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NCT Number: NCT06248658

Assessment of the Impact of Clinical Decision Support Systems Included in Electronic Health Records

A non--interventional study to assess the impact of clinical decision support systems included in electronic health records on compliance with guidelines, including routing of patients with CHF, follow-up care, prescription and dose titration of medicinal products.

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Key information

Conditions

Chronic Heart Failure (CHF) Cardiovascular Diseases Heart Diseases Heart Failure

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

National Medical Research Center for Cardiology, Ministry of Health of Russian Federation

Moscow, Russia

About this study

Circulatory system diseases are the leading cause of death in the Russian Federation. Ischemic heart disease (IHD) constitutes the largest share of circulatory system disease mortality, and also among the active working age population. According to the Federal State Statistics Service, IHD accounts for 54.2% in the structure of circulatory system disease mortality in the Russian Federation in 2020.

One of the most hazardous components of IHD is acute coronary syndrome (ACS). It is ACS that is one of the most common causes of CHD. In Russia, about 520,000 cases of ACS are recorded annually.

Chronic heart failure (CHF) is at the end of the cardiovascular disease continuum, which is characterized by a significant increase in overall and cardiovascular mortality risks. Therefore, a poor prognosis in this patient population, a high frequency of hospitalizations and a steady increase in the number of patients due to the population aging make CHF one of the priority areas for modern cardiology.

The most common cause of CHF is myocardial infarction. And, on the other hand, in about 20% of cases, acute myocardial infarction (AMI) is complicated by CHF, despite the success of reperfusion therapy. This patient group requires special attention. The mortality rates in patients with MI and HF are more than 10 times greater than in patients with MI without HF.

According to the guidelines for CHF 2020 approved by the Scientific and Practical Council of the Ministry of Health of Russia, the average annual mortality rate among patients with I-IV FC CHF in the Russian Federation is 6%, while in patients with clinically significant CHF, it is 12%. According to the EPOCH study data, it is known that the total mortality risk in CHF of any functional class (FC) is more than 10 times greater compared to the total mortality risk in the population of respondents without CHF, and the average life expectancy in patients with I-II FC and III-IV FC CHF is 7.8 and 4.8 years, respectively. Therefore, the scientific community agrees that mortality in patients with CHF is still high, and the rates of decline are insufficient. Consequently, the need for strategy development to reduce the demographic and financial losses from CHF is recognized in many countries, and the issues of implementing new technologies to reduce the mortality rates among patients with CHF are being studied and widely discussed in the literature.

High comorbidity and numerous hospitalizations turn the patients with heart failure (HF) into "super consumers" of the healthcare system resources. Comorbid CHF makes the disease burden even greater. For example, patients with a double burden of CKD and CHF (the most common comorbid combination, 43.8%) demonstrate unacceptably high rates of symptom burden, hospitalization rates, and mortality. The adjusted survival probability in patients with CHF and CKD after 2 years is 77.8% compared to 93.7% in patients without CHF and CHD (difference: 15.9%). One of the studies of CHF comorbidity demonstrated that atrial fibrillation (AF) in highly comorbid patients (average number of disease areas per patient with CHF: 4.6 ± 1.6) was more common than in patients with low comorbidity (23.4% and 7.5% of cases, respectively; p = 0.007).

Existing innovative therapeutic approaches in combination with the introduction of components of the CHF patient service can significantly influence the prognosis and reduce the burden on the healthcare system. However, in real-world clinical practice in the Russian Federation, the percentage of patients with HF who receive innovative drug therapy and the frequency of achieving target doses of disease modifying therapies are still low.

To reduce the circulatory system disease mortality, the Government of the Russian Federation has developed and is implementing the Federal Project "Combating Cardiovascular Diseases" and regional programs under the same name. They include the Program for Preferential Drug Provision for patients with AMI, CVA, as well as if they had CABG, PCI, and RFA procedures within the first two years of follow-up care. Consequently, the importance of Digital Systems is increasing, since they help identify such patients and perform their therapy in full.

