How Can I Start Getting My Opoids Prescribed Again
J Am Board Fam Med. Author manuscript; available in PMC 2013 Dec seven.
Published in last edited form as:
PMCID: PMC3855548
NIHMSID: NIHMS529091
Opioids for Back Pain Patients: Master Care Prescribing Patterns and Use of Services
Richard A. Deyo, Doctor, MPH, David H.M Smith, RPh, PhD, Eric S. Johnson, PhD, Marilee Donovan, RN, PhD, Carrie J. Tillotson, MPH, Xiuhai Yang, MS, Amanda Petrik, MS, and Steven K. Dobscha, MD
Abstruse
Background
Opioid prescribing for not-cancer pain has increased dramatically. We examined whether the prevalence of unhealthy lifestyles, psychological distress, healthcare utilization, and co-prescribing of sedative-hypnotics increased with increasing duration of prescription opioid employ.
Methods
We analyzed electronic information for 6 months earlier and after an index visit for dorsum pain in a large managed intendance plan. Use of opioids was characterized as "none", "acute" (≤ ninety days), "episodic", or "long-term." Associations with lifestyle factors, psychological distress, and utilization were adjusted for demographics and comorbidity.
Results
There were 26,014 eligible patients. Amid these, 61% received a form of opioid therapy, and xix% were long-term users. Psychological distress, unhealthy lifestyles, and utilization were associated in stepwise way with elapsing of opioid prescribing, non just with chronic utilise. Amid long-term opioid users, 59% received but brusque-acting drugs; 39% received both long and brusk acting drugs; 44% received a sedative-hypnotic. Of those with any opioid use, 36% had an emergency visit.
Conclusions
Opioid prescribing was common amidst patients with back pain. The prevalence of psychological distress, unhealthy lifestyles, and healthcare utilization increased incrementally with duration of opioid use. Despite safety concerns, co-prescribing of sedative-hypnotics was common. These data may aid in predicting long-term opioid utilise and improving the safety of opioid prescribing.
Chronic pain is a common complaint in master intendance. Over 2% of U.South. adults written report regular utilise of prescription opioids, and more than than half of these have chronic back pain.1 Surveys suggest that many such patients have persistent loftier levels of hurting and poor quality of life.ii Despite uncertainties about long-term efficacy and condom for chronic back pain, prescription opioid apply has increased rapidly, and complications related to overdoses and diversion have risen in parallel.iii–11
Patients with anxiety or low are more than likely than others to take opioids prescribed, yet have less analgesic benefit, are more prone to medication misuse, and are more than likely to use psychoactive drugs.12–14 Whether psychological distress is associated with astute opioid use, as opposed to chronic use, is unclear. A few studies have suggested that lifestyle factors such equally smoking and obesity are predictors of opioid misuse or early opioid prescriptions for pain, but these associations have non been well-studied in routine clinical care [Tetrault, Stover & Franklin]. Certain opioid prescribing patterns enhance important rubber concerns. For example, co-prescribing of opioids and benzodiazepines is recognized as a run a risk for unintentional overdose and death [Dunn, Franklin], but the frequency of such prescribing in routine care is not well characterized.
Given these uncertainties, it is important to meliorate sympathise which patients are virtually likely to receive opioids and whether certain patient characteristics are associated with long-term utilise. There is besides a need for improve data on related health services consumption and patient safe concerns (such as co-prescription of sedative-hypnotics),.
We used electronic health records for main care patients with chronic back hurting in a large managed care plan to examine patterns of opioid use.. Our goals were to clarify the nature of associations between mental wellness, lifestyle, and opioid prescribing, and to place potential strategies for improving the efficiency and rubber of opioid prescribing in main intendance. Our study aims were:
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To examine patient and prescribing characteristics associated with long-term opioid utilise. We hypothesized that diagnoses of substance corruption, depression, and feet would be associated with college rates of long-term opioid use. We likewise hypothesized that lifestyle factors (obesity, smoking) and greater comorbidity would be associated with greater opioid use. We further sought to determine whether these characteristics were associated only with long term opioid use or also with acute use, mayhap in a stepwise incremental fashion.
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To examine the prevalence of a patient prophylactic concern: co-prescription of sedative-hypnotics and opioids. We hypothesized that co-prescription of sedative-hypnotics may be common, despite cautions against this practice.
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To describe apply of other health care services that may exist associated with opioid use, including emergency room apply and other clinic visits. We hypothesized that among all patients with dorsum pain, emergency room utilise and clinic visit frequency would be higher among opioid users than not-users.
Such analyses would assist to clarify the likelihood of long-opioid use amid certain patients; make up one's mind if risky co-prescribing is an important trouble; and suggest strategies for providing more efficient care for an often challenging patient group.
METHODS
Setting
We conducted the report in the Kaiser Permanente Northwest (KPNW) wellness care system in Portland, Oregon. KPNW is a federally qualified, not-for-turn a profit HMO serving more than 470,000 members in northwest Oregon and southwest Washington. Members are demographically representative of the coverage area and represent nigh 17% of the area'southward population.
