OMHSAS Quality Management

Older Adult Committee

May 3, 2007

What is Quality Management?

An organized process to: Collect meaningful data, Turn the data into information Use that information to move the system

forward to meet your goals.

Common Issues in Quality Management

“You can’t tell if you are getting there if you don’t know where you are going”

“Data rich, information poor”

Factors in Quality Management

Relevance The impact of the factor merits the time and effort

spent measuring it, and is it actionable. Replicability

The intervention will achieve a predicted result all or most of the time.

Attribution Results are clearly attributable to what you measured

and not to other things you haven’t measured. Satisfaction

The results meet or exceed the consumers expectations

Types of Data

Encounter/claims dataSurvey DataStudy DataOther

Type of Data - Encounters

Claims or encounter data – Who got the service? How much service was delivered? How much did it cost? How do counties compare to each other? How does our data compare to national

standards?

Encounter Data - PBC

Performance Based Contracting Report Based largely on encounter data Measures include older adults, adults and

children, mental health and substance abuse Compared against epidemiological estimates

of prevalence

PBC – MH Users 18-64

PI #2.4, Percentage of Expected User Rate Receiving Any MH Service in HealthChoices, Ages 18 to 64

CY 200376%

CY 200476%

CY 200389%

CY 200392%

CY 200487%

CY 200496%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Southeast RegionAverage

Southwest RegionAverage

Lehigh/Capital RegionAverage

Gold Standard

PBC – SA Users 18-64

PI #2.6, Percentage of Expected User Rate Receiving Any SA Service in HealthChoices, Ages 18 to 64

CY 200343% CY 2003

33%

CY 200463%

CY 200447%

CY 200434%

CY 200365%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Southeast RegionAverage

Southwest RegionAverage

Lehigh/Capital RegionAverage

Gold Standard

PBC – Service Users - 65+

PI #2.7a, Annual Medicaid Service Users per 1,000 Eligibles, Ages 65+Regional Utilization of Any Service in CY 2004

60.2

44.9 47.0

-

10.0

20.0

30.0

40.0

50.0

60.0

70.0

Southeast Region Southwest Region Lehigh/Capital Region

StatewideAverage

PBC - Readmission Rate, 21 to 64

PI #4b, Percentage of Psychiatric Inpatient Discharges Who Are Readmitted Within 30 Days Post-Discharge, Ages 21 to 64

CY 2002Baseline14.8%

CY 2002Baseline14.9%

CY 2002Baseline14.5%

CY 200317.6%

CY 200313.4%

CY 200315.4%CY 2004

14.1%

CY 200416.6%

CY 200419.4%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Southeast RegionAverage

Southwest RegionAverage

Lehigh/Capital RegionAverage

Gold StandardandNationalNorm

PBC - Readmission Rate, 65+

PI #4c, Percentage of Psychiatric Inpatient Discharges Who Are Readmitted Within 30 Days Post-Discharge, Age 65+

CY 2002Baseline

3.5%

CY 2002Baseline12.3%

CY 20036.8%

CY 20048.2%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Southeast RegionAverage

Southwest RegionAverage

Lehigh/Capital Average

Gold StandardandNationalNorm

PBC - 7 Day Follow Up, 21 to 64

PI #5c, Percentage of Individuals Discharged From Psychiatric Inpatient With Follow-Up Service(s) Within 7 Days Post-Discharge, Ages 21 to 64

CY 200434%CY 2004

32%

CY 200436%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Southeast RegionAverage

Southwest RegionAverage

Lehigh/Capital Average

Gold Standard

NationalNorm

PBC - 7 Day Follow Up, 65+

PI #5d, Percentage of Individuals Discharged From Psychiatric Inpatient With Follow-Up Service(s) Within 7 Days Post-Discharge, Ages 65+

CY 200417%

CY 200414% CY 2004

10%

CY 200414%

CY 200419%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Philadelphia SoutheastSuburban

Allegheny SouthwestSuburban

Lehigh/Capital

Gold Standard

NationalNorm 1

Type of Data - Surveys

Satisfaction Data – Did consumers feel the services were helpful? Depending on instruments, can be analyzed

compared to other populations. Outcomes Data –

How are consumers doing in their lives? How are consumers doing with their

symptoms? Can be compared among programs.

Satisfaction Results

Measure 3rd Qtr 2005

2nd Qtr 2006

Change

Problem getting help he/she needed

35.9% 40.0% -4.1%

Chance to make treatment decisions

86.7% 83.1% +3.6%

Better quality of life 71.4% 79.1% +7.7%

Outcome Survey

POMS – Reported on priority populations (SMI and

SED) quarterly Standardized output specified No standardized tool or administration

methodology defined.

Type of Data - Studies

Study Data – Identify a particular issue of interest Can be conducted internally or by an external

organization Chart review of a statistically valid sample Is very labor intensive; must be replicated to

determine if there is change in the system.

Study Data – IPRO IP Follow-up

Year-to-Year Comparison of Aggregate Quality Indicator Rates

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

QI 1 QI 2 QI 3 QI 4

Indicator #

Rat

e MY 2002

MY 2004

MY 2005

Study Data – IPRO IP Follow-up

Quality Indicator Rates by Race

31.1

%

46.5

%

61.1

%

43.5

%

34.0

%

55.3

%

68.1

%

46.8

%

40.7

%

23.7

%

45.2

%

63.8

%

40.7

%

58.5

%

69.5

%

50.2

%

41.6

%

66.9

%

46.7

%

60.7

%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

QI 1 QI 2 QI 3 QI 4

Indicator #

Rat

e

Black/African AmericanAmerican Indian/Alaskan NativeAsianWhiteOther

Study Data – IPRO RTF Study

RTF Facility Measures 2001-2002

2004-2005

Onsite meeting with family within 7 days of admission

42.3% 79.7%

Documentation to OP provider sent within 7 days prior to date of discharge

5.5% 14.8%

Medication rationale documented in chart discharge planning notes

40.6% 50.3%

Other - NOMS

• Reduced Morbidity • Access/Capacity

• Employment/Education • Retention

• Criminal Justice • Perception of Care

• Stability in Housing • Cost Effectiveness

• Social Connectness • Use of EBPs