Possible reasons for the current situation include low effectiveness of organizational approaches, in particular, a low percentage of patients visiting outpatient facilities after discharge, non-compliance with follow-up care timing, extremely low frequency of laboratory tests and diagnostic procedures, including a test for NT-proBNP level.

Monitoring of key clinical parameters of CHF patients, given medical therapy, assessment of follow-up care effectiveness, evaluation of consumed healthcare system resources using electronic health records (EHR) is one of the effective approaches to better adherence of healthcare professionals (HCPs) to the Guidelines, improved quality of health care, which, in its turn, can help improve the prognosis and to achieve the target mortality rates in circulatory system diseases. However, despite the pronounced success in the fight against circulatory system diseases, including CHF, the use of EHR systems as a tool for assessing the effectiveness of HF patient management and collecting statistical data is still unexplored. The EHR systems, which are used for collection and analysis of data on HF patients, have been introduced by healthcare providers in several regions in the Russian Federation.

In this study, the implementation strategy involves provision HCPs (primary care physicians and cardiologists) with access to the service that allows analyzing the data on routing and key clinical parameters of CHF patients.

The primary objective of this study is to assess the effectiveness of the implementation of the CDSS (clinical decision support system) aimed at improving the HCP compliance with the main provisions of the guidelines for heart failure in real-world clinical practice in order to enhance the effectiveness of this patient category management and improve clinical outcomes in the pilot regions of the Russian Federation.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Any cardiac diagnosis ICD-10 codes I00-I99
  • Age: ≥18 years
  • CHF stage 2a and higher and/or FC II and higher
  • The data export for analysis is carried out through obtaining the structured electronic healthcare records (SHCR) from the Vertically Integrated Medical Information System "Cardiovascular Diseases" (VIMIS CVD). Such export implies obtaining documents of patients with IHD, ACS, CVA, AF and CHF, occlusion and stenosis of carotid artery, infective endocarditis and cardiac device-related endocarditis, which are sent by the region to VIMIS CVD.

Exclusion criteria

  • Age: <18 years

Treatment and study plan

Primary outcomes

  1. Percentage of patients who underwent BNP/NT-proBNP test and/or echocardiography basic diagnostic tests and, consequently, improved CHF detection rates

    Time frame: 12 months

    To assess the effectiveness of the CDSS implementation with regard to an increase in frequency of basic diagnostic tests and, consequently, improved CHF detection rates

    For the inpatient cohort, the percentage will be calculated as the number of patients who underwent at least one of the above diagnostic tests or a combination of two criteria during the observation period, divided by the number of patients included in the inpatient cohort.

    The percentages of patients who underwent each of the tests separately (BNP/NT-proBNP or EchoCG) are calculated separately.

    For the outpatient cohort, the percentage will be calculated as the number of patients who underwent at least one of the above diagnostic tests or a combination of two criteria during the observation period, divided by the number of patients included in the outpatient cohort.

    The percentages of patients who underwent each of the tests separately (BNP/NT-proBNP or EchoCG) are calculated separately.

Secondary outcomes

  1. Assessment of the data in the EHR for the index event and for the last reported case of health care delivery during the follow-up.

    Time frame: 12 months

    • Percentage of patients with a record about left ventricular ejection fraction (LVEF), with specified CHF stage, with specified NYHA FC CHF
    • Percentage of patients with HFrEF, HFmrEF, HFpEF
    • Percentage distribution by CHF stages (of those with the specified stage), by NYHA FC CHF (of those with specified FC)
    • Percentage of patients with a diagnosis code I50.x (standard coding) and/or I11.0, I13.0, I13.2, I25.5, I42.0, I42.9, I09.9, I43.0, I43.1, I43.2, I43.8, I42.5, I42.6, I42.7, I42.8 (extended coding)
    • Percentage of patients depending on the diagnosis source

  2. The basic socio-demographic characteristics and lifestyle peculiarities in CHF patients (gender)

    Time frame: 12 months

    Gender (female, male): % Mean, min and max (where applicable)

