Transcript Helping Patients Help Themselves: From sand bags to

Helping Patients Help Themselves:
-from sand bags to cell phones-
David L. Katz, MD, MPH, FACPM, FACP
Director, Prevention Research Center
Yale University School of Medicine
Medical Correspondent, ABC News
CMO, Confidant Systems, Inc.
Confidant Disease Management Meeting
Raleigh Durham, NC
August 23, 2006
Our sea of dietary troubles…
Obesity Trends* Among U.S. Adults
BRFSS, 1985
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1986
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1987
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1988
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1989
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1990
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
Obesity Trends* Among U.S. Adults
BRFSS, 1991
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1992
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1993
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1994
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1995
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1996
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
Obesity Trends* Among U.S. Adults
BRFSS, 1997
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
≥20
Obesity Trends* Among U.S. Adults
BRFSS, 1998
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
≥20
Obesity Trends* Among U.S. Adults
BRFSS, 1999
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
≥20
Obesity Trends* Among U.S. Adults
BRFSS, 2000
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
≥20
Obesity Trends* Among U.S. Adults
BRFSS, 2001
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
No Data
<10%
10%–14%
15%–19%
20%–24%
≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 2002
(*BMI(*BMI
≥30,
oror~
30lbs
lbs
overweight
5’ 4” woman)
30,
~ 30
overweight
for 5’4” for
person)
No Data
<10%
10%–14%
15%–19%
20%–24%
Source: Behavioral Risk Factor Surveillance System, CDC
≥25%
Obesity* Trends Among U.S. Adults
BRFSS, 2003
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person)
No Data
<10%
10%–14%
15%–19%
20%–24%
≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 2004
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” person)
No Data
<10%
10%–14%
15%–19%
20%–24%
≥25%
Obesity Trends* Among U.S. Adults
BRFSS, 1991, 1996, 2004
(*BMI 30, or about 30 lbs overweight for 5’4” person)
1991
1996
2004
No Data
<10%
10%–14%
15%–19%
20%–24%
≥25%
The wave has not yet crested…
Third of kids tip scales wrong way
Greatest number yet; more men are obese
By Nanci Hellmich
USA TODAY
4/5/06
Ogden CL et al. Prevalence of Overweight and Obesity in the United States,
1999-2004. JAMA. 2006;295:1549-1555
Kim J et al. Trends in Overweight from 1980 through 2001 among
Preschool-Aged Children Enrolled in a Health Maintenance Organization.
Obesity. 2006 Jul;14:1107-12
And it reaches every shore-
 at this year’s International Association of
Agricultural Economists' annual conference in
Australia, it was announced that for the first time in
history, the number of overweight people in the
world (roughly 1 billion) outnumbered the hungry
(roughly 850 million).
Obesity Portends Diabetes…
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1994
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1995
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1996
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1997
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1998
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 1999
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 2000
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 2001
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 2002
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 2003
Source: www.cdc.gov
Diabetes Trends* Among Adults in the U.S.
(Includes Gestational Diabetes)
BRFSS 2004
Source: www.cdc.gov
Prevalence of Metabolic Syndrome
 3,601 men and women aged > or =20 years from the
National Health and Nutrition Examination Survey
1999-2002
 Based on the NCEP definition:
 34.5 +/- 0.9% among all participants
 Based on the IDF definition:
 39.0 +/- 1.1% among all participants

Ford ES. Prevalence of the metabolic syndrome defined by the International Diabetes Federation
among adults in the U.S. Diabetes Care. 2005;28:2745-9
The Clinical Costs of IRS/DM are clear.
 Govindarajan G, Whaley-Connell A, Mugo M, Stump C, Sowers JR. The
cardiometabolic syndrome as a cardiovascular risk factor. Am J Med Sci.
2005;330:311-8.
 Neuhauser HK. The metabolic syndrome. Lancet. 2005;366:1922-3.
 Khunti K, Davies M. Metabolic syndrome. BMJ. 2005;331:1153-4.
 Carmena R. Type 2 diabetes, dyslipidemia, and vascular risk: rationale and
evidence for correcting the lipid imbalance. Am Heart J. 2005;150:859-70.
The Financial Costs…
 are a bit murkier, but very compelling.
 Obesity-IRS-DM drive up costs
 Earlier age of onset threatens to shorten life
expectancy
 Dying slowly is costly, but being dead is free
 Late intervention forestalls death at high cost, early
intervention instills health at low cost
Muddled Monetary Matters of both
Medical & Media Interest Olshansky SJ et al. A potential decline in life expectancy in the United States in







