Data in PACE and How it Relates to the World

Data TeamNational PACE Association

Data FlowThe myriad types of data currently received

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The Times They Are a Changin’ …

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The way data are collected and stored is

being dismantled

Relational databases are

passé

Ivory towers are being

dismantled

Authority from where to

draw conclusions is

shifting

The sweep is broad and far

reaching

Disease outbreak signals from social media

Reinhart, Rogoff study and

economic growth

“Changin” times impact Data in PACE

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• CMS mandates PACE organization data collection and submission. It is prescriptive

• On Lok offers DataPACE, a data management and benchmarking service

1989DataPACE

1st Generation

• New data collection developed by PACE Data Management Steering Committee to supplement DataPACE which by now is optional following the Balanced Budget Act of 1997

• State regulators for states where data are mandated have input into data domains

2006 DataPACE2

2nd Generation

• Data elements determined independently by NPA and representatives from PACE organizations with no regulatory input

• Data elements selected based on their ability to serve PACE operations and objectives

2016Common Data

Set (CDS)3rd Generation

Common Data Set – A Brief Primer

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Goals and Objectives

Data Sets Created

Process to Developthe CDS

Generate standard quality indicators Support PACE organizations internal quality

improvement programs Allow for efficient, meaningful, timely and

accurate benchmarking Accurately describe and compare PACE

enrollees to other populations to demonstrate PACE value

Support the improvement and universal adoption of PACE specific Electronic Health Record systems

Common Data Set – A Brief Primer

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Goals and Objectives

Data Sets Created

Process to Developthe CDS

Analyzed current data standards and practices in PACE, as well as existing geriatric assessment tools

Identified issues in existing data flow and designed the optimal future data flow process

Constituted a Data Steering Committee with representation from all types of PACE organizations and functional areas

Selected data elements of relevance to PACE Created file layouts in partnership with IT

professionals from PACE organizations Currently, soliciting and incorporating inputs

from PACE organizations to arrive at standardized definitions of services

Common Data Set – A Brief Primer

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Goals and Objectives

Data Sets Created

Process to Develop the CDS

CDS I: about 100 elements of assessment and demographic data

CDS II: about 60 elements of service and utilization data

Common Data Set is developed internally and independently at PACE, yet most major aspects are aligned with different data initiatives

occurring simultaneously in the healthcare arena

Convergence with Other Data Initiatives in Healthcare

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Impact Act

Tool for Functional Assessment

Standardized Items

Quality Measures proposed by

Econometrica

Provides strong counterpoint that best practices were used

Convergence with Impact Act and why the Act is Relevant for PACE

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POs use the same assessment tools as the PAC

providers or draw from them

CDS has been built using data

items from these same assessment

tools

As Impact Act aligns the different

assessment tools, CDS will be

calibrated towards this

alignment

The Improving Medicare Post-Acute Care Transformation Act of 2014 is a law intended to change and improve Medicare’s post-acute services and reporting

PAC providers and assessment tools usedLong term care hospitals - LCDS Home health agencies - OASISSkilled nursing facilities - MDS Inpatient rehab facilities - IRF-PAI

What is the Impact Act

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Requires post-acute care providers (PAC)* to report standardized patient assessment data, data on quality measures and data on resource use and other

measures

Requires the data to be inter-operable to allow for exchange among PAC and other providers to give them access to longitudinal information to facilitate

coordinated care and improve Medicare beneficiary outcomes

Modify PAC assessment instruments applicable to PAC providers for the submission of standardized patient assessment data on such providers and

enable data comparison across all providers

The lack of comparable information across PAC settings undermines the ability to evaluate and differentiate appropriate care settings for and by individuals and their caregivers

Common Features between the Impact Act and CDSInability to Compare Across Settings is Major Impetus for the Impact Act and CDS

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Comm

on Data SetIm

pact

Act

The lack of comparable data across POs undermines the ability to develop comparative consistency in benchmarking and distinguish PACE value from other options for duals. In addition, there is inability to: Create a profile of the PACE

participant

Provide direction for PACE specific EHRs

Require submission of standardized assessment data by PACs

CMS, however will not replace standardized instruments with one common assessment tool

Common Features between the Impact Act and CDSCollection of Standardized Assessment Data – Similar Philosophy

