Validity of International Classification of Diseases codes in identifying illicit drug use target conditions using medical record data as a reference standard: A systematic review

Sensitivity and specificity of International Classification of Diseases algorithms (ICD-9 and ICD-10) used to identify opioid-related overdose cases: A systematic review and an example of estimation using Bayesian latent class models in the absence of gold standards

OBJECTIVES

This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard.

METHODS

We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner's report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study.

RESULTS

Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect.

CONCLUSION

Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates.

Perspectives on benefits and risks of creation of an "injection drug use" billing code

People with substance use disorder (SUD) face barriers to prevention and treatment services, increasing risk for hospitalization and death. Injection drug use (IDU) can lead to an increased risk of overdose and infections. However, identifying people who inject drugs (PWID) within healthcare systems is challenging. International Classification of Disease (ICD-10) codes are used for billing and tracking healthcare utilization. In this commentary, experts in the field weigh the benefits and risks of creating an IDU-specific ICD-10 code. Potential benefits include earlier identification, better access to health services, and improved systems of resource allocation. Potential risks include further stigmatization of PWID and, if not tied to financial reimbursement, low rates of code utilization. As the current systems of identifying PWID are lacking, we feel that a guided operationalization of an ICD code to identify PWID could improve quantitative and epidemiological research accuracy and, therefore, support the health and well-being of PWID.

Prenatal methamphetamine use increases risk of adverse maternal and neonatal outcomes

BACKGROUND

Although methamphetamine use has been increasing in recent years and occurring within new populations and in broader geographical areas, there is limited research on its use and effect in pregnancy.

OBJECTIVE

This study aimed to examine the association between prenatal methamphetamine use and maternal and neonatal outcomes in a large, contemporary birth cohort.

STUDY DESIGN

This was a retrospective cohort study using California-linked vital statistics and hospital discharge data from 2008 to 2019. Methamphetamine use was identified using the International Classification of Disease, Ninth Revision and Tenth Revision, codes. Chi-square tests and multivariable Poisson regression models were used to evaluate the associations between methamphetamine use and maternal and neonatal outcomes.

RESULTS

A total of 4,775,463 pregnancies met the inclusion criteria, of which 18,473 (0.39%) had methamphetamine use. Compared with individuals without methamphetamine use, individuals with methamphetamine use had an increased risk of nonsevere hypertensive disorders (adjusted risk ratio, 1.81; 95% confidence interval, 1.71-1.90), preeclampsia with severe features (adjusted risk ratio, 3.38; 95% confidence interval, 3.14-3.63), placental abruption (adjusted risk ratio, 3.77; 95% confidence interval, 3.51-4.05), cardiovascular morbidity (adjusted risk ratio, 4.30; 95% confidence interval, 3.79-4.88), and severe maternal morbidity (adjusted risk ratio, 3.53; 95% confidence interval, 3.29-3.77). In addition, adverse neonatal outcomes were increased, including preterm birth at <37 weeks of gestation (adjusted risk ratio, 2.85; 95% confidence interval, 2.77-2.94), neonatal intensive care unit admission (adjusted risk ratio, 2.46; 95% confidence interval, 2.39-2.53), and infant death (adjusted risk ratio, 2.73; 95% confidence interval, 2.35-3.16).

CONCLUSION

Methamphetamine use in pregnancy is associated with an increased risk of adverse maternal and neonatal outcomes that persists after adjustment for confounding variables and sociodemographic factors. Our results can inform prenatal and postpartum care for this high-risk, socioeconomically vulnerable population.

Cannabis use disorder and perioperative outcomes following complex cancer surgery

INTRODUCTION

Cannabis usage is increasing in the United States, especially among patients with cancer. We sought to evaluate whether cannabis use disorder (CUD) was associated with higher morbidity and mortality among patients undergoing complex cancer surgery.

METHODS

Patients who underwent complex cancer surgery between January 2016 and December 2019 were identified in the National Inpatient Sample database. CUD was defined according to ICD-10 codes. Propensity score matching was performed to create a 1:1 matched cohort that was well balanced with respect to covariates, which included patient comorbidities, sociodemographic factors, and procedure type. The primary composite outcome was in-hospital mortality and seven major perioperative complications (myocardial ischemia, acute kidney injury, stroke, respiratory failure, venous thromboembolism, hospital-acquired infection, and surgical procedure-related complications).

RESULTS

Among 15 014 patients who underwent a high-risk surgical procedure, a cohort of 7507 patients with CUD (median age; 43 years [IQR: 30-56 years]; n = 3078 [41.0%] female) were matched with 7507 patients who were not cannabis users (median age; 44 years [IQR: 30-58 years); n = 2997 [39.9%] female). CUD was associated with slight increased risk relative to postoperative kidney injury (CUD, 7.8% vs. no CUD, 6.1%); however, in-hospital mortality was slightly lower (CUD, 0.9% vs. no CUD, 1.6%) (both p < 0.001). On multivariable analysis, after controlling for other risk factors, CUD was not associated with higher morbidity and mortality (adjusted odds ratio: 1.06, 95% CI: 0.98-1.15; p = 0.158).

CONCLUSION

CUD was not associated with a higher risk of postoperative morbidity and mortality following complex cancer surgery.

Validation of case-ascertainment algorithms using health administrative data to identify people who inject drugs in Ontario, Canada

OBJECTIVES

Health administrative data can be used to improve the health of people who inject drugs by informing public health surveillance and program planning, monitoring, and evaluation. However, methodological gaps in the use of these data persist due to challenges in accurately identifying injection drug use (IDU) at the population level. In this study, we validated case-ascertainment algorithms for identifying people who inject drugs using health administrative data in Ontario, Canada.

STUDY DESIGN AND SETTING

Data from cohorts of people with recent (past 12 months) IDU, including those participating in community-based research studies or seeking drug treatment, were linked to health administrative data in Ontario from 1992 to 2020. We assessed the validity of algorithms to identify IDU over varying look-back periods (ie, all years of data [1992 onwards] or within the past 1-5 years), including inpatient and outpatient physician billing claims for drug use, emergency department (ED) visits or hospitalizations for drug use or injection-related infections, and opioid agonist treatment (OAT).

RESULTS

Algorithms were validated using data from 15,241 people with recent IDU (918 in community cohorts and 14,323 seeking drug treatment). An algorithm consisting of ≥1 physician visit, ED visit, or hospitalization for drug use, or OAT record could effectively identify IDU history (91.6% sensitivity and 94.2% specificity) and recent IDU (using 3-year look back: 80.4% sensitivity, 99% specificity) among community cohorts. Algorithms were generally more sensitive among people who inject drugs seeking drug treatment.

CONCLUSION

Validated algorithms using health administrative data performed well in identifying people who inject drugs. Despite their high sensitivity and specificity, the positive predictive value of these algorithms will vary depending on the underlying prevalence of IDU in the population in which they are applied.

Healthcare utilization and left ventricular ejection fraction distribution in methamphetamine use associated heart failure hospitalizations

BACKGROUND

Although methamphetamine use associated heart failure (MU-HF) is increasing, data on its clinical course are limited due to a preponderance of single center studies and significant heterogeneity in the definition of MU-HF in the published literature. Our objective was to evaluate left ventricular ejection fraction (LVEF) distribution, methamphetamine use treatment engagement and postdischarge healthcare utilization among Veterans with heart failure hospitalization in the department of Veterans Affairs (VA) medical centers for MU-HF versus HF not associated with methamphetamine use (other-HF).

METHODS

Observational study including a cohort of Veterans with a first heart failure hospitalization during 2007 - 2020 using data in the VA Corporate Data Warehouse. MU-HF was identified based on the presence of an ICD-code for methamphetmaine use or positive toxicology results within 1-year of heart failure hospitalization. LVEF values entered in the medical record were identified using a validated natural language processing algorithm. Healthcare utilization data was obtained using clinic stop-codes and hosptilaization records.

RESULTS

Of 203,005 first-time heart failure hospitlaizations, 4080 were categorized as MU-HF. Median (interquartile range) of LVEF was 30 (20-45) % for MU-HF versus 40 (25-55)% for other-HF (P < .0001). Eighteen percent of MU-HF had LVEF ≥ 50% compared to 28% in other-HF. Discharge against medical advice was higher in MU-HF (8% vs 2%). Among Veterans with MU-HF, post hospital discharge methamphetamine use treatment engagement was low (18% at 30 days post discharge), with higher follow-up in primary care (76% at 30 days). Post discharge emergency department visits (33% versus 22% at 30 days) and rehospitalizations (24% versus 18% at 30 days) were higher in MU-HF compared to other-HF.

