Hospital quality indicators: a systematic review.

PURPOSE: The purpose of this paper is to identify and describe hospital quality indicators, classifying them according to Donabedian's structure, process and outcome model and in specific domains (quality, safety, infection and mortality) in two care divisions: inpatient and emergency services. DESIGN/METHODOLOGY/APPROACH: A systematic review identified hospital clinical indicators. Two independent investigators evaluated 70 articles/documents located in electronic databases and nine documents from the grey literature, 35 were included in the systematic review. FINDINGS: In total, 248 hospital-based indicators were classified as infection, safety, quality and mortality domains. Only 10.2 percent were identified in more than one article/document and 47 percent showed how they were calculated/obtained. Although there are scientific papers on developing, validating and hospital indicator assessment, most indicators were obtained from technical reports, government publications or health professional associations. RESEARCH LIMITATIONS/IMPLICATIONS: This review identified several hospital structure, process and outcome quality indicators, which are used by different national and international groups in both research and clinical practice. Comparing performance between healthcare organizations was difficult. Common clinical care standard indicators used by different networks, programs and institutions are essential to hospital quality benchmarking. ORIGINALITY/VALUE: To the authors' knowledge, this is the first systematic review to identify and describe hospital quality indicators after a comprehensive search in MEDLINE/PubMed, etc., and the grey literature, aiming to identify as many indicators as possible. Few studies evaluate the indicators, and most are found only in the grey literature, and have been published mostly by government agencies. Documents published in scientific journals usually refer to a specific indicator or to constructing an indicator. However, indicators most commonly found are not supported by reliability or validity studies.

Assessment of potential risk factors for breast cancer in a population in Southern Brazil.

PURPOSE: The aim of this study is to assess potential risk factors for breast cancer in a population in Southern Brazil and build a multivariate logistic model using these factors for breast cancer risk prediction. METHODS: A total of 4242 women between 40 and 69 years of age without a history of breast cancer were selected at primary healthcare facilities in Porto Alegre and submitted to mammographic screening. They were evaluated for potential risk factors. RESULTS: In all, 73 participants among the 4242 women had a breast cancer diagnosis during the follow-up of the project (10 years). The multivariate analysis considering all the patients aged 40-69 years showed that older age (OR 1.08, 95% CI 1.04-1.12), higher height (OR 1.04, 95% CI 1.01-1.09), and history of previous breast biopsy (OR 2.66, 95% CI 1.38-5.13) were associated with the development of breast cancer. Conversely, the number of pregnancies (OR 0.87, 95% CI 0.78-0.98) and use of hormone replacement therapy (OR 0.39, 95% CI 0.20-0.75) were considered a protective factor. Additionally, we performed an analysis separating the participants into groups of 40-49 and 50-69 years old, since a risk factor could have a specific behavior in these age groups. No additional risk factors were identified within these age brackets, and some factors lost statistical significance. CONCLUSION: The risk prediction model indicates that the following variables should be assessed in this specific population: age, height, having had previous breast biopsies, number of pregnancies, and use of hormone replacement therapy. These findings may help to better understand the causal model of breast cancer in Southern Brazil.