Abstract

The MarketScan Commercial Database (previously called the 'MarketScan Database') contains real-world data for healthcare research and analytics to examine health economics and treatment outcomes.

This page also contains the MarketScan Commercial Lab Database starting in 2018.

Methodology

MarketScan Research Databases are a family of data sets that fully integrate many types of data for healthcare research, including:

• De-identified records of more than 188 million patients (medical, drug and dental)

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• Laboratory results

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• Hospital discharges

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The MarketScan Databases track millions of patients throughout the healthcare system. The data are contributed by large employers, managed care organizations, hospitals, EMR providers, and Medicare.

Usage

This page contains the MarketScan Commercial Database.

We also have the following on other pages:

• The MarketScan Medicare Supplemental Database
• The MarketScan Dental Database
• The MarketScan Benefit Plan Design data
• MarketScan Redbook (The MarketScan Code Reference Book)

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Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to support@stanfordphs.freshdesk.com for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Data Documentation

Data access is required to view this section.

Section 2

Metadata access is required to view this section.

Section 3

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Usage FAQs (Answers provided in User Guide starting on page 56)

Metadata access is required to view this section.

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Abstract

The MarketScan Medicare Supplemental Database provides detailed cost, use and outcomes data for healthcare services performed in both inpatient and outpatient settings.

It Include Medicare Supplemental records for all years, and Medicare Advantage records starting in 2020.

This page also contains the MarketScan Medicare Lab Database starting in 2018.

Methodology

MarketScan Research Databases are a family of data sets that fully integrate many types of data for healthcare research, including:

• De-identified records of more than 250 million patients (medical, drug and dental)

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• Laboratory results

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• Hospital discharges

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The MarketScan Databases track millions of patients throughout the healthcare system. The data are contributed by large employers, managed care organizations, hospitals, EMR providers and Medicare.

Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

support@stanfordphs.freshdesk.com for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Data Documentation

Data access is required to view this section.

Section 2

Metadata access is required to view this section.

Section 3

Metadata access is required to view this section.

The SCAN data retrieval tools provides an interactive process to identify and retrieve data from individual SCAN sites. The user does not need to know the ID for the site but must know either it's general location or the name of the site

Abstract

The MarketScan Dental Database is a standalone product that corresponds with and is linkable to a given year and version of the IBM MarketScan Commercial Claims and Encounters Database and the MarketScan Medicare Supplemental and Coordination of Benefits Database. Currently, data is available for the years: 2005 - 2023. In order to view the MarketScan Dental user guide or data dictionary, you must have data access to this dataset.

Usage

In addition to what's on this page, we also have:

• The MarketScan Commercial Database
• The MarketScan Medicare Supplemental Database
• The MarketScan Benefit Plan Design data

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• MarketScan Redbook (The MarketScan Code Reference Book)

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Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

support@stanfordphs.freshdesk.com for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Data Documentation

Data access is required to view this section.

Section 3

Metadata access is required to view this section.

Section 4

Metadata access is required to view this section.

Section 5

Metadata access is required to view this section.

Section 6

Metadata access is required to view this section.

Popular DBMS, including MySQL, Postgres, MSSQL, Redis, Mongo, Oracle, ElasticSearch, Memcashed and database managers like phpMyAdmin.

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded.

This dataset presents the raw and processed sidescan mosaic for surveys completed along the 58‐km long Assateague barrier island stretching from the Ocean City inlet in Maryland, down past Chincoteague Island in northern Virginia. The data was collected June 20th-25th, 2014 and May 12th - 21th, 2015. Full coverage side-scan sonar and partial coverage bathymetry data were collected using an EdgeTech 6205 Multiphase Echosounder. In total, 73 square kilometers were mapped at primarily at 100m line spacing and 80 m swath range per channel (to allow overlap between lines).

Reupload of anonymized postmortem CT scans of the whole body originally published by Michael Kistler through the SICAS Medical Image Repository (smir.ch) as open access Virtual Skeleton Database (VSD). The CT datasets were provided by the forensic institutes of the universities of Bern and Zürich and shared under the Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license after ethical approval of the Cantonal Ethics Committee Bern. Further information can be found in:

• Kistler, M., Bonaretti, S., Pfahrer, M., Niklaus, R. & Büchler, P. The virtual skeleton database: an open access repository for biomedical research and collaboration. Journal of Medical Internet Research 15(11), e245; 10.2196/jmir.2930 (2013).
• Kistler, M. A database framework to incorporate statistical variability in biomechanical simulations. PhD thesis. Faculty of Medicine of the University of Bern; boristheses.unibe.ch/916 (2014).

Due to ongoing difficulties in accessing the SMIR website a mirror of the original VSDFullBody datasets without any alterations is provided.

CAUTION: The VSD contains a few inconsistencies, such as duplicate CT datasets. The uploader is not connected to the SMIR or VSD and, therefore, not responsible for errors in the VSD. However, errors that the uploader recognized during the work with the VSD were logged in an Excel file: VSD_Comments.xlsx

Datasets of the VSD were used for the creation of surface models of the lower body's osseous anatomy. Further information can be found in:

• Fischer, M. C. M. Database of segmentations and surface models of bones of the entire lower body created from cadaver CT scans. Scientific Data 10, 763; 10.1038/s41597-023-02669-z (2023).

The side scan sonar survey was done simultaneously with the bathymetry swath survey and used an EdgeTech Model 4125 Towfish bow-mounted from Lookdown at 400 and 900 kHz. The 4125 Towfish utilizes EdgeTech’s Full Spectrum CHIRP technology to produce higher resolution images than a non-CHIRP system. EdgeTech Discovery Software was used to acquire the side scan sonar data using the JSF format at a resolution of about 2.3 cm. All JSF files collected using EdgeTech’s Discover Software were processed using John Gann’s Chesapeake Technology SonarWiz5. Dimensions of contacts should be considered accurate to +/- 30% of the measured dimensions. This system also records the direct arrival intensity data.

