SHOW - MESHOW - ME

Chronic Medical Conditions

Associated with

Severe Mental Illness

My BackgroundMy Background

• DMH Medical Director• Consultant to MoHealthNet (Missouri Medicaid)• President NASMHPD Medical Director’s Council• Practicing FQHC Psychiatrist• Director Missouri Institute of Mental Health –

University of Missouri St Louis

National Association of State Mental National Association of State Mental Health Program Directors (NASMHPD)Health Program Directors (NASMHPD)

• Membership is the Commissioners/Directors of state mental health agencies all 50 states, 4 territories, and the District of Columbia who are responsible for the provision of mental health services to citizens utilizing the public system of care.

• Represents the $23 billion public mental health service delivery system serving 6.1 million people annually.

• NASMHPD Medical Directors Council identifies emerging clinical and provides policy guidance to national mental health leadership

Morbidity and Mortality in People with Morbidity and Mortality in People with Severe Mental IllnessSevere Mental Illness

• 13th Technical Report of The NASMHPD Medical Director’s Council

• Available in full at http://www.nasmhpd.org/medical_director.cfm

• Original Research by NASMHPD Research Institute (NRI)

• Funded by CMHS-SAMHSA

Overview: THE PROBLEMOverview: THE PROBLEM

• Increased morbidity and mortality associated with serious mental illness (SMI)

• Increased morbidity and mortality largely due to preventable medical conditions – Metabolic disorders, cardiovascular disease, diabetes mellitus– High prevalence of modifiable risk factors (obesity, smoking)– Epidemics within epidemics (eg, diabetes, obesity)

• Some psychiatric medications contribute to risk

• Established monitoring and treatment guidelines to lower risk are underutilized in SMI populations

Multi-State Pilot StudyMulti-State Pilot Study

• Compared DMH clients with general population• 1997 – 2000• States: Arizona Missouri

Oklahoma Rhode Island

Texas Utah

Virginia District of Columbia

Mortality Associated with Mental Disorders: Mortality Associated with Mental Disorders: Mean Years of Potential Life LostMean Years of Potential Life Lost

Compared with the general population, persons with major mental illness lose 25-30 years of normal life span

Year AZ MO OK RI TX UT

1997 26.3 25.1 28.5

1998 27.3 25.1 28.8 29.3

1999 32.2 26.8 26.3 29.3 26.9

2000 31.8 27.9 24.9

Lutterman, T; Ganju, V; Schacht, L; Monihan, K; et.al. Sixteen State Study on Mental Health Performance Measures. DHHS Publication No. (SMA) 03-3835. Rockville, MD: Center for Mental Health Services, Substance Abuse and Mental Health Services Administration, 2003. Colton CW, Manderscheid RW. Prev Chronic Dis. Available at: ttp://www.cdc.gov/pcd/issues/2006/apr/05_0180.htm.

ResultsResults

Measure Range Mean Mode

Standardized Mortality Rates

0.6 – 4.9 2.2 2.2

Average Years Life Lost

13.5 – 29.3 25.2 26.9

Average Age at Death

48.9 – 76.7 56.8 57.7

Total YPLL by Primary Cause for Public Total YPLL by Primary Cause for Public Mental Health Patients with Mental IllnessMental Health Patients with Mental Illness

Primary cause of deathTotal YPLL

(Person-years lost) Deaths (n)

Heart disease 14,871.2 612

Cancer 5,389.9 241

Suicide 4,726.1 115

Accidents, including vehicles 3,467.0 98

Chronic respiratory 2,700.9 113

Diabetes 1,419.6 61

Pneumonia/influenza 1,254.2 67

Cerebrovascular disease 1,195.9 58

All causes of death* 47,812.2 1,829*Note: Includes deaths from causes not listed; YPLL = years of potential life lost

Unpublished results courtesy of CW Colton

Combined data for schizophrenia and schizoaffective disorder from 5 US states (MO, OK, RI, TX and UT) from 1997 to 2001

-60

-50

-40

-30

-20

-10

0

10

79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95

Dec

line

(%)

Noncardiovascular Disease

Coronary Heart Disease (CHD)

Stroke

Morbidity and Mortality Weekly Report. 1999; 48(30):649-656.

Change in US General Population Age-Adjusted Change in US General Population Age-Adjusted Mortality (1979-1995)Mortality (1979-1995)

Year

Mortality Risk From All Causes and From Mortality Risk From All Causes and From Cardiovascular Disease Increased Among Cardiovascular Disease Increased Among Patients With Schizophrenia Between 1970-2003Patients With Schizophrenia Between 1970-2003

0

0.5

1

1.5

2

2.5

3

1970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2003

All Causes Cardiovascular Disease

0

0.5

1

1.5

2

2.5

1970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2003

All Causes Cardiovascular Disease

Test for time trends of excess relative risks for SMRs were statistically significant (P<0.001) for all cause mortality and mortality due to cardiovascular disease.

Men Women

Rel

ativ

e R

isk

for

Sta

nd

ard

ized

Mo

rtal

ity

Rat

io

Rel

ativ

e R

isk

for

Sta

nd

ard

ized

Mo

rtal

ity

Rat

io

Ösby U et al. BMJ. 2000;321:483-484, and unpublished data courtesy of Urban Osby.

