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

Metadata access is required to view this section.

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

Metadata access is required to view this section.

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

%3C!-- --%3E

• 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.

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.

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

Abstract

We had to delete V3 of MarketScan because of some unusual circumstances with the formats of some of the files we were sent (to prevent the duplication of records). V3.1 contains all of the info that was in V3, however V3.1 has 2022 data & a slightly different version of the 2021 data. The data on this page is the version of the 2021 data that was in V3. Our purpose in posting this is to enable researchers who completed analyses on V3 to replicate their work by combining the data here with the data on the main page.

FOR THE MAJORITY OF RESEARCHERS, however, we strongly recommend using V3.1, and ignoring this page, as it will be irrelevant for most research going forward. (Rule of thumb: If you are unsure whether you need the data on this page, then you probably don't need it.)

Usage

To recreate V3 of the data, use the data for 2020 and earlier that is on the main MarketScan Databases page, and combine it with the data on this page. That will give you the *exact *same data that was in V3.

The data documentation on the main MarketScan page also applies to the data on this page.

How is the data on this page different from the 2021 data on the main MarketScan page?

Metadata access is required to view this section.

Crude and age–standardized pregnancy rates per 1,000 person-year of females aged 13–19 years, overall and according to mental disorder type.

Abstract

We had to delete V3 of MarketScan Medicare Supplemental because of some unusual circumstances with the formats of some of the files we were sent (to prevent the duplication of records). V3.1 contains all of the info that was in V3, however V3.1 has 2022 data & a slightly different version of the 2021 data. The data on this page is the version of the 2021 data that was in V3. Our purpose in posting this is to enable researchers who completed analyses on V3 to replicate their work by combining the data here with the data on the main page.

FOR THE MAJORITY OF RESEARCHERS, however, we strongly recommend using V3.1, and ignoring this page, as it will be irrelevant for most research going forward. (Rule of thumb: If you are unsure whether you need the data on this page, then you probably don't need it.)

Usage

To recreate V3 of the data, use the data for 2020 and earlier that is on the main MarketScan Medicare Supplemental page, and combine it with the data on this page. That will give you the exact same data that was in V3.

The data documentation on the main MarketScan Medicare Supplemental page also applies to the data on this page.

How is the data on this page different from the 2021 data on the main MarketScan Medicare Supplemental page?

Metadata access is required to view this section.

These are peer-reviewed supplementary materials for the article 'Evaluation of inpatient and emergency department healthcare resource utilization and costs pre- and post-nusinersen for the treatment of spinal muscular atrophy using United States claims' published in the Journal of Comparative Effectiveness Research.Supplementary Figure 1: Mean (SD) number of inpatient admissions per patient in individuals with SMA in the 12 months before and after nusinersen treatment. Mean (SD) number of days spent in hospital per patient in individuals with SMA in the 12 months before and after nusinersen treatment.Supplementary Figure 2: Mean (SD) ED visits and costs per patient in individuals with SMA in the 12 months before and after nusinersen treatment.Supplementary Table 1: Patient baseline characteristics of cohorts aligned with steps of patient selection criteria (who were ultimately excluded) in comparison to final cohort.Aim: Nusinersen, administered by intrathecal injection at a dose of 12 mg, is indicated across all ages for the treatment of spinal muscular atrophy (SMA). Evidence on real-world healthcare resource use (HRU) and costs among patients taking nusinersen remains limited. This study aimed to evaluate real-world HRU and costs associated with nusinersen use through US claims databases. Patients & methods: Using the Merative™ MarketScan R ? Research Databases, patients with SMA receiving nusinersen were identified from commercial (January 2017 to June 2020) and Medicaid claims (January 2017 to December 2019). Those likely to have complete information on the date of nusinersen initiation and continuous enrollment 12 months pre- and post-index (first record of nusinersen treatment) were retained. Number and costs (US$ 2020) of inpatient admissions and emergency department (ED) visits, unrelated to nusinersen administration, were evaluated for 12 months pre- and post-nusinersen initiation and stratified by age: pediatric (

Annual counts of individuals enrolled in MarketScan Research Databases and counts of patients with ≥1 AMI diagnosis according to ICD-CM codes received in any healthcare setting (2014–2017).