KPNW maintains one hospital and 26 outpatient medical offices. An integrated, group-model delivery system provides the unabridged scope of treat members. Each health plan member receives a unique wellness record number upon enrollment, which continues fifty-fifty through gaps in membership. Contacts with the medical care organization and referrals to outside services are recorded in an electronic medical record. This computerized process stores patient demographics, medical history, and visit summaries. KPNW'due south data systems are accessible for research purposes; all members are informed of this as part of their membership agreement, and can elect to be excluded from all or some research studies. This study was approved by the Institutional Review Boards at the Kaiser Permanente Middle for Wellness Research and at Oregon Wellness and Science University.
KPNW provides prescriptions at a reduced price, and prescriptions are prepaid for a meaning proportion of the population. The automated outpatient pharmacy organisation records all prescriptions dispensed. Based on a membership survey, an estimated xc percent of prescriptions are filled at a program pharmacy, including those for members without a prepaid drug do good. For our study, we required that patients take i twelvemonth of continuous membership and drug coverage prior to the index visit. Considering of that coverage requirement, written report patients had financial and logistical incentives to use KPNW pharmacies for their prescriptions. While KPNW has a formulary of recommended medications, physicians may prescribe any marketed drug.
Health plan members are encouraged to choose a personal physician and return to that physician for medical care. Family practitioners, internists, and pediatricians provide primary care and maintain continuity of treatment.
Patients
Nosotros studied adult ambulatory patients aged 18 and over. To select patients with back pain, we chose every bit an index visit the beginning visit in 2004 with any one of 32 ICD-ix-CM diagnoses associated with low dorsum pain,15 and used electronic chemist's and medical tape data for i year earlier and vi months subsequently an index visit. To focus on patients with musculoskeletal back hurting, we excluded patients with cancer, spinal infections, or open up fractures. The ICD-9 codes used for inclusion and exclusion are listed in Table 1. Including all patients with even a single index visit for back pain implies a mix of patients with acute, subacute, and chronic pain.
Table one
ICD-nine-CM diagnosis and procedure codes use to select or exclude patients
| Dorsum Pain inclusion codes | |
| 721.iii | Lumbosacral spondylosis without myelopathy |
| 721.42 | Spondylogenic compression of lumbar spinal string |
| 722.x | Deportation of lumbar intervertebral disc without myelopathy |
| 722.32 | Schmorl'south nodes, lumbar |
| 722.52 | Degeneration of lumbar or lumbosacral intervertebral disc |
| 722.73 | Intervertebral disc disorder with myelopathy, lumbar |
| 722.83 | Postlaminectomy syndrome, lumbar |
| 722.93 | Other & unspecified disc disorder, lumbar |
| 724.02 | Spinal stenosis, lumbar |
| 724.ii | Lumbago; depression dorsum pain |
| 724.3 | Sciatica |
| 724.5 | Backache, unspecified |
| 724.6 | Disorders of sacrum |
| 738.4 | Caused spondylolisthesis |
| 739.iii, 739.4 | Somatic dysfunction, lumbar region or sacral region |
| 756.11 | Spondylolysis, lumbosacral region |
| 756.12 | Spondylolisthesis |
| 805.4, 805.half-dozen | Vertebral fracture without spinal cord injury, closed, lumbar, sacrum, or coccyx |
| 846.0–846.9 | Sprains and strains of sacroiliac region |
| 847.2, 847.3 | Sprains and strains, lumbar or sacrum |
| Exclusion codes | |
| 140–239.9 | Neoplasms |
| 324.one | Intraspinal abcess |
| 730–730.99 | Osteomyelitis |
| 805.i, 805.3, 805.five, 805.7, 805.ix | Open vertebral fractures |
| 03.2–03.29 | Chordotomy (procedure code) |
Defining Episodes of opioid employ
For this purpose, we considered electronic pharmacy and medical record data for 6 months earlier and subsequently an index visit (i.e., including data from 2003 and 2005). This time interval was used in the recognition that for many patients, the index visit in 2004 would non be their first back pain visit, as a relapsing course is common for low back pain. We sought to place opioid use that might precede or follow the index visit by a relatively short interval.
Using definitions from Von Korff et al,16 opioid use was defined every bit "none", "acute" (≤ ninety days), "episodic", or "long-term" (≥120 days or > 90 days with 10 or more fills). Episodic use was for greater than 90 days, but less than 120 days, and with fewer than x fills of opioid medication. This was intended to place opioid prescribing that was intermediate between acute and chronic employ.
This classification considered cumulative opioid apply during the year of observation, even though it might be discontinuous. Opioid use might correspond a unmarried or multiple opioid preparations (eg both a long-acting drug and a short-acting drug for "breakthrough" pain).
We considered use of the opioids listed in Tabular array 1, and classified them as long or short acting as in the table. We also used the morphine equivalent calculations shown in the table, which is slightly adapted from Von Korff and colleagues.16
Mental Health Diagnoses
We searched medical records for i year prior to the index visit for any coded ICD-9-CM diagnoses for depression (296.2, 296.3, 300.4, 309.0, 309.one, 311), anxiety (300.0–300.09), post-traumatic stress disorder (309.81), or substance abuse (303.xx, 304.twenty, 305.xx). The diagnoses were non based on standardized measures, simply on clinicians' judgments.
