Designing a Programming Language for Patient-Oriented Prescriptions (POP-PL)

February 8, 2019 updated by: Steven M Belknap, Northwestern University
The purpose of this study is to create a human-readable and executable computer language to implement medical prescriptions and to evaluate and refine this language, with the goal of improving safety and efficacy of patient care.

Study Overview

Status

Completed

Conditions

Detailed Description

Preventable errors in healthcare are a leading cause of patient injury and death. Despite extensive effort and the expenditure of billions of dollars, computerization has failed to solve this problem. Research has shown that software design and debugging of a paper prescription markedly decreases the rate of injury and death associated with use of opioids in hospitalized patients. To further the application of insights from software engineering to the practice of medicine, the PIs will design and build a Patient-Oriented Prescription Programming Language (POP-PL) and evaluate if this new platform can be used to improve medical management of patients. The design of POP-PL will be based on building an understanding of the process of medical treatment of patients. This project is a collaboration between computer scientists and clinicians at Northwestern Medicine. The collaborating clinicians are co-investigators on this research project and also are providing healthcare to the patients that are being observed. The computer scientists and other research staff have undergone human subjects research training and are co-investigators on this research project as well. The clinician-investigators will oversee research project staff during all observations of patients, clinical encounters between healthcare providers and patients, and interactions between healthcare providers and healthcare information systems. Researchers involved in this study will observe interactions between health care providers and patients and will collate these observations with data from electronic data sources. Since this research is based mainly upon observation and chart review and will not involve any interventions or changes to patient care, the risk to study participants is minimal, involving inadvertent disclosure of healthcare information. This risk will be mitigated by anonymizing collected data.

Study Type

Observational

Enrollment (Actual)

56

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • United States
    • Illinois
      • Chicago, Illinois, United States, 60611
        • Northwestern Memorial Hospital
      • Chicago, Illinois, United States, 60611
        • Northwestern Medicine Clinics

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 50 years (Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients seen at Northwestern Memorial Hospital and Northwestern Medicine Clinics

Description

Inclusion Criteria:

  • Patients between the ages of 18 and 50 years old who receive care at the Northwestern Maternal Fetal Medicine Clinic (MFM)
  • Patients between the ages of 18 and 50 years old who visit Northwestern Medicine outpatient facilities and are patients of a clinician who is a coinvestigator on this project.
  • Patients who are between the ages of 18 and 50 years old, are hospitalized at Northwestern Medicine inpatient facilities, and are patients of a clinician who is a coinvestigator on this project.

Exclusion Criteria:

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Evaluation of Differences between Ideal and Actual Performance of Prescriptions by Number of Deviations between Sequences of Events
Time Frame: 2 years
Investigators will express the intent of prescriptions in prescription programming language. Investigators will then compare the actual performance of the prescription in a clinical environment to the performance of the prescription in a simulated environment based on the same inputs as occurred in the real clinical environment.
2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Northwestern University

Investigators

  • Principal Investigator: Steven M Belknap, MD, Northwestern University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 1, 2016

Primary Completion (Actual)

January 17, 2019

Study Completion (Actual)

January 17, 2019

Study Registration Dates

First Submitted

May 16, 2016

First Submitted That Met QC Criteria

June 28, 2016

First Posted (Estimate)

June 30, 2016

Study Record Updates

Last Update Posted (Actual)

February 12, 2019

Last Update Submitted That Met QC Criteria

February 8, 2019

Last Verified

February 1, 2019

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • SMB01262016

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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