deaths of despair a - university of notre damewevans1/health_econ/deaths_of_despair_a.pdf · deaths...

9/27/2019

1

Deaths of Despair

Econ 43565

Bill Evans

Fall 2019

1

Introduction

• Long term secular decline in mortality

• Especially pronounced for minorities

• Starting in late 1990s, mortality rates started to climb for middle-aged whites – particularly low educated males

• Generated from particular deaths– Drug poisonings, suicides, alcohol liver disease

– Case and Deaton: “Deaths of despair”

2

This class

• Outline the basic trends– Trends are scary

– The declining economics prospects for low-skilled males is a part of the problem

• Two notes– Problem is concentrated in a particular group

– But economics is not the whole story

3

• Components of the trends

• Most of the deaths of despair is rising drug deaths

• Most of drug deaths are opioid/heroin

• Outline the origins of the opioid/heroin/fentanyl crisis

• Opioid crisis looks to be started by OxyContin

• Heroin crisis started by the reformulation of Oxy

• Fentanyl crisis piggy-back on the heroin crisis

4

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5 6

7

White 25‐29: 82% increaseBlack 25‐29: 8% decline

White 30‐34: 90% increaseBlack 30‐34: 12.5% decline

8

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9 10

11 12

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13

0

5

10

15

20

25

30

35

40

45

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

rate

Axis Title

Deaths of Despair and its Components

Deaths of despair

Drug poisonings

Alcohol-relatedliver mortality

Suicides

65% of the increasein the deaths if despair due to drugs

14

0

5

10

15

20

25

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

Year

Drug Poisonings, 1999-2016

All drugsAll drugsAll drugs

Heroin/opioids

Not heroin/opioids

77% of the increasein the drug poisoning rateis heroin/opioidpoisonings

15

0

10

20

30

40

50

60

80

90

100

110

120

130

140

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

rate

Mo

rta

lity

rate

Year

White, non-Hispanics, 25-34

All cause(left axis)

Heroin/opioid(right axis)

72% of the increasein the death rateis heroin/opioidpoisonings

0

10

20

30

40

170

180

190

200

210

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

rate

Mo

rta

lity

rate

Year




16


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5

17

0

10

20

30

40

50

380

390

400

410

420

430

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

rate

Mo

rta

lity

rate

Year





Case and Deaton

• Deaths of despair are a result of the breakdown in institutions: Jobs, earnings, family

• Time trends are easy to establish

• Correlation pronounced

• Correlation ≠ causation

18

19

0

0.1

0.2

0.3

0.4

0.5

0.6

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

cti

on

Year

Fraction Not Married by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS

High school or less Some college College grad20

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

cti

on

Year

Fraction Not Living Independently by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS

High school or less Some college College grad

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6

21

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

ctio

n

Year

Fraction Not in Labor Force by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS

High school or less Some college College grad22

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

$90,000

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

2017

$

Year

Real Earnings (2017$) of Full-Time/Full Year Workers by Education,White non-Hispanic Males 25-54, 1971-2017, March CPS

High school or less Some college College grad

23

-10

0

10

20

30

40

50

60

70

80

-0.1 -0.05 0 0.05 0.1 0.15 0.2

Ch

ang

e in

dru

g p

ois

on

ing

dea

th r

ate,

200

0/02

to

201

4/16

Change in condition, 2000/02 to 2014/16

Scatter Plot: ∆ in Marriage Rates vs. ∆ in Drug Poisoning Rate,White non-Hispanic Males, 25-54

ρ=0.28

24

-10

0

10

20

30

40

50

60

70

80

-0.1 -0.05 0 0.05 0.1 0.15

Ch

an

ge

in d

rug

po

iso

nin

g d

eat

h r

ate

, 20

00/0

2 t

o 2

014/

16


Scatter Plot: ∆ in % Workers w/ Low Earningsvs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54

ρ=0.25

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7

25

-10

0

10

20

30

40

50

60

70

80

-0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08

Ch

an

ge

in d

rug

po

iso

nin

g d

eat

h r

ate

, 20

00/0

2 t

o 2

014/

16


Scatter Plot: ∆ in % Workers not in Labor Force,vs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54

ρ=0.07

26

-10

0

10

20

30

40

50

60

70

80

-0.1 -0.05 0 0.05 0.1 0.15 0.2

Ch

an

ge

in d

rug

po

iso

nin

g d

eat

h r

ate

, 20

00/0

2 t

o 2

014/

16


Scatter Plot: ∆ in % W/ at least one Negative Event,vs. ∆ in Drug Poisoning Rate, White non-Hispanic Males, 25-54

ρ=0.32

Problem for Case and Deaton

• Institutional outcomes have been declining for Blacks as well

• Poorer levels and same trends in outcomes

• Why has the drug crisis not impacted this group?

