Assessment of Selected Overdose Poisoning Indicators in Health Care Administrative Data in 4 States, 2012

Association of Early Opioid Withdrawal Treatment Strategy and Patient-Directed Discharge Among Hospitalized Patients with Opioid Use Disorder

BACKGROUND

Medical hospitalizations for people with opioid use disorder (OUD) frequently result in patient-directed discharges (PDD), often due to untreated pain and withdrawal.

OBJECTIVE

To investigate the association between early opioid withdrawal management strategies and PDD.

DESIGN

Retrospective cohort study using three datasets representing 362 US hospitals.

PARTICIPANTS

Adult patients hospitalized between 2009 and 2015 with OUD (as identified using ICD-9-CM codes or inpatient buprenorphine administration) and no PDD on the day of admission.

INTERVENTIONS

Opioid withdrawal management strategies were classified based on day-of-admission receipt of any of the following treatments: (1) medications for OUD (MOUD) including methadone or buprenorphine, (2) other opioid analgesics, (3) adjunctive symptomatic medications without opioids (e.g., clonidine), and (4) no withdrawal treatment.

MAIN MEASURES

PDD was assessed as the main outcome and hospital length of stay as a secondary outcome.

KEY RESULTS

Of 6,715,286 hospitalizations, 127,158 (1.9%) patients had OUD and no PDD on the day of admission, of whom 7166 (5.6%) had a later PDD and 91,051 (71.6%) patients received some early opioid withdrawal treatment (22.3% MOUD; 43.4% opioid analgesics; 5.9% adjunctive medications). Compared to no withdrawal treatment, MOUD was associated with a lower risk of PDD (adjusted odds ratio [aOR] = 0.73, 95%CI 0.68-0.8, p < .001), adjunctive treatment alone was associated with higher risk (aOR = 1.13, 95%CI: 1.01-1.26, p = .031), and treatment with opioid analgesics alone was associated with similar risk (aOR 0.95, 95%CI: 0.89-1.02, p = .148). Among those with PDD, both MOUD (adjusted incidence rate ratio [aIRR] = 1.24, 95%CI: 1.17-1.3, p < .001) and opioid analgesic treatments (aIRR = 1.39, 95%CI: 1.34-1.45, p < .001) were associated with longer hospital stays.

CONCLUSIONS

MOUD was associated with decreased risk of PDD but was utilized in < 1 in 4 patients. Efforts are needed to ensure all patients with OUD have access to effective opioid withdrawal management to improve the likelihood they receive recommended hospital care.

Comparison of hospital claims and poison center data to evaluate health impact of opioids, cannabis and synthetic cannabinoids

INTRODUCTION

Over the past 10 years, opioids and cannabis have garnered significant attention due to misuse and legalization trends. Different datasets and surveillance mechanisms can lead to different conclusions the due to a variety of factors. The primary objective of this study was to compare and describe trends of opioid, cannabis, and synthetic cannabinoid-related healthcare encounters and poison center (PC) cases in Colorado, a state that has legalized cannabis.

METHODS

This was a retrospective study comparing hospital claims data (Colorado Hospital Association (CHA)) and poison center cases to describe opioid, cannabis and synthetic cannabinoid-related healthcare encounters and exposures in Colorado from 2013 to 2017 using related genetic codes and International Statistical Classification of Disease codes.

RESULTS

Both datasets observed increases in cannabis related encounters and exposures after recreational cannabis legalization in 2014. CHA reported an increase for cannabis-related ER visits from 14,109 in 2013 to 18,118 in 2017 while PC noted a 74.4% increase in cannabis-related cases (125 to 218). CHA inpatient visits associated with cannabis also increased (8311 in 2013 to 14,659 in 2017). On the other hand, Opioid-related exposures to the PC fell (1092 in 2013 to 971 in 2017) while both Opioid-related ER visits (8580 in 2013 to 12,928 in 2017) and inpatient visits in CHA increased (9084 in 2013 to 13,205).

CONCLUSIONS

This study demonstrates the differences in surveillance methodology for concurrent drug abuse epidemics using hospital claims and PC data. Both systems provide incomplete reports, but in combination can provide a more complete picture.

Epidemiology, Outcomes, and Trends of Patients With Sepsis and Opioid-Related Hospitalizations in U.S. Hospitals

OBJECTIVES

Widespread use and misuse of prescription and illicit opioids have exposed millions to health risks including serious infectious complications. Little is known, however, about the association between opioid use and sepsis.

