Building a Harmonized Datamart by Integrating Cross-Institutional Systems of Clinical, Outcome, and Genomic Data: The Pediatric Patient Informatics Platform (PPIP)

PURPOSE Siloed electronic medical data limits utility and accessibility. At the Dana-Farber/Boston Children's Cancer and Blood Disorders Center, cross-institutional data were inconsistent and difficult to access. To unify data for clinical operations, administration, and research, we developed the Pediatric Patient Informatics Platform ( PPIP), an integrated datamart harmonizing multiple source systems across two institutions into a common technology. PATIENTS AND METHODS Starting in 2009, user requirements were gathered and data sources were prioritized. Project teams, including biostatisticians, database developers, and an external contractor, were formed. Read-access to source systems was established. The 3-layer PPIP architecture was developed: STAGING, a near-exact copy of source data; INTEGRATION, where data were reorganized into domains; and, CONSUMPTION, where data were optimized for rapid retrieval. The diverse systems were integrated into a common IBM Netezza technology. Data filters were defined to accurately capture the Center's patients, and derived data items were created for harmonization across sources. An interactive online query tool, PPIP360, was developed using Microstrategy Analytics. RESULTS Driven by scientific objectives, the PPIP datamart was created, including 33,674 patients, 2,983 protocols, and 3.6 million patient visits from 14 source databases, 164 source tables, and 2,622 source data items. The PPIP360 has 605 data items and 33 metrics across 11 reports and dashboards. Dana-Farber and Boston Children's established a legal data-sharing agreement. The PPIP has supported hundreds of faculty, staff, and projects, including planning clinical trials and informing strategic planning. CONCLUSION The PPIP has successfully harmonized and integrated diagnostic, demographic, laboratory, treatment, clinical outcome, pathology, transplant, meta-protocol, and –omics data, for efficient, daily operational and research activities at Dana-Farber/Boston Children's Cancer and Blood Disorders Center, and future external sharing.

Google search data as a novel adjunct to patient and public involvement in rheumatology research

Patient and public involvement is essential in the design and implementation of research studies to ensure research remains relevant and in line with public priorities. Public views on a given area of research may be sought via platforms such as focus groups or surveys. Here, we present the use of an openly available Google search data query tool, which may be used alongside traditional forms of patient and public involvement in research to highlight public perceptions and priorities. We used an online search query tool (“AnswerThePublic.com”) to explore public Google searches relating to “arthritis,” and an exemplar rheumatic disease, “rheumatoid arthritis.” The most common searches relating to these diseases included quality of life, treatment, prognosis, as well as impacts on life, including work. However, they also reveal concerns that may be more difficult to elicit in face-to-face focus groups, such as questions on alcohol consumption in arthritis, and impacts on mental health. Using public search engine data in research, alongside the important traditional methods of patient and public involvement, is a cost-effective and time-efficient method of gauging public views and concerns on a given topic. It may facilitate broad scoping searches of public priorities and help to guide future research questions.

More Focus Is Needed to Reduce Adverse Events for Diabetes Devices

Advances in devices for people with diabetes have demonstrated many improvements; yet, the number of adverse events has almost doubled from 2018 to 2019. It is a challenge to examine these events due to a difficult query tool on the FDA website. There are several possible reasons why effort is not devoted to decreasing the number of adverse events including the fact that user error is a common cause. This commentary serves to raise awareness of the adverse event problem.

Trends of the incidence of drug use disorders from 1990 to 2017: an analysis based on the Global Burden of Disease 2017 data

