SMS Interventions for Reducing Medicine Overuse

Last registered on November 26, 2019

Pre-Trial

Trial Information

General Information

Title
SMS Interventions for Reducing Medicine Overuse
RCT ID
AEARCTR-0005118
Initial registration date
November 26, 2019

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 26, 2019, 10:41 AM EST

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

Locations

Region

Primary Investigator

Affiliation
Peking University

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2019-11-28
End date
2020-12-30
Secondary IDs
Abstract
Medicine overuse and misuse have became a subsequent issue once access is expanded. Antibiotic resistance is one serious consequence and its major contributor – antibiotics overuse and misuse are particularly prevalent in developing countries. In a context of weak regulation enforcement on the health service provider side, we propose a potential approach to address this issue from patient's demand. Partnered with a community health center in China, we examine whether sending people text messages of potential harm associated with antibiotics misuse and overuse could reduce demand and therefore reduce total purchase. Moreover, we design the experiment to evaluate the relative effectiveness of self- and social- interest messages.
External Link(s)

Registration Citation

Citation
Lu, Fangwen. 2019. "SMS Interventions for Reducing Medicine Overuse." AEA RCT Registry. November 26. https://doi.org/10.1257/rct.5118-1.0
Experimental Details

Interventions

Intervention(s)
The proposed intervention is focused on people that have visited ever our study site The intervention is to send people text messages with information on the potential consequences of antibiotics misuse and overuse. Since the consequence – antibiotics resistance does not only have an impact on one’s own health, but could also spread across people and thus creates an externality, the message will be either about the self or social health impact of antibiotics misuse and overuse.
Intervention Start Date
2019-12-01
Intervention End Date
2020-05-15

Primary Outcomes

Primary Outcomes (end points)
1) Whether there is any purchase of antibiotics in the outcome sample period
2) Dosage Prescribed for Antibiotics (measured in days)
3) Quantity of Antibiotics Purchase (measured in units sold at the health center)
4) Amount Spent on Antibiotics Purchase (measured in RMB)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1) Times purchasing antibiotics without spending on examination
2) Times purchasing antibiotics with diagnosis of acute respiratory infections
3) Times visited the health center
4) Purchase of medicine other than antibiotics
5) Spending on examination and other services
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our study sample are the individuals who have visited the community health center within the one year period prior to the intervention. We restrict the sample to be those who have their national ID information on record, have a 11 digit mobile phone number, and not older than 75.

Each individual will be randomly assigned to one of the three groups: two treatment groups and one control group. The control group will get a placebo message, which contains no information on antibiotics. The “self-health” treatment group receives message with self health related information, which tells people that misuse and overuse of antibiotics will contribute to the evolution of antibiotic-resistant bacteria in one’s own body. And the other group will receive “social-health” messages, which instead emphasize how the misuse and overuse will contribute to the spread of the antibiotic-resistant bacteria across population.
Experimental Design Details
Randomization Method
We will conduct a stratified randomization based on gender, age, and antibiotics purchase history using STATA.
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No cluster design
Sample size: planned number of observations
Around 14,000 individuals
Sample size (or number of clusters) by treatment arms
Around 4,500 individuals in control and each of the two treatment groups
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Taking the sample size as given (~14,000), we expect the Minimum Detectable Effect (MDE) to be a 0.25 deduction in dosage (days), 0.068 in quantity, and 1.23 decrease in spending (RMB) on antibiotics one month after the first dose of messages. This MDE is equivalent to around 30-39% drop in treatment groups compared to control. Aggregating up the outcome for two months, the MDE is expected to be 0.32 for dosage, 0.085 for quantity, and 1.64 for spending, which are around 25-30% of the control mean. The estimates of the baseline mean and standard deviation are obtained from the antibiotics purchase data from Dec 2018 and Jan 2019, same months of the year as we expect to collect the outcome data. For these calculations, we assume a significance level of 0.05 and a power of 0.8.
IRB

Institutional Review Boards (IRBs)

IRB Name
Internal Review Board at EconLab, Renmin University of China
IRB Approval Date
2018-11-13
IRB Approval Number
RUCecon-201811-2

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials