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Li Lisa M Lines, M. Lines Li e , MPH and d Robin Robi R bi E. E Clark, Clark Cl k, PhD

U i University ity off Massachusetts M h tt M Medical di l S School School, h l Worcester, W Worcester t MA; MA lisa.lines@umassmed.edu lisa li lines@umassmed li @ d edu d Presented d at AcademyHealth d l h Annuall Research h Meeting, Meeting i June 12, 12 2011, 2011 Seattle, Seattle l WA

3 Results 3. R llt

1. Background 1. Backg ou d P Prevalence l off Past Past-Year P t Year Y Opioid Opi id Use Use, U , 2005-2008 2005 2008

B p Buprenorphine phi i a prescription is p ipti medication di ti used d to t ttreatt opioid pi id addiction. addiction ddi ti Opioid Opioids Op d include i lud d h heroin oi a and/or d/ d/o p prescription iptio p painkillers pai kill (O ((OxyContin, (OxyContin yCo ti , Vicodin, Vi od Vicodin di , Percoset, P o t, etc Percoset etc.) t )

Alaska

C Can b be di dispensed p d iin office ffi settings, settings tti g , unlike lik methadone th d – this thi can iimprove p p patients’ patients ti t ’ ability bility tto h hold ld a jjob b and d may yp preventt relapse l p P ti t acceptance Patient pt is i higher high – avoids id stigma tig associated i t d with ith methadone th d clinics/t clinics/treatment li i / eatment D t Doctors mustt receive i special p i l Drug D g Enforcement E f tA Agency g y ((DEA)) certification tifi f ti tto prescribe p ib b bup b p buprenorphine o phi Th There are large l g diff differences by by state t t in i amountt off buprenorphine b p phi prescribed p ib d R Research hq question: i what h accounts for f the h variations i i iin buprenorphine b p phi use at the h state l level? l?

2 Methods 2. M th h d W developed We d l p d a state-level state t t level l ld database t b using i gd data t ffor buprenorphine b p phi prescribing p ibi g and d f t factors h hypothesized yp th h i d tto iinfluence fl variations i ti iin p prescribing ibi b g S Sources: DEA, Substance DEA, S b t Ab Abuse and dM Mental t lH Health lth Services S i Ad i i t ti Administration (SAMHSA)), National ((SAMHSA), N ti lC Conference f off State St t Legislatures L gi l t (NCSL) ((NCSL), ), C Columbia l bi U University i ity C t on Addiction Center Addi ti and dS Substance b t Ab Abuse (CASA) ( ) All d data t were ffrom 2005 2005-2008 2008 F t Factors: De a d p Demand: prevalence e ale ce o off p past past-year ty year use o yea off h heroin e oi a and/or d/ d/o p prescription esc ip pttio a analgesics alg gesics S pply number Supply: b off li licensed dp prescribers ib p per 10,000 10,000 users;; number b off opioid pi id treatment t t t programs p g ((OTP (OTPs)) p per 100,000 100,000 users;; Medicaid M di id coverage g off buprenorphine; b p phi ; state t t spending p di g on substance b t abuse b t treatment t t Li Linea Linear regression eg g ession i models d l were e e constructed const cted d with ith i h the h llog g off the h ccumulative m llatii e g grams ams off b p buprenorphine phi di t ib t d iin each distributed h state t t iin 2008 p per 1000 users as th the d dependent p d t variable a iiable bl

M Mean Mi State Min St t

Alaska

AK - 5 5.9 9

M Max

St t Source, State S Source , Data D t YYr

17,130 17,130

241

SD

69,460 69,460

PA

DEA, 2008 DEA,

84 6 84.6

12 7 12.7

SD

404 1 404.1

VT

DEA, 2008 DEA,

241 87 241.87

19

ND

1,531 1,531

CA NSDUH, NSDUH, 2005 2005-08 08

P Prevalence l off past past-year t year opioid i id use N b off DATA Number DATA-certified certified tifi d physicians p hy i i N b off DATA Number DATA-certified certified tifi d physicians p hy i i per p 10,000 10,000 opioid pi id users N b off OTPs Number OTP

5 0% 2.9% 5.0% 2 9%

SD

7 6% 7.6%

OK NSDUH, NSDUH 2005-08 2005 08

N b off OTPs Number OTP per p 100,000 100,000 opioid pi id users Substance b abuse b treatment spending spe d di g pe per subs substance b ta ce abuser abuse b % off states with i h anyy Medicaid M di id coverage g off buprenorphine b p phi