Aim Drug use disorders are an important issue worldwide. Systematic attempts to estimate the global incidence of drug use disorders are rare. We aimed to determine the incidence of drug use disorders and their trends. Methods We obtained the annual incident cases and age-standardised incidence rate (ASR) of drug use disorders from 1990 to 2017 using the Global Health Data Exchange query tool. The estimated annual percentage changes of the ASR were used to quantify and evaluate the trends in the incidence rate. Gaussian process regression and the Pearson's correlation coefficient were used to assess the relationship between the ASR and socio-demographic index (SDI). Results The number of drug use disorders’ cases increased by 33.5% from 1990 to 2017 globally, whereas the ASR exhibited a stable trend. The ASR was higher in men than in women. Most cases (53.1%) of drug use disorders involved opioid. A positive association (ρ=0.35, p < 0.001) was found between ASR and SDI. Teenagers aged 15–19 years had the highest incidence rate. Conclusions The incident cases of drug use disorders were increasing, but the incidence rate did not change significantly from 1990 to 2017. Current preventive measures and policies for drug use disorders might have little effect. The present results suggest that future strategies should focus on men, teenagers and high-risk regions in order to improve the current status of drug use disorders.

Dr. Query

Drugs can help us to treat disease, but sometimes medication can cause severe side effects. With a little knowledge, one can have drugs that are intended to prevent or avoid adverse outcome. Recognizing potential drugs enhances the quality of the healthcare system and reduces the risk associated with drug intake. Several factors like drug-drug interactions and side effects should be known to us before we intake drugs. So, the authors' motive is to develop a predictive mobile-based healthcare tool that would help drug consumers to find drugs which suit them best. As an outcome, the tool will provide the names of the top 10 medicines that will be best for specified indications and do not cause specified side effects and do not or least interact with mentioned drugs. Proposed mobile-based drug query tool will provide exact query matching drugs as well as close matches by leveraging machine learning in the tool.

Suitability Mapping for Managed Aquifer Recharge: Development of Web-Tools

Suitability maps for managed aquifer recharge (MAR) are increasingly used and hold the potential to be integrated into sustainable groundwater management plans. However, the quality of the maps strongly depends on the input data quality as well as the expertise of the decision-maker. The maps are commonly derived through GIS-based multi-criteria decision analysis (GIS-MCDA). To date, there is no common understanding of how suitability mapping should be conducted, as there is considerable variability concerning used GIS data and MCDA methodology. This study presents two web-tools that were conceptualized based on a review of GIS-MCDA studies in the context of MAR suitability mapping. The data retrieved from the review was compiled into a web-based query tool making the MAR- and MCDA-relevant information easily accessible. Based on the most commonly used MCDA practices in the assessed studies, we conceptualized and implemented a second web tool that comprises a simplified web GIS as well as supporting tools for weight assignment and standardization of the criteria. Both web tools will enable decision-makers to engage in MCDA for MAR mapping in a more structured and informed way. As the tools are open-source and web-based, they can facilitate the collaboration between multiple stakeholders and the easy sharing of results.

The Role of Sketch Engine in Multiple Types of Corpora

A large number of dictionary projects use Sketch Engine as it is the most renowned corpus management and corpus query tool. This paper sheds light on the significant role Sketch Engine plays in relation to different types of corpora. The software’s features that support the creation of multilingual dictionaries and lexigraphy are also discussed. The software keeps on updating its old features to facilitate the users, and also adds entirely new features every now and then

Suitability maps for managed aquifer recharge: a review of multi-criteria decision analysis studies

Suitability maps for managed aquifer recharge (MAR) sites hold a strong potential for integration into sustainable groundwater management plans. An uprising method to identify sites suitable for MAR implementation is geographic information system (GIS)-based multi-criteria decision analysis (MCDA). There are no guidelines or a common understanding on how suitability mapping should be conducted, and there is considerable variability as to what factors are assessed and how they are weighted. To increase knowledge on GIS-MCDA, a database has been built based on 63 studies applying GIS-MCDA in the context of MAR site selection. Information on the criteria, assigned weights, and methodologies has been retrieved from the documents. Statistical analysis of the database depicts the current state of art for suitability mapping methodologies as well as specific information for the different recharge methods. We further incorporated the compiled information into a web-based query tool that makes the information easily accessible and the utilization of the database more user friendly. This review as well as the created web-tool will help planners of MAR sites to engage in the MCDA in a more structured way by referring to previously conducted studies and by finding information suitable for their specific project. The application potential of suitability maps is discussed along with the shortcomings of this methodology.