Ohio Study-Discharged InpatientsOhio Study-Discharged InpatientsStandardized Mortality RatiosStandardized Mortality Ratios

Cause OverallN SMR

All causes of death 608 3.2†Intentional self-harm (suicide) 108 12.6†Symptoms, signs, & abnormal 32 9.7† clinical & laboratory findings, NECPneumonia & Influenza 16 6.6†Chronic lower respiratory diseases 31 5.5†Accidents (unintentional injuries) 83 3.8†Diseases of heart 126 3.4†Diabetes mellitus 18 3.4†Assault (homicide) 10 1.7Cerebrovascular diseases 10 1.5Malignant neoplasms (cancers) 44 0.9

† P<0.001

Maine Study Results: Comparison of Health Maine Study Results: Comparison of Health Disorders Between SMI & Non-SMI GroupsDisorders Between SMI & Non-SMI Groups

Osby U et al. Schizophr Res. 2000;45:21-28.

Schizophrenia: Schizophrenia: Natural Causes of Death Natural Causes of Death

• Higher standardized mortality rates than the general population from:– Diabetes 2.7x– Cardiovascular disease 2.3x– Respiratory disease 3.2x– Infectious diseases 3.4x

• Cardiovascular disease associated with the largest number of deaths – 2.3 X the largest cause of death in the general population

What are the Causes of Morbidity and Mortality What are the Causes of Morbidity and Mortality in People with Serious Mental Illness?in People with Serious Mental Illness?

• 88% of the deaths and 83% of premature years of life lost in persons with serious mental illness are due to “natural causes”– Cardiovascular disease– Diabetes– Respiratory diseases– Infectious diseases

How Does This Relate to What is Happening How Does This Relate to What is Happening in the General Population?in the General Population?

• There is an “epidemic” of obesity and diabetes, increasing risk of multiple medical conditions and cardiovascular disease. – Obesity – Diabetes – Metabolic Syndrome– Cardiovascular Disease

Identification of the Metabolic SyndromeIdentification of the Metabolic Syndrome

≥3 Risk Factors Required for Diagnosis

Risk Factor Defining Level

Abdominal obesity Men Women

Waist circumference >40 in (>102 cm) >35 in (>88 cm)

Triglycerides 150 mg/dL (1.69mmol/L)

HDL cholesterol Men Women

<40 mg/dL (1.03mmol/L) <50 mg/dL (1.29mmol/L)

Blood pressure 130/85 mm Hg

Fasting blood glucose 110 mg/dL (6.1mmol/L)

HDL = high-density lipoprotein.NCEP III. Circulation. 2002;106:3143-3421.

CHD Risk Increases with Increasing Number CHD Risk Increases with Increasing Number of Metabolic Syndrome Risk Factors of Metabolic Syndrome Risk Factors

Sattar et al, Circulation, 2003;108:414-419Whyte et al, American Diabetes Association, 2001Adapted from Ridker, Circulation 2003;107:393-397Adapted from Ridker, Circulation 2003;107:393-397

00.5

11.5

22.5

33.5

44.5

55.5

66.5

7

one two three four

Rel

ativ

e R

isk

Comparison of Metabolic Syndrome and Individual Comparison of Metabolic Syndrome and Individual Criterion Prevalence in Fasting CATIE Subjects and Criterion Prevalence in Fasting CATIE Subjects and Matched NHANES III SubjectsMatched NHANES III Subjects

Metabolic Syndrome Prevalence 36.0% 19.7% .0001 51.6% 25.1% .0001

Waist Circumference Criterion 35.5% 24.8% .0001 76.3% 57.0% .0001

Triglyceride Criterion 50.7% 32.1% .0001 42.3% 19.6% .0001

HDL Criterion 48.9% 31.9% .0001 63.3% 36.3% .0001

BP Criterion 47.2% 31.1% .0001 46.9% 26.8% .0001

Glucose Criterion 14.1% 14.2% .9635 21.7% 11.2% .0075

Meyer et al., Presented at APA annual meeting, May 21-26, 2005. McEvoy JP et al. Schizophr Res. 2005;(August 29).

Recommendations Recommendations

• Adopt American Diabetes Association (ADA) and American Psychiatric Association (APA) Second Generation Antipsychotic (SGA) monitoring as a standard of care practice for the population with serious mental illness – Be weighed on every visit; – Receive testing of glucose and lipids every year; – Receive blood pressure checks at 12 weeks and then annually– Receive treatment interventions ; • Promote opportunities for health care providers, including

peer specialists, to teach healthy lifestyles to families, individuals, and older adults

ADA/APA/AACE/NAASO Consensus on Antipsychotic ADA/APA/AACE/NAASO Consensus on Antipsychotic Drugs and Obesity and Diabetes: Monitoring ProtocolDrugs and Obesity and Diabetes: Monitoring Protocol**

*More frequent assessments may be warranted based on clinical status

Diabetes Care. 27:596-601, 2004

StartStart 4 wks4 wks 8 wks8 wks 12 wk12 wk qtrlyqtrly 12 mos.12 mos. 5 yrs.5 yrs.