Food allergies impose a large clinical and financial burden on patients and the health care system. However, little is known about the factors associated with health care resource use and costs. The aim of this study was to investigate health care resource use and costs in individuals with food allergies utilizing health care in the United States. We conducted a retrospective analysis of insurance claims data from the Merative MarketScan Research Databases (indexed from 1 January 2015 to 30 June 2022). All-cause and food allergy-related health care resource use, direct medical, and out-of-pocket costs for medical services were estimated for 12 months post-index using International Classification of Diseases [ICD] codes. Of 355,520 individuals with food allergies continuously enrolled in a health insurance plan for ≥12 months pre- and post-index, 17% had a food allergy-related emergency department visit and 0.9% were hospitalized. The top patient characteristic associated with all-cause and food allergy-related hospitalizations, all-cause costs, and food allergy-related outpatient visit costs was a Charlson Comorbidity Index score of ≥2. Food allergy-related direct medical and out-of-pocket costs were high among patients with a food allergy-related visit. Out-of-pocket cost per patient per year for outpatient visits, emergency department visits, and hospitalizations had an estimated mean of $1631 for patients with food allergy-related visits, which is ∼11% of the total costs for these services ($14,395 per patient per year). Study limitations are primarily related to the nature of claims databases, including generalizability and reliance on ICD codes. Nevertheless, MarketScan databases provide robust patient-level insights into health care resource use and costs from a large, commercially insured patient population. The health care resource use of patients with food allergies imposes a burden on both the health care system and on patients and their families, especially if patients had comorbidities. Some people with food allergies might need extra visits to the doctor or hospital to manage allergic reactions to food, and these visits add to the cost of medical services for both families and for health care providers. Using records of health insurance claims, we looked into the factors affecting medical visits and costs in people with food allergies in the United States. For people with food allergies, having additional medical conditions (measured using the Charleson Comorbidity Index) were linked with extra medical visits and costs. Out-of-pocket costs were high for people who visited a doctor or hospital for their food allergies (costing each person more than $1,600 per year). The total medical cost of food allergy-related care was $14,395 per person per year, paid for by families and health care providers. Our findings might help to better manage and treat people with food allergies and reduce medical costs.

Androgen deprivation therapy (ADT) is standard for advanced prostate cancer. Relugolix, a gonadotropin-releasing hormone (GnRH) receptor antagonist, is the only oral ADT, with limited real-world data on therapy persistence and adherence. This retrospective study evaluates persistence and adherence of relugolix, degarelix, and GnRH agonists (leuprolide, goserelin, triptorelin, histrelin) using data from the IBM MarketScan Research Database (Jan 2017 - Dec 2022). The IBM MarketScan Research Database (1 January 2017 - 31 December 2022) was used for enrollment history and claims. ADT adherence was measured by the proportion of days covered (PDC) at 3, 6, and 12 months, calculated as days on ADT divided by period duration. Kaplan-Meier analysis assessed treatment persistence by measuring time to treatment discontinuation. Relugolix had higher adherence (PDC ≥ 80%) at 12 months (60.8%) compared to degarelix (13.0%) and GnRH agonists (46.3%). Median time to discontinuation was also longer for relugolix (13.5 months) than degarelix (3.1 months) and GnRH agonists (8.8 months). Persistence and adherence rates were higher in metastatic prostate cancer. Findings support relugolix use as an oral treatment due to its favorable persistence and long-term adherence profiles. Prostate cancer is the second most common cancer among men in the US. Androgen deprivation therapy (ADT), a key treatment for advanced prostate cancer, lowers testosterone levels, a hormone that helps prostate cancer grow. ADT includes injectable gonadotropin-releasing hormone (GnRH) receptor agonists like leuprolide, which initially raise testosterone before lowering it, and antagonists like degarelix, (injectable) and relugolix (oral), which rapidly lower testosterone. A large clinical trial (phase III) showed relugolix rapidly and consistently lowered testosterone, with similar side effects to leuprolide but fewer major cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and death from any cause). There is limited published real-world data, including healthcare information like medical records and insurance claims, on how well patients stay on treatment (persistence) and take their medication as prescribed (adherence) for different forms of ADT, especially oral relugolix. Data from the IBM MarketScan Research Database (January 2017 to December 2022) was used to compare persistence and adherence among patients taking oral relugolix, injectable degarelix, and injectable GnRH receptor agonists. Patients taking relugolix had a higher rate of adherence to their treatment (60.8%) after 12 months versus those receiving injectable degarelix (13.0%) and other injectables, GnRH receptor agonists (46.3%). Patients on relugolix also stayed on their treatment longer (13.5 months) compared to those on injectable degarelix (3.1 months) and GnRH receptor agonists (8.8 months). These results were especially notable in patients with metastatic prostate cancer. This study demonstrates favorable persistence and adherence rates with oral relugolix in patients receiving ADT for advanced prostate cancer.

