Inovalon Medical Outcomes Research for Effectiveness and Economics Registry (MORE² Registry®) (USA)

Field Names
Records
Coordinating Country
United States
Region

United States

(Including all 50 states and Puerto Rico, representing 99.6% of US counties)

Brief Database Description

Inovalon’s Medical Outcomes Research for Effectiveness and Economics Registry (MORE² Registry®) is a data warehouse that empowers informed insight into national and regional healthcare trends, such as hospital utilization, medication adherence, chronic disease prevalence, and treatment effectiveness. This warehouse contains longitudinal patient-level healthcare data derived from one million physicians, 594,000 clinical facilities, 348 million unique patients, and 68 billion medical events. It represents a significant mix of commercial (including exchanges), Medicare Advantage, managed Medicaid memberships, as well as 100% of the Medicare fee-for-service (FFS) population (Parts A, B, and D claims). The registry goes beyond claims data to include information about demographics, enrollment, diagnoses, procedures, pharmacy, laboratory results, and 45 million lives with EHR data currently being integrated.

Database Type
Longitudinal Population Database
- - Medical and Pharmacy Insurance Claims
- - - Outpatient and inpatient
- - Electronic Medical Records
Registry

(This warehouse contains longitudinal patient-level healthcare data and represents a significant mix of commercial (including exchanges), Medicare Advantage, managed Medicaid memberships, as well as 100% of the Medicare fee-for-service (FFS) population (Parts A, B, and D claims). The registry goes beyond claims data to include information about demographics, enrollment, diagnoses, procedures, pharmacy, laboratory results, and 45 million lives with EHR data currently being integrated.)

Database Source
Medical Insurance Claims
EHR/EMR

(Includes EHR data, clinical encounter data, pharmacy, medical, and lab claims. There are 150+ individual plans/carriers representing national, regional, and local plans/carriers across all 50 states and 99.6% of counties.

Upstream source data are identifiable and can be linked with external data sources (e.g., registries, EHR, directories) using HIPAA-compliant methods to create customized de-identified research datasets.)

Frequency of Data Collection
Ongoing
Frequency of Data Update
Monthly

(Monthly updates with usual claims lag of about 3 months for medical claims and 1 month for pharmacy claims)

Years Covered
2000 - Present

(Data on commercial, managed Medicaid, and Medicare Advantage lives available for 2000-2018;
Medicare fee-for-service (FFS) data available 2009-present. EHR data available 2012-2018.)

Population Type
Outpatient/Non-Institutionalized
Inpatient
Insured (type e.g., Medicare, Medicaid)
Patient Type
Inpatient and Outpatient

Data include:
- Hospitalized (including admission and discharge dates),
- ER visits,
- ICU data, and
- Outpatient visits.

Date of Last Update
Ongoing

(The MORE² dataset is updated on an ongoing basis;
This profile was developed for the B.R.I.D.G.E. TO DATA site on March 22, 2022.)

Field Names
Records
Database Population Size
> 100 Million

Inovalon’s primary source de-identified dataset contains data pertaining to more than one million physicians, 594,000 clinical facilities, 348 million unique patients, and 68 billion medical events representative of all coverage types.

Active Population Size
> 100 Million

Inovalon’s primary source de-identified dataset contains data pertaining to more than one million physicians, 594,000 clinical facilities, 348 million unique patients, and 68 billion medical events representative of all coverage types.

Annual Change in Population
Please contact database manager for more information
Sample Weights - Extrapolation Factors
No
Final Population Size
N/A

(Not applicable as data are still being collected)

Field Names
Records
Age of Patients at Data Collection
Yes

DOB is collected

Approximate Percentage of Participants <18 years and those >65 years

Please contact database manager for more information

Gender Data
Yes
Percentage of Males/Females

Please contact database manager for more information

Ethnicity / Race Data
Yes

Available in EHR data and within Medicare Advantage population

Geographic Location

USA, including all 50 states and Puerto Rico, representing 99.6% of US counties

Date of Birth Recorded
Yes
Death Recorded
No
Availability of death certificate / autopsy information
N/A

(Not applicable)