  3. The performance of diagnostic procedures in the hospital setting (index hospitalization)

    Time frame: 12 months

    Physical diagnosis

    • Percentage of patients with at least one parameter value in the discharge summary (Body weight, SBP/DBP, HR) Instrumental diagnostics
    • Percentage of patients who underwent ECG, chest X-ray, echocardiography
    • Percentage of patients with an ejection fraction specified in the discharge summary Laboratory diagnostics
    • Percentage of patients who underwent a blood chemistry test in the hospital setting (Creatinine, eGFR in EHR, Potassium, Sodium, Bilirubin, ALT, AST)
    • Percentage of patients who underwent BNP or NT-proBNP measurement; a complete blood count, an urinalysis in the hospital setting

  4. The recommended therapy at discharge

    Time frame: 12 months

    • Percentage of patients who were recommended at discharge (RAAS inhibitors (ACE inhibitors or ARBs or ARNI (sacubitril/valsartan), Separately for each class: ACE inhibitors, ARBs, ARNI (with a breakdown by INN according to the Guidelines), Beta blockers, MRA, iSGLT2, Diuretics, Ivabradine)
    • Percentage of patients who were recommended specified or unspecified dosage, distribution by the level of the drug dose recommended at discharge (min, mean, therapeutic (max), unspecified dosage) (RAAS inhibitors (ACE inhibitors or ARBs or ARNI (sacubitril/valsartan), Beta blockers)

  5. The effectiveness of the CDSS implementation with regard to improvement in follow-up care

    Time frame: 12 months

    • Percentage of patients enrolled in CHF follow-up care
    • Percentage of patients being in CHF care at the date of cohort follow-up completion.
    • Percentage of patients whose EHRs contain all the necessary parameters to determine the specialist physician for follow-up care (functional class of angina, blood pressure, heart rate, levels of cholesterol, LDL-C, triglycerides, diabetes mellitus (DM), CKD, CKD stage, prescribed therapy)
    • Percentage of patients with a correctly identified specialist physician (primary care physician/cardiologist) for CHF follow-up care

  6. The effectiveness of the CDSS implementation with regard to improvement in follow-up care and patient routing

    Time frame: 12 months

    • Percentage of patients who continued observation at the outpatient stage after discharge: at least one (first after discharge) visit to a primary care physician or cardiologist within 1 (2, 4, 6, 8) weeks after discharge
    • Percentage of patients with 0, 1-2, 3-4, >4 outpatient visits to a primary care physician or cardiologist within 6/12 months after discharge
    • Percentage of patients with 0, 1-2, 3-4,> 4 outpatient visits to a primary care physician or cardiologist within 6/12 months after the index event

  7. The effectiveness of the CDSS implementation with regard to the performance of examination at the outpatient stage

    Time frame: 12 months

    • Percentage of outpatient visits with an EHR entry (Body weight, SBP/DBP, HR, Swelling)
    • Percentage of patients who had measurements at least at one outpatient visit (there is a record in the EHR)

  8. The effectiveness of the CDSS implementation with regard to improvement in the prescription and therapy continuity at the outpatient stage

    Time frame: 12 months

    • The percentage of patients who were prescribed/asked to continue medical therapy during the outpatient visit
    • Percentage of patients (for the inpatient cohort) who, at the outpatient visit, had a change in the drug INN compared to the one recommended at discharge
    • Percentage of patients whose therapy that was recommended at discharge was discontinued during an outpatient visit
    • Percentage of patients whose therapy doses were escalated/reduced at outpatient visits compared to the dose level prescribed/recommended during hospitalization
    • Percentage of patients whose therapy doses were escalated at outpatient visits
    • Percentage of patients whose therapy doses were reduced at outpatient visits
    • The percentage of patients who had any change in the dose of the medicinal product during outpatient visits

  9. The effectiveness of the CDSS implementation with regard to updating comorbidity in patients with CHF

    Time frame: 12 months

    • The percentage of patients with CHF and IHD, and separately CHF and MI / postinfarction cardiosclerosis, CHF and unstable angina, CHF and stable effort angina
    • The percentage of patients with CHF and AH
    • The percentage of patients with CHF and heart rhythm disorders (HRD)
    • The percentage of patients with CHF and CVA (stroke, TIA, CVD)
    • The percentage of patients with CHF and CKD
    • The percentage of patients with CHF and type 2 DM
    • The percentage of patients with 2, 3, and more comorbidities
    • The percentage of patients with vascular interventions

