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. Author manuscript; available in PMC: 2015 Mar 19.
Published in final edited form as: J Health Care Poor Underserved. 2015 Feb;26(1):182–198. doi: 10.1353/hpu.2015.0009

Prescription Practices involving Opioid Analgesics among Americans with Medicaid, 2010

Karin A Mack 1, Kun Zhang 1, Leonard Paulozzi 1, Christopher Jones 1
PMCID: PMC4365785  NIHMSID: NIHMS667594  PMID: 25702736

Abstract

Recent state-based studies have shown an increased risk of opioid overdose death in Medicaid populations. To explore one side of risk, this study examines indicators of potential opioid inappropriate use or prescribing among Medicaid enrollees. We examined claims from enrollees aged 18–64 years in the 2010 Truven Health MarketScan® Multi-State Medicaid database, which consisted of weighted and nationally representative data from 12 states. Pharmaceutical claims were used to identify enrollees (n=359,368) with opioid prescriptions. Indicators of potential inappropriate use or prescribing included overlapping opioid prescriptions, overlapping opioid and benzodiazepine prescriptions, long acting/extended release opioids for acute pain, and high daily doses. In 2010, Medicaid enrollees with opioid prescriptions obtained an average 6.3 opioid prescriptions, and 40% had at least one indicator of potential inappropriate use or prescribing. These indicators have been linked to opioid-related adverse health outcomes, and methods exist to detect and deter inappropriate use and prescribing of opioids.

Keywords: Medicaid, opioids, prescription drugs, overdose


The problem of overdose from prescription medications has emerged as a major public health issue in the United States.1 In 2013, drug overdoses killed 43,982 Americans, more than the number killed in motor vehicle traffic crashes. Opioid analgesics alone or in combination with benzodiazepines or other drugs account for nearly half of all drug overdose deaths.2 Misuse or abuse of pharmaceuticals also led to more than 1.4 million emergency departments (ED) visits—with over 420,000 involving opioid analgesics in 2011.3

Studies using administrative data from a limited number of health plans have described opioid use generally (such as number of opioid prescriptions received, average daily dose, and total days' supply,) and/or potential opioid misuse (such as high daily dosage, overlapping opioids, and overlapping opioids and benzodiazepines).47 Other studies and government reports have focused on opioid use and misuse specifically among the Medicaid population.810 This population is of concern because it has, on average, higher levels of mental health and substance abuse disorders than the general population9,11 and thus potentially greater risk for adverse outcomes with opioids. Indeed, two states have reported an increased risk of opioid overdose death in their Medicaid populations.12,13

This study expands the literature in this area by examining multiple indicators of use and potential misuse of opioids among Medicaid patients using one of the largest fully-integrated health insurance claims databases in the United States. The objective is to describe the volume of opioid prescribing among Medicaid enrollees, and provide an index of measures to describe potential misuse or inappropriate prescribing.

Methods

Data source

We conducted secondary data analyses of the Truven Health MarketScan® Multi-State Medicaid database, which consisted of weighted and nationally representative data from 12 geographically dispersed states. The MarketScan Medicaid database contains standardized, fully integrated, enrollee-level de-identified claims across inpatient, outpatient, and prescription drug services for both fee-for-services and capitation plans. Our analysis primarily drew data from pharmaceutical claims in 2010 for filled prescriptions, which included outpatient drug name, therapeutic class, national drug code, days of supply, and quantity for about 1.38 million Medicaid enrollees aged 18–64 years. In addition, the outpatient service claims and inpatient admission records were used to identify the underlying pain diagnoses related to opioid use. Inpatient admission records were employed only to identify the diagnoses associated with opioid prescriptions prescribed to enrollees at discharge. Drugs administered during hospitalizations were not included. No personal identifying information was available in the database, and this study did not require human subjects' review.