Measures of patient comorbidity and health care utilise
We recorded patient demographics, comorbidity score, smoking, and torso-mass index (BMI). We also measured aspects of wellness care utilization, including co-prescription of sedative-hypnotics, emergency room (ER) visits, other dispensary visits, and hospitalizations for the 1 year surrounding the index engagement (6 months earlier and 6 months after).
Sedative-hypnotic drugs were those identified using the Medi-Span Generic Product Identifier (GPI)17 or the American Hospital Formulary Service (AHFS) Drug Data compendium.18 These included benzodiazepines, barbiturates, so-called "z-drugs" (zolpidem, eszopiclone, zaleplon), carisoprodol, and less frequently prescribed drugs (diphenhydramine, chloral hydrate, meprobamate, and others).
Comorbidity was measured using the RxRisk score, a pharmacy-based model designed to predict future health care costs based on patient age, sex, Medicare or Medicaid insurance coverage, and use of drugs closely linked to specific chronic weather condition (e.grand., biguanides, insulins, sulfonylureas for diabetes).19,20 A score is calculated from a regression model that weights each diagnosis co-ordinate to its ability to predict future costs. To calculate scores, we used records for the one-year menses prior to the alphabetize visit. RxRisk was adult in a managed care arrangement with electronic records very like to KPNW. For adults, the RxRisk calculation excludes analgesics, because they are prescribed with as well much discretion to be appropriate for a payment adjustment model.19 In addition, nosotros considered number of hospitalizations in the by year as a crude marker of illness burden.
Analysis
Because we hypothesized that certain lifestyle and mental health conditions would increase as duration of opioid utilise increased, we used the Cochrane-Armitage test for trend to compare proportions of patient characteristics, diagnoses, health care utilization, and prescription patterns across ordered categories of opioid employ. This approach tests for an increasing or decreasing trend in patient characteristics and outcomes beyond ordered groups, as opposed to testing for whatsoever differences in proportions.
For continuous information, we used the Kruskall-Wallis nonparametric rank-sum test or univariable generalized linear models where appropriate. Multivariate analyses of dichotomous outcomes were conducted using logistic regression. For clinic visits, Poisson regression was used due to the non-normal distribution. Each model adjusted for patient age, sex, and comorbidity score. Depending on the analysis and study question, some models were also adapted for use of sedative-hypnotics, number of hospitalizations, morphine dose at last dispensing before the alphabetize visit, and type of opioid (long- or short-acting). Analyses were conducted using SAS version ix.two (SAS Institute, Cary, NC), and all comparisons utilized a two-tailed p<.05 to define statistical significance.
RESULTS
Subjects and diagnoses
There were 26,014 patients with a diagnosis of low dorsum pain who met our eligibility criteria. Of these, 15,830 (61%) received at to the lowest degree 1 opioid prescription in the year surrounding the index visit. Of those receiving opioids, 4,883 (18.eight% of all patients with back hurting) had an episode of long-term opioid use during that twelvemonth.
Among all patients with back pain, mean historic period was 50.3 years (SD 16.6), and 56.five% were women. Amidst those with a recorded race (31% were missing), 89.three% were White, 3.ii % Black, 2.5% Asian, and 1.one% American Indian or Alaska Native; 4% cocky-reported other races. Amid those reporting ethnicity (48% missing), iv.6% were Hispanic.
Nearly patients received not-specific diagnoses such as "low back pain", or "sprains and strains" (78%). Another 12% had herniated discs, sciatica, degenerative discs, or spinal stenosis. The residue received a variety of diagnoses (e.g. spondylolisthesis, airtight vertebral fractures).
The about frequently prescribed opioids were hydrocodone with acetaminophen; oxycodone with acetaminophen; acetaminophen with codeine; oxycodone HCl, and morphine sulfate. These 5 preparations accounted for 92% of prescriptions.
Patient characteristics associated with opioid utilise
Tabular array ii divides the patients with back hurting into iv categories of opioid use: none, astute, episodic, or chronic. The table represents each patient only once, according to his or her longest episode of opioid use. Mean patient age rose with increasing duration of opioid use, as did the proportion of women. The comorbidity score also increased with increasing elapsing of opioid use (all p<0.001). Obesity and smoking were likewise associated with longer opioid use. Among long term opioid users, 52.6% were electric current or recent smokers, and fifty.0% had a Trunk Mass Index (BMI) ≥30 (p<0.001).
