Evaluating Code Duplication to Identify Rich Business Objects from Data Transfer Objects

Java Enterprise Applications (JEAs) are complex software systems written using multiple technologies. Moreover they are usually distributed systems and use a database to deal with persistence. A particular problem that appears in the design of these systems is the lack of a rich business model. In this paper we propose a technique to support the recovery of such rich business objects starting from anemic Data Transfer Objects (DTOs). Exposing the code duplications in the application's elements using the DTOs we suggest which business logic can be moved into the DTOs from the other classes.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

The German business and information technologies project

The Business and Information Technologies (BIT) project strives to reveal new insights into how modern IT impacts organizational structures and business practices using empirical methods. Due to its international scope, it allows for inter-country comparison of empirical results. Germany — represented by the European School of Management and Technologies (ESMT) and the Institute of Information Systems at Humboldt-Universität zu Berlin — joined the BIT project in 2006. This report presents the result of the first survey conducted in Germany during November–December 2006. The key results are as follows: • The most widely adopted technologies and systems in Germany are websites, wireless hardware and software, groupware/productivity tools, and enterprise resource planning (ERP) systems. The biggest potential for growth exists for collaboration and portal tools, content management systems, business process modelling, and business intelligence applications. A number of technological solutions have not yet been adopted by many organizations but also bear some potential, in particular identity management solutions, Radio Frequency Identification (RFID), biometrics, and third-party authentication and verification. • IT security remains on the top of the agenda for most enterprises: budget spending was increasing in the last 3 years. • The workplace and work requirements are changing. IT is used to monitor employees' performance in Germany, but less heavily compared to the United States (Karmarkar and Mangal, 2007).1 The demand for IT skills is increasing at all corporate levels. Executives are asking for more and better structured information and this, in turn, triggers the appearance of new decision-making tools and online technologies on the market. • The internal organization of companies in Germany is underway: organizations are becoming flatter, even though the trend is not as pronounced as in the United States (Karmarkar and Mangal, 2007), and the geographical scope of their operations is increasing. Modern IT plays an important role in enabling this development, e.g. telecommuting, teleconferencing, and other web-based collaboration formats are becoming increasingly popular in the corporate context. • The degree to which outsourcing is being pursued is quite limited with little change expected. IT services, payroll, and market research are the most widely outsourced business functions. This corresponds to the results from other countries. • Up to now, the adoption of e-business technologies has had a rather limited effect on marketing functions. Companies tend to extract synergies from traditional printed media and on-line advertising. • The adoption of e-business has not had a major impact on marketing capabilities and strategy yet. Traditional methods of customer segmentation are still dominating. The corporate identity of most organizations does not change significantly when going online. • Online sales channel are mainly viewed as a complement to the traditional distribution means. • Technology adoption has caused production and organizational costs to decrease. However, the costs of technology acquisition and maintenance as well as consultancy and internal communication costs have increased.

Strengthening the Reporting of Observational Studies in Epidemiology for respondent-driven sampling studies: "STROBE-RDS" statement.

OBJECTIVES Respondent-driven sampling (RDS) is a new data collection methodology used to estimate characteristics of hard-to-reach groups, such as the HIV prevalence in drug users. Many national public health systems and international organizations rely on RDS data. However, RDS reporting quality and available reporting guidelines are inadequate. We carried out a systematic review of RDS studies and present Strengthening the Reporting of Observational Studies in Epidemiology for RDS Studies (STROBE-RDS), a checklist of essential items to present in RDS publications, justified by an explanation and elaboration document. STUDY DESIGN AND SETTING We searched the MEDLINE (1970-2013), EMBASE (1974-2013), and Global Health (1910-2013) databases to assess the number and geographical distribution of published RDS studies. STROBE-RDS was developed based on STROBE guidelines, following Guidance for Developers of Health Research Reporting Guidelines. RESULTS RDS has been used in over 460 studies from 69 countries, including the USA (151 studies), China (70), and India (32). STROBE-RDS includes modifications to 12 of the 22 items on the STROBE checklist. The two key areas that required modification concerned the selection of participants and statistical analysis of the sample. CONCLUSION STROBE-RDS seeks to enhance the transparency and utility of research using RDS. If widely adopted, STROBE-RDS should improve global infectious diseases public health decision making.

Time relevance, citation of reporting guidelines, and breadth of literature search in systematic reviews in orthodontics

INTRODUCTION As the importance of systematic review (SR) conclusions relies upon the scientific rigor of methods and the currency of evidence, we aimed to investigate the currency of orthodontic SRs using as proxy the time from the initial search to publication. Additionally, SR information regarding reporting guidelines, registration, and literature searches were recorded when available. MATERIALS AND METHODS A systematic PubMed search was carried out using the Clinical Queries page to identify orthodontic SRs cited between 1 January 2008 and 7 November 2013. Data related to reporting guidelines, review registration, dates of review processing, literature search, and abstract reporting were retrieved and classified by journal type. Survival analysis was used to assess the time to reach predefined manuscript stages for orthodontic and non-orthodontic journals. RESULTS One hundred twenty seven of the originally identified 585 SRs were considered eligible. The median interval from search until publication was 13.2 months (interquartile range: IQR = 9.7 months) irrespective of the journal type. There was evidence (P = 0.05) that SRs published by non-orthodontic journals appeared in PubMed faster than in orthodontic journals (non-orthodontic: median = 6.5 months; IQR = 5.7 months; orthodontic: median = 10.2 months; IQR = 5.6 months) from submission to publication and from acceptance to publication (non-orthodontic: median = 1.5 months; IQR = 2.4 months; orthodontic: median = 6.0 months; IQR = 6.2 months; P < 0.001). More than half of these SRs did not cite adherence to any reporting guidelines, whereas all but five studies were not prospectively registered. Search of unpublished research was undertaken in approximately 21 per cent and 29 per cent of the SRs published in non-orthodontic and orthodontic periodicals, respectively. CONCLUSIONS This study indicates that SR users should be aware that median time for orthodontic SRs from search to publication is 13.2 months. SRs published in non-orthodontic journals are likely to be more current in terms of submission until time to publication and acceptance until time to publication compared with those published in orthodontic journals.

Justification of Data Warehousing Projects

Project justification is regarded as one of the major methodological deficits in Data Warehousing practice. As reasons for applying inappropriate methods, performing incomplete evaluations, or even entirely omitting justifications, the special nature of Data Warehousing benefits and the large portion of infrastructure-related activities are stated. In this paper, the economic justification of Data Warehousing projects is analyzed, and first results from a large academiaindustry collaboration project in the field of non-technical issues of Data Warehousing are presented. As conceptual foundations, the role of the Data Warehouse system in corporate application architectures is analyzed, and the specific properties of Data Warehousing projects are discussed. Based on an applicability analysis of traditional approaches to economic IT project justification, basic steps and responsibilities for the justification of Data Warehousing projects are derived.

Systemic conditions and treatments as risks for implant therapy

PURPOSE: To evaluate whether systemic diseases with/without systemic medication increase the risk of implant failure and therefore diminish success and survival rates of dental implants. MATERIALS AND METHODS: A MEDLINE search was undertaken to find human studies reporting implant survival in subjects treated with osseointegrated dental implants who were diagnosed with at least one of 12 systemic diseases. RESULTS: For most conditions, no studies comparing patients with and without the condition in a controlled setting were found. For most systemic diseases there are only case reports or case series demonstrating that implant placement, integration, and function are possible in affected patients. For diabetes, heterogeneity of the material and the method of reporting data precluded a formal meta-analysis. No unequivocal tendency for subjects with diabetes to have higher failure rates emerged. The data from papers reporting on osteoporotic patients were also heterogeneous. The evidence for an association between osteoporosis and implant failure was low. Nevertheless, some reports now tend to focus on the medication used in osteoporotic patients, with oral bisphosphonates considered a potential risk factor for osteonecrosis of the jaws, rather than osteoporosis as a risk factor for implant success and survival on its own. CONCLUSIONS: The level of evidence indicative of absolute and relative contraindications for implant therapy due to systemic diseases is low. Studies comparing patients with and without the condition in a controlled setting are sparse. Especially for patients with manifest osteoporosis under an oral regime of bisphosphonates, prospective controlled studies are urgently needed.

The application of medical informatics to the veterinary management programs at companion animal practices in Alberta, Canada: a case study.

Companion animals closely share their domestic environment with people and have the potential to, act as sources of zoonotic diseases. They also have the potential to be sentinels of infectious and noninfectious, diseases. With the exception of rabies, there has been minimal ongoing surveillance of, companion animals in Canada. We developed customized data extraction software, the University of, Calgary Data Extraction Program (UCDEP), to automatically extract and warehouse the electronic, medical records (EMR) from participating private veterinary practices to make them available for, disease surveillance and knowledge creation for evidence-based practice. It was not possible to build, generic data extraction software; the UCDEP required customization to meet the specific software, capabilities of the veterinary practices. The UCDEP, tailored to the participating veterinary practices', management software, was capable of extracting data from the EMR with greater than 99%, completeness and accuracy. The experiences of the people developing and using the UCDEP and the, quality of the extracted data were evaluated. The electronic medical record data stored in the data, warehouse may be a valuable resource for surveillance and evidence-based medical research.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Reporting and handling missing outcome data in mental health: a systematic review of Cochrane systematic reviews and meta-analyses

OBJECTIVES The purpose of the study was to provide empirical evidence about the reporting of methodology to address missing outcome data and the acknowledgement of their impact in Cochrane systematic reviews in the mental health field. METHODS Systematic reviews published in the Cochrane Database of Systematic Reviews after January 1, 2009 by three Cochrane Review Groups relating to mental health were included. RESULTS One hundred ninety systematic reviews were considered. Missing outcome data were present in at least one included study in 175 systematic reviews. Of these 175 systematic reviews, 147 (84%) accounted for missing outcome data by considering a relevant primary or secondary outcome (e.g., dropout). Missing outcome data implications were reported only in 61 (35%) systematic reviews and primarily in the discussion section by commenting on the amount of the missing outcome data. One hundred forty eligible meta-analyses with missing data were scrutinized. Seventy-nine (56%) of them had studies with total dropout rate between 10 and 30%. One hundred nine (78%) meta-analyses reported to have performed intention-to-treat analysis by including trials with imputed outcome data. Sensitivity analysis for incomplete outcome data was implemented in less than 20% of the meta-analyses. CONCLUSIONS Reporting of the techniques for handling missing outcome data and their implications in the findings of the systematic reviews are suboptimal.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.