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Indian Pediatr 2019;56: 334 |
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An Indian Tool for Assessing Appropriateness of Pediatric
Hospitalization: Author's Reply
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Narendra Kumar Arora
The INCLEN Trust International, Okhla Industrial Area,
New Delhi, India.
Email:
nkarora@inclentrust.org
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We thank the expert for the critical clarifications. We submit the
following responses to the clarifications sought:
• The semi-Delphi method was adapted for the
appropriateness tool development/adaptation for Indian context. Thus
the objective was to develop the PAEP India tools for Indian context
with adaption and reference to the guidelines/protocols in practice.
• All the raters underwent an orientation session
to have common understanding using the PAEP reviewers’ manual. The
PAEP reviewers’ manual guides how to use the PAEP tools, and can be
made available on request.
• These 274 cases from medical colleges were
selected from the total admissions during July-Sep 2015 according to
age strata: newborns/£28
days; >28 days-12 months, 13-59 months, and >5-18 years (the number
breakup under each age band has been specified in the Results
section). These cases were randomly selected by the medical records
section from the admissions in these age strata under Neonatology,
Pediatric medicine and Pediatric surgery departments. The
investigators from the medical colleges had no influence on
selection of the cases.
• We expected that the admissions to medical
college affiliated hospitals were mostly appropriate (as observed
97.8% admissions categorized as appropriate). The study did not
examine the appropriateness proportion and variations according to
either seasonality, department or other determinants from these
medical colleges.
• The sample from Northern India was drawn for
validation of the tool. Thus an age band representative sample was
strategically selected for application.
The cases from Southern India were a dataset
available for application of the PAEP tool to document its performance.
These cases were part of a cohort (n=30688) to document the
hospitalizations during first year of life. In this cohort, all
hospitalizations were captured through weekly follow-up of the recruited
cases. All the hospitalizations for any period and to any level of
hospital (level 1, 2 or 3 and private or public) were captured. Out of
these cases, the breakup of admissions to hospitals at different levels
were: 7 cases to Level 1, 304 cases to Level 2 and 311 cases to Level 3
hospitals. While 409 cases were admitted to private hospitals, 213 cased
were admitted to public hospitals.
Regarding the performance of the PAEP tool in
different state and regional contexts, we have recommended its use in
diverse settings across India for performance assessment and
triangulation.
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