Methods and Advantages of Combining HOS and Your Organization’s Data to Improve Quality and Performance

Richard D. Hector, MA, MPH, PhD

Health Services Advisory Group

Medicare Advantage Quality Measurement &

Performance Assessment Training Conference

Baltimore MD

April 8 – 9, 2008

Goal

Demonstrate the advantages of linking HOS and Medicare

Advantage Organization data to identify quality and performance

results that support improvements in health-related quality of life

This could happen to you…

• On a great Monday morning after a wonderful weekend, you’re at your desk and ready to start a project that you had on the back burner.

• Your boss returns from a conference and is very excited about some results that were presented.

• Your boss wants you to replicate the results with your in-house data.

BMI, Physical Activity, and Health Care Utilization/Costs among Medicare Retirees Wang et al. Obesity Research, 2005, 13(8) Fig. 1

Adjusted Annual Total Health Care Costs by Physical Activity and BMI *

$12,715 $12,567 $12,795

$11,259$10,836

$11,515

$9,436$10,239$10,255

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

18.5<25 (n=8,920) 25<30 (n=20,572) 30+ (n=13,028)

Body Mass Index

Ann

ual T

otal

Cos

ts

0/Week 1-3/week 4+/Week

* Controlled: gender, age, major diseases, chronic diseases, overall health risks

Link HOS to Plan Data

Health Outcomes Survey Data Table

HICNUM SSN PATID Lastname Firstname Street City State Zip PCS …00123456 123456789 12345 Shakespeare William 12 Piper Ln Baltimore MD 12345 45 …00654321 987654321 54321 Hemingway Ernest 34 Fulton St Brooklyn NY 11222 30 …

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

Health Plan Data (Including claims paid)

HICNUM SSN PATID Lastname Firstname Street City State Zip Total Cost …00123456 123456789 12345 Shakespeare William 12 Piper Ln Baltimore MD 12345 7,845.00$ …00654321 987654321 54321 Hemingway Ernest 34 Fulton St Brooklyn NY 11222 12,345.00$ …

. . . . . . . . . . .

. . . . . . . . . . .

