implementing a population health model (hon pak)

Implementing a Population Health Model Health IT Perspective

2 . All Rights Reserved. 11 November 2016 © 3M 3M Confidential.

Disclosure

Hon S. Pak, MD Chief Medical Officer

3M Health Information Systems “We are Data Scientists of Language of Health, and we organize healthcare data and provide tools

to support our clients journey toward value based care“

PEHRC, Executive Committee AAD Coding and Reimbursement Committee

Editorial Board Telemedicine and e-Health Journal Past President, American Telemedicine Association

President of Lavonne Morse Foundation Former CIO and CMIO, Army Medical Department


Population Health Models and Value Based Payment Models

APMS

ACO/ PCMH

Bundled Payments

P4P Value Based Care

Example: Supporting a health system’s ability to manage risk-based contracts and bundled payment models.

Foundation: Data Aggregation and Classification

Value Based Care

Population Health Strategy Pillars


2

The Concentration of Health Care Spending

program spending and the top 5 percent are responsible for 38 percent of spending.1

With numbers like these, it is clear that per-person spending among the highest users is substantial and represents a natural starting point when thinking about how to curb health care spending. For instance, the average expenditure for each of the approximately 3 million people comprising the top 1 percent of spenders was more than $90,000 in 2009 (Figure 2). The top 5 percent of spenders were responsible for

$623 billion in expenditures or nearly $41,000 per patient. In contrast, mean annual spending for the bottom half of distribution was just $236 per person, totaling only $36 billion for the entire group of more than 150 million people.

While the highly skewed distribution of spending has been observed for many years, spending has actually become slightly less concentrated over time as high spending has spread to a broader swath of the population. For example, whereas 56 percent of

0%

0

10%

10 2015.4

95 990.0 0.1 0.4 1.32.9

5.6

10.4

18.8

34.8

50.5

78.2

100.0

30 40 50 60 70 80 90 100

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total Personal Health Care Spending= $1.259 Trillion

Top 1% of spenders account for >20% of spending ($275 billion)

Top 5% of spenders account for almost half of spending ($623 billion)

$36 Billion $1,223 Billion

Percent of Civilian Non-Institutionalized Population Ordered by Health Care SpendingCu

mul

ativ

e Pe

rcen

t of T

otal

Spe

ndin

g

FIGURE 1. CUMULATIVE DISTRIBUTION OF PERSONAL HEALTH CARE SPENDING, 2009

NIHCM Foundation analysis of data from the 2009 Medical Expenditure Panel Survey.

Foundation to Pop Health •  Aggregation of the data (claims, clinical,

and other)- Master Data Management •  Categorization/ Risk stratification of

population (Examples: DRG, APR, CRGs, etc)

Population Health Tools •  Bundle Payments: Patient Focused

Episode Groupers •  Shared Saving/ Risk Sharing/ Capitation

•  Opportunities for cost reduction (prevent readmissions, ER visits, complications)

•  Opportunities to identify gaps in care •  Pay for Performance

•  Provider/ system performance in comparison to national standards of care

•  Predictive models


Health Information Systems

19 . All Rights Reserved. 28 October 2015 © 3M 3M Confidential.

Maryland Quality-Based Reimbursement Program 2009–2011 RESULTS & NATIONAL OPPORTUNITY

Extrapolated from 2-year Maryland’s

6% inpatient cost savings to Medicare’s

Fee-for-Service national program

Hospital Pay-For-Performance Programs in Maryland Produced Strong Results, Including Reduced Hospital-Acquired Conditions - Sule Calikoglu, Robert Murray, Dianne Feeny, Health Affairs, 31, no. 12 (2012): 2649-2658

Health Information Systems

17 . All Rights Reserved. 28 October 2015 © 3M 3M Confidential.

Maryland Quality-Based Reimbursement Program STATE OVERVIEW


Opportunity/Challenge for Population Health

Additional Source of Data •  Patient-reported outcomes

data •  Social determinants of

health data •  Activity-based costing data

that will allow accurate management of financial margins in per-capita reimbursement contracts.


Experience matters

in today’s healthcare world

45MILLION

LIVES

63HEALTH PLANS & PAYERS

INSURANCE CARD

0000-5555-000-22

with whom 3M has relationships or from whom 3M accepts data*

300THOUSAND

PHYSICIANSreported by the AHA

Guide for the states fromwhich 3M manages orreceives payer data 2

covered through 3M’s payer data assets*

5,000+

healthcare provider customers*

15-20%

$44 millionin gross savings

COLORADO

reduction in hospital readmissions(relative to a comparison population prior to program implmentation.)

$6 millionnet reduction in total cost of

care for program enrollees

From the Accountable Care Collaborative Annual Report,Colorado Department of Health Care Policy and Financing (November 2013)

$105 million

3M helped the state of Maryland save

over a two-year span by reducing the incidence andcost of potentially preventable complications (PPC)*

*Data on file

Thank You

implementing a population health model (hon pak)

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