Religious Discrimination in Health: Evidence from an Audit Study in Indonesia

Last registered on December 06, 2022

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Pre-Trial

Trial Information

General Information

Title

Religious Discrimination in Health: Evidence from an Audit Study in Indonesia

RCT ID

AEARCTR-0010517

Initial registration date

November 30, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

November 30, 2022, 5:07 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated

December 06, 2022, 6:57 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

Indonesia

Region

Primary Investigator

Name

Renate Hartwig

Affiliation

University of Goettingen

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Other Primary Investigator(s)

PI Name

Teguh Dartanto

PI Affiliation

Universitas Indonesia

Contact Investigator

PI Name

Jan Priebe

PI Affiliation

University of Goettingen

Contact Investigator

Additional Trial Information

Status

On going

Start date

2021-06-01

End date

2023-06-30

Keywords

Behavior, Health

Additional Keywords

Audit Study, Discrimination, Health Care, Standardized Patient, Indonesia

JEL code(s)

H42, I11, I18, O15

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

A vast literature in economics documents large differences in health outcomes by gender, race, wealth, and religion. To what extent these differences are driven by biases of health care providers is less understood. In this study, we explore whether health care providers discriminate against people with different religious beliefs using an audit study design (standardized patient method) on the clinical case of tuberculosis, an illness that is still widespread in Indonesia. The audit study is conducted in three provinces of Indonesia – Sumatera Barat, Sulawesi Utara and Jawa Tengah. The study covers 400 doctors at 400 randomly selected primary health care facilities in these three provinces. We conduct 1,600 standardized patient visits in which we vary the religious belief the patient. We complement the audit study with detailed facility- and doctor surveys in order to study the underlying nature of the observed biases.

External Link(s)

Registration Citation

Citation

Dartanto, Teguh, Renate Hartwig and Jan Priebe. 2022. "Religious Discrimination in Health: Evidence from an Audit Study in Indonesia." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.10517-1.2

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Experimental Details

Interventions

Intervention(s)

We employ an audit study in which standardized patients (SP) of different religous beliefs portray a clinical case of tuberculosis to test if there is religious discriminiation by health care providers.

Intervention Start Date

2022-03-15

Intervention End Date

2023-02-28

Primary Outcomes

Primary Outcomes (end points)

I) Quality of care - (a) an indicator of obtaining a diagnosis (binary), (b), an indicator of obtaining the correct diagnosis (binary), (c) adherence to the correct checklist items (binary and count of essential anamneses and diagnostics) and (d) duration spent with the doctor (continuous).
II) Cost of treatment – cost of consultation (continuous).

Primary Outcomes (explanation)

We use four different measures of the quality of care. First, we measure the quality of care based on the diagnosis, i.e. if the provider provided a diagnosis and second and – more importantly – if the provider provided the correct diagnosis for the clinical case presented. Third, we measure the quality of care based on the quality of the medical consultation. We assess this by compiling information on the questions and examinations conducted (dummy and count variable). Fourth we also look at the time spent with the health professional as another metric of the quality of care.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary outcomes include variables that we will use to investigate mechanisms through heterogeneous treatment effects. Secondary outcomes are related to three distinct features of the intervention: (a) patient characteristics such as religion/religiousness and wealth, (b) provider characteristics such as religion/religiousness, implicit attitudes and beliefs towards certain religions, wealth, social preferences, time preferences, tolerance, in-group favoritisms, competition, and (c) social norms at the community-level.

Secondary Outcomes (explanation)

Experimental Design

Experimental Design Details

We employ an audit study in which standardized patients (SP) – all female – will portray a clinical case of tuberculosis. The audit study adopts a 4 X 2 cross-randomization design. Religion and Religiousness will be expressed in terms of differences in women’s clothing. There will be four religious groups (3 Muslim groups: very conservative, conservative, less conservative) and 1 non-Muslim group: Christian). In addition, we vary the perceived level of wealth (2 groups: rich vs. poor) of the standardized patient by varying the patient’s quality of clothing.
The audit study is complemented by detailed health facility- and doctor surveys. The health facility survey collects information on the staffing, equipment, patients and services offered. The doctor survey includes information on the personal background, work experience and knowledge, religiousness, implicit discriminatory beliefs, and other preferences.

Randomization Method

The random assignment was done by PIs with a replicable procedure using statistical software.

Randomization Unit

The unit of randomization is the SP visit.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

N.A.

Sample size: planned number of observations

We plan with a minimum sample of 400 primary health centers, across 3 provinces of Indonesia. At the health provider visit level, the total number of observations is 1,600 (4 standardized patient visits x 400 health care providers).

Sample size (or number of clusters) by treatment arms

We will assign 4 standardized patients to each health care provider. At the health provider visit level each treatment arms has 400 observations.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

In a basic group means comparison with 80% power, a significance level of 0.05, and unit standard deviations, the MDE is .09pp for the total sample of 1,600 standardized patient visits (Assumption: Baseline mean of 0.6 & 1 treatment vs. 1 control group comparison).

Supporting Documents and Materials

IRB