Use HIC or SS numbers to merge data sets

Plan

HOS

Data are simulated

Cardinal Health Plan

Data are simulated

Cardinal Health Plan

Data are simulated

Total Cost (simulated) by BMI and PCS

$8,4

18

$6,9

29 $8,2

23

$2,2

27

$6,2

89 $7,8

37

$6,9

03

$7,0

72

$9,2

94

$7,1

46 $8,6

47

$6,4

43 $7,6

76

$7,6

65 $9,4

07

$11,

624

$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

< 18.5 18.5 < 25 25 < 30 30+

Body Mass Index

Tota

l Cos

t

PCS Q1 PCS Q2 PCS Q3 PCS Q4

Data are simulated

PCS by BMI and General Health

19

30

41

52

56

21

29

42

49

55

20

30

40

47

52

23

29

38

43

50

15

20

25

30

35

40

45

50

55

60

Poor Fair Good Very good Excellent

General Health

PC

S< 18.5 18.5 < 25 25 < 30 30+

Data are simulated

Comorbidity by BMI and General Health

3.7

2.8

2.2

0.5

0.0

4.4

3.8

2.7

1.6

1.1

4.1

2.8

1.7

1.2

5.8

4.7

3.5

2.62.3

5.2

0

1

2

3

4

5

6

Poor Fair Good Very good Excellent

General Health

Com

orbi

dity

< 18.5 18.5 < 25 25 < 30 30+

Data are simulated

Comorbidity, PCS and General Health

19

30

41

52

56

21

29

42

49

55

20

30

40

47

52

23

29

38

43

50

15

20

25

30

35

40

45

50

55

60

Poor Fair Good Very good Excellent

General Health

PC

S

3.7

2.8

2.2

0.5

0.0

4.4

3.8

2.7

1.6

1.1

4.1

2.8

1.7

1.2

5.8

4.7

3.5

2.62.3

5.2

0

1

2

3

4

5

6

Poor Fair Good Very good Excellent

Co

mo

rbid

ity

< 18.5 18.5 < 25 25 < 30 30+

Data are simulated

Comorbidity, PCS and BMI

3.82 3.89 3.98

4.57

2.33

3.77

3.4

4.48

1.25

3.05

2.66 2.58

1

1.59

1.99

2.44

0

1

2

3

4

5

< 18.5 18.5 < 25 25 < 30 30+

Body Mass Index

Co

mo

rbid

ity

PCS Q1 PCS Q2 PCS Q3 PCS Q4

Data are simulated

Advantages of HOS Data

• HOS unique identifier for linking to in-house data

• Outcomes are calculated

• Well-being items validated

* PCS* MCS* Healthy Days* General Health* Chronic Diseases* Urinary Incontinence

More Advantages of HOS Data

• Trained interviewers

• Established sampling protocol

• Generalize to population of plan

• Check results against other States (e.g. public use files)

• Collaboration with persons outside of your organization

without jeopardizing confidentiality

• Large sample size (power)

HOS Program Timeline – HOSonline.org

• Annual baseline sample

• Two-year follow-up of baseline

Year 1

• January – March: Prepare survey, select sample, prepare interviewers

• April – July: Field survey for baseline & follow-up cohorts

• August – December: Clean, validate & score data

Year 2

• January – March: Manage and analyze data

• April –August: Prepare and disseminate data files, reports and data user guides

Quality Improvement Rationalizations (part 1)

Boat et al., February 6, 2008 JAMA 299 (5) p. 570

• Too busy to do anything more

• Cannot afford it

• Different approach already in place

• Already in the top quartile or top 10%

• Need more and better people

• Do not get paid for quality

Quality Improvement Rationalizations (part 2)

Boat et al., February 6, 2008 JAMA 299 (5) p. 570

• Quality improvement ideas cannot be applied to medicine because patients are heterogeneous

• Medical care is relational work requiring reflective professional practice

• Lack of knowledge about how to make changes in system

• Medical center is a teaching hospital

• Medical center is not a teaching hospital

Feedback from MA Plans (part 1)

Without a change in processes, beneficiaries experience similar outcomes

The period (interview to data dissemination) encourages focus on process rather than variation due to special causes

In-house project would have a similar duration (without the advantages)

• Data is outdated

Feedback from MA Plans (part 2)

• Your beneficiaries are sicker or different than patients in the survey

Link to your in-house data and customize the data to your beneficiaries

• Issues to consider with providers Providers witness the bad effects of processes Beneficial effects become part of the background Data-driven processes will have credibility with providers

Summary

The HOS is a rich data set. It can be used to show how quality and performance of care affect the health-related quality of life of patients enrolled in Medicare Advantage Organizations. HOS data files are available to any researcher through de-identified public use files.

However, when linked to in-house data, they can be a valuable resource. Plans can measure not only the effect of quality and performance on the health-related quality of life of patients, but also determine their effect on expenditures.

Since patients interviewed are a representative sample, policies to improve quality and performance can be evaluated knowing they affect all patients

Technical Queries

Health Services Advisory GroupHealth Services Advisory Group

For inquiries, please contact theFor inquiries, please contact theMedicare Health Outcomes Survey (HOS) Medicare Health Outcomes Survey (HOS)

Information and Technical SupportInformation and Technical SupportTelephone Line at (888) 880-0077 orTelephone Line at (888) 880-0077 or

E-mail Address (E-mail Address (hos@azqio.sdps.orghos@azqio.sdps.org).).

CMS HOS Website: CMS HOS Website: http://www.hosonline.orghttp://www.hosonline.org

Presentation Queries

Richard D. Hector, MA, MPH, PhD

Health Services Advisory Group

Phone: (602) 665 – 6133

Email: rhector@azqio.sdps.orgrhector@azqio.sdps.org

Thank you for your attention

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