Personal/family HxPersonal/family Hx XX XX

Weight (BMI)Weight (BMI) XX XX XX XX XX

Waist Waist circumferencecircumference

XX XX

Blood pressureBlood pressure XX XX XX

Fasting glucoseFasting glucose XX XX XX

Fasting lipid profileFasting lipid profile XX XX XXXX

OverviewOverview

• The rising tide of obesity in the general public• Obesity in persons with SMI

– Prevalence and Etiology– Implications

• Public health approaches to addressing obesity in persons with SMI

ObesityLifestyle

Ψ Medications

Heart DiseaseDiabetes

Primary Prevention

Diet and exercise

Initial Choice of Ψ meds

Secondary Prevention Tertiary Prevention

Switching Ψ medications

Medications for obesity and medical comorbidities

Bariatric Surgery

Screening

A Public Health Approach toA Public Health Approach toAddressing Obesity in SMIAddressing Obesity in SMI

0

10

20

30

40

50

60

70

Pre

vale

nce

(%)

Healthy Overweight Obese Healthy Overweight Obese

N=12,363

“Overweight” = BMI 25-29.9“Obese” = BMI 30 (National Heart, Lung, and Blood Institute, Obesity Guidelines)

MenMen WomenWomen

Prevalence of Metabolic Syndrome According Prevalence of Metabolic Syndrome According to BMI in the Adult General Populationto BMI in the Adult General Population

Park et al. Arch Intern Med. 2003;163:427.

Obesity Rate by CountryObesity Rate by Country

0 10 20 30 40 50

CHN

NGA

FRA

BRA

ITA

DEU

GBR

CAN

MEX

USA

Men

Women

Source: WHO Global Infobase, http://www.who.int/ncd_surveillance/infobase/en/index.html. Retrieved 8/10/06.

2005 WHO Global Comparable Estimates, both urban and rural populations

Risk of Obesity Among Patients Risk of Obesity Among Patients with SMIwith SMI

Disorder ↑Odds of Obesity

1. Simon GE et al Arch Gen Psychiatry. 2006 Jul;63(7):824-30.2. Petry et al Psychosom Med. 2008 Apr;70(3):288-973. Coodin et al Can J Psychiatry 2001;46:549–55

Depression 1.2 - 1.8x1,2

Bipolar Disorder 1.5 – 2.3x1,2

Schizophrenia 3.5x3

Causes of Obesity in Persons Causes of Obesity in Persons with SMIwith SMI

• Increased caloric intake• Decreased physical activity• Psychotropic medications

Diet in Persons Diet in Persons with SMIwith SMI

• Increased quantity and caloric intake1

• Potential differences in diet composition; lower fiber, higher fat, fewer fruits and vegetables2,3

• Similar patterns seen for low-income adults4,5

1. Strassnig, Brar and Ganguli Schizophr Res 2003;62:73–6.2. McCreadie et al Br J Psychiatry 2003;183:534–9.3. Brown et al Psychol Med 1999;29:697–701. 19994. Lin, B. AIB-796-1, USDA, Economic Research Service, February 2005.5. Kant AK Public Health Nutr. 2007 Feb;10(2):158-67.

Inactivity Among Patients Inactivity Among Patients with SMIwith SMI

Disorder ↑Odds of Inactivity

1. Daumit et al J Nerv Ment Dis. 2005 Oct;193(10):641-62. Elmslie et al J Clin Psych 2001 Jun;62(6):486-91.3. Farmer et al Am J Epidemiol. 1988 Dec;128(6):1340-51

Severe Mental Illness 1.5x1

Bipolar Disorder 3.2x2

Depression 2.0x3

Psychotropic Medications and Psychotropic Medications and Weight GainWeight Gain

• Most antidepressants1

• Most mood stabilizers2

• Most antipsychotic medications3

• However there are alternative drugs within each class that are potentially weight-neutral

1. Rader et al J Clin Psychiatry. 2006 Dec;67(12):1974-82.2. Kerry et al Acta Psychiatr Scand 1970: 46: 238-43.3.Newcomer J Clin Psychiatry. 2007;68 Suppl 4:8-13.

Another Patients ViewAnother Patients View

Obesity as a Risk Factor for Obesity as a Risk Factor for Antipsychotic NoncomplianceAntipsychotic Noncompliance

Noncompliant Respondents According to BMI Category

*P = 0.01 vs normal; Chi-square: P = 0.03.Test for linearity: .P = 0.01 Schizophrenia population.Weiden PJ, et al. Schizophr Res. 2004;66:51-57.

Non

com

plia

nce

(%)

*

*

Consequences of Obesity in Persons Consequences of Obesity in Persons with SMIwith SMI

• Medical morbidity• Stigma, reduced quality of life• Mortality

INTERVENTIONSINTERVENTIONS

• Public Health Approach - preventive• Behavioral Treatment – up to 15% wt loss• Psychiatric Medications

– Differential risk of weight gain– Switching to reduce weight

• Weight Loss Mediations – up to 10% loss• Surgery – substantial wt loss

Clinical Trials of Behavioral TreatmentClinical Trials of Behavioral Treatment

• Persons with mental illness do respond to behavioral weight loss interventions– About half of the patient experience clinically

significant weight loss– The outcomes are close to those of real-life results

with commercial weight loss programs– But the goals of treatment are not cosmetic

Number Needed to Treat (NNT): Number Needed to Treat (NNT): Behavior Therapy vs. Usual Care Behavior Therapy vs. Usual Care

NNT• For 3% weight loss 3• For 4% weight loss 3• For 5% weight loss 6

Brar JS, Ganguli R, et al. J Clin Psychiatry. 2005;66:205-212.