27 28

0

10

20

30

40

50

60

70

1999 2001 2003 2005 2007 2009 2011 2013 2015

Mo

rtal

ity

rate

Year

Drug Poisonings for Males, 24-54, by Race

White,non-Hispanic

Black,non-Hispanic

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29

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

cti

on

Year

Fraction Not Married by Race,Males 25-54, 1971-2017, March CPS

White non-Hispanic Black, non-Hispanic30

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

cti

on

Year

Fraction Not Living Independently by Race,Males 25-54, 1971-2017, March CPS

White non-Hispanic Black, non-Hispanic

31

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Fra

cti

on

Year

Fraction Not in Labor Force by Race,Males 25-54, 1971-2017, March CPS

White non-Hispanic Black, non-Hispanic32

$0

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

201

7$

Year

Real Earnings (2017$) of Full-Time/Full-Year Workers by Race,Males 25-54, 1971-2017, March CPS

White non-Hispanic Black, non-Hispanic

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The drug crisis

33 34

0

5

10

15

20

25

1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

Dea

ths/

100,

000

Year

Drug Poisoning Death Rate, 1989-2017

All drugs

Opioids

non-opioids

Opioids 2/3rds of deaths in 201775% of the ↑ drug deaths

Some facts

• Drug deaths now 72,000/year– MV fatalities: 40,100– Gun deaths: 40,000– Homicides: 19,500– Suicides: 47,173

• Between 1989 – 2017– 704,000 drug poisoning deaths– About the same number of US soldiers that have died in

armed conflicts from Spanish American War through Operation Enduring Freedom

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37

0

5

10

15

20

25

30

35

40

45

50

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

De

ath

s/1

00,

000

Year

States with Lower Changes in Opioid Death Rates

CA OR TX AR38

0

5

10

15

20

25

30

35

40

45

50

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

De

ath

s/1

00,

000

Year

States with the Highest Changes in Opioid Death Rates

KY OH WV RI

39

0

2

4

6

8

10

12

14

16

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th R

ate

Year

Opioid Death Rate, 1999-2017All opioids

40

0

1

2

3

4

5

6

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th R

ate

Year

Opioid Death Rates, 1999-2017

Opioids only

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41

0

1

2

3

4

5

6

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th R

ate

Year


Opioids only

Heroin only, orwith opioids

42

0

1

2

3

4

5

6

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th R

ate

Year


Opioids only


Fentanyl aloneor with heroinand/or opioids

43

0

1

2

3

4

5

6

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th R

ate

Year


Opioids only


Fentanyl aloneor with heroinand/or opioids

How did the opioid crisis come about

• Three distinct crisis– Opioid, then heroin, now fentanyl

• All are all related– Opioids led to heroin

– Heroin led to fentanyl

44

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Part 1: The Rise of OxyContin

45

Re-analysis of pain management

• <1990s, opioids mainly used for acute pain– Post surgery, cancer

• 1990s movement to use for chronic pain– 1996 – Consensus statement of two professional pain

societies –• “an epidemic of untreated pain”• Urged a more general use of opioids• < 1% of opioid users become addicted

– 1998 – Federation of State Medical Boards – MDs will not face discipline for heavy use of pain meds

– 2001 Joint Commission – pain is the “5th vital sign”

46

Enter OxyContin

• Synthetic drug with similar properties to heroin• Active ingredient is Oxycodone– Been around since 1917– Introduced to US in 1935– Percodan – Oxycodone and aspirin (1950)– Percocet – Oxycodone and acetaminophen (1974)

• OxyContin introduced in 1996– Purdue Pharma (Sackler Family)– Extended release (ER) drug – high mg content – $35 billion in worldwide sales through 2015

47

Enter OxyContin

• Released at same time as reform taking place

• Purdue actively marketed to doctors

• Originally marketed as “non habit forming”– Purdue trained sales force to mislead about addiction

– Porter and Jick (1980)