DESIGN

Retrospective cohort study.

SETTING

About 373 U.S. hospitals.

PATIENTS

Adults hospitalized between January 2009 and September 2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Sepsis was identified by clinical indicators of concurrent infection and organ dysfunction. Opioid-related hospitalizations were identified by the International Classification of Diseases, 9th Revision, Clinical Modification codes and/or inpatient orders for buprenorphine. Clinical characteristics and outcomes were compared by sepsis and opioid-related hospitalization status. The association between opioid-related hospitalization and all-cause, in-hospital mortality in patients with sepsis was assessed using mixed-effects logistic models to adjust for baseline characteristics and severity of illness.The cohort included 6,715,286 hospitalizations; 375,479 (5.6%) had sepsis, 130,399 (1.9%) had opioid-related hospitalizations, and 8,764 (0.1%) had both. Compared with sepsis patients without opioid-related hospitalizations (n = 366,715), sepsis patients with opioid-related hospitalizations (n = 8,764) were younger (mean 52.3 vs 66.9 yr) and healthier (mean Elixhauser score 5.4 vs 10.5), had more bloodstream infections from Gram-positive and fungal pathogens (68.9% vs 47.0% and 10.6% vs 6.4%, respectively), and had lower in-hospital mortality rates (10.6% vs 16.2%; adjusted odds ratio, 0.73; 95% CI, 0.60-0.79; p < 0.001 for all comparisons). Of 1,803 patients with opioid-related hospitalizations who died in-hospital, 928 (51.5%) had sepsis. Opioid-related hospitalizations accounted for 1.5% of all sepsis-associated deaths, including 5.7% of sepsis deaths among patients less than 50 years old. From 2009 to 2015, the proportion of sepsis hospitalizations that were opioid-related increased by 77% (95% CI, 40.7-123.5%).

CONCLUSIONS

Sepsis is an important cause of morbidity and mortality in patients with opioid-related hospitalizations, and opioid-related hospitalizations contribute disproportionately to sepsis-associated deaths among younger patients. In addition to ongoing efforts to combat the opioid crisis, public health agencies should focus on raising awareness about sepsis among patients who use opioids and their providers.

Epidemiological Characteristics of Sedative-Hypnotics and Opioid Painkillers at High-Frequency Exposure

Drug poisoning has a high incidence and serious consequences in medical institutions; its epidemiological characteristics also directly affect the changes in national laws and policies and the implementation of local management policies. Chinese statistics on drug-related abnormal death cases generally come from judicial appraisal centers and medical units. However, due to differences in work content and professional restrictions, there are differences in information management forms, which makes it difficult for appraisers to conduct a professional and systematic analysis of drug-related cases. This article focuses on the analysis of epidemiological characteristics of sedative-hypnotics and opioid painkillers and their exposure patterns in cases of poisoning death by analyzing the annual report of the American Association of Poison Control Center, combined with the characteristics of drug exposure in China.

Opioid Misuse and the Availability of Medical Marijuana Through Dispensaries

OBJECTIVE

In this study we assess whether changes in ZIP code-level density of medical marijuana facilities are related to changes in rates of opioid poisonings and opioid use disorder hospitalizations in California.

METHOD

A panel study using California hospital discharge data was conducted to assess the relationship between density of medical marijuana dispensaries and opioid poisonings and use disorder. There were 8,536 space-time units at the ZIP code level. Outcome measures included ZIP code counts of opioid poisonings and opioid use disorder; independent variables were local- and adjacent-area medical marijuana dispensaries and demographic and economic characteristics.

RESULTS

Independent of effects for covariates, densities of medical marijuana dispensaries were positively related to opioid use disorder (RR = 1.05, CI [1.03, 1.06]) and opioid poisonings (RR = 1.04, CI [1.02, 1.05]) in local areas, but negatively related to opioid misuse in spatially adjacent areas (RR = 0.91, CI [0.88, 0.94] for opioid use disorder, RR = 0.89, CI [0.86, 0.93] for opioid poisonings).

CONCLUSIONS

Although state-level studies suggest that more liberal marijuana policies may result in fewer opioid overdose deaths, our results within one state suggest that local availability of medical marijuana may not reduce those deaths. The relationship appears to be more complex, possibly based on socioeconomic conditions within and adjacent to areas with higher densities of medical marijuana dispensaries.