Measuring Master Data Quality: Findings from a Case Study

Data quality management plays a critical role in all kinds of organizations. Data is one of the most important criteria for strategic business decisions within organizations and the foundation for the execution of business processes. For the assessment of a company’s data quality, to ensure the process execution and to monitor the effectiveness of data quality initiatives, data quality has to be measured in the same way over a certain period of time. This can be achieved by implementing a measurement system. By now, the implementation of such a system to measure data quality is realized in very few organizations. This paper presents a case study describing the implementation process of a Master Data Quality Cockpit as well as the system used for measuring. The study assesses organizational, process-related, and system level changes as well as success factors necessary to implement such a tool

A Cybernetic View on Data Quality Management

Corporate data of poor quality can have a negative impact on the performance of business processes and thereby the success of companies. In order to be able to work with data of good quality, data quality requirements must clearly be defined. In doing so, one has to take into account that both the provision of high-quality data and the damage caused by low-quality data brings about considerable costs. As each company’s database is a dynamic system, the paper proposes a cybernetic view on data quality management (DQM). First, the principles of a closed-loop control system are transferred to the field of DQM. After that a meta-model is developed that accounts for the central relations between data quality, business process perfor-mance, and related costs. The meta-model then constitutes the basis of a simulation technique which aims at the explication of assumptions (e.g. on the effect of improving a data architecture) and the support of DQM decision processes

Product data quality in supply chains: the case of Beiersdorf

A number of business requirements (e.g. compliance with regulatory and legal provisions, diffusion of global standards, supply chain integration) are forcing consumer goods manufacturers to increase their efforts to provide product data (e.g. product identifiers, dimensions) at business-to-business interfaces timely and accurately. The quality of such data is a critical success factor for efficient and effective cross-company collaboration. If compliance relevant data (e.g. dangerous goods indicators) is missing or false, consumer goods manufacturers risk being fined and see their company's image damaged. Or if logistics data (e.g. product dimensions, gross weight) is inaccurate or provided not in time, business with key account trading partners is endangered. To be able to manage the risk of business critical data defects, companies must be able to a) identify such data defects, and b) specify and use metrics that allow to monitor the data's quality. As scientific research on both these issues has come up with only few results so far, this case study explores the process of identifying business critical product data defects at German consumer goods manufacturing company Beiersdorf AG. Despite advanced data quality management structures such defects still occur and can result in complaints, service level impairment and avoidable costs. The case study analyzes product data use and maintenance in Beiersdorf's ecosystem, identifies typical product data defects, and proposes a set of data quality metrics for monitoring those defect

Reducing preventable adverse events in obstetrics by improving interprofessional communication skills - Results of an intervention study.

BACKGROUND: Progress in medicine involves the structured analysis and communication of errors. Comparability between the individual disciplines is only possible to a limited extent and obstetrics plays a special role: the expectation of a self-determined and joyful event meets with possibly serious complications in highly complex care situations. This must be managed by an interdisciplinary team with an increasingly condensed workload. Adverse events cannot be completely controlled. However, taking controllable risk factors into account and with a focused communication a reduction of preventable adverse events is possible. In the present study, the effect of interprofessional team training on preventable adverse events in an obstetric department was investigated. METHODS: The training consisted of a 4-h interdisciplinary training session based on psychological theories. Preventable adverse events were defined in six categories according to potential patterns of causation. 2,865 case records of a refence year (2018) and 2,846 case records of the year after the intervention (2020) were retrospectively evaluated. To determine the communication training effect, the identified preventable adverse events of 2018 and 2020 were compared according to categories and analyzed for obstetrically relevant controllable and uncontrollable risk factors. Questionnaires were used to identify improvements in self-reported perceptions and behaviors. RESULTS: The results show that preventable adverse events in obstetrics were significantly reduced after the intervention compared to the reference year before the intervention (13.35% in the year 2018 vs. 8.83% in 2020, p < 0.005). Moreover, obstetrically controllable risk factors show a significant reduction in the year after the communication training. The questionnaires revealed an increase in perceived patient safety (t(28) = 4.09, p < .001), perceived communication behavior (t(30) = -2.95, p = .006), and self-efficacy to cope with difficult situations (t(28) = -2.64, p = .013). CONCLUSIONS: This study shows that the communication training was able to reduce preventable adverse events and thus increase patient safety. In the future, regular trainings should be implemented alongside medical emergency trainings in obstetrics to improve patient safety. Additionally, this leads to the strengthening of human factors and ultimately also to the prevention of second victims. Further research should follow up implementing active control groups and a randomized-controlled trail study design. TRIAL REGISTRATION: The study was approved by the Ethics Committee of University Hospital  (protocol code 114/19-FSt/Sta, date of approval 29 May 2019), study registration: NCT03855735

Association between winter anthocyanin production and drought stress in angiosperm evergreen species

Leaves of many evergreen angiosperm species turn red under high light during winter due to the production of anthocyanin pigments, while leaves of other species remain green. There is currently no explanation for why some evergreen species exhibit winter reddening while others do not. Conditions associated with low leaf water potentials (Ψ) have been shown to induce reddening in many plant species. Because evergreen species differ in susceptibility to water stress during winter, it is hypothesized that species which undergo winter colour change correspond with those that experience/tolerate the most severe daily declines in leaf Ψ during winter. Six angiosperm evergreen species which synthesize anthocyanin in leaves under high light during winter and five species which do not were studied. Field Ψ, pressure/volume curves, and gas exchange measurements were derived in summer (before leaf colour change had occurred) and winter. Consistent with the hypothesis, red-leafed species as a group had significantly lower midday Ψ in winter than green-leafed species, but not during the summer when all the leaves were green. However, some red-leafed species showed midday declines similar to those of green-leafed species, suggesting that low Ψ alone may not induce reddening. Pressure–volume curves also provided some evidence of acclimation to more negative water potentials by red-leafed species during winter (e.g. greater osmotic adjustment and cell wall hardening on average). However, much overlap in these physiological parameters was observed as well between red and green-leafed species, and some of the least drought-acclimated species were red-leafed. No difference was observed in transpiration (E) during winter between red and green-leaved species. When data were combined, only three of the six red-leafed species examined appeared physiologically acclimated to prolonged drought stress, compared to one of the five green-leafed species. This suggests that drought stress alone is not sufficient to explain winter reddening in evergreen angiosperms

Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr