From Information to Action: Using Evidence to Strengthen Primary Care in the SUS

Last registered on August 27, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
From Information to Action: Using Evidence to Strengthen Primary Care in the SUS
RCT ID
AEARCTR-0018382
Initial registration date
August 22, 2026

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
August 27, 2026, 12:13 PM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Bruna Borges
Affiliation
Institute for Health Policy Studies (IEPS)
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Joana Naritomi
PI Affiliation
London School of Economics and Political Science (LSE)
Contact Investigator
PI Name
Rudi Rocha
PI Affiliation
Sao Paulo School of Business Administration
Contact Investigator
PI Name
Diana Moreira
PI Affiliation
University of California, Davis, Department of Economics
Contact Investigator

Additional Trial Information

Status
In development
Start date
2026-06-23
End date
2028-12-31
Keywords
Governance, Health
Additional Keywords
primary health care, evidence-informed decision-making, public management, middle managers
JEL code(s)
I18; D83; C93
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study evaluates if structured support for accessing, interpreting, and using data and evidence can improve decision-making and implementation among public managers. More broadly, the study examines how middle-level public managers incorporate evidence into organizational routines and translate information into administrative action. Its empirical application is municipal primary health care in Brazil, with a focus on maternal and child health.

Although public organizations generate large amounts of data, managers often face barriers to using this information in their daily work. Data may be fragmented, difficult to interpret and compare, or costly to access under time and resource constraints. Moreover, even when managers can identify and prioritize local bottlenecks, they may lack accessible and credible evidence about which practices are effective and feasible. The intervention aims to address both barriers: its data and diagnosis components provide structured training, curated indicators, comparisons with peer municipalities, and individualized municipal diagnoses, while its additional solutions component presents recommended practices supported by rigorous evidence and promotes peer discussion about their operational implementation.

Participants in the study are professionals involved in the management of municipal primary health care services. Eligible registrants will be randomly assigned to one of two treatment groups. Treatment 1 provides training on data and indicators, guided use of the IEPS Data platform, an individualized municipal maternal and child health diagnosis, and peer discussion. Treatment 2 includes all Treatment 1 components and adds a module presenting evidence-based recommended practices, followed by peer discussion focused on operational processes and implementation.

The experimental comparison is between Treatment 2 and Treatment 1 and identifies the incremental effect of adding the solutions module to the data-literacy and municipal-diagnosis components. Because all registered municipalities are assigned to one of the two workshop versions, the study does not include a randomized no-treatment control group. As a secondary analysis, the study may estimate the overall effect of access to the workshop by comparing participating municipalities with municipalities not represented among registrants using a difference-in-differences design. A causal interpretation of this comparison will depend on sufficient overlap between the groups and on evidence supporting the plausibility of parallel pre-intervention trends; if these conditions are not supported, the analysis will be treated as exploratory.

Outcomes include interpretation of indicators, updating of beliefs about municipal performance, use of data in management, and adoption of evidence-aligned practices. The study will also examine whether changes in managerial practices translate into improvements in service-delivery processes and, over a longer horizon, maternal and child health outcomes.
External Link(s)

Registration Citation

Citation
Borges, Bruna et al. 2026. "From Information to Action: Using Evidence to Strengthen Primary Care in the SUS." AEA RCT Registry. August 27. https://doi.org/10.1257/rct.18382-1.0
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
Municipalities represented among eligible participants will be randomly assigned to one of two versions of an online workshop, and all participants from the same municipality will be assigned to the same version. The workshop focuses on the use of data and evidence in routine public management, with an empirical application to municipal primary health care and maternal and child health.

Both versions of the workshop introduce key concepts related to data literacy, including the interpretation of indicators, denominators, data limitations, trends over time, and comparisons across municipalities. Participants receive guidance on navigating the IEPS Data platform and an individualized report containing indicators for their municipality. They are then guided through a structured municipal diagnosis aimed at identifying and prioritizing relevant bottlenecks, followed by peer discussion.

Treatment 2 includes all the components offered in Treatment 1 and adds a solutions module. This module presents two recommended practices supported by rigorous causal evidence: WhatsApp groups for pregnant women, managed by primary health care teams to share maternal and child health information and facilitate communication; and reminder systems for prenatal appointments, diagnostic tests, postpartum follow-up, and childhood vaccination. Participants also discuss with peers the feasibility, operational processes, and implementation of these practices in municipal primary health care. This additional component is intended to reduce the cost of identifying effective and feasible responses and to help managers translate diagnosis and prioritization into action.
Intervention Start Date
2026-08-24
Intervention End Date
2026-12-11

Primary Outcomes

Primary Outcomes (end points)
1. Incorporation of information into routine management
2. Prioritization of maternal and child health bottlenecks
3. Adoption of effective management practices
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
4. Knowledge of health indicators
5. Assessment of relative performance and bottlenecks
6. Use of data systems and sources
7. Maternal and child health service delivery indicators
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Public managers working in municipal primary health care who register for the study are the eligible participants. Treatment assignment will occur at the municipality level: municipalities represented in the eligible sample are randomly assigned to one of two versions of the remotely delivered training activity, and all eligible participants from the same municipality will receive the same assignment.

Both groups will receive structured support related to the use of data and evidence in public management. One group will receive a core version of the training, while the other will receive an expanded version containing additional evidence and implementation-related content. The primary experimental comparison will estimate the incremental effect of the expanded version relative to the core version.

Outcomes will be measured through baseline and follow-up surveys and, where feasible, municipality-level administrative data.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Municipality
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
400 municipalities
Sample size: planned number of observations
800 primary health care managers
Sample size (or number of clusters) by treatment arms
Randomization is at the municipality level, with municipalities allocated equally between the two treatment arms. Based on the minimum detectable effect calculations, the preferred target is 400–600 municipalities in total: Treatment 1: approximately 200–300 municipalities; Treatment 2: approximately 200–300 municipalities.

The current pool for the first implementation wave includes approximately 300 participants from 180 municipalities, corresponding to approximately 90 municipalities and 150 participants per treatment arm under equal allocation.

Additional workshop cohorts and recruitment rounds may be opened to increase the number of participating municipalities. The initial expression-of-interest and contact pool covers approximately 500 municipalities, although many have not yet confirmed participation or selected a workshop session. The final sample size will therefore depend on baseline completion and participation confirmation before randomization.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan