Transcript NASHMPHD 2007 Slides

SHOW - ME
Chronic Medical Conditions
Associated with
Severe Mental Illness
My 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
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
Severe 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 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 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:
Mean Years of Potential Life Lost
Year
AZ
MO
OK
1997
26.3
25.1
28.5
1998
27.3
25.1
28.8
29.3
26.3
29.3
26.9
1999
32.2
26.8
2000
31.8
27.9
RI
TX
UT
24.9
Compared with the general population, persons with major mental
illness lose 25-30 years of normal life span
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.
Results
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
Mental Health Patients with Mental Illness
Combined data for schizophrenia and schizoaffective disorder from 5 US
states (MO, OK, RI, TX and UT) from 1997 to 2001
Total 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
Primary cause of death
All causes of death*
47,812.2
1,829
*Note: Includes deaths from causes not listed; YPLL = years of potential life lo
Unpublished results courtesy of CW Colton
Change in US General Population Age-Adjusted
Mortality (1979-1995)
Decline (%)
10
0
Noncardiovascular Disease
-10
-20
Coronary Heart Disease (CHD)
-30
-40
Stroke
-50
-60
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
Year
Morbidity and Mortality Weekly Report. 1999; 48(30):649-656.
Mortality Risk From All Causes and From
Cardiovascular Disease Increased Among Patients
With Schizophrenia Between 1970-2003
Men
Women
2.5
Relative Risk for
Standardized Mortality Ratio
Relative Risk for
Standardized Mortality Ratio
3
2.5
2
2
1.5
1.5
1
1
0.5
0.5
0
0
19701974
19751979
19801984
All Causes
19851989
19901994
19951999
Cardiovascular Disease
20002003
19701974
19751979
19801984
All Causes
19851989
19901994
19951999
20002003
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.
Ösby U et al. BMJ. 2000;321:483-484, and unpublished data courtesy of Urban Osb
Ohio Study-Discharged Inpatients
Standardized Mortality Ratios
Cause
All causes of death
Intentional self-harm (suicide)
Symptoms, signs, & abnormal
clinical & laboratory findings, NEC
Pneumonia & Influenza
Chronic lower respiratory diseases
Accidents (unintentional injuries)
Diseases of heart
Diabetes mellitus
Assault (homicide)
Cerebrovascular diseases
Malignant neoplasms (cancers)
† P<0.001
Overall
N SMR
608 3.2†
108 12.6†
32 9.7†
16
31
83
126
18
10
10
44
6.6†
5.5†
3.8†
3.4†
3.4†
1.7
1.5
0.9
Maine Study Results: Comparison of Health
Disorders Between SMI & Non-SMI Groups
Schizophrenia:
Natural Causes of Death
• Higher standardized mortality rates than the general population
from:
–
–
–
–
Diabetes
Cardiovascular disease
Respiratory disease
Infectious diseases
2.7x
2.3x
3.2x
3.4x
• Cardiovascular disease associated with the largest number of
deaths
– 2.3 X the largest cause of death in the general population
Osby U et al. Schizophr Res. 2000;45:21-28.
What are the Causes of Morbidity and Mortality
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
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 Syndrome
≥3 Risk Factors Required for Diagnosis
Risk Factor
Abdominal obesity
Men
Women
Triglycerides
HDL cholesterol
Men
Women
Blood pressure
Fasting blood glucose
HDL = high-density lipoprotein.
NCEP III. Circulation. 2002;106:3143-3421.
Defining Level
Waist circumference
>40 in (>102 cm)
>35 in (>88 cm)
150 mg/dL (1.69mmol/L)
<40 mg/dL (1.03mmol/L)
<50 mg/dL (1.29mmol/L)
130/85 mm Hg
110 mg/dL (6.1mmol/L)
Relative Risk
CHD Risk Increases with Increasing Number
of Metabolic Syndrome Risk Factors
7
6.5
6
5.5
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
one
two
Sattar et al, Circulation, 2003;108:414-419
Whyte et al, American Diabetes Association, 2001
Adapted from Ridker, Circulation 2003;107:393-397
three
four
Comparison of Metabolic Syndrome and Individual
Criterion Prevalence in Fasting CATIE Subjects and
Matched 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
• 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
Drugs and Obesity and Diabetes: Monitoring Protocol*
Start 4 wks 8 wks 12 wk
qtrly
12 mos. 5 yrs.
