39
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Ultrarestrictive Opioid Prescription Protocol for Pain Management After Gynecologic and Abdominal Surgery

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Importance

          Opioids are routinely prescribed for postoperative home pain management for most patients in the United States, with limited evidence of the amount needed to be dispensed. Opioid-based treatment often adversely affects recovery. Prescribed opioids increase the risk of chronic opioid use, abuse, and diversion and contribute to the current opioid epidemic.

          Objective

          To evaluate whether after hospital discharge, postsurgical acute pain can be effectively managed with a markedly reduced number of opioid doses.

          Design, Setting, and Participants

          In this case-control cohort study, an ultrarestrictive opioid prescription protocol (UROPP) was designed and implemented from June 26, 2017, through June 30, 2018, at a single tertiary-care comprehensive cancer center. All patients undergoing gynecologic oncology surgery were included. Patients undergoing ambulatory or minimally invasive surgery (laparoscopic or robotic approach) were not prescribed opioids at discharge unless they required more than 5 doses of oral or intravenous opioids while in the hospital. Patients who underwent a laparotomy were provided a 3-day opioid pain medication supply at discharge.

          Main Outcomes and Measures

          Total number of opioid pain medications prescribed in the 60-day perioperative period, requests for opioid prescription refills, and postoperative pain scores and complications were evaluated. Factors associated with increased postoperative pain, preoperative and postoperative pain scores, inpatient status, prior opioid use, and all opioid prescriptions within the 60-day perioperative window were monitored among the case patients and compared with those from consecutive control patients treated at the center in the 12 months before the UROPP was implemented.

          Results

          Patient demographics and procedure characteristics were not statistically different between the 2 cohorts of women (605 cases: mean [SD] age, 56.3 [14.5] years; 626 controls: mean [SD] age, 55.5 [13.9] years). The mean (SD) number of opioid tablets given at discharge after a laparotomy was 43.6 (17.0) before implementation of the UROPP and 12.1 (8.9) after implementation ( P < .001). For patients who underwent laparoscopic or robotic surgery, the mean (SD) number of opioid tablets given at discharge was 38.4 (17.4) before implementation of the UROPP and 1.3 (3.7) after implementation ( P < .001). After ambulatory surgery, the mean (SD) number of opioid tablets given at discharge was 13.9 (16.6) before implementation of the UROPP and 0.2 (2.1) after implementation ( P < .001). The mean (SD) perioperative oral morphine equivalent dose was reduced to 64.3 (207.2) mg from 339.4 (674.4) mg the year prior for all opioid-naive patients ( P < .001). The significant reduction in the number of dispensed opioids was not associated with an increase the number of refill requests (104 patients [16.6%] in the pre-UROPP group vs 100 patients [16.5%] in the post-UROPP group; P = .99), the mean (SD) postoperative visit pain scores (1.1 [2.2] for the post-UROPP group vs 1.4 [2.3] for pre-UROPP group; P = .06), or the number of complications (29 cases [4.8%] in the post-UROPP group vs 42 cases [6.7%] in the pre-UROPP group; P = .15).

          Conclusions and Relevance

          Implementation of a UROPP was associated with a significant decrease in the overall amount of opioids prescribed to patients after gynecologic and abdominal surgery at the time of discharge for all patients, and for the entire perioperative time for opioid-naive patients without changes in pain scores, complications, or medication refill requests.

          Abstract

          This case-control cohort study compares the total number of opioid pain medications prescribed after gynecologic and abdominal surgery, the number of requests for opioid prescription refills, and postoperative pain scores and complications before and after implementation of an ultrarestrictive opioid prescription protocol.

          Key Points

          Question

          Can postoperative pain be appropriately managed after hospital discharge with minimal or no opioids in patients undergoing gynecologic and abdominal surgery?

          Findings

          In this case-control cohort study of 1231 patients undergoing gynecologic oncology surgery, implementation of an ultrarestrictive opioid prescription protocol was associated with a significant decrease in the number of opioids dispensed at discharge. Using the ultrarestrictive opioid prescription protocol to manage postoperative pain was also associated with a significant decrease in the number of opioids dispensed during the entire perioperative period for opioid-naive patients without changes in postoperative pain scores, complications, or increases in the number of refill requests.

          Meaning

          A reduction in the number of opioids dispensed for postoperative pain management is safe and attainable.

          Related collections

          Most cited references8

          • Record: found
          • Abstract: found
          • Article: not found

          Wide Variation and Excessive Dosage of Opioid Prescriptions for Common General Surgical Procedures.

          To examine opioid prescribing patterns after general surgery procedures and to estimate an ideal number of pills to prescribe.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Overdose Deaths Involving Opioids, Cocaine, and Psychostimulants — United States, 2015–2016

            During 1999‒2015, 568,699 persons died from drug overdoses in the United States.* Drug overdose deaths in the United States increased 11.4% from 2014 to 2015 resulting in 52,404 deaths in 2015, including 33,091 (63.1%) that involved an opioid. The largest rate increases from 2014 to 2015 occurred among deaths involving synthetic opioids other than methadone (synthetic opioids) (72.2%) ( 1 ). Because of demographic and geographic variations in overdose deaths involving different drugs ( 2 , 3 ), † CDC examined age-adjusted death rates for overdoses involving all opioids, opioid subcategories (i.e., prescription opioids, heroin, and synthetic opioids), § cocaine, and psychostimulants with abuse potential (psychostimulants) by demographics, urbanization levels, and in 31 states and the District of Columbia (DC). There were 63,632 drug overdose deaths in 2016; 42,249 (66.4%) involved an opioid. ¶ From 2015 to 2016, deaths increased across all drug categories examined. The largest overall rate increases occurred among deaths involving cocaine (52.4%) and synthetic opioids (100%), likely driven by illicitly manufactured fentanyl (IMF) ( 2 , 3 ). Increases were observed across demographics, urbanization levels, and states and DC. The opioid overdose epidemic in the United States continues to worsen. A multifaceted approach, with faster and more comprehensive surveillance, is needed to track emerging threats to prevent and respond to the overdose epidemic through naloxone availability, safe prescribing practices, harm-reduction services, linkage into treatment, and more collaboration between public health and public safety agencies. Drug overdose deaths were identified in the National Vital Statistics System multiple cause-of-death mortality files,** using the International Classification of Diseases, Tenth Revision (ICD-10), based on ICD-10 underlying cause-of-death codes X40–44 (unintentional), X60–64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Among deaths with drug overdose as the underlying cause, the type of drug or drug category is indicated by the following ICD-10 multiple cause-of-death codes: opioids (T40.0, T40.1, T40.2, T40.3, T40.4, or T40.6) †† ; natural/semisynthetic opioids (T40.2); methadone (T40.3); heroin (T40.1); synthetic opioids other than methadone (T40.4); cocaine (T40.5); and psychostimulants with abuse potential (T43.6). Some deaths involved more than one type of drug; these deaths were included in the rates for each drug category. Therefore, categories are not mutually exclusive. §§ Age-adjusted overdose death rates ¶¶ were examined for 2015 and 2016 for all opioids, opioid subcategories (prescription opioids [i.e., natural/semisynthetic opioids and methadone] ( 4 ), heroin, and synthetic opioids), cocaine, and psychostimulants in the United States and by age, sex, racial/ethnic group, urbanization level,*** and state. State-level analyses included 31 states and DC that met the following criteria: 1) ≥80% of drug overdose death certificates named at least one specific drug in 2015 and 2016; 2) change from 2015 to 2016 in the percentage of death certificates reporting at least one specific drug was 10 percentage points in drug specificity. ¶¶ Absolute rate change is the difference between 2015 and 2016 rates. Percent change is the absolute rate change divided by the 2015 rate, multiplied by 100. Nonoverlapping confidence intervals based on the gamma method were used if the number of deaths was 10 percentage points in drug specificity. ¶¶ Absolute rate change is the difference between 2015 and 2016 rates. Percent change is the absolute rate change divided by the 2015 rate, multiplied by 100. Nonoverlapping confidence intervals based on the gamma method were used if the number of deaths was 10 percentage points in drug specificity. ¶¶ Absolute rate change is the difference between 2015 and 2016 rates. Percent change is the absolute rate change divided by the 2015 rate, multiplied by 100. Nonoverlapping confidence intervals based on the gamma method were used if the number of deaths was <100 in 2015 or 2016, and z-tests were used if the number of deaths was ≥100 in both 2015 and 2016. *** Statistically significant at 0.05 level. ††† Cells with ≤9 deaths are not reported. Rates based on <20 deaths are not considered reliable and not reported. From 2015 to 2016, opioid-involved deaths increased in males and females and among persons aged ≥15 years, whites, blacks, Hispanics, and Asian/Pacific Islanders. The largest relative rate change occurred among blacks (56.1%) (Table 1). The largest absolute rate increases of opioid-involved deaths and deaths involving synthetic opioids occurred among males aged 25–44 years and persons aged 25–34 years. However, deaths involving synthetic opioids increased in every subgroup examined (Table 2). Rates involving prescription opioids, heroin, cocaine, and psychostimulants increased for both sexes, whites, blacks, and most age groups (Table 1) (Table 2) (Table 3). Counties in large central and fringe metro areas experienced the largest absolute increases in deaths involving prescription and synthetic opioids, heroin, and cocaine; micropolitan areas experienced the largest increase in rates involving psychostimulants (Table 1) (Table 2) (Table 3). Opioid death rates differed across the 31 states and DC, with synthetic opioids driving increases in many states. ¶¶¶ Although several states experienced increases across drug categories, in many, the changes from 2015 to 2016 were not significant. Rates of deaths involving synthetic opioids ranged from 0.9 to 30.3 per 100,000, with the largest rates and increases concentrated in eastern states. New Hampshire (30.3 per 100,000), West Virginia (26.3), and Massachusetts (23.5) had the highest synthetic opioid death rates. Twenty states and DC experienced increases in overdose death rates involving synthetic opioids, with 10 experiencing increases by ≥100%; the largest such increase (392.3%) occurred in DC, followed by Illinois (227.3%) and Maryland (206.9%) (Table 2). Many states with large increases in synthetic opioid death rates also had large increases in rates involving other drug categories (e.g., Maryland, Virginia, and DC), including any opioid, prescription opioids (Table 1), heroin (Table 2), and cocaine (Table 3). Thirteen states and DC experienced significant increases in heroin-involved death rates, whereas a significant decrease (56.9%) occurred in New Hampshire (Table 2). In 2016, the highest rates were in DC (17.3 per 100,000), West Virginia (14.9), and Ohio (13.5). The rates of prescription opioid–involved overdose deaths significantly increased in seven states and DC, with the highest rates in West Virginia (19.7), Maryland (13.1), Maine (12.5), and Utah (12.5) (Table 1). The highest cocaine-involved overdose death rates occurred in DC (13.5), Rhode Island (10.7), and Ohio (10.1), with 15 states and DC experiencing a significant increase from 2015 (Table 3). Significant increases in overdose death rates from heroin, prescription opioids, and cocaine occurred primarily in states in the eastern part of the country. Fourteen states experienced significant increases in psychostimulant-involved overdose death rates. The highest rates were in midwestern and western states: Nevada (7.5), New Mexico (7.1), and Oklahoma (7.1) (Table 3). Discussion Drug overdoses resulted in 632,331 deaths from 1999 to 2016 in the United States, with 351,630 being opioid overdose deaths.**** The epidemic has continued to worsen, with deaths increasing from 2015 to 2016 across all drug categories examined. Opioid-involved overdoses accounted for two thirds of drug overdose deaths, with increases across age and racial/ethnic groups, urbanization levels, and in numerous states. The findings highlight wide state and regional variations. Some states (e.g., New Hampshire, Ohio, and West Virginia,) experienced the highest overdose death rates across multiple drug categories, and others (primarily in the Midwest and West) recorded the highest rates of psychostimulant-involved overdose deaths. In New Hampshire, although heroin-involved death rates declined from 2015 to 2016, deaths involving synthetic opioids increased, as they did in most states. In addition, in some states (e.g., Maryland, Rhode Island, and West Virginia), 2016 rates of prescription opioid–involved deaths were higher than were those involving heroin. These data highlight the persistent and multifaceted nature of overdoses. The first wave of opioid overdose deaths began in the 1990s and included prescription opioid deaths. †††† A second wave, which began in 2010, was characterized by heroin deaths ( 5 ). A third wave started in 2013, with deaths involving highly potent synthetic opioids, particularly IMF and fentanyl analogs ( 2 , 3 , 6 ). §§§§ Synthetic opioid-involved deaths in 2016 accounted for 30.5% of all drug overdose deaths and 45.9% of all opioid-involved deaths, with a 100% increase in the rate of these deaths compared with 2015. Synthetic opioids propelled increases with 19,413 deaths (more than any drug examined), and previous findings underscore the contribution of IMF. In addition, IMF is now being mixed into counterfeit opioid and benzodiazepine pills, heroin, and cocaine, likely contributing to increases in overdose death rates involving other substances ( 3 , 7 , 8 ). The findings in this report are subject to at least five limitations. First, at autopsy, substances tested for, and circumstances under which tests are performed to determine which drugs are present, vary by time and jurisdiction, and improvements in toxicologic testing might account for some reported increases. Second, 17% (2015) and 15% (2016) of drug overdose death certificates did not include the specific types of drugs involved, and the percentage of drug overdose death certificates with at least one drug specified varied widely by state, ranging from 52.5% to 99.3% in 2016. This variation limits rate comparisons between states. Third, because heroin and morphine are metabolized similarly ( 9 ), some heroin deaths might have been misclassified as morphine deaths, resulting in underreporting of heroin deaths. Fourth, potential race misclassification might lead to underestimates for certain categories, primarily for American Indian/Alaska Natives and Asian/Pacific Islanders. ¶¶¶¶ Finally, state-specific analyses are restricted to 31 states and DC, limiting generalizability. The ongoing and worsening drug overdose epidemic requires immediate attention and action. Faster access to data collected is needed to understand emerging threats in local communities and to tailor response activities. CDC’s Enhanced State Opioid Overdose Surveillance program funds 32 states and DC for more timely and comprehensive nonfatal and fatal overdose data, including funding for improved comprehensive toxicologic testing to identify emerging drug threats in opioid-involved fatal overdoses.***** Syndromic surveillance data allow communities to identify overdoses quickly ( 10 ). The State Unintentional Drug Overdose Reporting System provides improved collection of toxicology data to identify specific drugs involved ( 6 ), information gathered from death scene investigations, and risk factors associated with fatal overdoses. Given the continuing threat from prescription opioids and the evolving threat from illicit opioids and other substances, a multifaceted prevention approach is required. Efforts to ensure safe prescribing practices ††††† are enhanced by access to nonopioid and nonpharmacologic treatments for pain. Other important efforts include increasing naloxone availability, expanding access to medication-assisted treatment, and maximizing the ability of health systems to link persons to treatment and harm reduction services ( 10 ). CDC supports many of these efforts through the Prevention for States and Data-Driven Prevention Initiatives, §§§§§ which together support opioid overdose prevention efforts in 42 states and DC. Collaboration with law enforcement, first responders, and harm reduction partners is also important to understanding local variations in drug supply and lethality and to implementing a multisectoral prevention approach. Summary What is already known about this topic? From 1999 to 2015, the drug overdose epidemic resulted in approximately 568,699 deaths. In 2015, 52,404 drug overdose deaths occurred; 63.1% (33,091) involved an opioid. From 2014 to 2015, the age-adjusted opioid-involved death rate increased by 15.6%; the rapid increase in deaths was driven in large part by synthetic opioids other than methadone (e.g., fentanyl). What is added by this report? In 2016, there were 63,632 drug overdose deaths in the United States. Opioids accounted for 66.4% (42,249) of deaths, with increases across age groups, racial/ethnic groups, urbanization levels, and multiple states. Age-adjusted death rates for overdoses involving synthetic opioids other than methadone doubled from 2015 to 2016, and death rates from prescription opioids, heroin, cocaine, and psychostimulants also increased. What are the implications for public health practice? There is an urgent need to implement a multifaceted, collaborative public health and public safety approach. Building on existing resources, more rapidly available and comprehensive surveillance data are needed to track emerging drug threats to guide public action to prevent and respond to the epidemic through increased naloxone availability, harm reduction services, linkage into treatment (including medication-assisted treatment), safe prescribing practices, and supporting law enforcement strategies to reduce the illicit drug supply.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Reduction in Opioid Prescribing Through Evidence-Based Prescribing Guidelines

              This interrupted time series analysis found significant changes in multiple dimensions of pain medication usage after the implementation of postoperative opioid prescription guidelines in a single hospital.
                Bookmark

                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                7 December 2018
                December 2018
                7 December 2018
                : 1
                : 8
                : e185452
                Affiliations
                [1 ]Department of Gynecologic Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, New York
                [2 ]Department of Pharmacy, Roswell Park Comprehensive Cancer Center, Buffalo, New York
                [3 ]University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Buffalo, New York
                [4 ]Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York
                [5 ]Department of Dermatology, Roswell Park Comprehensive Cancer Center, Buffalo, New York
                [6 ]Division of Pain Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, New York
                Author notes
                Article Information
                Accepted for Publication: October 9, 2018.
                Published: December 7, 2018. doi:10.1001/jamanetworkopen.2018.5452
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2018 Mark J et al. JAMA Network Open.
                Corresponding Author: Emese Zsiros, MD, PhD, Department of Gynecologic Oncology, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY 14263 ( emese.zsiros@ 123456roswellpark.org ).
                Author Contributions: Drs Mark and Zsiros had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Mark, Argentieri, Hutson, Mayor, Szender, Lele, Paragh, Frederick, Zsiros.
                Acquisition, analysis, or interpretation of data: Mark, Gutierrez, Morrell, Eng, Hutson, Mayor, Szender, Starbuck, Lynam, Blum, Akers, Paragh, Odunsi, de Leon-Casasola, Frederick, Zsiros.
                Drafting of the manuscript: Mark, Hutson, Szender, Blum, Odunsi, Zsiros.
                Critical revision of the manuscript for important intellectual content: Mark, Argentieri, Gutierrez, Morrell, Eng, Mayor, Szender, Starbuck, Lynam, Akers, Lele, Paragh, Odunsi, de Leon-Casasola, Frederick, Zsiros.
                Statistical analysis: Mark, Gutierrez, Morrell, Hutson, Szender, Zsiros.
                Obtained funding: Mark, Zsiros.
                Administrative, technical, or material support: Mark, Argentieri, Mayor, Szender, Starbuck, Lynam, Blum, Akers, de Leon-Casasola, Zsiros.
                Supervision: Eng, Mayor, Akers, Odunsi, Frederick, Zsiros.
                Conflict of Interest Disclosures: Dr Paragh reported receiving nonfinancial support from Buffalo BioLabs, LLC, research support from Cleveland Bio Labs Inc, and professional fees from ADC Therapeutics outside the submitted work. Dr Zsiros reported receiving personal fees and nonfinancial support from Iovance Biotherapeutics and research support from Merck & Co outside the submitted work. No other disclosures were reported.
                Funding/Support: This study was supported by Roswell Park Comprehensive Cancer Center with the National Cancer Institute (NCI) grant P30CA016056 and the Roswell Park Alliance Foundation and NCI training grant T32CA108456 in surgical oncology.
                Role of the Funder/Sponsor: Roswell Park Comprehensive Cancer Center with the National Cancer Institute grant P30CA016056 supported the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Roswell Park Alliance Foundation supported the design and conduct of the study; analysis and interpretation of the data; and preparation and review of the manuscript. National Cancer Institute training grant T32CA108456 in surgical oncology supported the collection, management, analysis, and interpretation of the data and the preparation and review of the manuscript.
                Meeting Presentation: This study was presented at the Annual Meeting of the Society of Gynecologic Oncology; March 24, 2018; New Orleans, Louisiana.
                Article
                zoi180233
                10.1001/jamanetworkopen.2018.5452
                6324564
                30646274
                2b079a4d-b05e-41b7-8455-5dcb71dcec62
                Copyright 2018 Mark J et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 17 July 2018
                : 9 October 2018
                : 9 October 2018
                Categories
                Research
                Original Investigation
                Featured
                Online Only
                Obstetrics and Gynecology

                Comments

                Comment on this article