The CATH-Gene3D database describes protein families and domain architectures in complete genomes. Protein families are formed using a Markov clustering algorithm, followed by multi-linkage clustering according to sequence identity. Mapping of predicted structure and sequence domains is undertaken using hidden Markov models libraries representing CATH and Pfam domains. CATH-Gene3D is based at University College, London, UK.

Paper logs are the primary data collection tool used by observers of the Northeast Fisheries Observer Program deployed on commercial fishing vessels. After the data collected on the paper are entered into a database, the paper logs are scanned for each trip. After all trips for a calendar year are scanned, they are archived at the National Archives and Records Administration.

Corescan© Hyperspectral Core Imager Mark III (HCI-III) system data were acquired for hand samples, and subsequent billets made from the hand samples, collected during the U.S. Geological Survey (USGS) 2014, 2015, and 2016 field seasons in the Nabesna area of the eastern Alaska Range. The HCI-III system consists of three different components. The first is an imaging spectrometer which collects reflectance data with a spatial resolution of approximately 500 nanometers (nm) for 514 spectral channels covering the 450-2,500 nm wavelength range of the electromagnetic spectrum (Martini and others, 2017). The second is a spectrally calibrated RGB camera that collects high resolution imagery of the samples with a 50 micrometer (μm) pixel size. The third component is a three-dimensional (3D) laser profiler that measures sample texture, surface features and shape with a vertical resolution of 20 μm (Martini and others, 2017). Corescan reflectance data were provided for a total of 63 hand samples and four billets analyzed using the HCI-III system in three scans.

Abstract

The MarketScan Benefit Plan Design Database represents the benefit plans for large employers whose claims data comprise portions of the MarketScan Commercial Claims and Encounters Database. Currently, data is available for 2013 - 2023.

Usage

In addition to what's on this page, we also have:

• The MarketScan Commercial Database
• The MarketScan Medicare Supplemental Database
• The MarketScan Dental Database

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• MarketScan Redbook (The MarketScan Code Reference Book)

%3C!-- --%3E

Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

support@stanfordphs.freshdesk.com for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Documentation

Data access is required to view this section.

4043 Global import shipment records of Scan with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

R code and data for a landscape scan of data services at academic libraries. Original data is licensed CC By 4.0, data obtained from other sources is licensed according to the original licensing terms. R scripts are licensed under the BSD 3-clause license. Summary This work generally focuses on four questions:

Which research data services does an academic library provide? For a subset of those services, what form does the support come in? i.e. consulting, instruction, or web resources? Are there differences in support between three categories of services: data management, geospatial, and data science? How does library resourcing (i.e. salaries) affect the number of research data services?

Approach Using direct survey of web resources, we investigated the services offered at 25 Research 1 universities in the United States of America. Please refer to the included README.md files for more information.

For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu

This data set contains hourly resolution surface meteorological and soils data from the United States Department of Agriculture Natural Resources Conservation Service (USDA/NRCS) Soil Climate Analysis Network (SCAN). This data set includes data from the SCAN stations in the SMEX02 region for the period from 1 June to 31 July 2002. The data are columnar ASCII format.

The objective of this shape retrieval contest is to retrieve 3D models those are relevant to a query range scan. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database. Task description: In response to a given set of queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query. The set of query consists of range images. Data set: The query set is composed of 120 range images, which are acquired by capturing 3 range scans of 40 models from arbitrary view directions. The range images are captured using a Minolta Laser Scanner. The file format is in the ASCII Object File Format (.off) representing the scan in a triangular mesh. The target database contains 800 complete 3D models, which are categorized into 40 classes. In each class there are 20 models. The file format to represent the 3D models is the ASCII Object File Format (.off). Evaluation Methodology: We will employ the following evaluation measures: Precision-Recall curve; Average Precision (AP) and Mean Average Precision (MAP); E-Measure; Discounted Cumulative Gain; Nearest Neighbor, First-Tier (Tier1) and Second-Tier (Tier2). Please Cite the Paper: Dutagaci H, Godil A, Cheung CP, Furuya T, Hillenbrand U, Ohbuchi R. SHREC'10 Track: Range Scan Retrieval. In3DOR 2010 May 2 (pp. 109-115). http://dx.doi.org/10.2312/3DOR/3DOR10/109-115

Track share of shelf, predict revenue surprises, and drill down into brand and category level performance by household demography across thousands of brands and hundreds of manufacturers. Scanner Consumer Packaged Goods (CPG) data is sourced from thousands of retail stores and millions of underlying US households across grocery and drugstore chains. Available exclusively to investors.

The greater Seattle Coronavirus Assessment Network (SCAN) study is a response to the novel coronavirus outbreak (COVID-19). Since March 23rd, 2020, SCAN has worked in collaboration with Public Health Seattle & King County to deliver and collect at-home COVID-19 tests. The SCAN study is focused on testing people who are experiencing symptoms of COVID-19, and is working to increase testing in underrepresented communities and populations. The SCAN dashboard provides geographic and demographic information from King County about who is ordering a test kit (individuals, contacts and groups) and may differ from the testing data which includes all final results (positive, negative and inconclusive). Reported positives and positivity rate are a combination of general SCAN enrollment and contact testing results, and are not representative of overall population frequency. There was a pause in testing from May 13th through June 9th, during which time SCAN worked with the FDA to update procedures and certifications. Data is updated daily, subject to change and may vary across other technical reports due to the specific analyses being performed.