CONCLUSIONS

While the majority of MU-HF hospitalizations are HFrEF, a sizeable minority have HFpEF. This finding has implications for accurate MU-HF classification, treatment, and prognosis. Patients with MU-HF have low addiction treatment receipt and high postdischarge unplanned healthcare utilization. Increasing substance use disorder treatment in this population must be a priority to improve health outcomes. Care-coordination and linkage interventions are urgently needed to increase post-hospitalization addiction treatment and follow-up in an effort to increase evidence-base care and mitigate unplanned healthcare utilization.

Impact of Potential Case Misclassification by Administrative Diagnostic Codes on Outcome Assessment of Observational Study for People Who Inject Drugs

Introduction

Initiation of medications for opioid use disorder (MOUD) within the hospital setting may improve outcomes for people who inject drugs (PWID) hospitalized because of an infection. Many studies used International Classification of Diseases (ICD) codes to identify PWID, although these may be misclassified and thus, inaccurate. We hypothesized that bias from misclassification of PWID using ICD codes may impact analyses of MOUD outcomes.

Methods

We analyzed a cohort of 36 868 cases of patients diagnosed with Staphylococcus aureus bacteremia at 124 US Veterans Health Administration hospitals between 2003 and 2014. To identify PWID, we implemented an ICD code-based algorithm and a natural language processing (NLP) algorithm for classification of admission notes. We analyzed outcomes of prescribing MOUD as an inpatient using both approaches. Our primary outcome was 365-day all-cause mortality. We fit mixed-effects Cox regression models with receipt or not of MOUD during the index hospitalization as the primary predictor and 365-day mortality as the outcome.

Results

NLP identified 2389 cases as PWID, whereas ICD codes identified 6804 cases as PWID. In the cohort identified by NLP, receipt of inpatient MOUD was associated with a protective effect on 365-day survival (adjusted hazard ratio, 0.48; 95% confidence interval, .29-.81; P < .01) compared with those not receiving MOUD. There was no significant effect of MOUD receipt in the cohort identified by ICD codes (adjusted hazard ratio, 1.00; 95% confidence interval, .77-1.30; P = .99).

Conclusions

MOUD was protective of all-cause mortality when NLP was used to identify PWID, but not significant when ICD codes were used to identify the analytic subjects.

Comorbid psychiatric disease significantly mediates increased rates of alcohol use disorder among patients with inflammatory and pigmentary skin disorders: a case-control study in the All of Us Research Program

Dermatologic diseases have a well-documented association with depression and anxiety, which are in turn often comorbid with alcohol use disorder (AUD). Nonethleess, the relationship between dermatologic disease and AUD, and the relative contribution of depression and anxiety, are poorly understood. Here, we utilize the National Insittutes of Health All of Us Research Program to investigate the association between inflammatory and pigmentary dermatologic diseases with AUD. Furthermore, we investigate whether comorbid depression and anxiety mediates this relationship. We employed a matched case-control model with multivariable logistic regression. We also employed a mediation analysis. We found an increased odds of AUD among patients with atopic dermatitis, acne/rosacea, hidradenitis suppurativa, psoriasis, and pigmentary disorders (vitiligo, melasma, and post-inflammatory hyperpigmentation). This was partially mediated by anxiety and depression, especially for diseases with a significant cosmetic component. Overall, these findings highlight the profound psychological and physical health effects that inflammatory and pigmentary disease can have on patients, both independently and in combination with comorbid psychiatric disease.

Predictors of All-Cause 30-Day Readmissions in Patients with Heart Failure at an Urban Safety Net Hospital: The Importance of Social Determinants of Health and Mental Health

Introduction

Heart failure (HF) is a frequent cause of readmissions. Despite caring for underresourced patients and dependence on government funding, safety net hospitals frequently incur penalties for failing to meet pay-for-performance readmission metrics. Limited research exists on the causes of HF readmissions in safety net hospitals. Therefore, we sought to investigate predictors of 30-day all-cause readmission in HF patients in the safety net setting.

Methods

We performed a retrospective chart review of patients admitted for HF from October 2018 to April 2019. We extracted data on demographics and medical comorbidities and performed patient-specific review of social determinants and mental health in 4 domains: race/ethnicity, housing status, substance use, and mental illness. Multivariable Poisson regression modeling was employed to evaluate associations with 30-day all-cause readmission.