  10. The effectiveness of the CDSS implementation with regard to improvement in clinical outcomes of patients with CHF

    Time frame: 12 months

    • Percentage, absolute number of cases, incidence of (cases per 100 patient-years) hospitalizations for cardiac diagnoses within 1/3/6/12 months after the index event by types HF: HFrEF, HFmrEF, HFpEF and with a breakdown by hospitalization cause: CHF, for MI (AMI / NSTE-ACS/NSTE-ACS), for IHD (unstable angina pectoris), TIA, CVA, stroke, for heart rhythm disorder (including AF), for other cardiac diseases (including uncontrolled hypertension), CKD (renal impairment).
    • Percentage, absolute number, frequency (cases per 100 patient-years) of emergency calls during 3/6/12 months after the index event
    • Percentage of telemedicine consultations after the index event in total and by EF in CHF.

  11. The effectiveness of the CDSS implementation with regard to monitoring the provision of patients with CHF

    Time frame: 12 months

    • Percentage of patients after AMI and CHF, CVA and CHF, CABG and CHF, PCI and CHF, RFA and CHF with a prescription for the treatment of CHF
    • Percentage of patients receiving ARNI, iSGLT2, other therapy, in patients with HFrEF, HFmrEF, HFpEF
    • Frequency of emergency calls by patients receiving the treatment of CHF being in follow-up care for 6 months/12 months

  12. Characteristic of blood pressure in patients with increased risks of CHF occurrence or its course

    Time frame: 12 months

    Systolic blood pressure (SBP) and diastolic blood pressure (DBP): mean +-SD, median, quartiles, min and max

  13. The effectiveness of the CDSS implementation with regard to improvement in follow-up care and patient routing per one patient-year

    Time frame: 12 months

    • The average number of outpatient visits per one patient-year of follow-up after the index event: number of visits to the primary care physician, cardiologist, separately, and in total
    • The average number of outpatient visits per one patient-year of follow-up after discharge: number of visits to the primary care physician, cardiologist, separately, and in total.

  14. The effectiveness of the CDSS implementation with regard to the performance of diagnostic tests at the outpatient stage

    Time frame: 12 months

    -Percentage of patients who underwent the following tests over the analyzed period (Creatinine, eGFR (from EHR), BNP/NT-proBNP, Potassium, sodium, Bilirubin, ALT, AST, CBC (RBCs, Hb), ECG, Chest X-ray, EchoCG, Holter monitoring

  15. Characteristic of heart rate in patients with increased risks of CHF occurrence or its course

    Time frame: 12 months

    -HR (mean, +-SD, median, min and max quartiles)

  16. Characteristic of lipid profile and laboratory tests in patients with increased risks of CHF occurrence or its course

    Time frame: 12 months

    -Lipid profile (total cholesterol, LDL-C, HDL-C, VLDL-C, non-HDL-C, triglycerides, Lp(a)) as well as glucose, HbA1, creatinine, ALT, AST, Hb (Note: if several test results are available, the closest to the index date will be selected

  17. The basic socio-demographic characteristics and lifestyle peculiarities in CHF patients (age)

    Time frame: 12 months

    Age (years): % Mean, min and max (where applicable)

  18. The basic socio-demographic characteristics and lifestyle peculiarities in CHF patients (Weight, BMI)

    Time frame: 12 months

    Body weight (kg), height (m), body mass index (kg/m2) Weight and height will be combined to report BMI in kg/m2.

    % Mean, min and max (where applicable)

Sponsors and collaborators

Lead sponsor

National Medical Research Center for Cardiology, Ministry of Health of Russian Federation

Other Gov

Collaborators

  • National Society for the Study of Heart Failure and Myocardial Diseases
  • Novartis

Registry information

Official study title

A Non-interventional Study to Assess the Impact of Clinical Decision Support Systems Included in Electronic Health Records on Compliance With Guidelines

Important dates

Study start
2023
Primary completion
2025
Study completion
2025
First posted
Feb 8, 2024
Registry last updated
Apr 17, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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