Structural quality of healthcare facilities in India

Armenta, Bianca; Rathi, Naveen; Assasnik, Nushean; Kamimura, Akiko

doi:10.1108/ijhcqa-11-2016-0179

Cited by 5 publications

(6 citation statements)

References 15 publications

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“…There are some empirical studies which have identified causes for low access to healthcare and poor quality of healthcare services in Uttar Pradesh. It was found that poor quality of care is one of the reasons for insufficient healthcare facilities (Prinja, et al, 2012) and poor structural quality of hospitals and healthcare centres in the state (Armentha, et al, 2018). Narang (2010) used an adopted scale for measuring quality of healthcare services in Uttar Pradesh and found that availability of both medical equipment and doctors for women were negatively associated with the quality of healthcare facilities in the state.…”

Section: Review Of Literaturementioning

confidence: 99%

Regional disparities in healthcare services in Uttar Pradesh, India: a principal component analysis

Kumari

Raman

2021

GeoJournal

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This study investigates disparities in healthcare services in the districts of Uttar Pradesh, the most populous and one of the poorest states of India in the health sector. To measure the disparities in healthcare services, a composite index has been computed using Principal Component Analysis in three domains namely, health availability, health amenities and health affordability and 12 representative indicators. On the basis of the results, districts have been clubbed into five categories, such as high, high-medium, medium, medium-low and low according to their composite scores. The study also uses k-means cluster analysis to find out the set of districts which are similar within the group, but they are different between the groups. Key results indicate that the districts of the western region are more developed in comparison to the districts of the eastern region in terms of three indices such as availability, amenities, affordability of healthcare services and overall composite health index. Also, k-means cluster analysis shows that there are many districts which are identical in many respects; however, they are located in different regions of the state. This study may be helpful to understand the poor availability and affordability of healthcare services in the districts of Uttar Pradesh, which should be improved to meet the objectives of the basic-needs approach and the millennium development goals.

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Section: Review Of Literaturementioning

confidence: 99%

Regional disparities in healthcare services in Uttar Pradesh, India: a principal component analysis

Kumari

Raman

2021

GeoJournal

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“…A tool was developed, taking into consideration the quality parameters of healthcare settings in the Indian context, and with reference to the available literature (Kwan et al, 2019;Aggarwal et al, 2019;Armenta et al, 2018;Panda and Kondasani, 2017;Kanwar et al, 2016). While developing the tool, the authors also referred to survey manuals regarded as the common standards on quality and safety management in Besides, 30 binary response items (Yes/No) were incorporated into the questionnaire to measure the employees' perception of the processes and outcomes of their respective hospitals.…”

Section: Instrumentmentioning

confidence: 99%

A tool to assess the quality perception of healthcare employees

Kamalasanan

Sathiyamurthi

Subbarayalu

2020

IJHCQA

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PurposeThe purpose of this project was to determine the validity and reliability of the Healthcare Quality Perception (HQP) questionnaire tool designed to capture employees' perceptions of healthcare quality in Indian hospitals.Design/methodology/approachTwo hundred employees in private and public sector hospitals in India were randomly selected and given the HQP tool. It consisted of 38 Likert-scale items and six different subscales: (1) Planning and Documentation (n = 7); (2) Employee Participation in Quality Management Activities (n = 5); (3) Existence of Policies/Procedures/Guidelines (n = 5); (4) Quality and Patient Safety Management (n = 9); (5) Perceived Effect of Quality Improvement (n = 7) and (6) Training and Development Opportunities (n = 5). 156 completed questionnaires were received, demonstrating a 78% response rate. HQP tool subjected to statistical analysis to measure its reliability and validity. A p-value of less than 0.05 was considered as “significant.”FindingsFactor analysis pulled out six factors that conjointly demonstrated 66.4 % of the variance in healthcare professionals' (HCPs') perception of healthcare service quality in selected Indian hospitals. The overall Cronbach's alpha coefficient was measured at 0.959 for internal consistency reliability. This study demonstrates that the identified six critical factors are important determinants influencing HCPs' perception of the quality of healthcare services in private and public sector hospitals in India.Originality/valueThis study provides evidence for the reliability and validity of the newly developed HCP Scale for the assessment of employee perception of the quality of services offered in selected hospitals in India, with potential applications in other contexts.

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“…The World Health Organization, 1946, affirmed that “the highest attainable standard of health is a fundamental right of every human being” (Nicholson et al, 2016 ). Understanding health as a fundamental human right formulates a legal obligation on the respective governments to provide their citizens with accessible, available, and affordable quality healthcare (Armenta et al, 2018 ). The Study by Youkta et al ( 2022 ) reveals that out-of-pocket expenditure by households in India accounts for 60.6% of total health expenditures and 2.3% of the country’s GDP, indicating poor misallocation of funds.…”

Section: Introductionmentioning

confidence: 99%

An inter-district analysis of health infrastructure disparities in the Union Territory of Jammu and Kashmir

2023

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Achieving socioeconomic growth can be done by enhancing national health. The availability and provision of health infrastructure in an administrative territory affect the health of ordinary people. People's access to healthcare is inversely correlated with the availability of a region's health infrastructure. This study investigates inter-district health infrastructure disparities in the newly created Union Territory (UT) of Jammu and Kashmir. Using principal component analysis, this study developed a district-level health infrastructure index (HII) for 2018–2019. The study demonstrates the existence of inter-district disparities in the Union Territory's health infrastructure. Regarding health infrastructure, Doda has the highest HII and has been designated a 'developed' district. Doda is followed by Jammu, Kishtwar, Udhampur, Ramban, Samba, Reasi and Kulgam, which also fall into the ‘developed’ districts category. Backward districts include Kathua, Rajouri, Poonch, Budgam, Shopian, Kupwara, Ganderbal, Baramulla, Bandipora, and Anantnag. Srinagar district, with the lowest HII, was identified as the most backward district in the Jammu and Kashmir UT. All of the districts of the Kashmir division, apart from Kulgam, are classified as being ‘backward’ or ‘very backward’. Therefore, it is evident that the Jammu division of UT has a better health infrastructure than the Kashmir division.

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Structural quality of healthcare facilities in India

Cited by 5 publications

References 15 publications

Regional disparities in healthcare services in Uttar Pradesh, India: a principal component analysis

Regional disparities in healthcare services in Uttar Pradesh, India: a principal component analysis

A tool to assess the quality perception of healthcare employees

An inter-district analysis of health infrastructure disparities in the Union Territory of Jammu and Kashmir

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