Results

The study population included 290 patients, among whom the mean age was 59 years and 71% (n = 207) were male; 42% (120) were Black/African American (AA), 22% (64) were Hispanic/Latino, and 96% (278) had public insurance; 28% (79) were not housed, 19% (56) had a diagnosis of mental illness, and active substance use was common. The 30-day readmission rate was 25.5% (n = 88). Factors that were associated with increased risk of readmission included self-identifying as Black/AA (relative risk 2.28, 95% confidence interval 1.00-5.20) or Hispanic/Latino (2.53, 1.07-6.00), experiencing homelessness (2.07, 1.21-3.56), living in a shelter (3.20, 1.27-8.02), or intravenous drug use (IVDU) (2.00, 1.08-3.70).

Conclusion

Race/ethnicity, housing status, and substance use were associated with increased risk of 30-day all-cause readmission in HF patients in a safety net hospital. In contrast to prior studies, medical comorbidities were not associated with increased risk of readmission.

Methamphetamine-associated heart failure: a systematic review of observational studies

OBJECTIVE

To conduct a systematic review of observational studies on methamphetamine-associated heart failure (MethHF) .

METHODS

Six databases were searched for original publications on the topic. Title/abstract and included full-text publications were reviewed in duplicate. Data extraction and critical appraisal for risk of bias were performed in duplicate.

RESULTS

Twenty-one studies are included in the final analysis. Results could not be combined because of heterogeneity in study design, population, comparator, and outcome assessment. Overall risk of bias is moderate due to the presence of confounders, selection bias and poor matching; overall certainty in the evidence is very low. MethHF is increasing in prevalence, affects diverse racial/ethnic/sociodemographic groups with a male predominance; up to 44% have preserved left-ventricular ejection fraction. MethHF is associated with significant morbidity including worse heart failure symptoms compared with non-methamphetamine related heart failure. Female sex, methamphetamine abstinence and guideline-directed heart failure therapy are associated with improved outcomes. Chamber dimensions on echocardiography and fibrosis on biopsy predict the extent of recovery after abstinence.

CONCLUSIONS

The increasing prevalence of MethHF with associated morbidity underscores the urgent need for well designed prospective studies of people who use methamphetamine to accurately assess the epidemiology, clinical features, disease trajectory and outcomes of MethHF. Methamphetamine abstinence is an integral part of MethHF treatment; increased availability of effective non-pharmacological interventions for treatment of methamphetamine addiction is an essential first step. Availability of effective pharmacological treatment for methamphetamine addiction will further support MethHF treatment. Using harm reduction principles in an integrated addiction/HF treatment programme will bolster efforts to stem the increasing tide of MethHF.

Hospital discharges for substance-related injuries before and during the COVID-19 pandemic: a descriptive surveillance study using administrative data

BACKGROUND

The COVID-19 pandemic and associated behavioural changes have contributed to an increase in substance-related hospital discharges, and has altered the injury epidemiology landscape in Canada. We sought to evaluate hospital discharges for substance-related injuries during the pandemic compared with prepandemic and to identify subpopulations that have been greatly affected by substance-related injuries during the first year of the pandemic.

METHODS

We compared data on hospital discharges in Canada from before the pandemic (March 2019-February 2020) with discharges during the first year of the pandemic (March 2020-February 2021) using the Discharge Abstract Database. We identified discharges for substance-related injuries using codes from the International Statistical Classification of Diseases and Related Health Problems, 10th Revision. We calculated percent changes, age-standardized rates and age-specific rates of discharges for substance-related injuries.

RESULTS

Hospital discharges for substance-related injuries increased by 7.1% during the first year of the pandemic. Discharges for intentional injuries decreased by 6.3%, whereas unintentional substance-related injuries increased by 15.1% during this period. Male patients accounted for 95.6% of the increase in hospital discharges for substance-related injuries during the first year of the pandemic. We observed a percent increase among discharges for injuries related to alcohol, opioid, cannabinoid, hallucinogen, tobacco, volatile solvents, other psychoactive substances and polysubstance use.

INTERPRETATION

We observed an increase in hospital discharges for substance-related injuries during the first year of the COVID-19 pandemic, compared with the same time period before the pandemic. This work will provide useful insight into the ongoing management of the COVID-19 pandemic, as well as future policy and health care planning related to substance use in Canada.