Recommendations for PrescribersRecommendations for Prescribers

• Prescribing clinicians should use medications with lower risk of weight gain when possible – Choose low weight gain Medications initially– Switch to Lower Weight Gain Medication if

• Weight increases• Glucose intolerance occurs• Lipid levels rise

Recommendations for PrescribersRecommendations for Prescribers

• Utilize weight loss medication when appropriate – Only when Lifestyle changes fail– Only in patients with a BMI≥ 30 or a BMI≥ 27 with at least

two risk factors. • In consultation with the patient, recommend bariatric

surgery when all other methods of weight loss have been tried and failed– Only when all other interventions fail– Only in persons with a BMI of 40 or higher; or a BMI of 35 or

higher in a patient with a high-risk condition

Mean Change in Weight With AntipsychoticsMean Change in Weight With Antipsychotics

*4–6 week pooled data (Marder SR et al. Schizophr Res. 2003;1;61:123-36; †6-week data adapted from Allison DB, et al. Am J Psychiatry. 1999;156:1686-1696; Jones AM et al. ACNP; 1999.

Estimated Weight Change at 10 Weeks on “Standard” Dose

Haloper

idol

Risper

idone

Olanza

pine

Cloza

pine

6

Wei

gh

t C

han

ge

(kg

)

5

4

3

2

1

0

-1

-2

-3

Place

bo

Fluphen

azin

e

Zipra

sidone

Chlorp

rom

azin

e

Thiorid

azin

e/

Mes

oridaz

ine

13.2

Weig

ht C

han

ge (lb

)

11.0

8.8

6.6

4.4

2.2

0

-2.2

-4.4

-6.6

Quetia

pine

Aripip

razo

le

†

*

Data for ziprasidone, risperidone, quetiapine, and olanzapine from US labels.

Clinically Significant (7%) Weight Gain During Antipsychotic Treatment

0

5

10

15

20

25

30

35

Placeb

o

Aripipraz

ole

Placeb

o

Ziprasidone

Placeb

o

Risperi

done

Placeb

o

Quetiap

ine

Placeb

o

Olanza

pine

Inci

denc

e (%

)

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

1-Year Weight Gain: 1-Year Weight Gain: MMeanean Change From Baseline Weight Change From Baseline Weight

Ch

ang

e Fro

m B

aseline W

eigh

t (lb)

Weeks

Ch

ang

e F

rom

Bas

elin

e W

eig

ht

(kg

)

52484440363228242016128400

Olanzapine (12.5–17.5 mg)Olanzapine (all doses)QuetiapineRisperidoneZiprasidoneAripiprazole

0

5

10

15

20

25

30

0

2

4

6

8

10

12

14

Nemeroff CB. J Clin Psychiatry. 1997;58(suppl 10):45-49; Kinon BJ et al. J Clin Psychiatry. 2001;62:92-100; Brecher M et al. American College of Neuropsychopharmacology; 2004. Poster 114; Brecher M et al. Neuropsychopharmacology. 2004;29(suppl 1):S109; Geodon® [package insert]. New York, NY:Pfizer Inc; 2005. Risperdal® [package insert]. Titusville, NJ: Janssen Pharmaceutica Products, LP; 2003; Abilify® [package insert]. Princeton NJ: Bristol-Myers Squibb Company and Rockville, Md: Otsuka America Pharmaceutical, Inc.; 2005.

CATIE Trial Results: CATIE Trial Results: Weight Gain Per Month Treatment Weight Gain Per Month Treatment

NEJM 2005 353:1209-1223

-1

0

1

2

OLZOLZ RISRIS PERPERQUETQUET ZIPZIP

Wei

gh

t g

ain

(lb

) p

er m

on

thW

eig

ht

gai

n (

lb)

per

mo

nth

Conventionals OlanzapineRisperidone

-25

-20

-15

-10

-5

0

5

LS

Mea

n C

han

ge

(lb

)

49 53 584540363227231914106

*

***

***

**

**

***

*P<0.05 **P<0.01***P<0.0001

Switched from

Weiden P et al. Presented APA 2004.

Change in Weight From Baseline Change in Weight From Baseline 58 Weeks After Switch to Low Weight Gain Agent58 Weeks After Switch to Low Weight Gain Agent

Weeks

LS

Mea

n C

han

ge,

mg

/dL

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

**

10

-100

*

***

*

***

6 10 14 19 23 27 32 36 40 45 49 53 58

Conventionals OlanzapineRisperidoneSwitched from

*P<.05 **P<.0005***P<.0001

†Repeated measures analysis

Change in Triglycerides from Baseline over 58 Change in Triglycerides from Baseline over 58 Weeks after Switch to ZiprasidoneWeeks after Switch to Ziprasidone††

Weiden P, et al. Neuropsychopharmacology. 2008, 33(5):985-994.

American Diabetes Association, American Psychiatric Association, American American Diabetes Association, American Psychiatric Association, American Association of Clinical Endocrinologists, North American Association for the Association of Clinical Endocrinologists, North American Association for the Study of Obesity: Consensus Conference on Antipsychotic Drugs and Risk of Study of Obesity: Consensus Conference on Antipsychotic Drugs and Risk of Obesity and DiabetesObesity and Diabetes

+ = increased effect; - = no effect; D = discrepant results. + = increased effect; - = no effect; D = discrepant results.

