Assessment of Adherence to Clinical Practice Guidelines in Patients With Dyslipidemia Using a Clinical Decision Support System
Assessment of Adherence to Clinical Practice Guidelines in Patients With Dyslipidemia Using a Clinical Decision Support System
Objective: To validate the performance of the developed clinical decision support system (CDSS) for participants with lipid metabolism disorders based on a decision tree algorithm.
Materials and Methods: A clinical decision support system for participants with lipid profile abnormalities will be developed using the Orbeon open-source online form creation platform based on current clinical guidelines.
During the CDSS pilot implementation, the electronic medical records (EMRs) of 500 participants from the Institute of Personalized Cardiology of the Biomedical Science and Technology Park at Sechenov University will be analyzed.
Retrospective data on prescribed lipid-lowering therapy extracted from the EHR will be compared with the CDSS recommendations. The accuracy of the decisions will be assessed by three independent experts based on digitized clinical and laboratory patient profiles.
The primary endpoint of the study will be to determine the accuracy of the system.
Results: This study will result in the development (creation) and pilot application of the CDSS program in participants with dyslipidemia in real clinical practice.
Conclusion: The developed CDSS system for dyslipidemia will significantly reduce the time required for clinical decision-making and help avoid errors in the interpretation of patient data.
This study was conducted as a retrospective observational study and was aimed at developing and applying a decision support system for physicians treating patients with lipid metabolism disorders based on a decision tree algorithm as well as to assess the degree of compliance with clinical guidelines for the management of patients with dyslipidemia in real clinical practice.
As part of the study, a retrospective analysis of the electronic medical records of adult participants will be conducted. Clinical data will be extracted from medical records, including demographic characteristics, laboratory lipid profile indicators (total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides), kidney function indicators (creatinine level and estimated glomerular filtration rate), biochemical parameters, including alanine aminotransferase and creatine phosphokinase levels, as well as information on concomitant and past diseases.
The data of 500 participants will be structured and entered into an electronic form, which serves as the basis for a clinical decision support system implemented in the form of a decision tree algorithm. This system will be used exclusively for analytical purposes and make it possible to determine the indications for prescribing lipid-lowering therapy, its recommended intensity, and the need to adjust drug doses in accordance with current clinical guidelines.
The lipid-lowering therapy prescriptions actually administered by treating physicians and recorded in medical records will be compared with the recommendations generated by the clinical decision support system. An independent expert assessment will be conducted. An expert group consisting of three physicians will form their own recommendations for therapy based on each patients' clinical data, without having access to information about the actual prescriptions and the results of the algorithm, which ensured a blinded assessment of the endpoints.
Immediately after all patients have completed the questionnaire, two independent expert opinions will also be obtained for each patient. Then, by comparing the decisions of the attending physicians, the recommendations of the clinical decision support system, and the conclusions of the expert group, the degree of compliance of actual clinical practice with current clinical guidelines for the management of patients with dyslipidemia will be assessed.
The patient's personal data (surname, first name, patronymic, date of birth, contact details) will not be transferred. Each patient is assigned an individual number that is not linked to their personal data.
A web interface was developed based on a decision tree compiled from several current guidelines. A questionnaire was created for entering anonymized patient data. The system's output is a cardiovascular risk assessment or recommendations for lipid-lowering therapy.
Following clinical guidelines were used:
A statistical analysis will be conducted on the prevalence and nature of medical errors in the EXСEL system (descriptive statistics). No comparative analysis will be conducted. The parameters of the accuracy of the CDSS will be determined using a four-field table method.
The reference in this study is the decision of two of the three or all three experts on the correctness of the cardiovascular risk assessment, the correctness of the prescription of drug therapy, the correctness of the recommended diet and physical exercise, the correctness of patient monitoring (repeated blood tests, timely completion of examinations).
Inclusion Criteria:
Non-inclusion criteria:
Patients with insufficient data to complete the questionnaire;
Refusal to sign informed consent for participation in the study.
Exclusion Criteria:
Absence of a consensus opinion on the clinical case among two of the three experts.
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