Quality of Hypertensive Patients’ Electronic Health Records in Specialized Cardiological Centre: 6-Year Trends

  • Anna SemakovaEmail author
  • Nadezhda Zvartau
  • Ekaterina Bolgova
  • Aleksandra Konradi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 674)


Electronic health records (EHRs) have the potential to form the basis for a personalized approach to patient management, deliver high-quality care, and make the healthcare system more efficient and safer. Finding and studying the possible trends and long term changes of individual results in stored medical data may facilitate selection of an optimal treatment plan. Moreover, guidelines on disease management usually include only shifted results of clinical trials that are poorly generalized to routine clinical practice. In numerous EHR-related errors have been described, such as unstructured data, missing data, and incorrectly entered data. This study aims to assess the quality of hypertensive patients’ EHRs during 6 years after the implementation of EHRs in the specialized cardiological centre. The quality of patients’ EHRs was estimated by the completeness and consistency of stored data. We compared information entered into EHRs with diagnostic algorithms recommended by hypertension management guidelines. The results demonstrated the incompleteness and inconsistency of information in EHRs on risk factors, diabetes mellitus (DM), and subclinical organ damage. An assessment of six-year trends showed that the quality of data decreased in parallel with increase of workload of the clinic (estimated by the number of primary visits). Results indicate the urgent need for an action plan to resolve the problem of data incompleteness and inconsistency. Integration of specially designed clinical decision support system (CDSS) considered as a possible decision promoting an increase of EHRs quality. This study is part of a larger project aimed to develop of complex CDSS on cardiovascular disorders for medical research centre.


Electronic health records Risk factors Diabetes mellitus Subclinical organ damage Completeness and consistency of information Learning curves Statistical data analysis 



This paper is financially supported by The Russian Scientific Foundation, Agreement #14-11-00826 (10.07.2014).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Anna Semakova
    • 1
    Email author
  • Nadezhda Zvartau
    • 2
  • Ekaterina Bolgova
    • 1
  • Aleksandra Konradi
    • 2
  1. 1.ITMO UniversitySaint PetersburgRussia
  2. 2.Almazov Federal North-West Medical Research CenterSaint PetersburgRussia

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