DrugDrug Weight GainWeight Gain Diabetes RiskDiabetes Risk DyslipidemiaDyslipidemia

clozapineclozapine + + ++ + + ++ ++

olanzapineolanzapine + + ++ + + ++ ++

risperidonerisperidone + ++ + DD DD

quetiapinequetiapine + ++ + DD DD

aripiprazolearipiprazole +/-+/- -- --

ziprasidoneziprasidone +/-+/- -- --

Diabetes Care 27:596-601, 2004

ADA/APA/AACE/NAASO ADA/APA/AACE/NAASO Consensus Recommendations on Responding to Consensus Recommendations on Responding to Antipsychotic-associated Metabolic ChangesAntipsychotic-associated Metabolic Changes

• If weight gain is ≥ 5% of body weight, consider interventions, including switching to another second generation antipsychotic

• If glycemia or dyslipidemia worsen, consider switch to an second generation antipsychotic not associated with significant weight gain or diabetes

• Gradually discontinue/cross-titrate• Closely monitor psychiatric symptoms during

changeoverAmerican Diabetes Association. Diabetes Care. 2004;27:596-601.

Strategies for Reduction and Prevention of Strategies for Reduction and Prevention of Obesity in Persons with Severe Mental IllnessObesity in Persons with Severe Mental Illness

• 15th Technical Report of The NASMHPD Medical Director Council

• Available in late October at http://www.nasmhpd.org/medical_director.cfm

• Funded by NASMHP and CMHS-SAMHSA

Harris et al. Diabetes Care. 1998; 21:518.Mukherjee et al. Compr Psychiatry. 1996; 37(1):68-73.

Schizophrenic:General: 50-59 y

60-74 y75+ y

Percent of

population

Prevalence of Diagnosed Diabetes in General Population Versus Schizophrenic Population

Hypothesized Reasons Why There May Be More Hypothesized Reasons Why There May Be More Type 2 Diabetes in People With SchizophreniaType 2 Diabetes in People With Schizophrenia

• Genetic link between schizophrenia and diabetes

• Impact of lifestyle• Medication effect increasing insulin resistance

by impacting insulin receptor or postreceptor function

• Drug effect on caloric intake or expenditure (obesity, activity)

Mokdad et al. Diabetes Care. 2000;23:1278.Mokdad et al. JAMA. 1999;282:1519.Mokdad et al. JAMA. 2001;286:1195.

72

73

74

75

76

77

78

4.04.55.05.56.06.57.07.5

1990 1992 1994 1996 1998 2000

Pre

vale

nc

e (

%)

Pre

vale

nc

e (

%)

DiabetesMean body weight

kg

YearYear

Diabetes and Obesity: Diabetes and Obesity: The Continuing EpidemicThe Continuing Epidemic

Behavioral Risk Factor Surveillance System, CDC.

(*BMI 30, or about 30 lbs overweight for 5’4” person)

1996

2003

Obesity Trends* Among US AdultsObesity Trends* Among US AdultsBRFSS, 1991, 1996, 2003BRFSS, 1991, 1996, 2003

1991

No Data <10% 10%-14% 15%-19% 20%-24% 25%

No Data Less than 4% 4% to 6% Above 6%

Mokdad et al. Diabetes Care. 2000;23:1278-1283.

Diabetes and Gestational Diabetes Trends: Diabetes and Gestational Diabetes Trends: US Adults, BRFSS 1990US Adults, BRFSS 1990

Mokdad et al. Diabetes Care. 2000;23:1278-1283.

Diabetes and Gestational Diabetes Trends: Diabetes and Gestational Diabetes Trends: US Adults, BRFSS 1995US Adults, BRFSS 1995

No Data Less than 4% 4% to 6% Above 6%

Mokdad et al. Diabetes Care. 2001;24:412.

Diabetes and Gestational Diabetes Trends: Diabetes and Gestational Diabetes Trends: US Adults, BRFSS 1999US Adults, BRFSS 1999

No Data Less than 4% 4% to 6% Above 6%

Mokdad et al. JAMA. 2001;286(10).

Diabetes and Gestational Diabetes Trends: Diabetes and Gestational Diabetes Trends: US Adults, BRFSS 2000US Adults, BRFSS 2000

No Data Less than 4% 4% to 6% Above 6%

www.diabetes.org.

No Data Less than 4% 4% to 6% Above 6% Above 10%

Diabetes and Gestational Diabetes Trends: Diabetes and Gestational Diabetes Trends: US Adults, Estimate for 2010US Adults, Estimate for 2010

Adapted from: International Diabetes Center (IDC). Available at: www.parknicollet.com/diabetes/disease/diagnosing.cfm. Accessed March 26, 2006.

Years of Diabetes

Uncontrolled Obesity IGT Diabetes Hyperglycemia

Relative -Cell Function

100 (%)

-20 -10 0 10 20 30

PlasmaGlucose

Insulin Resistance

Insulin Level

126 (mg/dL)Fasting Glucose

Post-Meal Glucose

IGT = impaired glucose tolerance.

Natural History of Type 2 DiabetesNatural History of Type 2 Diabetes

18%

17%

12%

8%

4%

0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

Retinopathy

Cardiovascular

Absent Foot Pulses

Absent Reflexes

Urine Albumin

Prevalence of Diabetic Tissue Damage at Diagnosis of Type 2 Diabetes

PrevalencePrevalenceDagogo-Jack et al. Arch Int Med. 1997;157:1802-1817.

0

10

20

30

40

50

Haffner SM et al. N Engl J Med. 1998;339:229-234.

