DOI: 10.5061/dryad.3tx95x6nk
title: What drives poor quality of care for child diarrhea? Experimental evidence from India

description: Most healthcare providers in developing countries know that oral
 rehydration salts (ORS) is a lifesaving treatment for child diarrhea, yet
 few prescribe it. This know-do gap has puzzled experts for decades and has
 cost millions of lives. Using several randomized controlled trials among
 private providers in 253 towns in India, we estimated the extent to which
 ORS under-prescription is driven by financial incentives to sell more
 lucrative medicines, stock-outs of ORS, and provider perceptions that
 patients do not want ORS. We found that patients expressing a preference
 for ORS increased ORS prescribing by 27 percentage points. Eliminating
 stock-outs increased ORS provision by 6.8 percentage points. Eliminating
 financial incentives to sell medicines had no effect on average but
 increased ORS prescribing at pharmacies by 9 percentage points. Our
 findings, combined with patient exit surveys suggest that provider
 perceptions that patients do not want ORS explain 42% of
 under-prescribing, while stock-outs and financial incentives explain only
 6% and 5% respectively.
description: This data set includes data that was collected using provider
 surveys (recorded in Survey CTO), from standardized patient visits, and
 from caretaker surveys. The order of operations was:  
 Providers and caretakers were surveyed at the beginning of the
 study Standardized patients anonymously visited
 providers and completed a debrief survey directly after the
 visit A few hours after the standardized patient, the
 team visited the provider again to record information on medicine
 inventory
description: # What drives poor quality of care for child diarrhea? Experimental
 evidence from India These
 data were used for the paper "What drives poor quality of care for
 child diarrhea? Experimental evidence from India" by Wagner, Mohanan,
 Zutshi, Mukherji, and Sood. The data were collected in Bihar and
 Karnataka, India in 2022. ## Description of the data and file structure
 There are three different data sets included all in Stata (.dta) format:
 **1. ORS HH Main_noDCE:** This is a survey of caretakers who had a child
 10-years-old or younger with a case of diarrhea within 4 weeks prior to
 the survey. The key them of the survey is treatment seeking, what happened
 when they sought treatment, and what they did to treat their child's
 diarrhea. It also includes perceptions of and preferences for different
 child diarrhea treatments. This can be geo-linked to the other data sets
 via a town code but caretakers were not surveyed in every town for which
 the other surveys were conducted. **2. Provider Survey_noVig:** This is a
 baseline provider survey that records information on provider
 characteristics and how providers treat child diarrhea. This survey was
 completed 2-3 weeks before the standardized **3. SP_Debrief_Provider:**
 This is a standardized patient debrief survey that was completed within an
 hour of standardized patient visits that were presenting as fathers whose
 child had a case of diarrhea. This survey recorded information on what
 providers did during the standardized patient visits. Variables b57 to b66
 are from a provider follow-up visit that occured after but on the same day
 as the standardized patients visit. This data set also includes all of the
 variables from the provider survey (merged in from Provider Survey_noVig)
 which label variables names starting with "ps_". The provider
 survey and standardized patient debrief can be linked with the variable
 capi_id. These data were collected as part of a randomized controlled
 trial and provided free oral rehydration salts (ORS) for providers and
 varied the preferences of the standardized patients. The variable
 "treatment" indicates whether the provider was assigned free ORS
 and the variable sp_type_code indicates which SP role the provider
 received. All surveys used to create these data sets are including in this
 repository which can function as a codebook. Some of the variables from
 the surveys are missing from the publicly available data sets because of
 Dryad's de-identification criteria. ## Code/Software This repository
 includes the replication code for "What drives poor quality of care
 for child diarrhea? Experimental evidence from India" by Wagner,
 Mohanan, Zutshi, Mukherji, and Sood. Each Stata do file is labeled
 according to the table or figure from the paper that it produces.
 Regressions from Table 2 and S11 that included covariates are
 "commented out" from the code because Dryad's
 de-identification criteria restricted us from including them. The code for
 summary Tables S1, S2, S3, S6, S7, S22, and S23 also will not run because
 of missing variables.