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Studies that Answer Your Research Questions

Different types of studies are necessary to answer different types of research questions.  We have experience using a variety of data types, such as cross-sectional, longitudinal, patient registry, and customized databases to address research topics, including:

  • Health care resource utilization

  • Cost of treatment

  • Treatment patterns

  • Medication adherence and persistence

  • Disease incidence and prevalence

  • Burden (cost) of illness

  • Minimal clinically important difference

Robust Analytical Methods

Our data analyses are conducted using rigorous and appropriate analytical methods that stand up to peer review.  Study designs that are commonly implemented include retrospective cohort, nested case-control, and pre-post analyses.  Database analyses utilize many steps and as part of the process we:

  • Store database files on our secure server.  Data is de-identified and HIPAA compliant

  • Develop detailed protocols and statistical analysis plans (SAP)

  • Develop algorithms to identify specific study outcomes and events of interest

  • Extract analysis population based on inclusion/exclusion and other study criteria

  • Incorporate propensity scores when case-control designs are implemented to control for selection bias and confounding

  • Utilize comorbidity indices (e.g., Charlson, Elixhauser) to adjust for patient comorbidity

  • Apply appropriate analytical techniques to model outcomes including multi-variate regression (e.g., general linear, non-linear, mixed models), logistic, Poisson, negative binomial, etc. 

  • Cox proportional hazard models along with Kaplan-Meier techniques are used to assess time to event measures (e.g., survival analyses)

  • Results are delivered in the format of your choice, including:

    • technical reports​

    • slide decks

    • abstracts and presentations for professional meetings

    • peer reviewed journal articles

Data Sources We Analyze

We have experience in analyzing a broad array of data sources.  Below are some of the types of data we analyze, including:

Administrative Health Care Claims Data

We have broad experience in analyzing and leveraging data from large administrative claims databases to support and enhance the value message of your product.  

  • IBM MarketScan (formerly Truven) Commercial Claims and Encounters (CCAE) databases

    • Commercial claims from third party payers​

    • Medicare supplement

    • Medicaid

  • The Surveillance, Epidemiology, and End Results (SEER) database (oncology patient level clinical data linked to Medicare administrative claims)

  • Integrated Health Care Information Solutions (IHCIS) National Managed Care Benchmark database

  • Blue Health Intelligence databases (BHI)

  • IQVIA Pharmetrics

  • Premier Healthcare Database (PHD)

Patient Reported Outcomes (PRO) and Health-related Quality of Life (HR-QoL) Data

We can score and analyze both disease specific and general quality of life instruments.  Common general instruments include:

  • Short Form Survey 36 item (SF-36) and 12 item (SF-12) 

    • Individual scale scores​

    • Mental Component Scores (MCS)

    • Physical Component Scores (PCS)

  • Health Utilities Index (HUI)

  • EuroQol (EQ-5D)

    • 3-level​ instrument

    • 5-level instrument

    • Visual Analogue Scale (VAS)

  • Quality of Life Scale (QOLS)

Patient Registries and Survey Data

Patient registry and survey collected analyses have been performed in disease states such as Chrohn's disease, Alzheimer's disease, Parkinson's disease, and postpartum depression. 

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