Other Demographic Data
Yes

Demographics and low income status

Field Names
Records
Physician ID
N/A

Please contact database manager for more information

Physician Specialty
N/A

Please contact database manager for more information

Pharmacy ID
N/A

Please contact database manager for more information

Field Names
Records
Diagnosis Data
Yes
Diagnoses Coded
ICD-9-CM
ICD-10-CM
Diagnoses: Date Parameters
2000 - Present
Diagnoses: Maximum Number of Codes Allowed
Please contact database manager for more information
Physical Examination Findings
Yes

-Height
-Weight

Birth Defect Data
N/A

Please contact database manager for more information

Cancer Data
Yes

Cancer data include:
- Date of initial cancer diagnosis;
- Date of recurrent/metastatic cancer diagnosis;
- Stage;
- Histology;
- Cancer;
- ECOG and other Performance status; and
- Tumor markers

Tumor Type (Commercial, Medicare Advantage, Managed Medicaid; Medicare 100% FFS / Part D):
- Across Tumor Types (Pantumor): 422,9450; 6,522,255
- Acute Myeloid Leukemia (AML): 47,960; 148,676
- Bladder Cancer: 170,348; 499,804
- Breast Cancer: 947,812; 154,9246
- Chronic Myelogenous Leukemia: (CML); 29,043; 455,35
- Colorectal Cancer (CRC): 403,884; 750,334
- Esophageal Cancer: 463,01; 80,903
- Gastric Cancer: 58,859; 81,866
- Gastroesophageal Junction (GEJ): 16,830; 26,645
- Glioblastoma (GBM): 112,572; 119,515
- Head and Neck Cancer (HNC): 213,422; 646,879
- HNC In-Situ Carcinoma: ; 16,990; 55,147
- Hepatocellular Carcinoma (HCC): 98,040; 124,432
- Hodgkin Lymphoma (HL): 63,620; 68,623
- Leukemia: 123,825; 213,783
- Lung Cancer: 343,871; 606,507
- Lymphoma: 319,987; 347,382
- Melanoma: 338,562; 1,025,159
- Mesothelioma: 122,16; 17,793
- Multiple Myeloma (MM): 93,090; 111,945
- Non-Hodgkin's Lymphoma: 251,692; 284,470
- Prostate Cancer: 746,315; 1704,420
- Kidney Cancer (Exclud. Renal Pelvis); 151,527; 306,522

Biomarker data available for specific biomarkers that can be identified through claims codes (e.g., CPT code, LOINC codes); also available in EHR data. In addition, Avalere is in early discussions to integrate additional lab/biomarker data with another third party vendor.

Infectious Disease Data
N/A

Please contact database manager for more information

Environmental Exposures
N/A

Please contact database manager for more information

Behavioral Data Elements
Yes

Alcohol usage

Field Names
Records
Procedure Data
No
Procedures Coded
CPT
LOINC®
Number of Procedures Coded
Please contact database manager for more information
Procedure Date Parameters
2000 - Present
Laboratory Information
Yes

Screening tests:
- Prostate-specific antigen
- Mammography
- Endoscopy
- PAP smear
- Blood lipid
- ECG
Specific biomarkers are available for those that can be identified through claims codes (e.g., CPT code, LOINC codes); also available in EHR data. In addition, Avalere is in early discussions to integrate additional lab/biomarker data with another third-party vendor.

If a radiology test was performed Avalere is able to identify radiology data including the type of data.

Field Names
Records
Drug Data
Yes

Except for inpatient administered chemotherapy but including concomitant/non-cancer medications

Drug Date Parameters
2000 - Present
Drug Regimen & Route
Yes
Drug Manufacturer
N/A

Please contact database manager for more information

Drug Dosage
Yes

For oral administered medication only; not for certain BMI-based administered chemotherapy

Drug Days Supply
Yes
Drug Coding System: Maximum Number
Please contact database manager for more information
Drug Coding System: Primary
N/A