The MarketScan health claims database is a compilation of nearly 110 million patient records with information from more than 100 private insurance carriers and large self-insuring companies. Public forms of insurance (i.e., Medicare and Medicaid) are not included, nor are small (< 100 employees) or medium (1000 employees). We excluded the relatively few (n=6735) individuals over 65 years of age because Medicare is the primary insurance of U.S. adults over 65. The EQI was constructed for 2000-2005 for all US counties and is composed of five domains (air, water, built, land, and sociodemographic), each composed of variables to represent the environmental quality of that domain. Domain-specific EQIs were developed using principal components analysis (PCA) to reduce these variables within each domain while the overall EQI was constructed from a second PCA from these individual domains (L. C. Messer et al., 2014). To account for differences in environment across rural and urban counties, the overall and domain-specific EQIs were stratified by rural urban continuum codes (RUCCs) (U.S. Department of Agriculture, 2015). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Gray, C., D. Lobdell, K. Rappazzo, Y. Jian, J. Jagai, L. Messer, A. Patel, S. Deflorio-Barker, C. Lyttle, J. Solway, and A. Rzhetsky. Associations between environmental quality and adult asthma prevalence in medical claims data. ENVIRONMENTAL RESEARCH. Elsevier B.V., Amsterdam, NETHERLANDS, 166: 529-536, (2018).

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.

These are peer-reviewed supplementary materials for the article 'Resource utilization and economic outcomes following repetitive transcranial magnetic stimulation for treatment-resistant depression: a retrospective observational analysis' published in the Journal of Comparative Effectiveness Research.Supplementary table 1: Minimum, Median and Maximum Healthcare Costs for Patient Cohort Aim: We investigated the impact of repetitive transcranial magnetic stimulation (rTMS) for treatmentresistant depression on healthcare resource utilization as well as commercial and Medicare Fee-for-Service payer costs. Materials & methods: We conducted a retrospective observational analysis of claims data using Medicare Fee-for-Service datasets and commercial (Merative MarketScan Research Databases) datasets from 1 January 2021 to 30 September 2023. We identified two cohorts, a cohort that received rTMS and a cohort not treated with rTMS over an 18-month period. We used propensity score matching to balance the baseline characteristics of the cohorts, and we calculated the total cost of care based on payer allowed amounts from Merative MarketScan Research Databases and Standard Analytical Files. Results: Relative to the non-TMS cohort, the rTMS cohort incurred 37% more hospital outpatient visits (14.00 vs 10.21; p ≤ 0.0001) with 7% higher outpatient cost ($8946 vs $8363; p = 0.3400). Simultaneously, the rTMS cohort incurred 24% fewer inpatient admissions (0.25 vs 0.33; p = 0.0003) with 19% lower inpatient admission costs ($5666 vs $6978; p = 0.0392), 48% fewer emergency room visits (0.27 vs 0.53; p ≤ 0.0001) with 34% lower emergency room costs ($322 vs $487; p ≤ 0.0001), and $893 less in episode of care costs. Conclusion: This study suggests that patientswho receive rTMS for treatment-resistant depression required fewer high acuity hospital visits and incurred less expensive episode-of-care costs compared with patients who do not receive rTMS. From this perspective, rTMS is an investment that returns health and economic dividends through fewer high acuity hospital visits.

BackgroundThe rise in health spending in the United States and the prevalence of multimorbidity—having more than one chronic condition—are interlinked but not well understood. Multimorbidity is believed to have an impact on an individual’s health spending, but how having one specific additional condition impacts spending is not well established. Moreover, most studies estimating spending for single diseases rarely adjust for multimorbidity. Having more accurate estimates of spending associated with each disease and different combinations could aid policymakers in designing prevention policies to more effectively reduce national health spending. This study explores the relationship between multimorbidity and spending from two distinct perspectives: (1) quantifying spending on different disease combinations; and (2) assessing how spending on a single diseases changes when we consider the contribution of multimorbidity (i.e., additional/reduced spending that could be attributed in the presence of other chronic conditions).Methods and findingsWe used data on private claims from Truven Health MarketScan Research Database, with 16,288,894 unique enrollees ages 18 to 64 from the US, and their annual inpatient and outpatient diagnoses and spending from 2018. We selected conditions that have an average duration of greater than one year among all Global Burden of Disease causes. We used penalized linear regression with stochastic gradient descent approach to assess relationship between spending and multimorbidity, including all possible disease combinations with two or three different conditions (dyads and triads) and for each condition after multimorbidity adjustment. We decomposed the change in multimorbidity-adjusted spending by the type of combination (single, dyads, and triads) and multimorbidity disease category.We defined 63 chronic conditions and observed that 56.2% of the study population had at least two chronic conditions. Approximately 60.1% of disease combinations had super-additive spending (e.g., spending for the combination was significantly greater than the sum of the individual diseases), 15.7% had additive spending, and 23.6% had sub-additive spending (e.g., spending for the combination was significantly less than the sum of the individual diseases). Relatively frequent disease combinations (higher observed prevalence) with high estimated spending were combinations that included endocrine, metabolic, blood, and immune disorders (EMBI disorders), chronic kidney disease, anemias, and blood cancers. When looking at multimorbidity-adjusted spending for single diseases, the following had the highest spending per treated patient and were among those with high observed prevalence: chronic kidney disease ($14,376 [12,291,16,670]), cirrhosis ($6,465 [6,090,6,930]), ischemic heart disease (IHD)-related heart conditions ($6,029 [5,529,6,529]), and inflammatory bowel disease ($4,697 [4,594,4,813]). Relative to unadjusted single-disease spending estimates, 50 conditions had higher spending after adjusting for multimorbidity, 7 had less than 5% difference, and 6 had lower spending after adjustment.ConclusionsWe consistently found chronic kidney disease and IHD to be associated with high spending per treated case, high observed prevalence, and contributing the most to spending when in combination with other chronic conditions. In the midst of a surging health spending globally, and especially in the US, pinpointing high-prevalence, high-spending conditions and disease combinations, as especially conditions that are associated with larger super-additive spending, could help policymakers, insurers, and providers prioritize and design interventions to improve treatment effectiveness and reduce spending.

