Carisi A Polanczyk1,2,3, Karen B Ruschel4,5, Fabio Morato Castilho4,6, Antonio L Ribeiro4,6. 1. National Institute of Science and Technology for Health Technology Assessment (IATS), CNPq, 2350 Ramiro Barcelos, room 21507, Porto Alegre, RS, 90035-903, Brazil. cpolanczyk@hcpa.edu.br. 2. Graduate Program in Cardiology and Cardiovascular Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. cpolanczyk@hcpa.edu.br. 3. Cardiology Center, Hospital Moinhos de Vento, Porto Alegre, Brazil. cpolanczyk@hcpa.edu.br. 4. National Institute of Science and Technology for Health Technology Assessment (IATS), CNPq, 2350 Ramiro Barcelos, room 21507, Porto Alegre, RS, 90035-903, Brazil. 5. Graduate Program in Cardiology and Cardiovascular Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. 6. Hospital das Clínicas and School of Medicine, Universidade Federal Minas Gerais, Belo Horizonte, Brazil.
Abstract
PURPOSE OF REVIEW: This paper reviews performance measure in health, their importance, and methodologic issues, focusing on metrics for health failure patients. Quality measures are instruments to assess structural aspects or processes of care aiming to guarantee that optimal patient outcomes are achieved. As heart failure is a chronic condition in which established therapies reduce mortality and hospital admissions, there are quite a lot of initiatives that aim to monitor for quality of care and to coordinate the disease management. RECENT FINDINGS: Several performance measures were validated for these patients, from process of care (left ventricular function assessment and use of ACEi/ARBs and beta-blockers) to health outcomes (hospital mortality and readmissions). In the early years, studies demonstrated a relationship between quality measurements and health outcomes. Nonetheless, more recent ones based on large databases of patients' medical records have shown that traditional indicators explain only a small fraction of health and patient reported- and perceived outcomes. Public reporting of quality measures and payment conditioned to the quality of care provided were not able to show benefit in terms of hard outcomes. Data science and big data methods are promising in providing actionable knowledge for quality improvement, with real-time data that could support decision-making. Heart failure is a chronic condition that has proven to be useful for measuring medical and healthcare quality. Evidence-based indicators have already reached high rates of adherence and are currently poorly correlated with outcomes. Using real-life data and based on the patient's perspective can be useful tools to improve these indicators.
PURPOSE OF REVIEW: This paper reviews performance measure in health, their importance, and methodologic issues, focusing on metrics for health failurepatients. Quality measures are instruments to assess structural aspects or processes of care aiming to guarantee that optimal patient outcomes are achieved. As heart failure is a chronic condition in which established therapies reduce mortality and hospital admissions, there are quite a lot of initiatives that aim to monitor for quality of care and to coordinate the disease management. RECENT FINDINGS: Several performance measures were validated for these patients, from process of care (left ventricular function assessment and use of ACEi/ARBs and beta-blockers) to health outcomes (hospital mortality and readmissions). In the early years, studies demonstrated a relationship between quality measurements and health outcomes. Nonetheless, more recent ones based on large databases of patients' medical records have shown that traditional indicators explain only a small fraction of health and patient reported- and perceived outcomes. Public reporting of quality measures and payment conditioned to the quality of care provided were not able to show benefit in terms of hard outcomes. Data science and big data methods are promising in providing actionable knowledge for quality improvement, with real-time data that could support decision-making. Heart failure is a chronic condition that has proven to be useful for measuring medical and healthcare quality. Evidence-based indicators have already reached high rates of adherence and are currently poorly correlated with outcomes. Using real-life data and based on the patient's perspective can be useful tools to improve these indicators.
Entities:
Keywords:
Big data; Health indicators; Heart failure; Outcome; Quality of care; Readmission
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