Table two
Classification of Opioid Medications and Morphine Equivalent Conversion Factors per Milligram of Opioid*
| Major Group | Blazon of Opioid | Morphine Equivalent Conversion Factor/mg of Opioid |
|---|---|---|
| Curt –acting, non-Schedule II | Propoxyphene (with or without aspirin/acetaminophen/ibuprofen) | 0.23 |
| Codeine+(acetaminophen, ibuprofen, or aspirin) | 0.fifteen | |
| Hydrocodone+(acetaminophen, ibuprofen, aspirin, or homatropine) | ane.00 | |
| Tramadol with or without aspirin | 0.ten | |
| Butalbital and codeine (with or without aspirin, ibuprofen, acetaminophen) | 0.fifteen | |
| Dihydrocodeine (with or without aspirin, ibuprofen, acetaminophen) | 0.25 | |
| Pentazocine (with or without aspirin, ibuprofen, acetaminophen) | 0.37 | |
| Short-interim, Schedule Two | Morphine sulfate | one.00 |
| Codeine sulfate | 0.15 | |
| Oxycodone (with or without aspirin, ibuprofen, acetaminophen) | one.50 | |
| Hydromorphone | 4.00 | |
| Meperidine hydrochloride | 0.10 | |
| Fentanyl citrate transmucosal† | 0.125 | |
| Oxymorphone | 3.00 | |
| Long-interim, Schedule II | Morphine sulfate sustained release | 1.00 |
| Fentanyl transdermal‡ | 2.40 | |
| Levorphanol tartrate | eleven.0 | |
| Oxycodone HCL controlled release | ane.50 | |
| Methadone | 3.00 |
Mental Wellness Diagnoses
Diagnoses of depression, anxiety, post-traumatic stress disorder (PTSD), and substance corruption increased in a monotonic trend across categories of increasing duration of opioid utilize (p<0.001, Effigy 1 and Table ii). Amid long-term opioid users, 31% had a diagnosis of depression, and 49% had at to the lowest degree one of these four mental health diagnoses. Nonetheless, even patients with acute opioid apply had a college prevalence of depression than patients who had back pain with no opioid utilize (17.4% vs. 12.2%). This was true for each of the mental health diagnoses.
Graphic presentation of proportions of patients with diagnoses of depression, any of 4 mental health diagnoses, or sedative hypnotic use, as a office of elapsing of opioid use
All of the associations betwixt mental health diagnoses and elapsing of opioid employ remained statistically significant after adjusting for patient historic period, sex, comorbidity, hospitalizations, and (in some cases) sedative-hypnotic use, in logistic regression models (Table 3). For depression and substance corruption, the 2 virtually common of these diagnoses, the odds ratios showed a monotonic pattern of association with duration of opioid use.
Tabular array 3
Use of long and curt-acting opioids by duration of opioid utilise
| Acute opioid utilise | Episodic opioid use | Chronic opioid employ | |
|---|---|---|---|
| Short-acting opioid only (column %) | 98.3 | 85.2 | 59.4 |
| Long-interim opioid merely (column %) | 0.ane | 0.seven | 1.iii |
| Both long and short-interim opioid (column %) | 1.6 | 14.ane | 39.3 |
Health care apply, co-prescribing of sedative hypnotics
Greater allaying-hypnotic use was associated with longer opioid utilize in a stepwise style, ranging from 10% amid non-opioid users to 44.four% among chronic opioid users (Effigy i, Table four). These stepwise associations persisted in multivariate models adapted for age, sexual activity, comorbidity, and number of hospitalizations. For case, the odds ratio for sedative-hypnotic use was 4.0 (95% CI: 3.65–iv.39) for chronic opioid utilise as compared to none (Table iii). Benzodiazepines were the well-nigh commonly prescribed sedative-hypnotics: diazepam, lorazepam, alprazolam, clonazepam, oxazepam, and temazepam accounted for 80% of prescriptions. With the add-on of hydroxyzine and zolpidem, these drugs accounted for 94% of sedative-hypnotic prescriptions.
Table 4
Kaiser NW patient demographic characteristics and comorbid conditions according to duration of opioid use, 2004.†
| Characteristic | No opioids | Acute* opioids simply | Episodic* opioid use | Chronic* opioid use | p-value |
|---|---|---|---|---|---|
| n of subjects | 10,184 | x,543 | 404 | 4,883 | - |
| Mean age, yearsa | 49.1 | 49.1 | 56.6 | 54.vi | <0.001 |
| Number (%) femaleb | 5,529 (54.three) | 5,847 (55.five) | 240 (59.four) | 3,071 (62.9) | <0.001 |
| BMI, number (%) 30 or greaterb | three,490 (36.8) | four,525 (45.4) | 185 (47.2) | 2,403 (50.0) | <0.001 |
| Number (%) Electric current smoker or recentb | 3,538 (37.iv) | 4,620 (45.9) | 176 (46.iii) | 2,476 (52.6) | <0.001 |
| Number (%) with diagnosis of depression in previous twelvemonthb | 1,247 (12.2) | i,839 (17.4) | 95 (23.5) | i,526 (31.3) | <0.001 |
| Number (%) with diagnosis of anxiety in previous yearb | 449 (4.four) | 594 (5.6) | 25 (half dozen.ii) | 573 (11.7) | <0.001 |
| Number (%) with diagnosis of PTSD in previous yearb | 54 (0.five) | 102 (one.0) | 1 (0.3) | 116 (2.4) | <0.001 |
| Number (%) with diagnosis of substance abuse in previous twelvemonthb | 946 (nine.3) | one,467 (13.9) | 60 (14.9) | one,233 (25.three) | <0.001 |
| Number (%) with whatever of the iv mental health diagnosesb | 2,185 (21.5) | 3,108 (29.v) | 146 (36.1) | 2,405 (49.3) | <0.001 |
| Median Comorbidity score (RxRisk)c | one,276 | 1,580 | ii,464 | 3,366 | <0.001 |
Well-nigh sixty percentage of long-term opioid users received only brusk-acting opioids. Among the 40% who received long-acting opioids, nearly all received both long and curt-acting opioids (Table 3). Among those with acute opioid utilize, 98% received only short-acting drugs.
