Introduction
Different healthcare organizations routinely review various quality measures for numerous matters. The National Committee for Quality Assurance (NCQA) sponsors the Healthcare Effectiveness Data and Information Set (HEDIS), which is used by the majority of hospitals and clinics in the US (Nash et al., 2019). Measures for managing diabetes applicable to in-patient settings include blood pressure control, eye examination, and HbA1c control (NCQA, 2020). However, in outpatient settings, it is impossible to control either HbA1c or blood pressure control closely. Thus, these metrics cannot apply to outpatient settings.
Evaluation of Metrics
These three metrics are crucial for improving healthcare quality. The information gathered by healthcare personnel through monitoring of blood pressure, HbA1c control, and eye examination helps to understand if the patient’s health is getting worse. The metrics allow the creation of triggers that alarm the healthcare personnel that immediate interventions or changes in the care plan are needed. In general, the impact of these performance metrics is positive, as it helps to increase the effectiveness and efficiency of care, as well as patient satisfaction (Georgsson & Staggers, 2016).
Automated Trigger Systems
Automated trigger systems are decision-making support systems that help to indicate that a patient needs prompt attention. Implementation of automated trigger systems has positively affected patient safety, as nurses can quickly inform doctors about emergencies (Alotaibi & Federico, 2017). It is a reactive measure rather than proactive, as it helps the medical personnel react to emergencies at the earliest possible time. These systems improve patient outcomes, as well as reduce morbidity and mortality (Alotaibi & Federico, 2017). Therefore, I believe that automated trigger systems have improved the quality of care since they have been implemented.
References
Alotaibi, Y. K., & Federico, F. (2017). The impact of health information technology on patient safety. Saudi medical journal, 38(12), 1173-1180.
Georgsson, M., & Staggers, N. (2016). Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics. Journal of the American Medical Informatics Association, 23(1), 5-11.
Nash, D. B., Joshi, M. S., & Ransom, E. R., & Ransom, S. B., (Eds.). (2019). The healthcare quality book: Vision, strategy, and tools (4 ed.). Health Administration Press.
National Committee for Quality Assurance. (2020). Required HEDIS® and CAHPS® Measures for HEDIS Reporting Year 2020. NCQA. Web.