Sensitivity, specificity and predictive values of ICD-10 substance use codes in a cohort of substance use-related endocarditis patients

Background: Healthcare databases have the potential to become efficient tools for epidemiological research in People Who Inject Drugs (PWID). The validity of ICD-10 codes for specific substances in this population has not been assessed.Objectives: Validate ICD-10 diagnosis codes relating to the use of specific substance classes in a cohort of endocarditis patients.Methods: Our study sample consisted of 379 first-episode infective endocarditis patients (Male: 208, Female: 171), aged 18-55, admitted to any of three hospitals in London, Ontario from 2007 to 2018. Of these, 287 used drugs. We validated ICD-10 substance use codes for opioids (F11), stimulants (F15), cocaine (F14) and multiple substances (F19). Sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were calculated for each code, using self-reported substance use documented on medical record review as a gold standard. We conducted a comparative analysis between code-negative users and code-positive users for each substance.Results: All substance use codes shared the same pattern: high specificity, high PPV and low sensitivity, with code F11 yielding the highest PPV (96.3%; 95% C.I.: 90.8-98.6) and sensitivity (42.6%; 95% C.I. 36.3-49.1). The code-positives and code-negatives for each substance did not differ significantly in any characteristics compared.Conclusion: Our results suggest that the individual ICD-10 codes analyzed should not be used for research without adjustment for low sensitivity. However, due to high PPV and specificity, these codes may still have potential for research use. Because code-negative patients did not differ from code-positive patients, their data may be extrapolated to the overall group of substance users.

Natural Language Processing and Machine Learning to Identify People Who Inject Drugs in Electronic Health Records

Background

Improving the identification of people who inject drugs (PWID) in electronic medical records can improve clinical decision making, risk assessment and mitigation, and health service research. Identification of PWID currently consists of heterogeneous, nonspecific International Classification of Diseases (ICD) codes as proxies. Natural language processing (NLP) and machine learning (ML) methods may have better diagnostic metrics than nonspecific ICD codes for identifying PWID.

Methods

We manually reviewed 1000 records of patients diagnosed with Staphylococcus aureus bacteremia admitted to Veterans Health Administration hospitals from 2003 through 2014. The manual review was the reference standard. We developed and trained NLP/ML algorithms with and without regular expression filters for negation (NegEx) and compared these with 11 proxy combinations of ICD codes to identify PWID. Data were split 70% for training and 30% for testing. We calculated diagnostic metrics and estimated 95% confidence intervals (CIs) by bootstrapping the hold-out test set. Best models were determined by best F-score, a summary of sensitivity and positive predictive value.

Results

Random forest with and without NegEx were the best-performing NLP/ML algorithms in the training set. Random forest with NegEx outperformed all ICD-based algorithms. F-score for the best NLP/ML algorithm was 0.905 (95% CI, .786-.967) and 0.592 (95% CI, .550-.632) for the best ICD-based algorithm. The NLP/ML algorithm had a sensitivity of 92.6% and specificity of 95.4%.

Conclusions

NLP/ML outperformed ICD-based coding algorithms at identifying PWID in electronic health records. NLP/ML models should be considered in identifying cohorts of PWID to improve clinical decision making, health services research, and administrative surveillance.

Hospitalisation with injection-related infections: Validation of diagnostic codes to monitor admission trends at a tertiary care hospital in Melbourne, Australia

INTRODUCTION

Injection-related infections (IRI) cause morbidity and mortality in people who inject drugs. Hospital administrative datasets can be used to describe hospitalisation trends, but there are no validated algorithms to identify injecting drug use and IRIs. We aimed to validate International Classification of Diseases (ICD) codes to identify admissions with IRIs and use these codes to describe IRIs within our hospital.

METHODS

We developed a candidate set of ICD codes to identify current injecting drug use and IRI and extracted admissions satisfying both criteria. We then used manual chart review data from 1 January 2017 to 30 April 2019 to evaluate the performance of these codes and refine our algorithm by selecting codes with a high-positive predictive value (PPV). We used the refined algorithm to describe trends and outcomes of people who inject drugs with an IRI at Alfred Hospital, Melbourne from 2008 to 2020.

RESULTS

Current injecting drug use was best predicted by opioid-related disorders (F11), 80% (95% confidence interval [CI] 74-85%), and other stimulant-related disorders (F15), 82% (95% CI 70-90%). All PPVs were ≥67% to identify specific IRIs, and ≥84% for identifying any IRI. Using these codes over 12 years, IRIs increased from 138 to 249 per 100 000 admissions, and skin and soft tissues infections (SSTI) were the most common (797/1751, 46%).

