Accelerating CMS Outcomes Data to Near Real Time: Challenges & Solutions - PowerPoint Presentation

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Accelerating CMS Outcomes Data to Near Real Time: Challenges & Solutions

Rosemarie Hakim, PhD CMS

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Background

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Medicare data have been available for research for decades

Privacy Act of 1974 allows use of identifiable data for research by a recipient who has provided CMS “with advance adequate written assurance that the record will be used solely as a statistical research or reporting record, and the record is to be transferred in a form that is not individually identifiable

”

The Computer Matching and Privacy Protection Act of 1988

allows matching of federal records with non-federal records to produce aggregate statistical data without any personal identifiers

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What Works Well Today

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Available dataChronic Condition Warehouse (CCW)

A research database that contains 100% Medicare files and.. Medicaid files

Assessment files

Part D Prescription Drug Event data

for Fee-for-service institutional and non-institutional claims

Linked by a unique, unidentifiable beneficiary key allow analysis across the continuum of care

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CCW contd.

Plan characteristicsPharmacy characteristicsPrescriber characteristicsFormulary file - beginning with year 2010

CCW data files may be requested for any of the predefined chronic condition cohorts, or users may request a customized cohort(s) specific to research focus areas.

Chronic Conditions Dashboard

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CCW conditions Acquired Hypothyroidism

Acute Myocardial InfarctionAlzheimer's DiseaseAlzheimer's Disease, Related Disorders, or Senile DementiaAnemiaAsthma

Atrial Fibrillation

Benign Prostatic Hyperplasia

Cancer, Colorectal

Cancer, Endometrial

Cancer, Breast

Cancer, Lung

Cancer, Prostate

Cataract

Chronic Kidney Disease

Chronic Obstructive Pulmonary Disease

Depression

Diabetes

Glaucoma

Heart Failure

Hip / Pelvic Fracture

Hyperlipidemia

Hypertension

Ischemic Heart Disease

OsteoporosisRheumatoid Arthritis / OsteoarthritisStroke / Transient Ischemic Attack

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Medicare – ccw condition period prevalence , 2010

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Cardiovascular conditions- Trends

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Other data available 10

Master Beneficiary Annual Summary File

Durable Medical Equipment

Medicare-Medicaid Linked Enrollee Analytic Data Source

MedPAR (Hospital and SNF)

Outpatient

Others (see ResDAC.org)

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Strengths of CMS Administrative Data11

Clinical validity - accurate and reliable:

Admission and discharge dates, diagnoses, procedures, source of care, demographics, place of residence, date of death,

Link to Other CMS Datasets

Population Coverage

>98% percent of adults age 65 and over are enrolled in Medicare.

> 99% percent of deaths in the US among persons age 65 and older are accounted

> 45 million beneficiaries enrolled in the Medicare program, allowing for detailed sub-group analysis with high statistical power.

Linkage to External Data Sources

:

US Census

Registries

Other providers (e.g. VA, Medicaid)

National death index/State vital statistics

Surveys (e.g. Health and Retirement Study)

Provider Information

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What Is Missing, Broken or Does Not Work Well Today

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Reliance on billing codes13

Conditions must be diagnosed to appear in the utilization files

Some diseases (hypertension, depression and diabetes) are underdiagnosed

No information on care

needed

but not provided

Services that providers know will be denied may be not be submitted as bills

Diagnosis information may not be comprehensive enough for detailed analysis

Prevalence may be misinterpreted as incidence

: knowing a person has a chronic disease does not reveal how long they have had the condition or the severity of their condition

The Part D prescription drug event file contains no diagnosis codes

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Reliance on billing codes14

Different care settings use different coding systems for procedures

Inpatient care is coded using ICD-9 procedure codes

Physician/supplier and DME data use CPT and HCPCS codes

Hospital outpatient care is a mix of CPT and revenue center code

No physiological measurements or test results

Not all beneficiaries have Part D coverage

Little information of unknown quality available about managed care enrollees

No information on services for which claims are not submitted (e.g. immunizations provided at Walgreens)

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Other limitations15

Specific programing expertise needed to analyze claims

In most cases, complex statistical techniques needed to correct biases

Propensity scores

Missing data algorithms

Data validation techniques

Severity adjusters

Sensitivity analyses

Complex regressions

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Challenges and solutions

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Research Data Time Lag 17

CCW data on 2-year lag for general research community

However – closer to real time data are available

In 6 months

96.7% of inpatient and 96.9% of outpatient claims are complete

How to get closer to real time data

Affordable Care Act allows

qualified entities

to acquire data for the evaluation of the performance of providers of services and suppliers

Data use agreement under a contract with CMS

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Matching Data to Medicare Claims18

Deterministic matching

Use

unique

personal identifiers (UPIs) present in Medicare claims and in registry/trial data

Good

Matching SSNs

Better

Matching SSNs and DOB

Best

Matching SSNs, DOB, gender, and provider

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Matching Data without UPIs19

No unique identifiers in data to be matched to claims

Good results can be obtained using non-unique variables:

DOB or age

Dates (admission, procedure date)

Gender

Hospital

Geographic region

Provider

Diagnosis

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Matching Data without UPIs contd.

20Probabilistic (fuzzy) matching

Uses wide range of potential identifiers

Computes weights based on sensitivity & specificity of identifier

Weights used to calculate the probability that 2 records refer to the same entity

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Matching rates 21

Authors

Data source

Type of matching

Results

St. Peter et al. 2011

Dialysis Clinical Outcomes Revisited (DCOR) Trial/Medicare

Unique identifiers

Nearly 100%

Brennan

et al. 2012

PCI Registry/Medicare

Deterministic

86%

Hammill

et al. 2009

Heart failure registry/Medicare

Deterministic

81%

Hammill

et al. 2009

Hospital HF records /Medicare

Deterministic

91%

Setoguchi

et al. 2012

ICD

Registry/Medicare

Deterministic

61%

Setoguchi

et al. 2012

ICD

Registry/Medicare

Probabilistic

85%

CDC/NCHS

2003-2004

NHANES

/Medicare

Probabilistic

98%

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Short term priorities

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Make Good Use of CMS Data 23

Build linking capability into study or registry

Include capability to link to Medicare claims data in informed consent

Plan data collection to include important linking variables

Use data for long term follow up for IDE studies and RCTs

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Make Good Use of CMS Data contd.

24Develop expertise – use of administrative data is increasing

Educational materials on CMS and ResDAC websites

ResDAC gives courses on using CMS data

Develop statistical expertise in using administrative data -

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Long Term Priorities

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Health Data Initiatives26

Office of Information Products and Data Analytics (OIPDA)

Develops, manages, uses, and disseminates data and information resources

Goal of improving access to and use of CMS data

Manages the

CMS Data Navigator

- web-based search tool

CMS’ EHR incentive program – encourages data interoperability and development of Health Information Exchanges

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Thank you 27

rosemarie.hakim@cms.hhs.gov

Chronic Conditions Data Warehouse

https://www.ccwdata.org/web/guest/home

ResDAC

http://www.resdac.org/