Fat

al o

r no

nfat

al M

I (%

)

3.5%

18.6% 20.2%

45.0%

Equivalent MI Risk Levels

No Prior MI Prior MI No Prior MI Prior MINondiabetic Subjects Type 2 Diabetic Subjects

(n = 1373) (n = 1059)

Diabetes is a CVD Risk Equivalent to Previous Diabetes is a CVD Risk Equivalent to Previous Myocardial InfarctionMyocardial Infarction

Disparities in care: impact of mental illness on Disparities in care: impact of mental illness on diabetes managementdiabetes management

313,586 Veteran Health Authority patients with diabetes76,799 (25%) had mental health conditions (1999)Frayne et al. Arch Intern Med. 2005;165:2631-2638

Depression

Anxiety

Psychosis

Mania

Substance use disorder

Personality disorder

0.8 1.0 1.2 1.4 1.6

No HbA test done

0.8 1.0 1.2 1.4 1.6

No LDL test done

0.8 1.0 1.2 1.4 1.6

No Eye examinatio

n done

0.8 1.0 1.2 1.4 1.6

No Monitoring

0.8 1.0 1.2 1.4 1.6

Poor glycemic control

0.8 1.0 1.2 1.4 1.6

Poor lipemic control

Odds ratio for:

Mental Disorders and SmokingMental Disorders and Smoking

• Higher prevalence of cigarette smoking(56-88%) for SMI patients (overall U.S. prevalence 25%)

• More toxic exposure for patients who smoke (more cigarettes, larger portion consumed)

• Smoking is associated with increased insulin resistance

• 44% of all cigarettes in US are smoked by persons with mental illness

George TP et al. Nicotine and tobacco use in schizophrenia. In: Meyer JM, Nasrallah HA, eds. Medical Illness and Schizophrenia. American Psychiatric Publishing, Inc. 2003; Ziedonis D, Williams JM, Smelson D. Am J Med Sci. 2003(Oct);326(4):223-330

Access To Health CareAccess To Health Care

• An issue for all people with limited income, particularly preventive care

• Over use of emergency and specialty care• Complicated by mental illness• Significantly lower rates of primary care• Significantly lower rates of routine testing• Very poor dental care• Little integration of primary care and psychiatry

Problem: Problem: SMI and Reduced Use of Medical ServicesSMI and Reduced Use of Medical Services

• Fewer routine preventive services (Druss 2002)• Worse diabetes care (Desai 2002, Frayne 2006)• Lower rates of cardiovascular procedures (Druss

2000)

Newcomer J, Hennekens CH. JAMA. 2007;298:1794-1796.Druss BG et al. Arch Gen Psychiatry. 2001;58:565-572.

Problem: Problem: SMI and Reduced Use of Medical ServicesSMI and Reduced Use of Medical Services

• Less likely to be screened or treated for dyslipidemia, hyperglycemia, hypertension

• Less likely to receive angioplasty or CABG• Less likely to receive drug therapies of proven

benefit (thrombolytics, aspirin, beta-blockers, ACE inhibitors) post-myocardial infarction

• More likely to have premature mortality post-myocardial infarction

Survival Following MyocardialSurvival Following MyocardialInfarctionInfarction

• 88,241 Medicare patients, 65 years of age and older, hospitalized for MI

• Mortality increased by– 19%: any mental disorder– 34%: schizophrenia

• Increased mortality explained by measures of quality of care

Druss BG et al. Arch Gen Psychiatry. 2001;58:565-572.

Comparison of Metabolic Syndrome and Individual Criterion Prevalence in Fasting CATIE Subjects and Matched NHANES III Subjects

Males

CATIE NHANES p

N=509 N=509

Females

CATIE NHANES p

N=180 N=180

Metabolic Syndrome Prevalence

36.0% 19.7% .0001 51.6% 25.1% .0001

Waist Circumference Criterion 35.5% 24.8% .0001 76.3% 57.0% .0001

Triglyceride Criterion 50.7% 32.1% .0001 42.3% 19.6% .0001

HDL Criterion 48.9% 31.9% .0001 63.3% 36.3% .0001

BP Criterion 47.2% 31.1% .0001 46.9% 26.8% .0001

Glucose Criterion 14.1% 14.2% .9635 21.7% 11.2% .0075

Meyer et al., Presented at APA annual meeting, May 21-26, 2005. McEvoy JP et al. Schizophr Res. 2005;80:19-32.

The CATIE StudyThe CATIE Study

At baseline investigators found that:• 88.0% of subjects who had dyslipidemia• 62.4 % of subjects who had hypertension • 30.2% of subjects who had diabetes

WERE NOT RECEIVING TREATMENT

Nasrallah HA, et al. Schizophr Res. 2006;86:15-22.

A Few ObservationsA Few Observations

• The leading contributors include significant preventable causes

• Lifestyle issues are significant• Iatrogenic effects of medications are significant• Inattention by medical and behavioral health

professionals is significant• And inadequate care is probably very expensive!

PMPM by Medicaid EligibilityPMPM by Medicaid Eligibility

• Elderly $1284• Disabled $1466• Indigent Adult $387• Children $238• Foster Kids $500• Other Kids $863• Pregnant Women $514• All other $920

The ProblemThe Problem

Clinical Cost Drivers: Untreated Medical Illness Poor patient adherence to effective treatments Medical Errors

Administrative Cost Drivers:Lack of coordination of benefitsProvider administrative burdenFragmentation of systems of care

Recovery for Persons with SMI

CMHC MissionCMHC Mission

CMHC ProblemCMHC Problem

Early Death from Physical Illness Prevents

Recovery from SMI

Overview - PROPOSED SOLUTIONSOverview - PROPOSED SOLUTIONS

• Prioritize the Public Health Problem• Target Providers, Families and Clients• Focus on Prevention and Wellness

