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Related Concept Videos

Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

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Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
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Hypertension III: Clinical Manifestations and Diagnostic Studies01:30

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Hypertension is asymptomatic and also referred to as the "silent killer" until it progresses to a severe stage or causes target organ disease. Patients may experience symptoms stemming from the strain on blood vessels and tissues in various organs or the heart's increased workload.Physical exams might show no abnormalities other than high blood pressure. Signs of vascular damage, when present, correspond to the organs supplied by the affected vessels, leading to target organ damage. For...
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Hypertension V: Nursing Management01:23

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The nursing management of hypertension involves accurately assessing symptoms, making a comprehensive nursing diagnosis, collaborating with patients to set goals, and implementing targeted interventions to mitigate the condition's impact and improve patient well-being.Comprehensive AssessmentThe initial step in nursing care for hypertension involves a thorough patient assessment. It includes evaluating symptoms such as headaches, dizziness, blurred vision, and previous hypertension episodes.
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Hypertension, the most common cardiovascular disease, is diagnosed through repeated measurements of elevated blood pressure. Its risks, including damage to the kidney, heart, and brain, are directly proportional to blood pressure levels. Starting from 115/75 mm Hg, the risk of cardiovascular disease doubles with each increment of 20/10 mm Hg. The diagnosis relies on blood pressure measurements, not on patient symptoms, as hypertension is often asymptomatic until end-organ damage is imminent or...
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Hypertension is a widespread, long-term medical condition where blood pressure in the arteries remains elevated. It is characterized by systolic blood pressure readings of 130 mm Hg or above or diastolic blood pressure (DBP) readings of 80 mm Hg or higher. Unmanaged hypertension poses significant health risks, making the distinction between primary (or essential) hypertension and secondary hypertension crucial, as their management and implications vary.Primary HypertensionPrimary hypertension,...
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Pre-Procedural Guidelines for Assessing Blood Pressure01:10

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Accurate blood pressure assessment is crucial for diagnosing and managing various health conditions. To ensure the reliability of these measurements, healthcare professionals must adhere to standardized pre-procedural guidelines. These guidelines enhance patient safety and improve the overall quality of healthcare. The following steps are essential for obtaining accurate and consistent blood pressure readings, from using the appropriate tools to ensuring effective communication with the...
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Hypertension identification using inpatient clinical notes from electronic medical records: an explainable,

Elliot A Martin1, Adam G D'Souza2, Seungwon Lee2

  • 1Centre for Health Informatics (Martin, D'Souza, Lee, Eastwood, Quan) and Department of Community Health Sciences (Eastwood, Quan), Cumming School of Medicine, University of Calgary; Alberta Health Services (Martin, D'Souza, Lee), Calgary, Alta.; Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alta eamartin@ucalgary.ca.

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Summary
This summary is machine-generated.

Machine learning accurately identifies hypertension in electronic medical records (EMRs), outperforming traditional ICD codes. This approach enhances health services research and performance measurement.

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Area of Science:

  • Health Informatics
  • Machine Learning in Healthcare
  • Clinical Research

Background:

  • Accurate case identification is crucial for health services research, performance measurement, and risk adjustment.
  • Existing methods like manual chart review or diagnosis codes have limitations in cost, time, and validity.
  • Developing robust hypertension case definitions in electronic medical records (EMRs) is needed.

Purpose of the Study:

  • To develop and evaluate a machine learning-based hypertension case definition using inpatient clinical notes within EMRs.
  • To compare the performance of machine learning algorithms against traditional International Statistical Classification of Diseases and Related Health Problems (ICD) codes for hypertension identification.

Main Methods:

  • A cohort of 3040 adult patients discharged from Calgary acute care facilities in 2015 was randomly selected.
  • Machine learning algorithms were developed using EMR free-text clinical notes.
  • Performance was compared to an algorithm using ICD-10 codes from the Discharge Abstract Database, with chart review as the gold standard.

Main Results:

  • Of 3040 patients, 48.5% had hypertension; the hypertension group was older and had fewer females.
  • EMR-based machine learning models demonstrated significantly higher sensitivity (>90%) compared to the ICD algorithm (47%).
  • Positive predictive values for EMR models were also high (>90%), comparable to the ICD algorithm (97%).

Conclusions:

  • Hypertension is well-documented and classifiable within EMRs using concept search on free text.
  • Machine learning offers valuable insights into clinical documentation patterns within EMRs.
  • This approach can inform the development of both machine learning and non-machine learning phenotypes for improved case identification.