the 21st century. N Engl J Med. 2005;352:1138-45
Daviglus ML et al. Relation of body mass index in young adulthood and middle
age to Medicare expenditures in older age. JAMA. 2004;292:2743-9.
Thompson D et al. .Lifetime health and economic consequences of obesity.
Arch Intern Med. 1999;159:2177-83.
Miller T. Increasing longevity and Medicare expenditures. Demography.
2001;38:215-26.
Peeters A et al. Obesity in adulthood and its consequences for life expectancy: a
life-table analysis. Ann Intern Med. 2003;138:24-32.
Why America Has to Be Fat. A Side Effect of Economic Expansion Shows Up
in Front. Washington Post, January 22, 2006
The price of obesity. Los Angeles Times, August 1, 2005
Heavy workers, hefty price. USA Today, Sept. 12, 2005
The Costs of Chronic Disease,
hot of the presses
 Obesity, chronic disease drive Medicare costs up
USA Today http://www.usatoday.com/news/washington/2006-08-22medicare-obesity_x.htm
 Obesity and certain chronic conditions were major factors driving virtually
all Medicare spending growth for the past 15 years, according to a new
analysis of Medicare cost and patient data. The rate of obesity among
Medicare patients doubled from 1987 to 2002, and spending on those
individuals more than doubled. These findings suggest policymakers
should direct their attention toward programs that encourage healthier
lifestyles among seniors and those nearing retirement.
…& the Rising Tides of
Nutritional Tribulation…
What it is…
Adult Population
100%
Overweight / Obesity
Insulin Resistance
Diabetes Mellitus
Cardiovascular Disease
Time
And What it SHALL be…
Children !!
100%
Overweight / Obesity
Insulin Resistance
Diabetes Mellitus
Time
Cardiovascular Disease
Why are we
“eating ourselves to death” !?!
BECAUSE WE CAN!
The nature of our trouble,
the trouble in our nature…
Causes of Obesity ?
Complex Simplicity
 energy imbalance: calories in, calories out!
 basal metabolism
 postprandial thermogenesis
 physical activity
 genetic factors




metabolic syndrome
Ob gene
neurohormonal regulation (e.g., neuropeptide Y; adiponectin; PYY; ghrelin)
basal metabolic rate (Pima Indians)
 Hypertrophic vs. hyperplastic obesity
 metabolic set-point
 the weight loss plateau
Too many calories in…
 3800 calories produced in US each day for every
man, woman, and child (www.usda.gov); something
has to be done with them all!
 Nielsen SJ, Popkin BM. Pattern and Trends in Food
Portion Sizes, 1977-1998. JAMA. 2003;289:450-453
…too few calories out.
If the going is tough…
 Why don’t the tough just get going?
To take responsibility…
To carry the burden of chronic diseaseit takes a system…
 Wagner, E. H. (2004). Chronic disease care. Bmj, 328(7433),
177-178.
 Wagner, E. H., Austin, B. T., Davis, C., Hindmarsh, M.,
Schaefer, J., & Bonomi, A. (2001a). Improving chronic
illness care: Translating evidence into action. Health Aff
(Millwood), 20(6), 64-78.
 Wagner, E. H., Glasgow, R. E., Davis, C., Bonomi, A. E.,
Provost, L., McCulloch, D., et al. (2001b). Quality
improvement in chronic illness care: A collaborative
approach. Jt Comm J Qual Improv, 27(2), 63-80.
Dollars & Sense Late stage interventions to prevent/manage
sequelae of IRS may be clinically beneficial,
financially disastrous
 Early, pre-emptive management offers the
promise of both clinical and financial benefit
Or in other words…
 It takes a lot less investment to avoid dropping
an egg in a frying pan, than it does to
unscramble it afterwards.
 We should be in the business of building better
baskets, rather than the business of
unscrambling eggs. Just ask the King’s horses
and men…
So: failure to make the financial case
for prevention…
 is failure to think boldly enough about what
prevention really ought to mean.
Case Management makes sense,
and saves dollars Crow CS, Lakes SA, Carter MR. A nursing case management program for