Study population

From the pharmaceutical claims we identified 3,534,564 opioid prescriptions for the 1.38 million enrollees aged 18–64 years (Figure 1). We excluded 704,624 opioid prescriptions for non-continuously enrolled Medicaid recipients in 2010; 173,125 opioid prescriptions that lacked the dispensing information necessary for the calculation of outcome indicators; and 67,073 opioid prescriptions that were refill prescriptions that could not be linked to their original diagnoses. We also excluded 68,642 opioid prescriptions for enrollees under institutional long-term-care, and 218,678 for enrollees with a cancer diagnosis in their outpatient or inpatient service claims. Cancer diagnosis were based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes including 338.3; 140–172.9; 174–215.9; 217–229.10; and 235–239.9. Finally, roughly 1% (37,405) of the opioid prescriptions were for buprenorphine products and were excluded due to their primary use for the treatment of opioid dependence (methadone received at narcotic treatment centers is excluded by default given that we did not capture narcotic treatment center claims). This selection process resulted in 2,265,017 opioid prescriptions for 359,368 Medicaid enrollees as our final study population (see Figure 1). A list of opioids analyzed is available upon request, and morphine equivalent conversion factors used have been previously described.14

Figure 1.

Figure 1

Opioid prescriptions drawn from pharmaceutical claims flow chart.

Subpopulation with identified diagnoses

To calculate a subset of outcome indicators that are specific to certain types of pain, we linked opioid prescription claims to the diagnoses on outpatient or inpatient service claims by matching enrollee ID and the date of service in these claims. Consistent with the existing literature,15 we linked opioid prescriptions to the outpatient services or inpatient discharges that occurred within 14 days of the prescription dispense dates. If multiple outpatient or inpatient records existed within this interval, we linked to the one that occurred on the day closest to the drug dispense dates. When inpatient and outpatient dates of service overlapped, we used the outpatient claims for the linkage. Prescription refills were assigned the diagnoses on the original prescriptions. We successfully linked 1,772,632 (78.3%) of the 2,265,017 opioid prescriptions to diagnoses for 323,879 enrollees (90% of the overall study population). Of the remaining 21.7% of prescriptions, 19.5% could not be linked because the outpatient services or inpatient discharges had occurred more than 14 days prior to the prescription dispensing date or in 2009; 2.2% could not be linked because MarketScan did not have the enrollee's outpatient service claims.

Outcome indicators

We adapted outcome indicators that had been identified by expert panels and clinical guidelines1622 and validated by their association with abuse of overdose.2326 These indicators captured both general opioid use as well as potential misuse by patients or inappropriate prescription practices by providers.

At the enrollee level, indicators of general opioid use included the total number of opioid prescriptions, total days' supply of opioids, and medical diagnoses (such as acute pain, other pain, or both) associated with opioid prescriptions. Acute pain and other pain diagnoses were based on ICD-9-CM codes (Table 1 footnote b and c). Indicators of potential misuse or inappropriate prescription practices consisted of: (1) opioid overlap, defined as opioid prescriptions that overlap seven or more days (including early refills); (2) opioid and benzodiazepine overlap, defined as opioid and benzodiazepine prescriptions that overlap seven or more days; (3) high daily opioid dose, defined as a prescribed daily dose of 100 morphine milligram equivalents (MMEs) or greater; and (4) rapid opioid dose escalation, measured as having a 50% or greater increase in mean MMEs per month twice consecutively during the year.

Table 1. Demographic Characteristics and General Opioid Use Indicators Among Medicaid Enrollees Prescribed Opioid Analgesics, Marketscan 2010.

Males (n=94,278) Females (n=265,090) Total (n=359,368)



Characteristic n % n % n %
Age, years
 18–34 31,520 33.4% 133,252 50.3% 164,772 45.9%
 35–44 16,945 18.0% 48,238 18.2% 65,183 18.1%
 45–54 25,777 27.3% 46,863 17.7% 72,640 20.2%
 55–64 20,036 21.3% 36,737 13.9% 56,773 15.8%
 Mean* 41.4 years 36.9 years 38.1 years
Medication use
No. of opioid prescriptions obtained
 1 28,065 29.8% 85,266 32.2% 113,331 31.5%
 2 12,835 13.6% 42,719 16.1% 55,554 15.5%
 3 or more 53,378 56.6% 137,105 51.7% 190,483 53.0%
 Mean* 7.1 6.0 6.3
Combinations of drugs obtained in 2010a
 Opioid & benzodiazepine* 26,554 28.2% 81,244 30.6% 107,798 30.0%
 Opioid & muscle relaxant* 30,656 32.5% 89,263 33.7% 119,919 33.4%
 Opioid, benzodiazepine, & muscle relaxant* 11,946 12.7% 41,494 15.7% 53,440 14.9%
Total days' supply for opioids
 <30 46,543 49.4% 158,502 59.8% 205,045 57.1%
 30–59 8,270 8.8% 23,134 8.7% 31,404 8.7%
 60–89 4,528 4.8% 11,579 4.4% 16,107 4.5%
Days' supply con't
 90+ 34,937 37.1% 71,875 27.1% 106,812 29.7%
 Median 30 15 17
Mean morphine mg equivalent dose 46.3 44.1 44.7
Diagnoses associated with opioid drugs
 Acute pain only*b 18,722 19.9% 60,722 22.9% 79,444 22.1%
 Other pain only*c 18,178 19.3% 45,354 17.1% 63,532 17.7%
 Acute and other pain*d 29,000 30.8% 77,794 29.3% 106,794 29.7%
 Other diagnoses* 16,619 17.6% 57,461 21.7% 74,080 20.6%
 Unknowne 11,759 12.5% 23,759 9.0% 35,518 9.9%
*

Difference between males and females is significant p<.01

a

For this indicator, “combinations of drugs obtained in 2010,” drugs were not necessarily prescribed together in a single visit or in a similar time period. For example, an enrollee in the first category might have obtained an opioid prescription in January of 2010 and a benzodiazepine prescription in December of 2010. Indicators that assess drug overlap are listed in table 3.

b

Acute pain was determined by whether the enrollee had a diagnosis of a disease or an injury or a surgical procedure that could cause acute pain. Diagnoses for acutely painful diseases and injuries and their ICD9-CM codes were: sickle cell with crisis (282.62); acute pain (338.11,338.12,338.18,338.19); dental abscess with sinus (522.5); dental abscess without sinus (522.7); gallstone (574); acute pancreatitis (577); kidney stone (592); pathological fracture (733.1); acute injury (800–904.9); other acute injury (910–959.9); external cause of injury codes (E800–E849.9; E880–E909.9; E916–E928.9; E953–E968.9; E970–E976.9; E983–E999.9). After the exclusion of minor procedures, surgical procedures included: excision of breast tissue; other major skin, breast, or musculoskeletal surgeries; other major respiratory, cardiovascular, hemic and lymphatic, digestive, eye/ocular, ear/auditory or urinary procedures; repair of inguinal hernia procedures; major male genital procedures; dilation and currettage; major female genital procedures; decompression, carpal tunnel surgery; major endocrine system, and nervous system procedures; cataract removal; other major surgery procedures; cesarean section deliveries; major maternity procedures and related care; and dental, or major restorative surgery.

c

Diagnoses likely to be associated with other pain and their ICD9-CM codes included: chronic pain (338.21, 338.22, 338.28, 338.29, 338.4); migraine headache (346.0–346.9); tension headache (307.81); arthritis or joint pain (710.0–719.9); dorsopathies, or back pain (720.0–724.9); and arthritis or joint pain (725.0–729.9)

d

Enrollees listed as having acute and chronic pain conditions associated with opioid drugs included those who had both types of pain diagnoses listed in a single opioid related office visit as well as those who had separate opioid related visits for each type of pain.

e

Causes for opioid use were unknown because these enrollees' opioid prescriptions could not be linked to any outpatient/inpatient service claims.

Three indicators specific to long-acting/extended-release (LA/ER) prescriptions were examined given their elevated risk for addiction and initiation abuse: (1) LA/ER opioid prescriptions written for acute pain conditions; (2) overlapping LA/ER opioid prescriptions; and (3) LA/ER prescriptions obtained by an opioid “naïve” person, defined as a person who had no prescription for an opioid for at least 60 days prior to that for an LA/ER opioid.

At the prescription level, indicators of general opioid use included the number of days' supply and the prescribed daily doses for opioid prescriptions for acute, back, and other pain. Back pain included both acute and other back pain and was based on ICD-9-CM codes recommended by the American College of Occupational and Environmental Medicine (ACOEM) practice guidelines.27 Indicators of potential inappropriate prescription practices are the same as those described for enrollees though expressed in number of prescriptions.

Statistical analysis

We calculated the distributions of various levels of usage among all enrollees receiving an opioid prescription overall, by sex, and by pain type. The prevalence for indicators of potential misuse by patients or inappropriate prescription practices by providers was calculated as both a percentage of enrollees and a percentage of prescriptions. We used t-tests or chi-square tests for comparisons by sex.

Results

Enrollee-level indicators

In the overall study population of Medicaid enrollees with at least one opioid prescription (opioid recipients), 74% were female. The mean age of opioid recipients was 41.4 years among males and 36.9 years among females (Table 1). Males received on average one more opioid prescription than females (males mean = 7.1; females 6.0). More than half of all opioid recipients had three or more opioid prescriptions (53%) in 2010. Notably, 7% of the study population had 20 or more opioid prescriptions during the data year—with more than 800 enrollees receiving 50 or more opioid prescriptions (data not shown).

Just under one half of the male recipients (49.4%) received less than 30 total days' supply of opioids, and about 37.1% received more than 90 days' supply of opioids in 2010. Among women, nearly 60% received less than a 30 days' supply, and 27.1% received more than 90 days' supply of opioids during 2010. Over 13,000 (14%) male opioid recipients received 200–364 days of opioids in the past year, and 11,326 (12%) received more than a 365 days' supply. For women nearly 27,000 (10%) received 200–364 days, and 21,269 (8%) received more than 365 days (data not shown).

We were able to identify the associated medical diagnoses for opioid prescriptions for 90% of the overall study population; 22% of the recipients obtained opioids for acute pain conditions only; 17.7% received opioids for other pain conditions only; and 29.7% obtained opioids for both acute and other pain conditions. Another 20.6% of the recipients received opioid prescriptions for diagnoses not included in the lists of acute or other pain conditions (e.g., acute pharyngitis, chronic airway obstruction, unspecified dental caries, urinary tract infection, and other general symptoms)

The most common indicator of inappropriate use was having an opioid/b enzodiazepine overlap (Table 2); 22.6% of the opioid recipients had at least one such event during the study period. Seventeen percent of the study population had daily doses of 100 MMEs or higher per opioid prescription at least once during the study period, and of those recipients, 17% had daily doses of 100 MMEs or higher for more than 90 days (data not shown). Roughly 1% of the opioid recipients had opioid dose escalation. Overall 40.7% of the opioid recipients had at least one indicator of inappropriate use: one-quarter (24.7%) had one indicator, 11% had two and 5% had three. Among those who had LA/ER opioid prescriptions, 21.8% received LA/ER opioids for an acute pain condition at least once.

Table 2. Indicators of Potential Inappropriate Use Among Medicaid Enrollees Prescribed Opioid Analgesics By Gender, Marketscan 2010.

Males (n=94,278) Females (n=265,090) Total (n=359,368)



