The 'Cost of Health Services in India (CHSI)' is the first large scale multi-site facility costing study to incorporate evidence from a national sample of both private and public sectors at different levels of the health system in India. This paper provides an overview of the extent of heterogeneity in costs caused by various supply-side factors.A total of 38 public (11 tertiary care and 27 secondary care) and 16 private hospitals were sampled from 11 states of India. From the sampled facilities, a total of 327 specialties were included, with 48, 79 and 200 specialties covered in tertiary, private and district hospitals respectively. A mixed methodology consisting of both bottom-up and top-down costing was used for data collection. Unit costs per service output were calculated at the cost centre level (outpatient, inpatient, operating theatre, and ICU) and compared across provider type and geographical location.The unadjusted cost per admission was highest for tertiary facilities (₹ 5690, 75 USD) followed by private facilities (₹ 4839, 64 USD) and district hospitals (₹ 3447, 45 USD). Differences in unit costs were found across types of providers, resulting from both variations in capacity utilisation, length of stay and the scale of activity. In addition, significant differences in costs were found associated with geographical location (city classification).The reliance on cost information from single sites or small samples ignores the issue of heterogeneity driven by both demand and supply-side factors. The CHSI cost data set provides a unique insight into cost variability across different types of providers in India. The present analysis shows that both geographical location and the scale of activity are important determinants for deriving the cost of a health service and should be accounted for in healthcare decision making from budgeting to economic evaluation and price-setting.
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http://dx.doi.org/10.1186/s12913-022-08707-7 | DOI Listing |
Sci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
View Article and Find Full Text PDFBMJ Open Qual
January 2025
Professor Department of Obstetrics and Gynaecology, Lady Hardinge Medical College, New Delhi, India.
Background: Allowing a birth companion is the basic right of a mother and is identified as an important component of respectful maternity care. The implementation of this intervention has been a challenge in heavy-load public health facilities in India.
Local Problem: Despite the proven benefits of the presence of birth companions on maternal-fetal outcomes, there was no policy of allowing birth companions in our hospital.
Pediatr Nephrol
January 2025
Pediatric Nephrology Services, Department of Pediatrics, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, 605006, India.
Background: Limited research exists regarding the genetic profile, clinical characteristics, and outcomes of refractory rickets in children from India.
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Int J Cancer
January 2025
Inequalities in Cancer Outcomes Network (ICON) group, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK.
We aimed to investigate socio-economic inequalities in second primary cancer (SPC) incidence among breast cancer survivors. Using Data from cancer registries in England, we included all women diagnosed with a first primary breast cancer (PBC) between 2000 and 2018 and aged between 18 and 99 years and followed them up from 6 months after the PBC diagnosis until a SPC event, death, or right censoring, whichever came first. We used flexible parametric survival models adjusting for age and year of PBC diagnosis, ethnicity, PBC tumour stage, comorbidity, and PBC treatments to model the cause-specific hazards of SPC incidence and death according to income deprivation, and then estimated standardised cumulative incidences of SPC by deprivation, taking death as the competing event.
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