AK - 56 56.8 8 WA - 6.9 69

WA - 56 56.8 8 MT - 5 5.4 4

OR - 6.3

MN - 4 4.1 1

VT - 4 4.6 6

ID - 6.1 61 WI - 5 5.7 7

NY - 4.2 MI - 5 5.6 6

WY - 4.4 44

H Hawaii ii

NE - 3.6

PA - 4.1 41 IN - 6.3 63 IL - 4.2 42

UT - 5.9 59

OH - 5 5.3 3

CO - 5.6 56 KS - 5.2 52

AZ - 6 6.6 6

PA - 163 163.4 4 OH - 68.1 68 1

NV - 30 30.7 7 IL - 34 34.2 2

UT - 120.3 120 3 KS - 18.2 18 2

KY - 109 109.1 1 TN - 95 95.8 8

HI - 40.3 40 3 AZ - 35.7 35 7

NC - 39.4

OK - 35.6 35 6 AR - 18.9 18 9

NM - 50.6 50 6

GA - 4 4.8 8

SC - 63 63.5 5

MS - 146.1 146 1

MS - 3.8 38

MD - 181.4 VA - 55.6 55 6

MO - 31 31.2 2

NC - 4.3 43

NJ - 169 169.3 3

WV - 133.2

IN - 59 59.9 9

CO - 29.9 29 9

CA - 34 34.3 3

NH - 115.2 MA - 200 200.2 2

IA - 13 13.9 9

GA - 49 49.3 3

AL - 111.9

TX - 41.6 41 6

LA - 6

LA - 97.1 FL - 4 4.7 7

Legend

NY - 86 MI - 71.9 71 9

NE - 19

SC - 4 4.1 1 AL - 5.1 51

TX - 4.5 45

H Hawaii ii

KY - 6.5 65

AR - 6.6 66

WI - 58

WY - 51 51.8 8

VA - 4.7 47

MO - 4.7 47

VT - 404 404.1 1

ID - 38 38.9 9 SD - 12.7 12 7

MD - 3.8

OK - 7.6 76 NM - 5 5.8 8

NJ - 3 3.4 4

ME - 322.9 322 9

ND - 33 33.1 1 MN - 36.7 36 7

NH - 4.8

WV - 5.3

TN - 7.1 71

HI - 4 4.2 2

OR - 43.5

MA - 5.5 55

IA - 3 3.4 4

NV - 6 6.6 6 CA - 5 5.2 2

MT - 81 81.9 9

ME - 4.3 43

ND - 3 3.6 6

SD - 2 2.9 9

9 8% off h 9.8% hospital pit i l admissions d i i ffor substance b t abuse b iin 2008 iinvolved l dp painkillers i kill B p Buprenorphine ph hi i ap is partial ti l opioid pi id d agonist, agonist g i t, which hi h h in i the th h US iis g generally lly combined bi b d with ith h naltrexone altt e o e to t reduce educe d potential pote p t ttial ffor o abuse b ((t (trade ade d name: a e Subo S b o e)) Suboxone)

T bl 1. Table 1 Descriptive D ipti characteristics h t i ti off the th sample pl

B p Buprenorphine phi ggrams

Ab Abuse off p prescription ipti pain p i medication di ti was th the second second-most d mostt common type typ off illi illicit it d g use in drug i the th U United it d States St t iin 2008 ((after ft marijuana) ijj ) 400% iincrease over 10 y years iin th the p proportion p ti off A Americans i ttreated t d ffor p prescription ipti painkiller p i kill abuse b

G Grams off Buprenorphine B p phi per p 1000 Opioid Opi id Users, U Users, 2008

Prevalence of Opioid Use, Use %

Legend Grams of Buprenorphine per 1000 Users

29-3 2.9 3.8 8

12 7 - 43.4 12.7 43 4

38-4 3.8 4.6 6

43 5 - 86.0 43.5 86 0

46-5 4.6 5.4 4

86 1 - 133 86.1 133.1 1

54-6 5.4 6.3 3

133 2 - 200 133.2 200.1 1

63-7 6.3 7.6 6

200 2 - 404.1 200.2 404 1

T d iin B Trends Buprenorphine p phi Prescribing, P Prescribing ibi g, 2005 2005-2009: 2009 2009: O Overall ll & iin S Selected l t d States St t