DISCUSSION AND CONCLUSION

Validated ICD-based algorithms can inform passive surveillance systems. Strategies to reduce hospitalisation with IRIs should be supported by early intervention and prevention, particularly for SSTIs which may represent delayed access to care.

Antibiotic therapy completion for injection drug use-associated infective endocarditis at a center with routine addiction medicine consultation: a retrospective cohort study

Background

Addiction medicine consultation and medications for opioid use disorder are shown to improve outcomes for patients hospitalized with infective endocarditis associated with injection drug use. Existing studies describe settings where addiction medicine consultation and initiation of medications for opioid use disorder are not commonplace, and rates of antibiotic therapy completion are infrequently reported. This retrospective study sought to quantify antibiotic completion outcomes in a setting where these interventions are routinely implemented.

Methods

Medical records of patients hospitalized with a diagnosis of bacteremia or infective endocarditis at an urban hospital between October 1, 2015 and December 31, 2017 were screened for active injection drug use within 6 months of hospitalization and infective endocarditis. Demographic and clinical parameters, receipt of antibiotics and medications for opioid use disorder, and details of re-hospitalizations within 1 year of discharge were recorded.

Results

Of 567 subjects screened for inclusion, 47 had infective endocarditis and active injection drug use. Addiction medicine consultation was completed for 41 patients (87.2%) and 23 (48.9%) received medications for opioid use disorder for the entire index admission. Forty-three patients (91.5%) survived to discharge, of which 28 (59.6%) completed antibiotic therapy. Twenty-nine survivors (67.4%) were re-hospitalized within 1 year due to infectious complications of injection drug use.

Conclusions

Among patients admitted to a center with routine addiction medicine consultation and initiation of medications for opioid use disorder, early truncation of antibiotic therapy and re-hospitalization were commonly observed.

Preconception health service provision among women with and without substance use disorders

BACKGROUND

Drug and alcohol use during pregnancy is associated with significant adverse birth outcomes and maternal morbidity. Addressing health and risky behaviors before pregnancy, in the preconception period, can improve both maternal and infant outcomes. However, the prevalence of preconception service delivery among women with substance use disorders (SUD) is unknown.

METHODS

Using Optum®, a de-identified Electronic Health Record dataset containing data from 5 million nationally distributed US adults from 2010 to 2018, we conducted a cross-sectional analysis of 18-55-year-old women with delivery between 2012 and 2018 (n = 52,565). Preconception services received in the year before pregnancy were identified using ICD-9/10 V and Z codes. Logistic regression was used to assess the relationship of any SUD vs. no SUD and preconception services received before and after adjusting for confounding.

RESULTS

Average age was 29.3 ( ± 5.0 years); 6.4% (n = 3371) of the sample had a diagnosis of any SUD and 6.0% (n = 3144) received any preconception services in the year before pregnancy. Women with SUD vs. without had higher prevalence of receiving any preconception services (9.6% versus 5.7%, p < 0.001). Compared to women without SUD, women with SUD had increased odds of receiving preconception services adjusting for medical comorbidities (OR=1.39; 95% CI=1.22-1.58) that was no longer significant when psychiatric comorbidities were added (OR=1.11; 95% CI=0.97-1.27).

CONCLUSIONS

There are numerous missed opportunities to provide preconception services to women with and without SUD. While delivering preconception services, healthcare providers have an opportunity to screen for SUD which may be more prevalent among women with psychiatric and medical problems.

Clinical and demographic factors associated with stimulant use disorder in a rural heart failure population

BACKGROUND

Heart failure is becoming increasingly common among patients under 50 years of age, particularly in African Americans and patients with stimulant use disorder. Yet the sources of these disparities remain poorly understood. This study identified key demographic and clinical factors associated with stimulant use disorder in a largely rural heart failure patient registry.

METHODS

Patient records reporting a diagnosis of heart failure between January 2008 and March 2020 were requested from West Virginia University Hospital Systems (n=37,872). Odds of stimulant use disorder were estimated by demographic group (age, race, sex), insurance carrier, and clinical comorbidities using logistic regression.

