Software suite of proprietary databases that contain one of longest running and largest collection of privately and publicly insured, de identified patient data in USA. Family of data sets that fully integrate many types of data for healthcare research.

Abstract

MarketScan databases in the OMOP data model (https://www.ohdsi.org/data-standardization/the-common-data-model/)

The IBM MarketScan® Research Databases contain real-world data for healthcare research and analytics to examine health economics and treatment outcomes.

Abstract

This is an empty dataset for the purposes of managing permissions. This dataset will be decommissioned in January of 2021. Please add it to any study where you are using IBM MarketScan. This will ensure you do not lose data access.

This dataset is a de-identified summary table of prevalence rates for vision and eye health data indicators from the 2016 MarketScan® Commercial Claims and Encounters Data (CCAE) is produced by Truven Health Analytics, a division of IBM Watson Health. The CCEA data contain a convenience sample of insurance claims information from person with employer-sponsored insurance and their dependents, including 43.6 million person years of data. Prevalence estimates are stratified by all available combinations of age group, gender, and state. Detailed information on VEHSS MarketScan analyses can be found on the VEHSS MarketScan webpage (cdc.gov/visionhealth/vehss/data/claims/marketscan.html). Information on available Medicare claims data can be found on the IBM MarketScan website (https://marketscan.truvenhealth.com). The VEHSS MarketScan summary dataset was last updated November 2019.

The potential therapeutic benefit of fluoxetine with standard of care treatment was evaluated in GBM patients cohort using electronic medical records from the IBM MarketScan Dataset (2003-2017). GBM Patients with two other SSRIs, citalopram and escitalopram, were used as controls. The dataset includes six figures: data S1 Figures 1-6 which provide more details of the data overview, data extraction pipeline, exclusion criteria, enrichment for GBM patients, statistical analyses, and results.

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

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Section 4

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Section 5

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Section 6

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Demographics of unique persons in IBM MarketScan database with at least one health insurance claim with diagnosis of bipolar disorder, schizophrenia, Parkinson disease, personality disorder, epilepsy, or major depression during 2003 to 2013.

The most common first-line PD medication for US patients in the IBM marketscan databasea.

Steps to identify care episodes for three study populations from the linked claims-EHR databases.

Background: Trajectories of comorbidities among individuals at risk of Alzheimer’s disease (AD) may differ from those aging without AD clinical syndrome. Therefore, characterizing the comorbidity burden and pattern associated with AD risk may facilitate earlier detection, enable timely intervention, and help slow the rate of cognitive and functional decline in AD. This case-control study was performed to compare the prevalence of comorbidities between AD cases and controls during the 5 years prior to diagnosis (or index date for controls); and to identify comorbidities with a differential time-dependent prevalence trajectory during the 5 years prior to AD diagnosis.Methods: Incident AD cases and individually matched controls were identified in a United States claims database between January 1, 2000 and December 31, 2016. AD status and comorbidities were defined based on the presence of diagnosis codes in administrative claims records. Generalized estimating equations were used to assess evidence of changes over time and between AD and controls. A principal component analysis and hierarchical clustering was performed to identify groups of AD-related comorbidities with respect to prevalence changes over time (or trajectory), and differences between AD and controls.Results: Data from 186,064 individuals in the IBM MarketScan Commercial Claims and Medicare Supplementary databases were analyzed (93,032 AD cases and 93,032 non-AD controls). In total, there were 177 comorbidities with a ≥ 5% prevalence. Five main clusters of comorbidities were identified. Clusters differed between AD cases and controls in the overall magnitude of association with AD, in their diverging time trajectories, and in comorbidity prevalence. Three clusters contained comorbidities that notably increased in frequency over time in AD cases but not in controls during the 5-year period before AD diagnosis. Comorbidities in these clusters were related to the early signs and/or symptoms of AD, psychiatric and mood disorders, cerebrovascular disease, history of hazard and injuries, and metabolic, cardiovascular, and respiratory complaints.Conclusion: We demonstrated a greater comorbidity burden among those who later developed AD vs. controls, and identified comorbidity clusters that could distinguish these two groups. Further investigation of comorbidity burden is warranted to facilitate early detection of individuals at risk of developing AD.

Baseline characteristics of HF patients stratified by ejection fraction class (HFrEF, < 0.45; or HFpEF, ≥ 0.45).

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.

Primary analysis and subgroup- specific performance.

Recent studies have suggested that dipeptidyl peptidase 4 (DPP4) inhibitors increase the risk of development of bullous pemphigoid (BP), which is the most common autoimmune blistering skin disease; however, the associated mechanisms remain unclear, and thus far, no therapeutic targets responsible for drug-induced BP have been identified. Therefore, we used clinical data mining to identify candidate drugs that can suppress DPP4 inhibitor-associated BP, and we experimentally examined the underlying molecular mechanisms using human peripheral blood mononuclear cells (hPBMCs). A search of the US Food and Drug Administration Adverse Event Reporting System and the IBM® MarketScan® Research databases indicated that DPP4 inhibitors increased the risk of BP, and that the concomitant use of lisinopril, an angiotensin-converting enzyme inhibitor, significantly decreased the incidence of BP in patients receiving DPP4 inhibitors. Additionally, in vitro experiments with hPBMCs showed that DPP4 inhibitors upregulated mRNA expression of MMP9 and ACE2, which are responsible for the pathophysiology of BP in monocytes/macrophages. Furthermore, lisinopril and Mas receptor (MasR) inhibitors suppressed DPP4 inhibitor-induced upregulation of MMP9. These findings suggest that the modulation of the renin-angiotensin system, especially the angiotensin1-7/MasR axis, is a therapeutic target in DPP4 inhibitor-associated BP.

Baseline demographics and medical characteristics by exposure group.

Characteristics and exposure case count for patients with RD.

Incidence rates of primary composite outcome, acute myocardial infraction, stroke, and heart failure among new users of DPP-4 inhibitors, sulfonylureas, and metformin.

The US Advisory Committee on Immunization Practice recommends routine human papillomavirus (HPV) vaccination at 11–12 years of age, but states that vaccination may be initiated as early as 9 years. Our primary goal was to assess whether initiating HPV vaccination at 9–10 years of age, compared to 11–12, was associated with a higher rate of series completion by 13 years of age, and to identify factors associated with series completion by age 13. The study used vaccine claims and other data from the IBM MarketScan Commercial Claims and Encounters (privately insured) and IBM MarketScan Multi-State Medicaid (publicly insured) databases. Participants were 9–12 years of age and initiated HPV vaccination between January 2006 and December 2018 (publicly insured) or February 2019 (privately insured). Among 100,117 privately insured individuals, those initiating the HPV vaccination series at 9–10 years of age had a significantly higher series completion rate by 13 years of age than did those initiating at 11–12 years of age (76.2% versus 48.1%; p 

Difference-in-differences estimates (percentage points) of the Effect of DelCAN on LARC insertion among 15–44 year olds enrolled in employer sponsored insurance.