n % n % n %
Indicators of Potential Inappropriate Use
Any opioid overlapa
 None 71,840 76.2% 216,728 81.8% 288,568 80.3%
 Once* 6,657 7.1% 15,919 6.0% 22,576 6.3%
 Two or more incidents* 15,781 16.7% 32,443 12.2% 48,224 13.4%
Opioid/benzodiazepine overlapb
 None 73,345 77.8% 204,838 77.3% 278,183 77.4%
 Once 3,539 3.8% 10,623 4.0% 14,162 3.9%
 Two or more incidents 17,394 18.4% 49,629 18.7% 67,023 18.7%
High daily opioid dosec
 None 77,928 82.7% 219,086 82.6% 297,014 82.6%
 Once* 6,928 7.3% 26,494 10.0% 33,422 9.3%
 Two or more incidents* 9,422 10.0% 19,510 7.4% 28,932 8.1%
Opioid rapid dose escalationd
 Any escalation 1,013 1.1% 3,118 1.2% 4,131 1.1%
Indicators
 No indication of inappropriate use 54,627 57.9% 158,391 59.7% 213,018 59.3%
 One type of indicator of inappropriate use 23,057 24.5% 65,965 24.9% 89,022 24.7%
 2 different indicators of inappropriate use* 10,946 11.6% 28,406 10.7% 39,352 11.0%
 ≥3 different indicators of inappropriate use* 5,648 6.0% 12,328 4.7% 17,976 5.0%
Long acting/extended release opioids for acute pain conditionse
 None 7,804 77.8% 13,004 78.4% 20,808 78.2%
 Once 1,289 12.9% 2,229 13.4% 3,518 13.2%
 Two or more incidents 934 9.3% 1,351 8.1% 2,285 8.6%
Long acting/extended release opioids that overlap with other long acting/extended release opioids
 None 7,183 71.6% 12,166 73.4% 19,349 72.7%
 Once 1,163 11.6% 1,885 11.2% 3,018 11.3%
 Two or more incidents* 1,681 16.8% 2,563 15.4% 4,244 16.0%
Long acting/extended release opioids prescribed for opioid naive persons
 Any such incidents 2,562 25.6% 3,945 23.7% 6,507 24.5%
*

Difference between males and females is significant p<.01

a

Days' supply of one opioid prescription overlaps with another opioid prescription for at least 7 days for a given enrollee.

b

Days' supply of one opioid prescription overlaps with one or more benzodiazepine prescription for at least 7 days for a given enrollee.

c

≥100 morphine milligram equivalents (MMEs)

d

Having a 50% or greater increase in mean MME per month twice consecutively during the year.

e

The numbers of enrollees who received LA/ER opioids were 10,027 and 16,614 for males and females, respectively.

Prescription level indicators

Among the 1,772,632 prescriptions that were linked to diagnoses, about 16.5% of them were written for acute pain conditions alone, and a higher proportion (34.9%) were for other pain alone. Ten percent were associated with both acute pain and other pain conditions, and 15.3% were associated with back pain diagnoses. The remaining 38.5% of the prescriptions were linked to diagnoses not included in the lists of acute or other pain conditions (as noted above).

The mean days' supply for acute, other, and back pain was nine, 20, and 21 days, respectively (Table 3). For acute pain, 70.6% of prescriptions were written for nine or fewer days, and 14% were written for 30 or more days. The mean daily opioid dose for prescriptions for acute pain was higher for men (53.1 MME) than females (49 MME). Notably, 9% of prescriptions for acute pain were written for 100 MME per day or more.

Table 3. Indicators for General Prescription Practices and Potential Inappropriate Practices for Opioid Analgesics According To Acute, Chronic, or Back Pain Diagnosis, Medicaid Enrollee Prescriptions By Gender, Marketscan 2010.

Prescriptions for Male Enrollees Prescriptions for Female Enrollees Total Prescriptions



Indicator N % N % N %
Indicators of General Prescription Practices
No. opioid Rx for acute paina 77,022 215,802 292,824
Days' supply for acute pain diagnosis
 ≤9 48,790 63.3% 157,958 73.2% 206,748 70.6%
 10–29 13,856 18.0% 31,089 14.4% 44,945 15.3%
 30–49 14,351 18.6% 26,722 12.4% 41,073 14.0%
 50–69 9 0.0% 25 0.0% 34 0.0%
 70–89 0 0.0% 1 0.0% 1 0.0%
 ≥90 16 0.0% 7 0.0% 23 0.0%
 Mean* 11.0 8.8 9.3
 Median 5.0 5.0 5.0
Average daily dose for acute pain diagnosis
 Unknown 56 0.1% 129 0.1% 185 0.1%
 <40 40,697 52.8% 119,933 55.6% 160,630 54.9%
 40–59 14,977 19.4% 42,752 19.8% 57,729 19.7%
 60–79 9,586 12.4% 24,333 11.3% 33,919 11.6%
 80–99 3,970 5.2% 9,514 4.4% 13,484 4.6%
 100–119 1,845 2.4% 6,433 3.0% 8,278 2.8%
Daily dose con't
 120–199 4,005 5.2% 9,236 4.3% 13,241 4.5%
 ≥200 1,886 2.4% 3,472 1.6% 5,358 1.8%
 Mean* 53.1 49.0 50.1
 Median 37.5 37.5 37.5
No. opioid Rx for other painb 188,408 430,052 618,460
Days' supply for other pain diagnosis
 ≤9 38,113 20.2% 116,055 27.0% 154,168 24.9%
 10–29 49,898 26.5% 115,207 26.8% 165,105 26.7%
 30–49 100,324 53.2% 198,711 46.2% 299,035 48.4%
 50–69 41 0.0% 42 0.0% 83 0.0%
 70–89 6 0.0% 9 0.0% 15 0.0%
 ≥90 26 0.0% 28 0.0% 54 0.0%
 Mean* 21.6 19.6 20.2
 Median 30.0 25.0 28.0
Average daily dose for other pain diagnosis
 Unknown 120 0.1% 247 0.1% 367 0.1%
 <40 88,833 47.1% 236,516 55.0% 325,349 52.6%
 40–59 35,482 18.8% 75,294 17.5% 110,776 17.9%
 60–79 25,554 13.6% 49,153 11.4% 74,707 12.1%
 80–99 11,921 6.3% 23,075 5.4% 34,996 5.7%
 100–119 1,705 0.9% 4,037 0.9% 5,742 0.9%
 120–199 15,364 8.2% 27,830 6.5% 43,194 7.0%
Daily dose con't
 ≥200 9,429 5.0% 13,900 3.2% 23,329 3.8%
 Mean* 62.2 52.6 55.5
 Median 40.0 33.3 37.5
No. opioid Rx for back painc 89,383 181,610 270,993
Days' supply for back pain diagnosis
 ≤9 16,357 18.3% 43,598 24.0% 59,955 22.1%
 10–29 22,887 25.6% 47,906 26.4% 70,793 26.1%
 30–49 50,109 56.1% 90,079 49.6% 140,188 51.7%
 50–69 20 0.0% 13 0.0% 33 0.0%
 70–89 3 0.0% 1 0.0% 4 0.0%
 >90 7 0.0% 13 0.0% 20 0.0%
 Mean* 22.3 20.5 21.1
 Median 30.0 28.0 30.0
Average daily dose for back pain diagnosis
 Unknown 71 0.1% 107 0.1% 178 0.1%
 <40 41,762 46.7% 99,665 54.9% 141,427 52.2%
 40–59 17,500 19.6% 33,078 18.2% 50,578 18.7%
 60–79 12,132 13.6% 20,920 11.5% 33,052 12.2%
 80–99 5,538 6.2% 9,277 5.1% 14,815 5.5%
 100–119 707 0.8% 1,550 0.9% 2,257 0.8%
 120–199 7,256 8.1% 11,409 6.3% 18,665 6.9%
 ≥200 4,417 4.9% 5,604 3.1% 10,021 3.7%
 Mean* 61.8 51.8 55.1
 Median 40.0 33.3 37.5
Indicators of Potential Inappropriate Prescription Practices
 Any opioid overlap*d 228,845 34.3% 448,795 28.1% 677,640 29.9%
 Any opioid/benzodiazepine overlap*e 188,581 28.3% 511,285 32.0% 699,866 30.9%
High daily dose*f 90,016 13.5% 166,100 10.4% 256,116 11.3%
 Long acting/extended release opioidsg for acute pain conditions 4,649 5.7% 6,929 5.3% 11,578 5.4%
 LA/ER opioids prescribed for opioid naive persons 2,885 3.5% 4,395 3.4% 7,280 3.4%
 Long acting/extended release opioids that overlap with other LA/ER opioids 20,873 25.4% 31,441 24.1% 52,314 24.6%
*