• Track Morbidity and Mortality in Public Mental Health Populations

• Implement Established Standards of Care• Prevention, Screening and Treatment

• Improve Access to and Integration of Physical Health and Mental Health Care

Step 1 – Create Disease Registry Step 1 – Create Disease Registry

• Get Historic Diagnosis from Admin Claims

• Get Clinical Values from Metabolic Screening• Combine into EHR Disease Registry• Online Access available to all Providers

Metabolic Syndrome Disease RegistryMetabolic Syndrome Disease Registry

• Metabolic Syndrome– Obesity - weight height– Cholesterol – Triglycerides – Blood pressure– Blood sugar

• Screening Required Annually since January 1• Disease registry with results maintained on cyber

access• Billing Code under Rehab Option

Onsite LabsOnsite Labs

• For– Uninsured– Transportation challenged– Non-compliant

• Technology– Finger prick, chemstick testing– CLIA Waived– Machine costs $2500– $12 /test for Cholesterol, trigycerides, glucose

Step 2 – Identify Step 2 – Identify

• Compare Combined Disease Registry Data to accepted Clinical Quality Indicators

• Identify Care Gaps• Sort patients with care gaps into agency specific

To-Do lists• Send to CMHC nurse care manager• Set up PCP visit and pass on info with requst to

treat

Defining Health HomesDefining Health Homes

• Enumerated in Sec. 1945 of the Social Security Act

• Provides states the option to cover care coordination for individuals with chronic conditions through health homes

• Eligible Medicaid beneficiaries have:• Two or more chronic conditions,• One condition and the risk of developing another, or• At least one serious and persistent mental health

condition

Defining health homesDefining health homes

• Provides 90% FMAP for eight quarters for:• Comprehensive care management• Care coordination• Health promotion• Comprehensive transitional care• Individual and family support• Referral to community and support services

• Services by designated providers, a team of health care professionals or a health team

Population BasedPopulation Based

Payments for HH services will be paid PMPM, not unit by unit

Service needs will be identified by patient health history and status

Outcomes will be measured by groups of clients (i.e., by organization, region, medication used, co-morbid conditions)

DMH NET – Strategy DMH NET – Strategy

• Health technology is utilized to support the service system.

• “Care Coordination” is best provided by a local community-based provider.

• Community Support Workers who are most familiar with the consumer provide care coordination at the local level.

• Nurse Liaisons working within each provider organization provide system support.

• Statewide coordination and training support the network of providers.

Missouri Health Home InitiativesMissouri Health Home Initiatives

• Missouri Medicaid state plan amendment– CMHC healthcare home

• CMHCs and CMHC affiliates– Primary care chronic conditions healthcare

home• FQHCs, RHCs, Physician practices

• Missouri Foundation for Health Patient-Centered Home Multi-payer Learning Collaborative

87

CMHC as Health Care HomeCMHC as Health Care Home

• Case management coordination and facilitation of healthcare

• Medical disease management for persons with SMI

• Preventive healthcare screening and monitoring by MH providers

• Integrated/consolidated CMHC/CHC Services• Primary Care Nurse Managers Care

Recommendation – Medical Needs Have Recommendation – Medical Needs Have Same Priority as MH NeedsSame Priority as MH Needs

• Obtaining a “medical home” – a primary care provider responsible for overall coordination

• Medication adherence – just as important for non-MH meds

• Assisting in scheduling and keeping medical care appointments

Care CoordinationCare CoordinationIntegrates Healthcare Issues into CMHC Care Integrates Healthcare Issues into CMHC Care MechanismsMechanisms

• Include healthcare goals in treatment planInclude healthcare goals in treatment plan• Include healthy lifestyle goals in treatment planInclude healthy lifestyle goals in treatment plan• Identify client’s internal health care expert/champion Identify client’s internal health care expert/champion • Develop health and wellness servicesDevelop health and wellness services• Provide nurse healthcare liaison – proven practiceProvide nurse healthcare liaison – proven practice• Verify healthcare services are occurring by utilizing dataVerify healthcare services are occurring by utilizing data

Provide Information to Other Healthcare Provide Information to Other Healthcare ProvidersProviders

• HIPAA permits sharing information for coordination of care

• Nationally consent not necessary• Exceptions:

– HIV– Substance abuse treatment – not abuse itself– Stricter local laws

Clients Eligible for CMHC HHClients Eligible for CMHC HH

• A serious and persistent mental illness

– Adults with SMI (Schizophrenia, Bipolar Disorder, Major Depression Recurrent)

– Youth with Severe Emotional Disturbance

Clients Eligible for CMHC HHClients Eligible for CMHC HH

• A mental health condition, OR• A substance abuse condition, AND• One other chronic health condition

• asthma, • cardiovascular disease, • diabetes, • substance abuse disorder, • developmental disability • overweight BMI>25

Provider InfrastructureProvider Infrastructure

• Reimbursed by HH funding– Physician led team– Primary care nurse – Health coaches– Clinical support staff– Pharmacy consultant– Primary care consultation– Information technology

Provider InfrastructureProvider Infrastructure

• NOT reimbursed by funding but by existing fee-for- service systems, including DMH and Medicaid– Community support worker– Physician services– Peer specialist– Psychosocial rehabilitation– Medication– Primary care medical services – Labs

Comprehensive Care Comprehensive Care ManagementManagement

• Identification and targeting of high-risk individuals

• Monitoring of health status and adherence• Development of treatment guidelines • Individualized planning with the consumer