Polypharmacy in spinal cord injury (SCI) is common and predisposes patients to increased risk of adverse events. Evaluation of long-term health consequences and economic burden of polypharmacy in patients with SCI is explored. Retrospective cohort. The IBM Marketscan Research Databases claims-based dataset was queried to search for adult patients with SCI with a 2-year follow-up. Two matched cohorts were analyzed: those with and without polypharmacy, analyzing index hospitalization, readmissions, payments, and health outcomes. A total of 11 569 individuals with SCI were included, of which 7235 (63%) were in the polypharmacy group who took a median of 11 separate drugs over two years. Opioid analgesics were the most common medication, present in 57% of patients with SCI meeting the criteria of polypharmacy, followed by antidepressant medications (46%) and muscle relaxants (40%). Risk of pneumonia was increased for the polypharmacy group (58%) compared to the non-polypharmacy group (45%), as were urinary tract infection (79% versus 63%), wound infection (30% versus 21%), depression (76% versus 57%), and adverse drug events (24% versus 15%) at 2 years. Combined median healthcare payments were higher in polypharmacy at 2 years ($44 333 vs. $10 937, P 

Real-world healthcare data hold the potential to identify therapeutic solutions for progressive diseases by efficiently pinpointing safe and efficacious repurposing drug candidates. This approach circumvents key early clinical development challenges, particularly relevant for neurological diseases, concordant with the vision of the 21st Century Cures Act. However, to-date, these data have been utilized mainly for confirmatory purposes rather than as drug discovery engines. Here, we demonstrate the usefulness of real-world data in identifying drug repurposing candidates for disease-modifying effects, specifically candidate marketed drugs that exhibit beneficial effects on Parkinson’s disease (PD) progression. We performed an observational study in cohorts of ascertained PD patients extracted from two large medical databases, Explorys SuperMart (N = 88,867) and IBM MarketScan Research Databases (N = 106,395); and applied two conceptually different, well-established causal inference methods to estimate the effect of hundreds of drugs on delaying dementia onset as a proxy for slowing PD progression. Using this approach, we identified two drugs that manifested significant beneficial effects on PD progression in both datasets: rasagiline, narrowly indicated for PD motor symptoms; and zolpidem, a psycholeptic. Each confers its effects through distinct mechanisms, which we explored via a comparison of estimated effects within the drug classification ontology. We conclude that analysis of observational healthcare data, emulating otherwise costly, large, and lengthy clinical trials, can highlight promising repurposing candidates, to be validated in prospective registration trials, beneficial against common, late-onset progressive diseases for which disease-modifying therapeutic solutions are scarce.

Comprehensive dataset of 1 Flea markets in Can Lộc District, Ha Tinh, Vietnam as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1 Seafood markets in Can Lộc District, Ha Tinh, Vietnam as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

BackgroundPostmenopausal bleeding (PMB) is a common gynecologic condition. Although it can be a sign of uterine cancer, most patients have benign etiology. However, research on quality of diagnostic evaluation for PMB has been limited to cancer patients. To extend this research, we examined the timeliness of diagnostic evaluation for PMB among patients with benign conditions.MethodsUsing the 2008–2019 MarketScan Research Databases, we identified 499176 patients (456741 with commercial insurance and 42435 with Medicaid insurance) who presented with PMB but did not have gynecologic cancer. For each patient, we measured the time from their PMB reporting to the date of their first diagnostic procedure. The association between patient characteristics and time to first diagnostic procedure was examined using Cox proportional hazards models (for the overall sample and then stratified by insurance type).ResultsOverall, 54.3% of patients received a diagnostic procedure on the same day when they reported PMB and 86.6% received a diagnostic procedure within 12 months after reporting PMB. These percentages were 39.4% and 77.1%, respectively, for Medicaid patients, compared to 55.7% and 87.4%, respectively, for commercially insured patients (p