Simply over 36% of those with any opioid use had an Emergency Room (ER) visit during the study year, and about a third of these were associated with a back pain diagnosis (Table iv). An opioid prescription was filled within 5 days post-obit 56% of ER visits. These percentages were similar amidst patients with any elapsing of opioid use. Emergency room utilize remained associated with opioid utilise afterward adjustment for historic period, sexual practice, comorbidity, number of hospitalizations, and sedative hypnotic apply. In this instance, odds ratios for any duration of opioid use were similar and clustered around 2.0 (e.g., OR for chronic opioid utilise compared to no opioid use was ane.85, 95% CI 1.69, 2.02, p<0.01).
These patients with back hurting made heavy use of other clinic services. The median number of all dispensary visits in the yr surrounding the index date was 18 for patients receiving chronic opioids, eight for those not on opioids, and intermediate for those with acute or episodic opioid use (Table 4). In a Poisson regression, the trend for increasing clinic use remained associated with greater elapsing of opioid use. For example, even afterward adjustment for age, sexual practice, comorbidity, and number of hospitalizations, patients receiving long term opioids had a 41% college rate of clinic visits than patients with no opioid use (RR: ane.41, 95% CI: 1.37,1.45). The number of different opioid prescribers also increased with increasing duration of opioid use (Table 4). Virtually patients were non seen in a specialty pain clinic: merely 12% of fifty-fifty chronic opioid users had such a visit in the twelvemonth surrounding the index visit.
Although only three.6% of non opioid users were hospitalized during this time, over 20% of episodic or long-term opioid users were hospitalized (Table four). In logistic regression models, the high take a chance of hospitalization among episodic and chronic opioid users persisted even later on adjustment for age, gender, comorbidity score, and utilize of allaying-hypnotics. The odds ratio among those with acute utilise of opioids was 2.89 (95% CI: 2.55, 3.28), for episodic apply, iv.70 (95% CI 3.57, 6.19) and for chronic utilise 3.90 (95% CI 3.twoscore, 4.47).
DISCUSSION
Opioid prescribing was common among patients with back pain, and near 20% received long-term opioids. Increasing duration of opioid use was associated with increasing historic period and comorbidity, suggesting that some opioid prescribing was related to weather other than back hurting, or in addition to dorsum pain. Our data suggest that patients with dorsum pain have a substantial comorbidity load that is associated with the duration of opioid use. Using information from the development of the RxRisk score,19 we can guess that the hateful RxRisk score of our patients receiving chronic opioid therapy was similar to that of age and sex-matched peers with coronary or peripheral vascular affliction. The hateful score of our "no opioid" group is about the aforementioned equally that of patients with hypertension.
Increasing duration of opioid use was strongly associated with an increasing prevalence of mental health conditions (depression, anxiety, PTSD, or substance corruption): almost 50% of patients receiving long-term opioids had at least ane of these diagnoses. Similarly, health habits (obesity, smoking) were associated with duration of opioid use. The charge per unit of smoking among long-term opioid users was particularly loftier (over l%).
Our information confirm other observations regarding mental health and chronic opioid employ.eleven,12 However, our findings indicate that this association is non confined to long-term opioid users, in some threshold manner, just is establish in incremental stepwise mode at all durations of opioid use. The causality of these associations is unclear. In a study of sequential surveys, depression and anxiety disorders at the first survey predicted a higher likelihood of opioid utilise at the second survey iii years later.21 Thus information technology seems plausible that low leads to more opioid use, though it may also be truthful that opioid utilize results in greater depression, or that these conditions are both associated with some confounding factor. Etiology aside, these associations may be of involvement if they are just predictive of long-term opioid employ.
The wisdom of long-acting opioid use for chronic hurting remains controversial, but is based on theoretical considerations of more consequent pain control and more normal sleep patterns, if dosing is less frequent.22 These considerations led to a KPNW guideline recommending long-acting drug utilize for chronic pain, and this was used as a quality indicator during the report menstruum. Although utilise of long-acting opioids increased with duration of use, the frequent use (59%) of brusque-acting opioids among patients receiving long-term therapy supports Von Korff's concept of "defacto" long-term prescribing.fifteen That is, many patients may go long-term opioid users through clinical inertia, with clinicians continuing to refill prescriptions for short-acting opioids and not considering a deliberate determination for long term employ with informed consent and an opioid agreement. This is typically recommended later approximately three months of opioid prescribing.