48

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49

Enter OxyContin

• Released at same time as reform taking place• Purdue actively marketed to doctors• Originally marketed as “non habit forming”– Purdue trained sales force to mislead about addiction– Porter and Jick (1980)– In 1996, Purdue was allowed to say addiction is rare

when appropriately used– Forced to stop in 2001– 2007 – Paid $600 million in fines to Feds

50

Advertising plan

• 1996 – advertise OxyContin for cancer patients

• 1997 and on – push for chronic pain sufferers

• Budgeted $640 million to advertise from 1996-2000

51 52

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Triplicate Prescription Pad states

• 9 states in 1995 (CA, HI, ID, IL, IN, MI, NY, RI, TX)• 3 copies

– For Schedule II drugs• Narcotic analgesics (including OxyContin)• Barbituates• Stimulants

– One kept by the Doc– Two given to pharmacy – one sent to state– State monitors use

• Schedule III drugs included at the time – Vicodin– Codeine– Combination drugs– Dihydrocodeinone

53

Purdue and Triplicate states

• Focus groups – Doc’s don’t like triplicate pads – “Based on the discussion with the two groups of doctors in the

triplicate state, albeit a small sample, it did not appear that they used Class II narcotics for treatment of non-cancer pain. Most did not want to go through the trouble involved, and they did not want to give the Government an excuse to monitor their activities”

• Heavy use of Schedule III drugs– “Writing triplicate prescriptions was more trouble than others, due

to the details of the forms and the various people that need to be copied on them. To the extent that they can avoid this extra effort, they will try to follow alternate protocols”

54

Purdue and Triplicate states

• Especially true for acute pain– “For the most severe conditions, such as those occurring as a result of

trauma or post-operative conditions, they would prescribe a narcotic. In the non-triplicate states, this was often a class II Opioid, whereas in the one triplicate state we visited, it was a Class III opioid” (p.26)

• Barrier to success in these states– “However, because oxycodone is a Class II opioid, prescribing

OxyContin will entail a triplicate prescription in those states requiring them. In addition, Class II opioids cannot be phoned in to the pharmacy, while Class III opioids can. These regulations create a barrier when positioning OxyContin versus the Class III opioids”

55

• Advertising strategy – avoid triplicate states– “Among the physicians in this triplicate state who do use

Class II narcotics in the treatment of non-cancer pain, our research suggests the absolute number of prescriptions they would write each year is very small, and probably would not be sufficient to justify any separate marketing effort” (p. 59)

56

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57

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100K

Year

Drug Death Rates by Triplicate Status

non-TriplicateStates

TriplicateStates

58

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100K

Year



TriplicateStates

59

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100K

Year



TriplicateStates

Forecasts based < 1996 data

60

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100K

Year



TriplicateStates

Forecasts based < 1996 data

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16

61

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100

K

Year

Opioid Death Rates by Triplicate States

non-Triplicatestates

Triplicatestates

62

0

2

4

6

8

10

12

14

16

18

20

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Dea

ths/

100K

Year

Non-Opioid Death Rate by Triplicate Status

non-Triplicatestates

Triplicatestates

Part 2: The Movement to Heroin

63

Oxy reformulation

• Purdue Pharma responds to critics by releasing abuse-resistant version

• FDA approves reformulation on April 5, 2010

• New formulation is released without notice on August 10, 2010

• Old drugs immediately pulled from market

64

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Old and New OxyContin crushed

65

Problem

• Demand for opioids is still there

• The ability to get high is NOT

• Solution: switch to a close substitute

• That alternative: heroin

66

Heroin markets in US

• Historically – heroin markets divided by the Mississippi River– East was white powder heroin from SE Asia

–West was black tar heroin from Mexico

• Largest markets: NE and MW

• Mexican heroin making larger inroads all across US– Taken over Chicago, Philly, DC, NJ, part of NY

67

New suppliers: Xalisco Boys cartel

• Pioneered new distribution system:

• Cell owner supplies heroin from Mexico

• Cell manager in US city/town – receives shipments

– runs the business

• Telephone operator stays in an apartment all day receiving orders and relays these to drivers

• Drivers meet consumers and sell the heroin

68

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18

• High focus on product quality and customer service

• When they enter a city they sought out high users

• Now– US awash in heroin

– Amazingly high quality

– Very low price

69

Real heroin prices

70

0

500

1,000

1,500

2,000

2,500

3,000

3,500

1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013

Pri

ce p

er g

ram

pur

e, 2

012

US

Dol

lars

Year

Dating the switch to heroin

71

Dating the heroin crisis

• Examine lots of national time series– Opioid use/abuse

– Heroin abuse

• Use a statistical procedure to date a “structural break”