Personal/family Hx
X
Weight (BMI)
X
Waist
circumference
X
Blood pressure
X
X
X
Fasting glucose
X
X
X
X
X
X
X
X
X
X
X
X
X
*More frequent assessments may be warranted based on clinical
status
Fasting lipid profile
Diabetes Care. 27:596-601, 2004
Overview
• 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
A Public Health Approach to
Addressing Obesity in SMI
Primary Prevention
Secondary Prevention
Lifestyle
Tertiary Prevention
Heart Disease
Diabetes
Obesity
Ψ Medications
Diet and exercise
Initial Choice of Ψ meds
Screening
Switching Ψ medications
Medications for obesity and
medical comorbidities
Bariatric Surgery
Prevalence of Metabolic Syndrome According
to BMI in the Adult General Population
70
Prevalence (%)
60
50
40
30
20
10
0
Healthy
N=12,363
Overweight
Obese
Healthy
Men
“Overweight” = BMI 25-29.9
“Obese” = BMI 30
(National Heart, Lung, and Blood Institute, Obesity Guidelines)
Park et al. Arch Intern Med. 2003;163:427.
Overweight
Women
Obese
Obesity Rate by Country
2005 WHO Global Comparable Estimates, both urban and rural populations
USA
MEX
CAN
GBR
DEU
ITA
BRA
Men
Women
FRA
NGA
CHN
0
10
20
30
40
50
Source: WHO Global Infobase,
http://www.who.int/ncd_surveillance/infobase/en/index.html. Retrieved 8/10/06.
Risk of Obesity Among Patients
with SMI
Disorder
↑Odds of Obesity
Depression
1.2 - 1.8x1,2
Bipolar Disorder
1.5 – 2.3x1,2
Schizophrenia
1. Simon GE et al Arch Gen Psychiatry. 2006 Jul;63(7):824-30.
2. Petry et al Psychosom Med. 2008 Apr;70(3):288-97
3. Coodin et al Can J Psychiatry 2001;46:549–55
3.5x3
Causes of Obesity in Persons
with SMI
• Increased caloric intake
• Decreased physical activity
• Psychotropic medications
Diet in Persons
with 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. 1999
4. 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
with SMI
Disorder
↑Odds of Inactivity
Severe Mental Illness
1.5x1
Bipolar Disorder
3.2x2
Depression
2.0x3
1. Daumit et al J Nerv Ment Dis. 2005 Oct;193(10):641-6
2. 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
Psychotropic Medications and
Weight 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 View
Obesity as a Risk Factor for
Antipsychotic Noncompliance
Noncompliant Respondents According to BMI Category
Noncompliance (%)
*
*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.
*
Consequences of Obesity in Persons
with SMI
• Medical morbidity
• Stigma, reduced quality of life
• Mortality
INTERVENTIONS
• 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 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):
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 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 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 Antipsychotics
6
13.2
5
11.0
†
4
8.8
3
6.6
2
4.4
*
1
2.2
0
0
-1
-2.2
-2
-4.4
-3
-6.6
Weight Change (lb)
Weight Change (kg)
Estimated Weight Change at 10 Weeks on “Standard” Dose
*4–6 week pooled data (Marder SR et al. Schizophr Res. 2003;1;61:123-36; †6week data adapted from Allison DB, et al. Am J Psychiatry. 1999;156:1686-1696;
Jones AM et al. ACNP; 1999.
Incidence (%)
Clinically Significant (7%) Weight Gain
During Antipsychotic Treatment
35
35
35
35
35
30
30
30
30
30
25
25
25
25
25
20
20
20
20
20
15
15
15
15
15
10
10
10
10
10
5
5
5
5
5
0
0
0
0
0
Data for ziprasidone, risperidone, quetiapine, and olanzapine from US
labels.
14
30
Olanzapine (12.5–17.5 mg)
Olanzapine (all doses)
Quetiapine
Risperidone
Ziprasidone
Aripiprazole
12
10
25
20
8
15
6
10
4
2
5
0
0
0
4
8
12
16
20
24
28
32
36
40
44
48
52
Change From Baseline Weight (lb)
Change From Baseline Weight (kg)
1-Year Weight Gain:
Mean Change From Baseline Weight
Weeks
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:
Weight gain (lb) per month
Weight Gain Per Month Treatment
2
1
0
OLZ
-1
NEJM 2005 353:1209-1223
QUET
RIS
PER
ZIP
Change in Weight From Baseline
58 Weeks After Switch to Low Weight Gain Agent
6
10 14
19 23 27 32 36 40 45
49 53 58
LS Mean Change (lb)
5
0
*
-5
***
**
-10
***
-15
-20
**
*P<0.05
**P<0.01
***P<0.0001
***
-25
Switched from
Conventionals
Risperidone
Weiden P et al. Presented APA 2004.
