SubHero Banner
Text

OptumLabs is reporting industry standard measures on important themes. To better understand and use the reports, you can access resources on the building blocks, including what the measures are, data sources used, methods to calculate them and more.

Review the summary topics below and download our companion guide for more detailed information on our reporting.

Download companion guide

Text

We offer a starting point for health care stakeholders to examine these two themes by summarizing a few starter insights from the results. Our interactive reports then offer more insights to inform health care quality and policy discussions and spur more research.

Horizontal Rule

Reports overview

Text

We offer two reports that allow you to explore quality measures in two thematic areas, comparing processes and outcomes and transition to Medicare. The reports let you view the measures by demographic and geographic attributes.

We've provided some initial observations to get you started in our starter insights and offer a means to see and build on those insights in a dynamic, visual reporting tool.

You can access the reporting tool using the links provided on the home page, in our starter insights and in the resources tiles below. 

Horizontal Rule
Text

Measures 

The Comparing Processes and Outcomes report examines this theme through the lens of national standard diabetes and cancer process and outcomes measures. The Transition to Medicare report uses the lens of approved alternative diabetes and hospitalization and harm measures.

To compare process and outcome measures, we selected some of the most commonly reported process measures in diabetes and cancer to understand their relationship to outcomes and help inform conversations about which measures really matter.

We also selected measures that provide insights into transition to Medicare. These measures focus on patients with chronic conditions whose greater care coordination needs might be sensitive to disruptions in care.

Below is a list of the measures we use to report on these themes and domain areas. For more information, download the detailed companion guide.

Comparing Processes and Outcomes

Table
Diabetes Measures Cancer Measures

Processes

  • Comprehensive Diabetes Care: 
    • Eye Exam 
    • Foot Exam
    • Blood Sugar (HbA1c) Testing
    • Blood Sugar Control (<8.0%)
    • Blood Sugar Poor Control (>9.0%)
    • Blood Pressure Control
    • Medical Attention for Nephropathy

Processes

  • Screening:  Breast Cancer 
  • Screening:  Cervical Cancer
  • Screening:  Colorectal Cancer
  • Screening:  Tobacco Use

Outcomes

  • Prevention Quality Indicators:
    • Diabetes Short-term Complications  
    • Diabetes Long-term Complications
    • Lower Extremity Amputation
    • Uncontrolled Diabetic Admission

Outcomes

  • Breast Cancer  Incidence and Mortality*
  • Cervical Cancer  Incidence and Mortality*
  • Colorectal Cancer  Incidence and Mortality*
  • Lung Cancer Incidence and Mortality*

*Source: CDC U.S. Cancer Statistics

Text

Transition to Medicare

Table
Diabetes Measures Hospitalization and Harm Measures
  • Comprehensive Diabetes Care: 
    • Eye Exam 
    • Foot Exam
    • Blood Sugar (HbA1c) Testing
    • Blood Sugar Control (<8.0%)
    • Blood Sugar Poor Control (>9.0%)
    • Blood Pressure Control
    • Medical Attention for Nephropathy
  • Prevention Quality Indicators:
    • Diabetes Short-term Complications  
    • Diabetes Long-term Complications
    • Lower Extremity Amputation
    • Uncontrolled Diabetic Admission
  • All-Cause Admissions:
    • Admission Rates for Patients with Diabetes 
    • Admission Rates for Patients with Heart Failure
    • Admission Rates for Patients with Multiple Chronic Conditions
  • Hospitalizations:
    • Hospitalizations per 1000 member years
    • 30-day Rehospitalizations per 1000 member years
  • Other causes of harm:
    • Potentially Avoidable Complications (PAC) in People with Chronic Conditions
    • Potentially Harmful Drug-Disease Interactions in Older Individuals
Horizontal Rule
Text

Data sources 

Our reports use combined de-identified commercial (employer-based individual insurance coverage and Medicare Advantage) and 100 percent Medicare FFS claims data sources.