We practice not know the extent to which clinicians cautioned patients against concurrent use of sedative-hypnotics and opiates, only their co-prescribing presents a potential prophylactic concern. Sedative-hypnotics in combination with opioids may increase the risk of over-sedation, overdose, and bloodshed. Furthermore, benzodiazepine use may predict subsequent use of opioids.23 The greater use of allaying-hypnotics with longer-term opioid utilize is contrary to the expectation based on expert recommendations, but has also been observed in other health care systems.14, 24, 25 Information technology is unclear if the loftier employ of allaying-hypnotics among long-term opioid users is a effect of pre-existing anxiety or sleep disorders, sleep disorders induced by opioids, or a manifestation of "addictive personalities." Some of these drugs -- specifically diazepam -- may take been used for muscle relaxant actions, suggesting an opportunity for clinician education.
Emergency room use was high among opioid users of whatsoever duration, though a minority of visits was associated with back pain. All the same, more than half the ER visits were associated with a prescription for an opioid medication. These patients were as well high utilizers of all clinic services. Some apply is likely associated with monitoring and refills of opioids, merely comorbidity and mental health concerns may likewise be important. As with clinic visits, the probability of hospitalization was associated with opioid use. Episodic or chronic use was associated with nearly iv-fold odds of beingness hospitalized, fifty-fifty after adjusting for age, gender, comorbidity, and sedative-hypnotic apply. A minority of patients were seen a specialty hurting dispensary, suggesting that most, fifty-fifty with chronic opioid use, are managed in master or emergency intendance. This was truthful even though access to pain clinic care was readily available in the form of pain direction group visits throughout the practice region.
The number of different opioid prescribers increased with increasing duration of opioid use. This may advise inadequate continuity of prescribing clinicians, just information technology may also be an inevitable consequence of long-term apply, and may partially reflect admission-to-care initiatives. For example, if a patient's prescribing clinician is unavailable when medication supplies run depression, the patient'south firsthand needs would exist met by other available clinicians (e.g. 'doctor of the 24-hour interval'). This situation is more likely to occur for patients with greater utilise of services.
Strengths and Limitations
Our data accept the advantages of representing a big population, many providers, and almost complete capture of healthcare utilization. However, there are important limitations. The study population is representative of the racial/ethnic mix in the Portland metropolitan area, but nether-represents minority populations. Thus, the results must be generalized with caution. Although every patient had back pain, we do not know the original indication for prescribing opioids. Clinical feel suggests that this may frequently be unclear for long-term opioid users, fifty-fifty when the full medical record is examined. Furthermore, many patients have multiple pain conditions, and information technology may exist misleading to single out one diagnosis.24 Nosotros cannot know the degree to which the associations we found are causal or the direction of whatever causation. However, the graded association of many variables with the duration of opioid utilize strengthens an argument for causal associations. These findings may exist useful for risk management even if they simply predict, rather than accept an etiologic office.
In the instance of diagnosed substance abuse, we cannot decide if these diagnoses are related to the prescribed opioids, other drugs, or both. To the extent that clinicians may use these diagnosis codes to indicate dependence on long-term prescribed opioids, they may exist overused and misleading. Most patients with more than a few weeks of opioid therapy will experience withdrawal symptoms if opioids are discontinued, unremarkably referred to as "dependence." This is distinctive from the compulsive and aberrant drug use of addiction, though this distinction is not always clearly made, and we cannot know from these data how the diagnosis of "substance abuse" is being used.
From pharmacy data alone, we cannot know if patients were receiving opioids from other sources, including illicit use. Many states have a statewide Prescription Monitoring Programme that collects dispensing data from all pharmacies and helps to place potential misuse, but such a system is not yet operational in Oregon. We did non appraise whether opioid doses were increasing or decreasing during an episode of employ. Our information are from 2004 and may not fully reverberate current practise, merely they establish a baseline against which future findings tin can exist measured. Conclusions: These data propose directions for improving the safety of opioid prescribing. The indications for combined opioid and sedative-hypnotic therapy should exist scrutinized. Such co-prescribing has already go a target for quality comeback in some main care practices.26 This business concern might exist part of an calendar for patient-dr. shared decision-making before embarking on long-term opioid use.
Redoubling efforts to ensure prescriber continuity for long-term opioid users may as well be important, to monitor the interaction of comorbid conditions and medications, and to reduce use of clinic, emergency department, and infirmary care. If many visits are motivated by patients seeking their side by side prescriptions—rather than clinical complaints— system interventions or alternative treatment approaches may be warranted. The reasons for loftier dispensary- and infirmary-utilization deserve closer investigation, to determine other strategies for mitigating such use. Because opioid prescribing appears to be increasing near chop-chop among patients with mental health and substance corruption diagnoses,11 main care physicians may demand to go more vigilant in screening for these conditions and addressing them prior to initiating opioid therapy.
