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
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
Northwestern University
Chicago, Illinois, United States
Evaluation of Differences between Ideal and Actual Performance of Prescriptions by Number of Deviations between Sequences of Events
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.
Time frame: 2 years
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