Difference between males and females is significant p<.01

a

Acute pain was determined by whether the enrollee had a diagnosis of a disease or an injury or a surgical procedure that could cause acute pain. Diagnoses for acutely painful diseases and injuries and their ICD9-CM codes were: sickle cell with crisis (282.62); acute pain (338.11,338.12,338.18,338.19); dental abscess with sinus (522.5); dental abscess without sinus (522.7); gallstone (574); acute pancreatitis (577); kidney stone (592); pathological fracture (733.1); acute injury (800–904.9); other acute injury (910–959.9); external cause of injury codes (E800–E849.9; E880–E909.9; E916–E928.9; E953–E968.9; E970–E976.9; E983–E999.9). After the exclusion of minor procedures, surgical procedures included: excision of breast tissue; other major skin, breast, or musculoskeletal surgeries; other major respiratory cardiovascular, hemic and lymphatic, digestive, eye/ocular, ear/auditory or urinary procedures; repair of inguinal hernia procedures; major male genital procedures; dilation and currettage; major female genital procedures; decompression, carpal tunnel surgery; major endocrine system, and nervous system procedures; cataract removal; other major surgery procedures; cesarean section deliveries; major maternity procedures and related care; and dental, or major restorative surgery.

b

Diagnoses likely to be associated with chronic pain and their ICD9-CM codes included: chronic pain (338.21, 338.22, 338.28, 338.29, 338.4); migraine headache (346.0–346.9); tension headache (307.81); arthritis or joint pain (710.0–719.9); dorsopathies, or back pain (720.0–724.9); and arthritis or joint pain (725.0–729.9)

c

Back pain could be either acute or chronic. ICD9-CM diagnostic codes included 307.89, 721.2, 721.3, 724.2, 724.4, 724.5, 724.6, 724.7, 724.8, 846, 846.0, 846.1, 846.2, 846.3, 846.8, 846.9, 847, 847.2, 847.4, and 847.9.

d

Days' supply of one opioid prescription overlaps with another opioid prescription for at least 7 days for a given enrollee. The numbers of opioid prescriptions obtained by males and females are 666,265 and 1,598,752 respectively.

e

Days' supply of one opioid prescription overlaps with one or more benzodiazepine prescription for at least 7 days for a given enrollee.

f

≥100 morphine milligram equivalents (MMEs).

g

The numbers of total LA/ER opioids prescriptions were 82,199 and 130,731 for males and females respectively and percentages are based on those numbers.

For other pain, nearly half (48.4%) of the prescriptions were for 30 or more days. The mean daily dose for opioid prescriptions for other pain was higher for males (62 MME) than females (52.6 MME). While other pain conditions were treated for longer periods of time than acute pain conditions, the average dosage employed was comparable to that used for acute pain. For back pain, over half of the prescriptions were for 30 days or more. The mean daily dose for back pain was similar to that for other pain at 61.8 MME for males and 51.8 MME for females.

As for indicators of potential inappropriate prescribing, roughly 30% of opioid prescriptions overlapped with other opioid prescriptions, and 30.9% overlapped with a benzodiazepine prescription. Among LA/ER opioid prescriptions, a quarter overlapped with other LA/ER opioid prescriptions; 5.4% were written for acute pain conditions; and 3.4% were obtained by opioid-naïve patients.

Discussion

In 2010, more than 2.2 million opioid prescriptions were written for 359,368 adults without cancer diagnoses who were continuously enrolled in Medicaid programs in 12 states. Most patients obtained a single opioid prescription without also obtaining prescriptions for benzodiazepines or muscle relaxants. Nearly 60% of recipients had opioid prescriptions written for less than 30 days. However, signs of potential opioid misuse by patients or inappropriate prescribing by providers were evident among this study population. One quarter of patients had one indicator of potential misuse of opioids and 16% (or over approximately 57,000 patients) had two or more indicators of potential inappropriate use. These numbers are substantially higher than a recent analysis examining similar indicators among privately insured patients, where 19.2% of patients had one indicator of potential inappropriate misuse or prescribing practices and 5.8% had two or more indictors.14 In general, this is consistent with findings from previous studies examining opioid use among Medicaid patients compared with privately insured patients.7

