output variables required for measuring the efficiency of healthcare system were identified. A Data Envelopment Analysis (DEA) approach was used and efficiency frontier identified with the rankings of the BRICS and OECD countries. India is thus benchmarked against its peers (BRICS) and against OECD countries. Finding: India was found to operate at the efficiency frontier along with China, Russia, Brazil, and South Africa, however it ranked fourth. When benchmarked against OECD countries, India operates on the efficiency frontier along with Canada, Greece, Japan, Korea, Mexico, Spain, Sweden, Switzerland, Turkey, Great Britain, Chile and Israel. Countries like Germany, United States of America, Czech Republic, Slovakia and Lithuania operate at a lower healthcare efficiency and need to use their resources wisely. Practical/Research Implications: Developing countries like India can look to improve its healthcare system delivery by replicating best practices of healthcare systems from its peers and the top 10 OECD countries. Majority of the OECD countries in the top 10 have implemented universal health coverage, have higher physician and nurse density and higher hospital bed ratios. They are inclined towards branded drugs vis-à-vis generics and have follow evidence based medicine. From a theoretical perspective, it adds to the body of literature of DEA and health system efficiency. Originality/Value: This is a pioneer study that benchmarks India against its peers and against OECD countries drawing unique insights about healthcare efficiency

Spatial Solution to Measure Regional Efficiency — Introducing Spatial Data Envelopment Analysis

When investigating healthcare efficiency at the regional level, the problem of interactions between neighbouring locations arises. The health of the population in a given region is related to the healthcare in other areas through a medical tourism, a limited number of highly specialised institutions, competition between institutions, etc. Ignoring these inter-regional links may result in a systematic bias in the efficiency analysis. Similar issues may hinder any regional studies. Hence, the main purpose of this paper is to introduce a new approach to measuring efficiency in regional studies through spatial data envelopment analysis (SDEA). The paper offers a proper mathematical formulation of the new methodology and highlights differences between classic data envelopment analysis (DEA) and the newly developed method. The motivation for seeking a new solution to the problem of spatially adequate assessment of regional efficiency is derived from the literature review and a discussion of the presented theoretical examples. The classic DEA allows for multidimensional analysis of the performance of homogenous independent decision-making units. However, in regional studies, an area where DEA has gained popularity, the assumption of the isolation of decision-making units seems to be unfounded. In the SDEA approach, the region-specific spatial context is incorporated into the analysis via the W matrix and spatial interactions are reflected in the model through spatially weighted inputs and outputs. Therefore, in our paper, we verify the hypothesis that spatial interactions are an indispensable factor of regional efficiency analysis. A study of healthcare efficiency in European regions is presented as an illustration of the utility of the new methodology. Furthermore, we compare the results of the classic DEA approach with those of the SDEA, which is augmented with the spatial equivalents of inputs and outputs. Our results suggest that classic DEA undervalues regional healthcare efficiency by underestimating the region-specific spatial context.2 Researchers may find the introduced SDEA method useful in all space related fields when investigated phenomenon exhibits spatial autocorrelation. In particular, the new approach may deepen the regional efficiency analysis of innovation, development, logistics, tourism, etc.

Defining Smart Community in the Context of Healthcare Efficiency in the UK

This literature review article creates a new definition for the concept of smart community and applies the concept to the issue of improving healthcare efficiency in the UK. The definition emerges by mapping the evolution of the smart community concept from the mid-1990s up to 2020. The emergent concept is then applied to healthcare efficiency through discussion about related concepts including smart cities, coproduction, social capital, social computing, and cyber physical systems. The review takes a qualitative approach to exploring literature about concepts, an approach that recognises and engages with the complex interconnectedness of terminology in the digital sphere. Smart community was selected because it originated in response to financial crisis. The relevance to theory is creating a context-specific definition of smart community. By defining smart community in the context of healthcare, insights have emerged that could be useful to practice as well as theory.