Finally, these data suggest strategies for using electronic medical records to place patients at high risk for long-term opioid utilise, drug misuse, or drug complications, and to support clinical controlling. Such patterns may be unapparent from examining individual newspaper records. Others have begun to develop software to identify possible misuse or unsafe practices,27 and some decision aids are already being implemented in KPNW. This may stand for a modern version of the approach advocated past Fry, who recommended examining one's ain practice population to identify patterns of illness and care that could atomic number 82 to improvements in care.28
Table 5
Logistic regression models for the associations of mental health diagnoses with elapsing of prescription opioid utilise. Tabled figures are odds ratios (95% Conviction intervals).†
| Depression | Anxiety | PTSD* | Substance Abuse | Sedative- hypnotic use | |
|---|---|---|---|---|---|
| None (reference category) | 1.00 | ane.00 | 1.00 | 1.00 | 1.00 |
| Acute‡ | 1.fifteen (one.06,1.25) | 1.00 (0.88, ane.14) | 1.34 (0.96,1.88) | one.44 (one.32, 1.57) | ane.94 (i.79, 2.11) |
| Episodic‡ | 1.35 (1.05, i.74) | 0.95 (0.62, one.45) | 0.31 (0.04, 2.28) | 1.56 (1.17, 2.08) | 2.99 (2.38, 3.75) |
| Chronic‡ | 1.49 (ane.35, 1.64) | 1.44 (1.24, 1.66) | two.07 (1.44, 2.96) | two.77 (2.fifty, 3.08) | 4.00 (three.65, 4.39) |
Table 6
Health care use and complications according to elapsing of opioid use
| Type of wellness care apply | No opioids | Acute opioids but | Episodic opioid use | Chronic opioid utilize | p-value |
|---|---|---|---|---|---|
| northward of subjects | 10,184 | 10,543 | 404 | 4,883 | |
| Median opioid dose at last dispensing, morphine equivalenta | NA* | 30.0 mg | 20.0 mg | xxx.0 mg | <0.001 |
| Median number of opioid prescribersa | NA* | ane | 2 | 3 | <0.001 |
| Number (%) receiving allaying-hypnotic Rx in 6 mos earlier/after index visitb | 1,018 (x.0) | two,163 (20.5) | 134 (33.2) | two,166 (44.4) | <0.001 |
| Number (%) with ER visit vi mos. earlier/after index dateb | one,725 (16.9) | 3,627 (34.4) | 148 (36.6) | 1,948 (39.nine) | <0.001 |
| ER visit with back hurting diagnosis, number (%) of patients with any ER visitb | 405 (23.five) | 1,246 (34.4) | 50 (33.eight) | 535 (27.5) | 0.66 |
| Opioid prescription filled within v days of ER visit, % of patients with ER visitb | 1 (0.1) | 2,048 (56.5) | 85 (57.iv) | 1,091 (56.0) | <0.001 |
| Median number of clinic visits of any type in 6 mos before/after index datea | 8 | eleven | 17 | 18 | <0.001 |
| Number (%) with whatsoever pain clinic visit in 6 mos before/after index dateb | 99 (ane.0) | 227 (2.2) | 25 (half-dozen.2) | 585 (12.0) | <0.001 |
| Number (%) with whatever hospitalization in vi mos. earlier or later on index date, %b | 364 (iii.6) | ane,126 (10.7) | 87 (21.5) | one,012 (20.vii) | <0.001 |
Acknowledgments
This study was made possible with back up from the Oregon Clinical and Translational Research Found (OCTRI), grant number UL1 RR024140 from the National Center for Enquiry Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research.
Footnotes
The authors written report no relevant commercial conflicts of involvement
References
1. Hudson TJ, Edlund MJ, Steffick DE, Tripathi SP, Sullivan Physician. Epidemiology of regular prescribed opioid utilise: results from a national, population-based survey. J Hurting Sympt Mgmt. 2008;36:280–288. [PMC free article] [PubMed] [Google Scholar]
2. Eriksen J, Sjogren P, Bruera E, Ekholm O, Rasmussen NK. Critical bug on opioids in chronic non-cancer hurting: an epidemiological study. Pain. 2006;125:172–9. [PubMed] [Google Scholar]
3. Martell BA, O'Connor PG, Kerns RD, Becker WC, Morales KH, Kosten TR, Fiellin DA. Systematic review: opioid treatment for chronic back pain: prevalence, efficacy, and association with addiction. Ann Intern Med. 207(146):116–127. [PubMed] [Google Scholar]
four. Caudill-Slosberg MA, Schwartz LM, Woloshin S. Office visits and analgesic prescriptions for musculoskeletal pain in U.s.: 1980 vs. 2000. Pain. 2004;109:514–nine. [PubMed] [Google Scholar]
v. Martin BI, Deyo RA, Mirza SK, Turner JA, Comstock BA, Hollingworth Westward, Sullivan SD. Expenditures and health status amid adults with back and neck problems. JAMA. 2008;299:656–664. [PubMed] [Google Scholar]
6. Franklin GM, Mai J, Wickizer T, Turner JA, Fulton-Kehoe D, Grant L. Opioid dosing trends and mortality in Washington Country workers' compensation, 1996–2002. Am J Ind Med. 2005;48(2):91–nine. [PubMed] [Google Scholar]