Olanzapine
Change in Triglycerides from Baseline over 58
Weeks after Switch to Ziprasidone†
Weeks
10 14 19 23 27 32 36 40 45 49 53 58
LS Mean Change, mg/dL
6
10
0
-10
-20
-30
-40
*
*P<.05
**P<.0005
***P<.0001
-50
-60
-70
-80
-90
-100
*
**
***
***
Switched from
Conventionals
Risperidone
Weiden P, et al. Neuropsychopharmacology. 2008, 33(5):985-
†Repeated
measures analysi
Olanzapine
American Diabetes Association, American Psychiatric Association, American
Association of Clinical Endocrinologists, North American Association for the
Study of Obesity: Consensus Conference on Antipsychotic Drugs and Risk of
Obesity and Diabetes
Drug
Weight Gain
Diabetes Risk
Dyslipidemia
clozapine
olanzapine
risperidone
quetiapine
aripiprazole
ziprasidone
+++
+++
++
++
+/+/-
+
+
D
D
-
+
+
D
D
-
+ = increased effect; - = no effect; D = discrepant results.
Diabetes Care 27:596-601, 2004
ADA/APA/AACE/NAASO
Consensus Recommendations on Responding to
Antipsychotic-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
changeover
American Diabetes Association. Diabetes Care. 2004;27:596-601.
Strategies for Reduction and Prevention of
Obesity 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
Prevalence of Diagnosed Diabetes in General
Population Versus Schizophrenic Population
Percent of
population
Schizophrenic:
General: 50-59 y
60-74 y
75+ y
Harris et al. Diabetes Care. 1998; 21:518.
Mukherjee et al. Compr Psychiatry. 1996; 37(1):68-73.
Hypothesized Reasons Why There May Be More
Type 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)
Diabetes and Obesity:
The Continuing Epidemic
7.5
7.0
6.5
6.0
5.5
5.0
4.5
4.0
1990
78
77
76
75
74
73
72
1992
Mokdad et al. Diabetes Care. 2000;23:1278.
Mokdad et al. JAMA. 1999;282:1519.
Mokdad et al. JAMA. 2001;286:1195.
1994 1996
Year
1998
2000
kg
Prevalence (%)
Diabetes
Mean body weight
Obesity Trends* Among US Adults
BRFSS, 1991, 1996, 2003
(*BMI 30, or about 30 lbs overweight for 5’4” person)
1991
1996
2003
No Data
<10%
10%-14%
15%-19%
20%-24%
25%
Behavioral Risk Factor Surveillance System, CDC.
Diabetes and Gestational Diabetes Trends:
US Adults, BRFSS 1990
No Data
Less than 4%
Mokdad et al. Diabetes Care. 2000;23:1278-1283.
4% to 6%
Above 6%
Diabetes and Gestational Diabetes Trends:
US Adults, BRFSS 1995
No Data
Less than 4%
4% to 6%
Mokdad et al. Diabetes Care. 2000;23:1278-1283.
Above 6%
Diabetes and Gestational Diabetes Trends:
US Adults, BRFSS 1999
No Data
Less than 4%
Mokdad et al. Diabetes Care. 2001;24:412.
4% to 6%
Above 6%
Diabetes and Gestational Diabetes Trends:
US Adults, BRFSS 2000
No Data
Mokdad et al. JAMA. 2001;286(10).
Less than 4%
4% to 6%
Above 6%
Diabetes and Gestational Diabetes Trends:
US Adults, Estimate for 2010
No Data
www.diabetes.org.
Less than 4%
4% to 6%
Above 6%
Above 10%
Natural History of Type 2 Diabetes
Obesity
IGT
Uncontrolled
Diabetes Hyperglycemia
PostMeal
Glucos
Fasting
e
Glucose
Plasma
Glucose
126 (mg/dL)
Relative -Cell
Function
100 (%)
Insulin Resistance
Insulin Level
-20 -10
0
10 20 30
Years of Diabetes
IGT = impaired glucose tolerance.
Adapted from: International Diabetes Center (IDC). Available at:
www.parknicollet.com/diabetes/disease/diagnosing.cfm. Accessed March 26, 2006.
Prevalence of Diabetic Tissue Damage at
Diagnosis of Type 2 Diabetes
Urine Albumin
4%
Absent Reflexes
8%
Absent Foot Pulses
12%
Cardiovascular
17%
Retinopathy
18%
0%
2%
4%
6%
8% 10% 12% 14% 16% 18% 20%
Prevalence
Dagogo-Jack et al. Arch Int Med. 1997;157:1802-1817.