MethodMethod

• Screen for general health with priority for high risk conditions

• Prescribers will screen, monitor and intervene for metabolic syndrome and related care gaps

• Treatment per practice guidelines: eg, heart disease, diabetes, smoking cessation, use of novel anti-psychotics

• Offer prevention and intervention for modifiable risk factors and care gaps

• Track and improve performance thru patient disease registry

Metabolic Syndrome Disease RegistryMetabolic Syndrome Disease Registry

• Metabolic Syndrome– Blood pressure - weight– Cholesterol - height– Triglycerides - blood sugar

• Screening Required Annually since January 1• Disease registry with results maintained on EHR • Utilize Clinical and Claims data to identify care

gaps

DMHNET HEIDIS IndicatorsDMHNET HEIDIS Indicators

• DM1: Use of inhaled corticosteroid medications by persons with a history of COPD (chronic obstructive pulmonary disease) or Asthma.

• DM2: Use of ARB (angiotensin II receptor blockers) or ACEI (angiotensin converting enzyme inhibitors) medications by persons with a history of CHF (congestive heart failure).

• DM3: Use of beta-blocker medications by persons with a history of CHF (congestive heart failure).

• DM4: Use of statin medications by persons with a history of CAD (coronary artery disease).

• DM5: Use of H2A (histamine 2-receptor antagonists) or PPI (proton pump inhibitors) medications for no more than 8 weeks by persons with a history of GERD (gastro-esophageal reflux disease).

Initial ResultsInitial Results

• Provide specific lists of CMHC clients with care gaps as identified by HEIDIS indicators to CMHC primary care nurse liaisons quarterly

• Provide HEIDIS indicator/disease state training on standard of care to CMHC MH case managers

• First quarter focus on indicator one-asthma substantially reduced percentage with care gap– Range 22% - 62% reduction– Median 45% reduction

Care CoordinationCare Coordination

Coordinating with the patients, caregivers and providers Implementing plan of care with treatment

team Planning hospital discharge Scheduling Communicating with collaterals

Mapping & Data IntegrationMapping & Data Integration

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DrugMembership

Office Laboratory

Diagnosis

Hospital

ER

Integrated

Data Repository

Pharmacy Pharmacy ClaimsClaims

Medical Medical ClaimsClaims

ReferencReference Datae Data

CyberAccessCyberAccessTMTM

• Current Features– Patient demographics– Electronic Health Record

• Record of all participant prescriptions• All procedures codes• All diagnosis codes

– E prescribing– Preferred Drug List support

• Access to preferred medication list• Precertification of medications via clinical algorithms• Prior authorization of medications

– Medication possession ratio– Disease Registry for CMHCs

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Health TechnologyHealth Technology

• Care Management Technologies (CMT) Programs – Behavioral Pharmacy Management– CMHC Pharmacy Management Reports– Medication Adherence Reports– Care Gap task lists for Nurse Care Managers– HEIDIS Gaps and Performance – Data Analytic Custom Support

• ACS-Heritage Programs– CyberAccess– Direct Inform– Disease Registry for Metabolic Syndrome

Health PromotionHealth Promotion

• Population-based (non-client, outpatient, and CPRC)

• Patient self-management • Health education• Smoking prevention• Obesity reduction• Reversal of social determinates of health

Support Patient Wellness through Self Support Patient Wellness through Self Management using Peer SpecialistsManagement using Peer Specialists

• Implement a physical health/wellness approach that is consistent with recovery principles, including supports for smoking cessation, good nutrition, physical activity and healthy weight.

• Educate patient on implications of psychotropic drugs• Teach/support wellness self-management skills• Teach/support decision making skills using Direct Inform • Use motivational interviewing techniques• New psychosocial rehab focus

– Smoking cessation– Enhancing Activity– Obesity Reduction/Prevention

Comprehensive Transitional CareComprehensive Transitional Care

• Hospital admission follow-up• Hospital discharge follow-up• Development of intermediate care tools• Data and patient registry supported

Individual & Family SupportIndividual & Family Support

• Family education• Peer support and/or NAMI/MHA• Patient advisory and input processes• Direct inform

DirectInform DirectInform

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Referral to Community and Social Referral to Community and Social Support ServicesSupport Services

• CPRC teams will be well established for this• Non-CPRC clients have not had as much support

with housing benefits, medical assistance programs, legal services, employment, schools, etc.

• Local SB 40 Boards• NAMI/MHA

OUTCOMESOUTCOMES

• Cost• Quality of Care

• Medication adherence

• HEDIS indicators

• Clinical Outcomes• Avoidable hospital readmissions

• Experience of care• MHSIP

Practice TransformationsPractice Transformations

• Focus on overall health• More medically oriented team members• Open access scheduling• No-show/cancellation policies• Increased patient input processes• Significant increase in data reporting and

outcomes• Treatment planning tools supported by treatment

guidelines

Hennekens CH. Circulation. 1998;97:1095-1102.

Goals: Lower Risk for CVDGoals: Lower Risk for CVD

• Blood cholesterol – 10% = 30% in CHD (200-180)

• High blood pressure (> 140 SBP or 90 DBP)– 4-6 mm Hg = 16% in CHD; 42% in stroke

• Cigarette smoking cessation– 50%-70% in CHD

• Maintenance of ideal body weight (BMI = 25) – 35%-55% in CHD

• Maintenance of active lifestyle (20-min walk daily)– 35%-55% in CHD