• All series break right after the reformuation of OxyContin

72

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73

0

1

2

3

4

5

6

7

8

9

2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01

RX

s/10

00

Year.Month

Monthly RXs for Oxycodone/1000 Subscribers, Marketscan Data

Actual Predicted

8/2010

74

0

10

20

30

40

50

60

2004.1 2006.1 2008.1 2010.1 2012.1 2014.1

KG

s /1

000

Year.Month

KGs of Oxycodone Shipments/1000, ARCOS Data

Actual Predicted

2010:Q3

75

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

2004.1 2006.1 2008.1 2010.1 2012.1 2014.1

% 3

0-d

ay U

se

Year.Month

% Use Pain Meds Recreationally in past 30 Days, NDUHS

Actual Predicted

2010:Q2

76

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01

Dea

ths/

100,

000

Year.Month

Monthly Heroin Deaths/100,000

Actual Predicted

9/2010

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20

77

0.00

0.01

0.02

0.03

0.04

0.05

2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01

En

cou

nte

rs/

1000

Year.Month

Inpatient and Outpatient Encounters for Heroin Poisoning /1000 Subscribers, Marketscan Data

Actual Predicted

9/2010

Heroin + Opioid Death Rates

78

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01

Dea

ths/

100,

000

Year.Month

Heroin + Opioid Deaths

79

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

2004.01 2005.01 2006.01 2007.01 2008.01 2009.01 2010.01 2011.01 2012.01 2013.01 2014.01

Dea

ths/

100,

000

Year.Month

Actual Predicted

4/2012

The results

• Reformulation of OxyContin brought about a shift to heroin

• The decline in deaths to opioids was compensated 1-for-1 with deaths from heroin

• Problem: Federal governments’ only solution to the opioid crisis SO FAR has been to encourage abuse-deterrent formulation

• Little likelihood of success as long as heroin and fantanyl is so prevalent

80

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Part 3: The Movement to Fentanyl

81

Fentanyl

• ~2013, heroin begins to be laced with fentanyl

• Fentanyl 50 x more potent than morphine– Prince died of a fentanyl OD

• Source– Legal diversion

– Created in clandestine labs

• Mixed w/ heroin

• Counterfeit opioid pills

82

Amount needed to OD, Heroin and Fentanyl

83

How is Fentanyl making it to the US?

• Order by mail from China– “The most common distribution medium is via the

U.S. Postal Service,” US Treasury

– FedEx/UPS subject to electroic tracking of foreign packages to identify source USPS is not

–Work in small independent networks

– 700 fentanyl-related sales listing on English language dark web sites

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How is Fentanyl making it to the US

• Mexican drug gangs– Produced in Mexico– $32,000 in raw ingredients can produce 1 million

pills w/a street value of $20 million– Brought in as a raw drug– Any mixing with other drugs is done at the retail and

not wholesale level– Sinaloa Jalisco cartels are the most likely sources– Few years ago, going wholesale price for

heroin/pound in Mexico was $600. Now $100

85

Tradeoffs

• Chinese mail-order– Lower volume, high purity (90%)

• Mexican gangs–Much higher volume, lower purity (<10%)

86

87

0

1

2

3

4

5

6

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th r

ate

Year

Fentanyl Death Rate, 1999-2017

Fentanyl alone

Fentanyl withheroin, or with heroinand opioids

Fentanyl withopioids

88

0

2

4

6

8

10

12

1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

Dea

th r

ate

Year

Fentayl Death Rates by State Heroin Death Rate in 2009

Highest 1/3

Middle 1/3

Lowest 1/3

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Restrictions

• 2018 – At G-20 dinner with Trump and Xi in Buenos Aires, Xi agreed to reclassify fentanyl controlled substance

• Makes these dark web sites in China subject to enforcement by state government

89

• Some success– Has decreased darkweb sellers

– Of USPS seized with fentanyl, most are now from US

• Some concerns– China may now be shipping precursors to Mexico

–Mexico produces the fentanyl

90

deaths of despair a - university of notre damewevans1/health_econ/deaths_of_despair_a.pdf · deaths...

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