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Comm

on Data SetIm

pact

Act

Requires submission of standardized assessment data by POs

CDS created keeping in mind POs need to use assessment tools best suited for their program

Functional Status

Cognitive Function

Special Services

Medical Conditions

and Impediment

Data in Similar Categories will be Collected

Common Features between the Impact Act and CDSData is Participant-centric and Supports Quality Strategies that are Similar

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Comm

on Data SetIm

pact

Act

The principal is that data follows the person from setting to setting

Makes possible access to longitudinal information for all providers to facilitate coordinated care and improved outcomes

Data is participant centric: each data element is tied to a participant

Makes possible access to longitudinal information for predictive analytics to assist with determining optimal level of care and appropriate intervention

Cognitive and

functional status and

changes

Skin integrity

and changes

Medication recon-

ciliation

Incidence of major

falls

Quality Domains

Care preference

of an individual

Common Features between the Impact Act and CDSOrganization of Data in Domains

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Quality Measure Domains

Assessment Categories

Other DEL Domains

CDS IParticipant

Characteristics

CDS IIParticipant Experience

The data element library will be a centralized repository of assessment data mapped to HIT vocabularies, domains etc.

In the CDS, variations will be mapped to derive a standardized native data set

Impa

ct A

ctCom

mon Data Set

Common Data Set is developed internally and independently at PACE, yet most major aspects are aligned with different data initiatives

occurring simultaneously in the healthcare arena

Convergence with Other Data Initiatives in Healthcare

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Impact Act

Tool for Functional Assessment

Standardized Items

Quality Measures proposed by

Econometrica

Provides strong counterpoint that best practices were used

Based on the post-acute care settings in the Continuity Assessment Record and Evaluation (CARE) tool, it is a demonstration funded by CMS

What is the Tool for Functional Assessment Standardized Items (FASI)

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Requires testing the reliability of a setting-agnostic, interoperable set of data elements from the CARE tool called “items”, that can support standardized

assessment of individuals across the continuum of care in community based long term services and supports programs

Intended for use amongst various populations: Elders (65 years and older); younger adults (18-64) with physical disabilities and adults of any age with

intellectual or developmental disabilities

Assessment data is intended for use for multiple purposes like use of standardized items to determine individual eligibility for state programs or to help

determine levels of care

Interoperability: Data elements support standardized assessment of individuals across continuum of care in community based long term services and supports programs

Multiple purposes for data Individual eligibility for

programs

Determine levels of care

Common Features between the FASI and CDS

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Comm

on Data SetF

A S

I

Data is participant-centric for participant condition and for all services by all providers in all locations

Multiple purposes for data Quality measures

Analytics to determine optimal interventions

Common Data Set is developed internally and independently at PACE, yet most major aspects are aligned with different data initiatives

occurring simultaneously in the healthcare arena

Convergence with Other Data Initiatives in Healthcare

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Impact Act

Tool for Functional Assessment

Standardized Items

Quality Measures proposed by

Econometrica

Provides strong counterpoint that best practices were used

A private research and management consulting firm that provides analyses, modeling, and economic evaluations for clients in the private and public sectors

What is Econometrica

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CMS contracted with Econometrica to adapt, implement, and maintain quality measures for the nationwide PACE program. The contract name is Development, Implementation, and Maintenance of Quality Measures for the Programs of All-

Inclusive Care for the Elderly

The primary objectives of this project is to analyze existing quality measure sets to determine the extent to which they can be modified, refined, or enhanced to

be appropriate to the uniqueness of the PACE programand organization

Focus on three areas of measurement - Falls, Falls with Injury, and Pressure Injury

Quality Care and Improved Outcomes Objective of Econometrica

measures is to help CMS provide oversight

Develop prevention measures which CMS and Econometrica believe are vital to ensuring quality of care for PACE participants

Cognizant about burden extra data collection imposes

Common Features between Econometrica and CDS

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Comm

on Data SetEcon

omet

rica Quality Improvement and

demonstrate PACE value Objective of CDS is to capture

data elements that are needed to create meaningful measures

CDS is flexible and can accommodate changes required to support Econometrica methodology

CDS has been designed to minimize data burden by incorporating existing data structures

Data in PACE and How It Relates to the World

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Discussion

Where do we go from here