Diabetes is a CVD Risk Equivalent to Previous
Myocardial Infarction
50
Fatal or nonfatal MI (%)
45.0%
40
Equivalent MI Risk Levels
30
18.6%
20
20.2%
10
3.5%
0
No Prior MI
Prior MI
Nondiabetic Subjects
(n = 1373)
Haffner SM et al. N Engl J Med. 1998;339:229-234.
No Prior MI
Prior MI
Type 2 Diabetic Subjects
(n = 1059)
Disparities in care: impact of mental illness on
diabetes management
Depressio
n
Anxiety
Psychosis
Mania
Substance
use
disorder
Personalit
y disorder
Odds ratio for:
0.8 1.0 1.2 1.4 1.6
0.8 1.0 1.2 1.4 1.6
0.8 1.0 1.2 1.4 1.6
0.8 1.0 1.2 1.4 1.6
0.8 1.0 1.2 1.4 1.6
0.8 1.0 1.2 1.4 1.6
No HbA
test done
No LDL
test done
No Eye
examinatio
n done
No
Monitoring
Poor
glycemic
control
Poor
lipemic
control
313,586 Veteran Health Authority patients with
diabetes
76,799 (25%) had mental health conditions (1999)
Frayne et al. Arch Intern Med. 2005;165:2631-2638
Mental 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 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:
SMI 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)
Problem:
SMI 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 postmyocardial infarction
Newcomer J, Hennekens CH. JAMA. 2007;298:1794-1796.
Druss BG et al. Arch Gen Psychiatry. 2001;58:565-572.
Survival Following Myocardial
Infarction
• 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
N=509
N=509
p
Females
CATIE NHANES
N=180
N=180
p
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 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 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 Eligibility
•
•
•
•
•
•
•
•
Elderly
Disabled
Indigent Adult
Children
Foster Kids
Other Kids
Pregnant Women
All other
$1284
$1466
$387
$238
$500
$863
$514
$920
The Problem
 Clinical Cost Drivers:
 Untreated Medical Illness
 Poor patient adherence to effective treatments
 Medical Errors
 Administrative Cost Drivers:
Lack of coordination of benefits
Provider administrative burden
Fragmentation of systems of care
CMHC Mission
Recovery for
Persons with SMI
CMHC Problem
Early Death from
Physical Illness Prevents
Recovery from SMI
Overview - 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
• 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 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 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
• 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 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 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 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
• 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 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 PatientCentered Home Multi-payer Learning
Collaborative
87
CMHC 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
Same 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 Coordination
Integrates Healthcare Issues into CMHC Care
Mechanisms
•
•
•
•
•
•
Include healthcare goals in treatment plan
Include healthy lifestyle goals in treatment plan
Identify client’s internal health care expert/champion
Develop health and wellness services
Provide nurse healthcare liaison – proven practice
Verify healthcare services are occurring by utilizing data
Provide Information to Other Healthcare
Providers
• 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 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 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 Infrastructure
• Reimbursed by HH funding
– Physician led team
– Primary care nurse
– Health coaches
– Clinical support staff
– Pharmacy consultant
– Primary care consultation
– Information technology
Provider 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
Management
• Identification and targeting of high-risk
individuals
• Monitoring of health status and adherence
• Development of treatment guidelines
• Individualized planning with the consumer
Method
• 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 Registry
• Metabolic Syndrome
– Blood pressure
– Cholesterol
– Triglycerides
- weight
- height
- 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 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 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 Coordination

Coordinating with the patients, caregivers
and providers
Implementing plan of care with treatment
team
 Planning hospital discharge
 Scheduling
 Communicating with collaterals

Mapping & Data Integration
Diagnosis
Membership
Integrated
Pharmacy
Claims
Medical
Claims
Reference
Data
7/7/2015
Drug
Data Repository
Office
Hospital
Laboratory
ER
102
CyberAccessTM
• 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
7/7/2015
103
Health 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 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
Management 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 Care
•
•
•
•
Hospital admission follow-up
Hospital discharge follow-up
Development of intermediate care tools
Data and patient registry supported
Individual & Family Support
•
•
•
•
Family education
Peer support and/or NAMI/MHA
Patient advisory and input processes
Direct inform
DirectInform
7/7/2015
109
Referral to Community and Social
Support 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
OUTCOMES
• Cost
• Quality of Care
• Medication adherence
• HEDIS indicators
• Clinical Outcomes
• Avoidable hospital readmissions
• Experience of care
• MHSIP
Practice 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
Goals: 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
Hennekens CH. Circulation. 1998;97:1095-1102.