The Impact of Real-Time Benefits Physician-Targeted Price Transparency on Patient Out-of-Pocket Costs
Last registered on March 31, 2021

Pre-Trial

Trial Information
General Information
Title
The Impact of Real-Time Benefits Physician-Targeted Price Transparency on Patient Out-of-Pocket Costs
RCT ID
AEARCTR-0006909
Initial registration date
January 04, 2021
Last updated
March 31, 2021 6:38 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
NYU School of Medicine
Other Primary Investigator(s)
PI Affiliation
Additional Trial Information
Status
On going
Start date
2021-01-13
End date
2021-06-10
Secondary IDs
I10, I12, I18
Abstract
The goal of this study is to evaluate whether presenting patient out-of-pocket cost information to the provider at the time of prescribing leads to orders for medications with lower out-of-pocket costs. We implement a real-time benefits check (RTBC) tool to randomly selected providers across NYU Langone Health’s outpatient physician practices. The RTPC tool provides physicians with information about patient out-of-pocket (OOP) cost for medications at the point of outpatient prescribing. If the physician is submitting a prescription order and a clinically-appropriate alternative with a lower OOP cost is available, an alert with OOP cost information for the drug being initially ordered as well as up to three lower-cost alternatives will be displayed. We will analyze whether implementation of this tool led to reduced out-of-pocket costs on ordered medications.
External Link(s)
Registration Citation
Citation
Desai, Sunita and Leora Horwitz. 2021. "The Impact of Real-Time Benefits Physician-Targeted Price Transparency on Patient Out-of-Pocket Costs." AEA RCT Registry. March 31. https://doi.org/10.1257/rct.6909-1.2000000000000002.
Experimental Details
Interventions
Intervention(s)
The goal of the real-time benefits check (RTBC) tool is to facilitate prescribing of lower-cost alternatives by providing patient out-of-pocket cost information to physicians at the point of prescribing. RTBC is developed through a partnership between Surescripts and Epic.
For a subset of prescriptions ordered RTBC provides physicians with information about patient out-of-pocket (OOP) cost for medications at the point of outpatient prescribing. OOP is inclusive of any copay, coinsurance, and deductible that the patient owes and information is specific to the patient's prescription drug benefit plan. If the physician is submitting a prescription order and a clinically-appropriate alternative with a lower out-of-pocket cost is available, an alert with out-of-pocket cost information for the drug being ordered as well as up to three lower-cost alternatives will be displayed. The physician can then prescribe the original drug or one of the alternative drugs.
Intervention Start Date
2021-01-13
Intervention End Date
2021-06-10
Primary Outcomes
Primary Outcomes (end points)
out-of-pocket cost per day
Primary Outcomes (explanation)
primary outcome, which will be measured at the medication-order level is out-of-pocket cost per day for a drug ordered. It will be computed by dividing the out-of-pocket cost of a drug by the days supply.
Secondary Outcomes
Secondary Outcomes (end points)
Whether an order was placed for a mail-order pharmacy
Days supply
Whether lowest cost option was prescribed
Secondary Outcomes (explanation)
Whether an order was placed for a mail-order pharmacy: A secondary outcome, also specified at the order level, is whether a drug prescription was ordered from a mail-order pharmacy, since switching to a mail-order pharmacy often presents an opportunity for savings

Days supply: Since increasing the days supply for a prescription is a margin on which savings could occur, we will also test for changes in the days supply of an order
Experimental Design
Experimental Design
Departments across NYU Langone Health's outpatient faculty practices will be randomized to being shown out-of-pocket cost alerts at the time of prescribing or not.
Experimental Design Details
Randomization Method
Randomization done in an office by a computer
Randomization Unit
Randomization by department. Randomization will be stratified by broad clinical specialty categories
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
908 departments
Sample size: planned number of observations
28,221
Sample size (or number of clusters) by treatment arms
Treatment arm: 567 departments (2514 physicians) ; Control arm: 660 departments (2663 physicians)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our power calculation was based on a 5% effect size, based on effects found in the literature on price transparency for medical services.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is 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