Please contact database manager for more information

Drug Coding System: Other
N/A

Please contact database manager for more information

Drug Generic Name
Yes
Drug Additional Information
N/A

Please contact database manager for more information

Field Names
Records
Biobank Type
N/A
Human Specimen
N/A
Blood Type
N/A
Biomarkers
N/A
Patient ID
N/A
Number of Samples
N/A
Frequency of Sample Collection
N/A
Pre-diagnostic Sample Collection
N/A
Post-treatment Sample Collection
N/A
Method of Sample Collection
N/A
Age at Sample Collection
N/A
Date of Sample Collection
N/A
Reason for Sample Collection
N/A
Method of Sample Storage
N/A
Length of Sample Storage
N/A
Pathology
N/A
DNA Isolation
N/A
RNA Isolation
N/A
Cell Culture
N/A
Genetic Testing
N/A
Access for Research: Specimens
N/A
Access for Research: Genetic Data
N/A
Access for Research: Epidemiologic Data
N/A
Quality Assurance Procedures
N/A
Family History
N/A
Medical History
N/A
Biobank Linkage
N/A
Field Names
Records
Type of Genetic Database
N/A
Source of Genetic Data
N/A
Specimen Genotyped
N/A
Tissue Form
N/A
Genetic Template
N/A
Gene-Drug Response
N/A
Gene-Disease Relationship
N/A
Gene-Health Outcome Relationship
N/A
Gene-Environment Response
N/A
Method of Imputing Genetic Data
N/A
Genetic Variant Identification
N/A
Genetic Data Level
N/A
Genotyping Method
N/A
Method of Genetic Variant Filtering
N/A
Haplotypes
N/A
Haplogroups
N/A
Variable Number of Tandem Repeats (VNTR)
N/A
Single Nucleotide Polymorphisms (SNPs)
N/A
Variant Type
N/A
Variant Class
N/A
Mutation Indicated
N/A
Position
N/A
Amino Acid Change
N/A
Genotype / Polymorphism
N/A
Allele Frequency
N/A
Linkage Disequilibrium (r²)
N/A
Noncarriers Indicated
N/A
Association Statistics
N/A
Genetic Relatedness Pairing
N/A
Data Sharing: Genetic Data
N/A
Access for Research
N/A
Genetic Data Linkage
N/A
Description of Genetic Data Linkage
N/A
Field Names
Records
Cost Data
Yes
Cost Denomination
United States Dollar (USD)
Type of Cost Data
Yes

Healthcare costs are calculated by applying standardized Medicare allowed payment amounts to each type of service based on published Medicare rates.

Description of Surrogate Link
N/A

Please contact database manager for more information

Field Names
Records
Data Validation Against Original Source
Yes
Access to Medical Records
No
Linkage to Other Databases
Yes
Brief Description of Linkage Capabilities

Upstream source data are identifiable and can be linked with external data sources (e.g., registries, EHR, directories) using HIPAA-compliant methods to create customized de-identified research datasets.

Field Names
Records
Database Contact Data

Contact form: https://www.inovalon.com/contact/inquiries/

Alternate Contact

N/A

(Not applicable)

Source of Database Funding
Private

Inovalon, Inc.

Sponsoring Government Agency
N/A

(Not applicable)

Sponsoring Pharmaceutical Manufacturer

N/A

(Not applicable)

Database Usage Restrictions
Private Access
Charge for Database Usage
Yes
Data Media Format
N/A

Please contact database manager for more information

Number of Publications Using Database
>10
References of Studies Using/Describing Database

1. Meaddough EL, Sarasua SM, Fasolino TK, Farrell CL. The impact of pharmacogenetic testing in patients exposed to polypharmacy: a scoping review. The Pharmacogenomics Journal. 2021 Aug;21(4):409-22.

2. Petrilla AA, Shah A, Feliciano J, Woolery J, LeBlanc TW. Burden of illness and treatment patterns among patients with peripheral T-cell lymphoma in the US healthcare setting. Current medical research and opinion. 2021 Jul 3;37(7):1189-97.

3. Madduri D, Hagiwara M, Parikh K, Pelletier C, Delea TE, Kee A, Chari A. Real-world treatment patterns, healthcare use and costs in triple-class exposed relapsed and refractory multiple myeloma patients in the USA. Future Oncology. 2021 Feb;17(5):503-15.

4. Pollissard L, Shah A, Punekar RS, Petrilla A, Pham HP. Burden of illness among Medicare and non-Medicare US populations with acquired thrombotic thrombocytopenic purpura. Journal of Medical Economics. 2021 Jan 1;24(1):706-16.

5. Mentz RJ, Pulungan Z, Kim S, Yang M, Teigland C, Hilkert R, Djatche LM. Quality outcomes, healthcare resource utilization and costs in Medicare patients with chronic heart failure with reduced ejection fraction with and without a worsening event. Journal of medical economics. 2021 Jan 1;24(1):698-705.

