Project description:In the recent years, the burgeoning non-performing assets (NPAs) have become a matter of concern and scrutiny in India as the surge in NPAs impinge on the credit services of the banks, make the banks vulnerable to external shocks, leave them with less cushion in case of idiosyncratic shocks and thus, leading to the abrasion of their productive capital. In this backdrop, some very normative questions become inevitable. How has the technical efficiency of the banks in India changed over time especially after the asset quality review, 2016? How does undesirable output like non-performing assets (NPA) impact the technical efficiency of banks in India? Does technical efficiency have anything to do with the ownership of banks? These are some of the questions we endeavour to answer through our study by employing three cornerstone methodologies namely DEA, Malmquist productivity index and SFA in the banking sector for the period 2014-2020.The results obtained from employing DEA and SFA both points toward the heterogeneity in the technical efficiency of public sector banks and private sectors banks operating in India. The results obtained from DEA are majorly three-fold. Firstly, private sector banks have fared better than the public sector banks, while the SFA scores show that the public sector ownership promotes efficiency. Secondly, the technical efficiency of public sector banks has consistently been falling from 2014 to 2017 only to rise in the later years, evidence corroborated by the SFA scores also. This trend is in line with the slew of measures adopted by the government and RBI like AQR and mergers of banks subsequently. Although according to the Malmquist productivity decomposition results, we find that productivity of banks have been falling for the period 2014-2020. Thirdly, the non-performing assets are detrimental for the efficiency of the banks. Like DEA, the SFA results also shows the presence of technical inefficiency in the Indian banking sector and a similar trend in the technical efficiency wherein the scores decline from 2014 through 2017 and then they rise subsequently.Supplementary informationThe online version contains supplementary material available at 10.1007/s40953-021-00247-x.

Project description:The two primary objectives of this paper are: (a) to demonstrate how Comma, a business modeling methodology based on commitments, can be applied in healthcare process modeling, and (b) to evaluate the effectiveness of such an approach in producing healthcare process models. We apply the Comma approach on a breast cancer diagnosis process adapted from an HHS committee report, and presents the results of an empirical study that compares Comma with a traditional approach based on the HL7 Messaging Standard (Traditional-HL7). Our empirical study involved 47 subjects, and two phases. In the first phase, we partitioned the subjects into two approximately equal groups. We gave each group the same requirements based on a process scenario for breast cancer diagnosis. Members of one group first applied Traditional-HL7 and then Comma whereas members of the second group first applied Comma and then Traditional-HL7-each on the above-mentioned requirements. Thus, each subject produced two models, each model being a set of UML Sequence Diagrams. In the second phase, we repartitioned the subjects into two groups with approximately equal distributions from both original groups. We developed exemplar Traditional-HL7 and Comma models; we gave one repartitioned group our Traditional-HL7 model and the other repartitioned group our Comma model. We provided the same changed set of requirements to all subjects and asked them to modify the provided exemplar model to satisfy the new requirements. We assessed solutions produced by subjects in both phases with respect to measures of flexibility, time, difficulty, objective quality, and subjective quality. Our study found that Comma is superior to Traditional-HL7 in flexibility and objective quality as validated via Student's t-test to the 10% level of significance. Comma is a promising new approach for modeling healthcare processes. Further gains could be made through improved tooling and enhanced training of modeling personnel.

Project description:In this work, we examined healthcare seeking behavior (HSB) of patients visiting public healthcare facilities in an urban context. We conducted a cross-sectional survey across twenty-two primary and secondary public healthcare facilities in the South-west Delhi district in India. The quantitative survey was designed to ascertain from patients at these facilities their HSB-i.e., on what basis patients decide the type of healthcare facility to visit, or which type of medical practitioner to consult. Based on responses from four hundred and forty-nine participants, we observed that factors such as wait time, prior experience with care providers, distance from the facility, and also socioeconomic and demographic factors such as annual income, educational qualification, and gender significantly influenced preferences of patients in choosing healthcare facilities. We used binomial and multinomial logistic regression to determine associations between HSB and socioeconomic and demographic attributes of patients at a 0.05 level of significance. Our statistical analyses revealed that patients in the lower income group preferred to seek treatment from public healthcare facilities (OR = 3.51, 95% CI = (1.65, 7.46)) irrespective of the perceived severity of their illness, while patients in the higher income group favored directly consulting specialized doctors (OR = 2.71, 95% CI = (1.34, 5.51)). Other factors such as having more than two children increased the probability of seeking care from public facilities. This work contributes to the literature by: (a) providing quantitative evidence regarding overall patient HSB, especially at primary and secondary public healthcare facilities, regardless of their presenting illness, (b) eliciting information regarding the pathways followed by patients visiting these facilities while seeking care, and (c) providing operational information regarding the surveyed facilities to facilitate characterizing their utilization. This work can inform policy designed to improve the utilization and quality of care at public primary and secondary healthcare facilities in India.

Project description:BackgroundImproving geographic access can aid in managing tuberculosis (TB) by enabling early diagnosis and treatment initiation. Although geospatial techniques have been used to map the transmission patterns of drug-resistant TB in South Africa, fewer studies have investigated the accessibility of TB diagnostic services. This study evaluated the accessibility of TB diagnostic services and disease distribution in the eThekwini district of South Africa.MethodsIn this cross-sectional study, population data for 2021 were disaggregated into smaller analysis units and then re-aggregated through the dasymetric mapping technique. Data on notified TB patients, including Global Positioning System coordinates of clinics, were obtained from the District of Health Information System, exported to ArcGIS 10.8.2 and used to calculate distances to the nearest clinics and hospitals.Results92% of the population (3 730 494 people) in eThekwini could access TB diagnostic services within 5 km. Patients travelled an average distance of 4.7 km (range: 0.1-26.9 km). TB diagnostic services were highly accessible in the Northern and Central regions and moderately accessible in the predominately rural Western and Southern regions. The smallest population of eThekwini resides in rural areas; however, 40.7% of its residents live >5 km from a diagnosing facility, with patients in the South having to travel up to 44.5 km. TB incidence was higher in the predominately rural West and South regions compared with the Central and North regions which are mainly comprised of urban and suburban areas. Our findings also showed that 98.4% of the clinics in eThekwini were located within 30 km of a hospital at an average distance of 9.6 km within the district. However, the distribution of these hospitals does not demonstrate equitable access as the majority are located within the Central region, and fewer are found in the other three regions of eThekwini.ConclusionsAddressing the disparities in access to TB diagnostic services is required in the eThekwini district. Leveraging the existing mobile health clinics can assist with this, particularly, in rural areas with inadequate access. Additionally, active-case finding should be intensified in these regions since they had a higher TB burden per population. Prioritising interventions in these areas is crucial for reducing the impact of the disease on affected communities.

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Modelling efficiency in primary healthcare using the DEA methodology: an empirical analysis in a healthcare district

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