It is important to note that most of the prescriptions for opioids appeared to fall within the range of appropriate use and standard care. Nevertheless, there is cause for concern. The opioid misuse indicators examined in this study have been linked to opioid-related adverse health outcomes in other studies. Increased numbers of opioid prescriptions, overlapping or early refill prescriptions, dose escalation, and greater days' supply of opioids have all been associated with increased risk of clinically recognized abuse.23,24 Higher daily dose has been associated with misuse, emergency department visits, and overdoses.2426 Acute pain is not an indication for an LA/ER opioid, and such use is considered inappropriate by clinical guidelines19 and yet in this study, 21.8% of those who received a LA/ER opioid, did so for acute pain. Further, most LA/ER opioids carry warnings against initiation among opioid-naïve patients.

The New York City Department of Health and Mental Hygiene has recommended no more than a seven-day supply of opioids for acute pain,28 however, in this study 15.3% of opioid prescriptions for acute pain were prescribed for 10–29 days, and 14% were for 30 or more days. For severe, acute low back pain specifically, the American College of Occupational and Environmental Medicine practice guidelines only recommend opioids on a limited basis, with treatment to last no more than two weeks.27 Opioids are not recommended to be used for long-term treatment of chronic back pain.29 In this study, over half (51.7%) of opioid prescriptions for back pain were written for 30–49 days, more than recommended by expert consensus.

While women make up 58% of the total Medicaid population, they were 74% of our study population. Our study is consistent with previous literature in finding that women constitute the majority of users of opioids both alone and in combination with benzodiazepines.15 We found that the mean number of opioid prescriptions differed by one script per year between female and male opioid recipients (6.0 and 7.1 respectively); however, the annual mean days' supply was much lower for women than men (96.4 and 133 respectively). Despite the fact that men are more likely to use prescription painkillers non-medically, to abuse opioids, and to die from drug overdoses involving opioids,30,31 the percentage increase in the number of recent deaths from prescription painkillers is greater among women.32 The prevalences of indicators of possible misuse in this study were only slightly lower among women in this Medicaid population.

Limitations

Our study has several limitations. The potential inappropriate indicators have been validated by their association with misuse or abuse in other studies. In some cases, of course, such behaviors represent appropriate care for patients not misusing drugs, e.g., overlapping prescriptions resulting from changes in dosage or in drug type as a result of some adverse effect, or use of short-acting opioids for break through pain in patients receiving long-acting or extended release opioids. Claims data were designed to support financial transactions rather than to capture clinical information, and as such may suffer some inherent flaws, however they remain an important source of health data.33 Pharmacy claims represent filled prescriptions reimbursed rather than actual drug consumption and do not capture prescriptions paid for with cash. Prescriber information was incomplete to the extent that analyses based on prescriber data would have severe limitations. Last, relying on ICD-9CM codes to determine the reason for a prescription is subject to error. Many conditions are painful but are not usually counted among common causes of pain. Type of pain might also have been misclassified. While these analyses are unable to determine whether patient or prescriber was the source of any potential prescribing or use problems, our analysis represents a comprehensive look at opioid use and potential inappropriate among Medicaid recipients in the largest fully-integrated commercial claims database in the United States, and they point to situations that warrant further investigation to determine causal factors.

While the majority of opioid prescriptions among this population might have been appropriate, a substantial number were prescribed in a manner that suggests inappropriate patient use or provider prescribing practice. Robust prescription opioid utilization review programs using integrated claims data, similar to our analyses, might reduce misuse and overdose risk, help improve quality of care, and reduce unnecessary health care costs.6,34 Such programs, combined with other systematic prevention strategies such as prescription drug monitoring programs, that track information on controlled substance prescriptions filled in a state, and use of opioid prescribing guidelines may assist providers to address improper opioid use, reduce the risk of adverse outcomes, and improve the appropriate prescribing of opioid medications.

Acknowledgments

Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

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