6. Shah A, Petrilla A, Rebeira M, Feliciano J, Lisano J, LeBlanc TW. Health care resource utilization and costs among Medicare beneficiaries newly diagnosed with peripheral T-cell lymphoma: a retrospective claims analysis. Clinical Lymphoma Myeloma and Leukemia. 2021 Jan 1;21(1):e1-9.

7. Pollissard L, Shah A, Punekar R, Petrilla A, Pham HP. Burden of Illness Among Medicare and Non-Medicare Populations with Acquired Thrombotic Thrombocytopenic Purpura, 2010-2018. Blood. 2020 Nov 5;136:19-20.

8. Petrilla AA, Sutton BS, Leinwand BI, Parente A, Ferrari L, Wade CT. Incremental burden of mental health conditions in adult patients with focal seizures. Epilepsy & Behavior. 2020 Nov 1;112:107426.

9. Petrilla A, Marrett E, Shen X, Kwong WJ, Pezalla E. Association between formulary coverage and use of abuse-deterrent prescription opioids, risk for abuse or overdose, and associated healthcare resource utilization. American health & drug benefits. 2020 Feb;13(1):21.

10. Forma F, Green T, Kim S, Teigland C. Antipsychotic medication adherence and healthcare services utilization in two cohorts of patients with serious mental illness. ClinicoEconomics and Outcomes Research: CEOR. 2020;12:123.

    Database Contact
    Database Contact Data

    Contact form: https://www.inovalon.com/contact/inquiries/

    Alternate Contact

    N/A

    References of Studies Using/Describing Database

    1. Meaddough EL, Sarasua SM, Fasolino TK, Farrell CL. The impact of pharmacogenetic testing in patients exposed to polypharmacy: a scoping review. The Pharmacogenomics Journal. 2021 Aug;21(4):409-22.

    2. Petrilla AA, Shah A, Feliciano J, Woolery J, LeBlanc TW. Burden of illness and treatment patterns among patients with peripheral T-cell lymphoma in the US healthcare setting. Current medical research and opinion. 2021 Jul 3;37(7):1189-97.

    3. Madduri D, Hagiwara M, Parikh K, Pelletier C, Delea TE, Kee A, Chari A. Real-world treatment patterns, healthcare use and costs in triple-class exposed relapsed and refractory multiple myeloma patients in the USA. Future Oncology. 2021 Feb;17(5):503-15.

    4. Pollissard L, Shah A, Punekar RS, Petrilla A, Pham HP. Burden of illness among Medicare and non-Medicare US populations with acquired thrombotic thrombocytopenic purpura. Journal of Medical Economics. 2021 Jan 1;24(1):706-16.

    5. Mentz RJ, Pulungan Z, Kim S, Yang M, Teigland C, Hilkert R, Djatche LM. Quality outcomes, healthcare resource utilization and costs in Medicare patients with chronic heart failure with reduced ejection fraction with and without a worsening event. Journal of medical economics. 2021 Jan 1;24(1):698-705.

    6. Shah A, Petrilla A, Rebeira M, Feliciano J, Lisano J, LeBlanc TW. Health care resource utilization and costs among Medicare beneficiaries newly diagnosed with peripheral T-cell lymphoma: a retrospective claims analysis. Clinical Lymphoma Myeloma and Leukemia. 2021 Jan 1;21(1):e1-9.

    7. Pollissard L, Shah A, Punekar R, Petrilla A, Pham HP. Burden of Illness Among Medicare and Non-Medicare Populations with Acquired Thrombotic Thrombocytopenic Purpura, 2010-2018. Blood. 2020 Nov 5;136:19-20.

    8. Petrilla AA, Sutton BS, Leinwand BI, Parente A, Ferrari L, Wade CT. Incremental burden of mental health conditions in adult patients with focal seizures. Epilepsy & Behavior. 2020 Nov 1;112:107426.

    9. Petrilla A, Marrett E, Shen X, Kwong WJ, Pezalla E. Association between formulary coverage and use of abuse-deterrent prescription opioids, risk for abuse or overdose, and associated healthcare resource utilization. American health & drug benefits. 2020 Feb;13(1):21.

    10. Forma F, Green T, Kim S, Teigland C. Antipsychotic medication adherence and healthcare services utilization in two cohorts of patients with serious mental illness. ClinicoEconomics and Outcomes Research: CEOR. 2020;12:123.