Quality at heart (Electronic Health Record)
Quality at heart (Electronic Health Record)
Background
Performance and outcome measurement is an important tool for making organizations aware of their behavior—to help understand what has happened—and for providing guid-ance on how to improve, i.e., to become learning organizations [1]. The US National Quality Measures Clearinghouse currently contains 2,429 such quality measures [2], and one of them will be used in this essay. It is a process-related, clinical quality measure for the man-agement of heart failure, jointly developed by three American professional organizations:
Percentage of heart failure patients with a current or prior left ventricular ejection fraction (LVEF) less than 40 % who were prescribed beta-blocker therapy [3, p. 26, deliberately simplified].
This measure is calculated as a fraction, where the numerator contains the number of heart failure patients with left ventricular dysfunction who were prescribed beta-blockers, while the denominator contains the total number of such patients (heart failure patients with left ventricular dysfunction). However, not all patients can be or should be on beta-blocker therapy, and these exceptions decrease the denominator. For example, there are medical reasons such as low blood pressure or asthma [3].
Assignment
Assume that the performance measure given above is to be calculated in an electronic health record (EHR). This means that data regarding diagnosis, LVEF measurement, medi-cations, and contraindications (if applicable) have to be retrieved. What kind of structure is needed and does it matter if the EHR is connected to a terminology system such as SNOMED CT or not?
Hints
Humans are complex, and so are our medical histories and medical records. The impli-cations of this should not be underestimated in a discussion on structure in EHRs.
Recall and precision may be a suitable framework in this analysis.
The single most important aspect of a course writing is to show what you have learned dur-ing the course: that you have met intended learning outcomes (ILOs). Please consult the syllabus or the extended ILOs in the course information as a guide to finding key aspects in this endeavor. However, security (as in protection of privacy and confidentiality) and legal aspects should be excluded. Also remember that the assumed target reader is a fellow stu-dent with no knowledge of medical informatics.
More information—including the essay manual—can be found on the essay page in Lisam.
References
1. Institute of Medicine (US), Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington: National Academy Press; 2001
2. Agency for Healthcare Research and Quality (US). National Quality Measures Clearinghouse [Internet]. Rockville (MD): The Agency; [cited 2017 Jun 28]. Browse by measure domain; [cited 2017 Jun 28]; [about 2 screens]. Available from: https://www.qualitymeasures.ahrq.gov/browse/domain
3. American College of Cardiology Foundation; American Heart Association; Physician Consortium for Performance Improvement. Heart failure performance measurement set [Internet]. 2nd ed. Chicago: Physician Consortium for Performance Improvement; 2016 Apr [cited 2017 Jun 28]. 49 p. Available from: https://www.thepcpi.org/pcpi/media/PCPI-Maintained-Measures/ Heart-Failure-Measure-Worksheets-Updated-April-2016.pdf