FL - 65 65.5 5

Th mean p The prevalence l off p pastt y past-year year opioid pi id use was ~5% 5% F From 2005 tto 2009 2009,, th the mean amountt off buprenorphine b p phi per p 1000 opioid pi id users increased i d ffrom 13 13g g tto 97 97g gp per y year I 2008 In 2008,, th the p population population-adjusted p l ti adjusted djj t d amountt off buprenorphine b p phi prescribed p ib d was highest high in i V Vermont, Vermont, M Maine Maine, i , and dM Massachusetts Massachusetts, h , and d llowestt in i South S th Dakota, D Dakota k t , IIowa, Iowa, and dK Kansas I unadjusted In djj t d bivariate bi i t analyses, analyses ly , hi higher gh numbers b off p physicians hy i i and d off O OTP OTPs were significantly ig ifi f tlly associated i t d with ith h hi higher h gh b p buprenorphine phi volume l I multivariate In ulti t a iate t a analyses analyses, aly yses,, only o ly th the t e supply supp pply of of physicians phys y icia s remained e ai ed d significantly ig ifi f tly associated i t d

4 Conclusions 4. C l i A the At h state level, llevell, the h supply pply off p physicians hy i i p predicts di the h population p population-adjusted p l i adjusted djj d volume l off buprenorphine b p phi prescribed p ib d S te substance St State b t n e abuse b e treatment t e tment spending p pending di g and nd d Medi Medicaid di id coverage o e ge g off buprenorphine b p eno phine phi d not appear do pp ppe to affect ffe ff t the h volume oll me off buprenorphine b p phi prescribed p ib d St t tthat States thatt e encourage cou age g p physician hy ysicia ce certification tifi t cattio may ay y iimprove p o e access tto effective effectti e op opioid pioid d ttreatment eatt e t Thi assumes that This th t access is i currently tly iinadequate, inadequate d q t ,b based d on existence i t off waiting iti g li lists t iin many y areas F Future studies di should h ld examine i ffactors associated i d with i h physicians phy i i d deciding idi g to b become DATA certified, certified ifi d, iincluding l di g state policies p li i that th t encourage g certification tifi ti

B p Buprenorphine phi g p per 1000 opioid pi id users N b off opioid Number pi id d users ((000))

303

11

SD

1,822 1,822

NY

SAMHSA, 2008 SAMHSA,

13 9 13.9

23 2.3

AR

66 4 66.4

VT

C l l ti Calculation

23 4 23.4

0

*

157

NY

SAMHSA 2008 SAMHSA,

10 3 10.3

0

*

45

DC

C l l ti Calculation

$$113

$$5

WI

$$746

CT

CASA, 2005 CASA,

84%

NCSL, 2008 NCSL,

*MT MT,, ND ND,, SD SD,, WY

T bl 2. Table 2 Bivariate Bi i t associations i ti between b t buprenorphine b p phi volume l and d state t t characteristics h t i ti

C f * Std. Coef Coef. S d Err. Std EErr N b off DATA Number DATA-certified certified tifi d physicians phy i i per 10,000 p 10,000 opioid pi id users N b off OTPs Number OTP per p 100,000 100 000 opioid pi id users sers S State spending p di g on substance b abuse b t t treatment t per p substance bt abuser b M di id coverage Medicaid g

P value l

95% Conf. Conf C f Interval I l

0 047 0.047

0 006 0.006

< 001 <.001

(0 034 to 0.060) ((0.034 0 060))

0 044 0.044

0 010 0.010

< 001 <.001

(0 023 to ((0.023 t 0.064) 0 064))

0 001 0.001

0 001 0.001

.159 159

((-00.001 0 001 to t 00.003) 003))

-00.092 0 092

0 300 0.300

.760 760

((-00.695 0 695 to t 00.511) 511))

*Ordinary Ordinaryy least least-squares squares q regression g coefficient

T bl 3. Table 3 Multivariate M lti i t associations i ti b between t b buprenorphine p phi volume l and d state t t characteristics h t i ti

C f * Std. Coef Coef. Std EErr. Err N b off DATA Number DATA-certified certified ifi d physicians p hy i i per p 10 10,000 ,000 opioid pi id d users N b off OTPs Number OTP per p 100,000 100,000 opioid pi id users

P value l

95% Conf. Conf C f Interval I t l

0 048 0.048

0 010 0.010

< 001 <.001

(0 028 to ((0.028 t 0.068) 0 068))

-00.002 -0.002 0 002

0 013 0.013

.869 869

(-00.027 ((-0.027 0 027 to 00.023) 023))

*O *Ordinary Ordinary di y least l least-squares t squares q regression g i coefficient ffi i t

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