They also use de-identified electronic health record (EHR) derived clinical data.  Together, these data sources offer a longitudinal, national view into quality.

Note: Administrative data sources include many potential limitations. The most significant of these include billing variation, enrollment duration differences, lack of supplemental data capture through non-claims based sources, small sample sizes in certain geographies and population risk differences. More specifics on limitations are in the companion guide.

To learn more, download the detailed report companion guide

Horizontal Rule
Text

Methods

Quality measures were calculated using industry-standard specifications. For the population that transitioned to Medicare, we developed a methodology to follow individuals transitioning into primary Medicare coverage and assign the year of that transition.

To learn more, download the detailed report companion guide

Horizontal Rule
Text

FAQs

Accordion Block
  • OptumLabs is a collaborative research and innovation center working to help solve some of health care’s biggest problems with a combination of a comprehensive data set, leading edge data science and the expertise of over 25 thought-leading partners.

    Its core linked data assets include de-identified data from a large U.S. health plan with claims from commercial and Medicare Advantage enrollees and de-identified EHR data from a nationwide network of provider groups.

    The database contains longitudinal health information on enrollees and patients, representing a diverse mixture of ages, ethnicities and geographical regions across the United States. The EHR data is sourced from provider groups and reflects all payers, including uninsured patients. 

    To learn more about OptumLabs, visit optumlabs.com.

    OR
  • A Qualified Entity (QE) is an organization permitted to combine Medicare data with other claims data for the purposes of reporting on quality measures that can be used to improve the performance of health care providers and suppliers.

    The Qualified Entity program was created as part of the Affordable Care Act to facilitate health system improvement using insights from data.

    The program allows Qualified Entities to apply to receive Centers for Medicare and Medicaid Services (CMS) claims data for the purpose of combining that data with a commercial claims data set and using it to report back publicly on health system quality measures.

    Once certified in the Qualified Entity Certification Program (QECP), QEs are eligible to receive standardized extracts of Medicare Parts A and B claims data and Part D prescription drug event data. To learn more visit the QECP website

    OR
  • To become a QE, an organization must complete a comprehensive application process that demonstrates expertise in performance measurement, the ability to combine Medicare data with existing claims data, and adherence to rigorous data privacy and security procedures.
    OR
  • QEs may apply to receive Medicare data for the areas they operate in and report on, which may be national or regional in scope.

    Because OptumLabs operates in all U.S. regions, our scope for public reporting is national, including all states, Puerto Rico and the District of Columbia. As a national QE, OptumLabs receives 100 percent of the Parts A, B and D CMS claims and enrollment data.

    OR
  • The OptumLabs QE public reports present measures through two distinctive lenses. The first report, Comparing Processes and Outcomes, compares measures of health care processes to related measures of health care outcomes.

    The other report, Transition to Medicare, focuses on care quality for individuals making their first transition from private commercial (often employer-sponsored) health insurance to Medicare insurance.

    The transition to Medicare theme is one that has not been examined before because it was not possible without the ability to link commercial insurance data on a patient level to Medicare fee-for-service (FFS) data.

    Each thematic report contains two sub-domains that report groupings of relevant measures. For the Comparing Processes and Outcomes report, the sub-domains are cancer and diabetes, which provide insights on common disease domains.

    For the Transition to Medicare report, the sub-domains are diabetes and hospitalizations and harm, which provide insights on how quality of care, particularly for conditions requiring highly coordinated care, is impacted as people transition from commercial insurance to Medicare for the first time.

    OR
  • Measures available to QEs for public reporting are maintained on a list of Standard and Alternative measures by the QECP. To see the current list of Standard and Alternative measures, visit Report Resources on the QECP website.
    OR
  • Some of the measures in the OptumLabs QE reports are standard, and others are alternative measures. Standard measures are those that are developed and curated by other organizations, such as NCQA, PCPI, CMS and more.

    OptumLabs calculates standard measures using our data sources for the Comparing Processes and Outcomes report. Alternative measures are those that OptumLabs modified to support a reporting theme.

