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Correspondence

Indian Pediatr 2019;56: 334

An Indian Tool for Assessing Appropriateness of Pediatric Hospitalization: Author's Reply

 

Narendra Kumar Arora

The INCLEN Trust International, Okhla Industrial Area, New Delhi, India.
Email:
nkarora@inclentrust.org

 


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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