low-income high-risk diabetic clients: a projected cost-benefit analysis.
Lippincotts Case Manag. 2006 Mar-Apr;11(2):90-8
Sears NJ. Deriving cost savings while enhancing quality of care through
effective case management in the acute care facility. Lippincotts Case
Manag. 2006 Jan-Feb;11(1):59-60
Coleman J. Case management imbedded into disease management: the
formula for effective disease management in HMOs and IDSs. Case
Manager. 2005 Nov-Dec;16(6):40-2
Garrett M. Medicare chronic care improvement program puts the spotlight
on case management. Case Manager. 2005 Jul-Aug;16(4):56-8
Adams MH, Crow CS. Development of a nurse case management service:
a proposed business plan for rural hospitals. Lippincotts Case Manag. 2005
May-Jun;10(3):148-58
Markle A. The economic impact of case management. Case Manager. 2004
Jul-Aug;15(4):54-8
It gets even better when case
management can be automated-
 Automated Computer-Tailored Feedback
Effective for Weight Loss
 Arch Intern Med. 2006;166:1620-1625.
Sometimes, we all need
somebody to lean on…
 The benefits of follow up contact by practice staff between clinical
consultations with the physician in the form of email exchanges, mailing of
print materials, and brief telephone discussions to assess progress and
ensure compliance has been established.






Bray et al., 2005
GESICA Investigators, 2005
Kaplan et al., 2003
Kelly et al., 2005
Logue et al., 2005
McBride & Rimer, 1999, "Randomised trial of telephone intervention in
chronic heart failure: Dial trial", 2005)
Katz DL, Faridi Z. Health Care System Approaches to Obesity Prevention &
Control. In: Handbook on Obesity Epidemiology & Prevention. Springer: In
press, 2006
Getting by with a little help from a ‘friend’-
 Or Confidant.
NICHE
 Novel Interactive Cell phone technology for
Health Enhancement
 NIH funded
 Just completed
Confidant System
 Glucometer & Pedometer/Accelerometer interface
with cell-phone to transmit daily glucose and step
count to central server.
 Patients receive tailored feedback and messages
based upon clinical data via cell-phone text
messaging system.
 Patients and health care providers are able to
access central server via internet and
view/download readings.
Study Design




Randomized Controlled Trial - Randomized by site
Sites were 2 comparable Community Health Centers (CHC) in CT
Population: 30 patients with type 2 diabetes (15 patients per site)
Eligibility










Men and women
Any racial/ethnic group
English speaking
Age 18 or older
Type 2 diabetes diagnosed at least 1 yr prior and confirmed by clinical data
Diabetes controlled by diet or oral medications for at least 3 months
No exogenous insulin use
HbA1c less than 8%
Serum creatinine less than 1.5 mg/dl
Attendance at 90 minutes of diabetes education by a Certified Diabetes
Educator
Methods
Intervention site (n=15)
 Two Nurse Practitioners attended one-hour train-the-trainer sessions in using the
Confidant System
 Patients received the Confidant System and were trained in its use by the nurses
 Intervention lasted 3 months
 Patients tested glucose upon awakening and wore pedometer daily
 Completed wireless upload of data to Confidant server once daily
 Received tailored messages via cell-phone based upon uploaded data
Control Site (n=15)
 Continued standard diabetic self care for 3 month period
 Tracked step count using hip pedometer and self-report
Results (cont.)
Utility in Diabetes Management
Quantitative Data on Clinical Outcomes and Diabetes Management Surveys
Table 2. Differences Within Each Group After Intervention
Characteristic
Intervention
n=15
p-value
Control
n=15
p-value
HbA1c (%), mean (±SD)
-0.1 (0.3)
0.15341
0.3 (1.0)
0.38131
DSES, mean (±SD)
Total Scale
Routines
Self-treat
Certainty
Diet
Exercise
-0.5 (0.6)
-0.5 (1.2)
-0.6 (0.9)
-0.6 (1.2)
-0.4 (1.3)
-0.3 (0.9)
0.00801
0.13701
0.03601
0.10901
0.19601
0.38901
0.0 (1.0)
-0.3 (1.0)
0.0 (1.5)
0.3 (1.8)
0.0 (1.3)
0.4 (1.3)
0.83401
0.12701
0.90601
0.46901
0.97501
0.46401
1
Wilcoxon Signed Rank Test
Knowledge is Power…
 if truth is EQSPOSed
Avoiding (gastric) Bypassby Resolving an Impasse.
 HELP is on the way...
 Katz DL. Behavior Modification in Primary Care: the Pressure
System Model. Prev Med. 2001;32:66-72
Can you hear me NOW?
 The CONFIDANT System
 http://www.confidantinc.com/
To turn the tide of chronic disease…
Thank you.
David L. Katz, MD, MPH, FACPM, FACP
Director, Yale Prevention Research Center
CMO, Confidant Systems, Inc.
130 Division St.
Derby, CT 06418
(203) 732-1265
[email protected]
www.davidkatzmd.com