    OptumLabs created alternative measures to support the Transition to Medicare report, as we needed to develop a methodology to identify patients who are transitioning to Medicare coverage for the first time. Additional information on the measures and calculations can be found in the detailed report companion guide.

    OR
  • While OptumLabs followed measure specifications to calculate the standard and alternative measures in the reports, some differences exist between data sources that can lead to differences in measure results.

    For example, there may be billing variations and/or differences in enrollment duration of individuals that may impact measure results across different data sources. This can create systematic shifts in results, which is known as statistical bias.

    In addition, outcome measure rates presented in the report are crude (raw) unadjusted rates, which may differ from similar measures from the same population, gathered by other means.

    OR
  • Two primary sources of data were combined and then used to calculate the measures in the OptumLabs QE public reports.

    The first includes a 100 percent sample of medical claims data received under the QECP for Medicare Parts A, B, D from 2009 to 2015. The second includes data contained in the OptumLabs Data Warehouse (OLDW).

    All data used in OptumLabs reporting comes from real-world data sources and is not collected expressly for reporting purposes.

    More information about Medicare Parts A, B, D data OptumLabs received in the QECP can be found at the CMS Research Data and Assistance Center (ResDAC) website.

    The OLDW includes de-identified data from a large U.S. health plan with claims from commercial and Medicare Advantage enrollees, as well as de-identified EHR data from a nationwide network of provider groups.

    The database contains longitudinal health information on enrollees, representing a diverse mixture of ages, ethnicities and geographical regions across the United States.

    The health plan provides comprehensive full insurance coverage for physician, hospital and prescription drug services. The EHR data sourced from provider groups reflects all payers, including uninsured patients.

    All data used to create the OptumLabs QE public reports are de-identified in compliance with HIPAA. 

    There are inherent limitations in using these data sources and they may deviate from national quality reporting system benchmarks, such as HEDIS®, STARS, or other quality programs which often make use of supplemental data collection from medical charts and subjective judgment from medical personnel. To learn more about limitations overall or for specific measures in this report, please refer to the detailed report companion guide.

    All measure rates reported at the national, census region, and state levels include combined data from OptumLabs Data Warehouse and QE Medicare Data. When coverage type is stratified, Commercial and Medicare Advantage rates do not include QE Medicare data. The cancer incidence and mortality rates in the report are sourced from the Centers for Disease Control U.S. Cancer Statistics and do not include QE Medicare data.

    OR
  • A number of measures presented in the OptumLabs public reports require clinical data elements not found in claims data or services that are not typically billed in claims. As a result, claims data alone are insufficient to report certain measure results.

    Measures that require clinical data include HbA1c Control and Poor Control, Blood Pressure Control, Tobacco Use Screening and Diabetic Foot Exam.

    OR
  • OptumLabs has developed a dynamic, online reporting tool to publish its QE measure results on the OptumLabs website. This tool allows users to customize the exploration of measure results to their individual interests and preferences. 

    Our website also contains starter insights to jumpstart exploration in the reporting tool in each sub-domain area: Comparing Processes and Outcomes (sub-domains: diabetes and cancer) and Transition to Medicare (sub-domains: diabetes, and hospitalizations and harm).

    OR
  • Both OptumLabs and CMS enforce a cell suppression policy to protect data privacy. In addition, measure results may not be considered valid if the number of individuals available for measure calculation falls below a certain minimum.

    When this happens, the results are suppressed and indicated as a single asterisk (*) that indicates “insufficient data” for the measure.

    OR
  • In some cases, you might experience a blank (or empty) visualization, figure or map in the interactive report. This will occur when there are no results for that particular measure and set of report selections in the underlying data.

    If you encounter a missing or blank figure after making a selection in the report, change your selection criteria. The most common cause of this is related to the data source selection.

    OR
Horizontal Rule

Resources

Card Box

Report information

Read more to better understand our report, including data sources, measures, methodology and more.

Measures reporting

Explore the data in our interactive report.