vii. Luo X, Pietrobon R, Hey 50. Patterns and trends in opioid utilise among individuals with back pain in the United States. Spine. 2004;29:884–91. [PubMed] [Google Scholar]
viii. Zerzan JT, Morden NE, Soumerai S, et al. Trends and geographic variation of opiate medication utilise in land Medicaid fee-for-service programs, 1996 to 2002. Med Care. 2006;44:1005–10. [PubMed] [Google Scholar]
ix. Compton WM, Volkow ND. Major increases in opioid analgesic abuse in the Usa: concerns and strategies. Drug Alcohol Depend. 2006;81:103–7. [PubMed] [Google Scholar]
10. Paulozzi LJ, Budnitz DS, Xi Y. Increasing deaths from opioid analgesics in the Us. Pharmacoepidemiol Drug Saf. 2006;15:618–27. [PubMed] [Google Scholar]
xi. Edlund MJ, Martin BC, Devries A, Fan M-Y, Braden JB, Sullivan Doctor. Trends in use of opioids for chronic noncancer pain among individuals with mental wellness and substance use disorders: the TROUP Study. Clin J Pain. 2010;26:1–8. [PMC free article] [PubMed] [Google Scholar]
12. Edlund MJ, Steffick D, Hudson T, Harris KM, Sullivan M. Risk factors for clinically recognized opioid abuse and dependence among veterans using opioids for chronic non-cancer pain. Pain. 2007;129:355–62. [PubMed] [Google Scholar]
13. Wasan AD, Davar G, Jamison R. The association between negative touch on and opioid analgesia in patients with discogenic low back hurting. Pain. 2005;117:450–61. [PubMed] [Google Scholar]
xiv. Hermos JA, Young MM, Gagnon DR, Fiore LD. Characterizations of long-term oxycodone/acetaminophen prescriptions in veteran patients. Curvation Intern Med. 2004;164:2361–66. [PubMed] [Google Scholar]
xv. Cherkin DC, Deyo RA, Volinn E, Loeser JD. Employ of the International Classification of Diseases (ICD-9-CM) to place hospitalizations for mechanical low back issues in administrative databases. Spine. 1992;17:817–825. [PubMed] [Google Scholar]
xvi. Von Korff One thousand, Saunders 1000, Ray GT, et al. De facto long-term opioid therapy for noncancer pain. Clin J Pain. 2008;24:521–7. [PMC gratis article] [PubMed] [Google Scholar]
19. Fishman PA, Goodman MJ, Hornbrook MC, Meenan RT, Bachman DJ, O'Keefe Rosetti MC. Gamble adjustment using automated ambulatory pharmacy data: the RxRisk Model. Medical Care. 2003;41:84–99. [PubMed] [Google Scholar]
20. Farley FJ, Harley CR, Devine JW. A comparison of comorbidity measurements to predict healthcare expenditures. Am J Manag Intendance. 2006;12:110–117. [PubMed] [Google Scholar]
21. Sullivan MD, Edlund MJ, Zhang L, Unutzer J, Wells KB. Association between mental health disorders, trouble drug use, and regular prescription opioid use. Curvation Intern Med. 2006;166:2087–93. [PubMed] [Google Scholar]
22. Kalso E, Allan Fifty, Dobrogowski J, et al. Practise strong opioids have a office in the early direction of dorsum pain? Recommendations from a European expert panel. Electric current Med Res Opinion. 2005;21:1819–28. [PubMed] [Google Scholar]
23. Skurtveit South, Furu K, Bramness J, Selmer R, Tverdal A. Benzodiazepines predict utilize of opioids – a follow-up report of 17,074 men and women. Pain Medicine. 2010;11:805–814. [PubMed] [Google Scholar]
24. Morasco BJ, Duckart JP, Carr TP, Deyo RA, Dobscha SK. Clinical characteristics of veterans prescribed high doses of opioid medications for chronic not-cancer hurting. Hurting. 2010 Aug 27; [Epub ahead of print] [PMC free article] [PubMed] [Google Scholar]
25. Boudreau D, von Korff M, Rutter CM, et al. Trends in long-term opioid therapy for chronic non-cancer hurting. Pharmocoepidemiol Drug Saf. 2009;18:1166–75. [PMC free article] [PubMed] [Google Scholar]
26. Hooper South, Bruno R, Sharpe Thousand, Tahmindjis A. Alprazolam prescribing in Tasmania: a twofold intervention designed to reduce inappropriate prescribing and concomitant opiate prescription. Australasian Psych. 2009;17:300–305. [PubMed] [Google Scholar]
27. Parente ST, Kim SS, Finch Doc, Schloff LA, Rector TS, Seifeldin R, Haddox JD. Identifying controlled substance patterns of utilization requiring evaluation using administrative claims data. Am J Manag Care. 2004;10:783–790. [PubMed] [Google Scholar]
28. Fry J. Common Diseases: their nature, incidence, and care. four. Lancaster: MTP press Limited; 1985. pp. 9–10. [Google Scholar]
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3855548/
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