Use of logistic regression for developing risk-adjusted quality indicators in nursing.

OBJECTIVES: A low rate of newly developed pressure ulcers is considered as an important quality indicator in nursing. However, the result of a hospital depends not only on the quality of care but on the risk profile of its patients as well. Therefore, based on multiple logistic regression models we describe a method for calculating risk-adjusted quality indicators in nursing. METHOD: Based on data of 1,009,989 patients from 1747 hospitals in 2009, we developed two multiple logistic regression models to identify and to weigh a possible joint influence of several risk factors on newly developed pressure ulcers. In a further step, we calculated risk-adjusted rates. RESULTS: Factors remaining in the regression models were "micro-movements on admission", "diabetes mellitus", "age" and "days on intensive care unit". Based on the corresponding regression coefficients and the logistic function, the expected rate of newly developed pressure ulcers was calculated for every hospital. Finally, expected rates and observed rates both were used to calculate risk-adjusted rates. CONCLUSION: The simultaneous consideration of relevant risk factors by means of risk-adjusted quality indicators ensures a fair comparison of hospitals.

[Organization of methodological support and cross-project research activities in multicenter research programmes - experiences of the centers for methodological support within the "rehabilitation science" research network]. / Organisation methodischer Beratung und projektübergreifender Forschungsaktivitäten in multizentrischen Forschungsprogrammen - Erfahrungen der Methodenzentren im Verbundforschungsprogramm Rehabilitationswissenschaften.

On completion of the funding period of six years within the federal programme for research in medical rehabilitation, an evaluative summary is given of the work performed and the experiences made in the cross-sectional projects offering methodological support. While specific research profiles had prevailed in each of the eight regional research networks, two institutions had been implemented with similar task assignments within all networks; i. e., (i) a central office, and (ii) a center for methodological support (CMS) had been available in order to enhance methodological research infrastructure and research quality of the clinical projects. This article outlines the support offered as well as further tasks of the CMS. Further, it is argued that organized, scientifically based methodological support and consultation should be part of any research network. Finally, a number of important aspects are discussed which should be taken into account to enhance research quality in medical rehabilitation in the future.

[Analyzing interrater agreement for categorical data using Cohen's kappa and alternative coefficients]. / Analyse der Beurteilerübereinstimmung für kategoriale Daten mittels Cohens Kappa und alternativer Masse.

Within rehabilitation research ratings are one of the most frequently used assessment procedures. For example, therapists frequently make categorical judgements aiming to get information whether specific patient characteristics prevail or not (dichotomous rating format) or which of several alternatives holds for a patient (polytomous rating format). Interrater agreement is an important prerequisite to ensure that reliable and meaningful information concerning patients' state can be inferred from the data obtained. Cohen's kappa (Cohen's kappa) is the most frequently used measure to quantify interrater agreement. The properties of Cohen's kappa are characterized and conditions for the appropriate application of kappa are clarified. Because sometimes specific properties of kappa are not appropriately considered, misleading interpretations of this measure may easily arise. This is the case because the value of Cohen's kappa is affected by information aspects that are independent of the quality of the rating process. In order to avoid such misconceptions, alternative evaluation strategies are described for dichotomous rating formats which enhance agreement analysis and thus ensure a more valid interpretation. In addition, it is shown how weighted Cohen's kappa (omega) may be used to analyze polytomous rating formats.

[Aspects of sample size determination and power calculation illustrated on examples from rehabilitation research]. / Aspekte der Fallzahlkalkulation und Powerberechnung anhand von Beispielen aus der rehabilitationswissenschaftlichen Forschung.

Often it is reported in medical studies that an expected effect could not be detected. This may be the case if the sample size had been too small to detect an effect which actually exists. This often is due to the fact that sound sample size estimation had been omitted prior to the study outset. As a result, it is not known how many persons should have been involved in the study to detect this effect if present. On the other hand, if sample size estimation has not been realized, more persons than needed might be included in the study. This is problematic for economic and in particular for ethical reasons. The aim of this paper is to point out the principles of sample size estimation as well as to emphasize its importance not only in general but also in medical rehabilitation research.