RESULTS

Multivariable regression analysis identified higher odds of stimulant use disorder among Black/African Americans (1.95 [1.32, 2.77]) and patients who report drinking one or more alcoholic drinks per week (2.23 [1.72, 2.88]). Lower odds of stimulant use disorder were identified among patients with hypertension (0.59 [0.47, 0.73]), or diabetes (0.65 [0.52, 0.81]).. Likewise, lower odds of stimulant use disorder were noted among females, patients older than 30 years of age and those not enrolled in Medicaid.

CONCLUSION

These results highlight the alarming extent to which Medicaid enrollees, Black/African Americans, people aged 18-24 and 25-44, or persons with a past alcohol use disorder diagnosis are associated with stimulant use disorder among heart failure populations living in largely rural areas. Additionally, they emphasize the need to develop policies and refine clinical care that affects this vulnerable population's prognoses.

Prescription opioid treatment for non-cancer pain and initiation of injection drug use: large retrospective cohort study

OBJECTIVE

To assess the association between long term prescription opioid treatment medically dispensed for non-cancer pain and the initiation of injection drug use (IDU) among individuals without a history of substance use.

DESIGN

Retrospective cohort study.

SETTING

Large administrative data source (containing information for about 1.7 million individuals tested for hepatitis C virus or HIV in British Columbia, Canada) with linkage to administrative health databases, including dispensations from community pharmacies.

PARTICIPANTS

Individuals age 11-65 years and without a history of substance use (except alcohol) at baseline.

MAIN OUTCOME MEASURES

Episodes of prescription opioid use for non-cancer pain were identified based on drugs dispensed between 2000 and 2015. Episodes were classified by the increasing length and intensity of opioid use (acute (lasting <90 episode days), episodic (lasting ≥90 episode days; with <90 days' drug supply and/or <50% episode intensity), and chronic (lasting ≥90 episode days; with ≥90 days' drug supply and ≥50% episode intensity)). People with a chronic episode were matched 1:1:1:1 on socioeconomic variables to those with episodic or acute episodes and to those who were opioid naive. IDU initiation was identified by a validated administrative algorithm with high specificity. Cox models weighted by inverse probability of treatment weights assessed the association between opioid use category (chronic, episodic, acute, opioid naive) and IDU initiation.

RESULTS

59 804 participants (14 951 people from each opioid use category) were included in the matched cohort, and followed for a median of 5.8 years. 1149 participants initiated IDU. Cumulative probability of IDU initiation at five years was highest for participants with chronic opioid use (4.0%), followed by those with episodic use (1.3%) and acute use (0.7%), and those who were opioid naive (0.4%). In the inverse probability of treatment weighted Cox model, risk of IDU initiation was 8.4 times higher for those with chronic opioid use versus those who were opioid naive (95% confidence interval 6.4 to 10.9). In a sensitivity analysis limited to individuals with a history of chronic pain, cumulative risk for those with chronic use (3.4% within five years) was lower than the primary results, but the relative risk was not (hazard ratio 9.7 (95% confidence interval 6.5 to 14.5)). IDU initiation was more frequent at higher opioid doses and younger ages.

CONCLUSIONS

The rate of IDU initiation among individuals who received chronic prescription opioid treatment for non-cancer pain was infrequent overall (3-4% within five years) but about eight times higher than among opioid naive individuals. These findings could have implications for strategies to prevent IDU initiation, but should not be used as a reason to support involuntary tapering or discontinuation of long term prescription opioid treatment.

Characterizing trends in methamphetamine-related health care use when there is no ICD code for "methamphetamine use disorder"

BACKGROUND AND AIMS

The recent surge in methamphetamine use highlights the need for timely data on its health effects and healthcare service use impact. However, there is no ICD code for methamphetamine use. This study quantifies the positive predictive value of ICD-9-CM and ICD-10-CM psychostimulant codes for methamphetamine use.

METHODS

A retrospective chart review of 220 adults aged 18 and older who had an inpatient admission with a psychostimulant-associated billing diagnosis at an urban safety-net hospital. Diagnoses were categorized as either methamphetamine-related or involving another specific psychostimulant. The positive predictive value of both ICD-9-CM or ICD-10-CM psychostimulant diagnosis codes for methamphetamine use was calculated.

RESULTS

ICD-9-CM and ICD-10-CM psychostimulant codes had high positive predictive values of 78.2% (95% CI 70.3%-86.0%) and 85.5% (95% CI 78.8%-92.1%), respectively, for methamphetamine use. The most common non-methamphetamine psychostimulant in our cohort was khat, a cathinone-containing plant native to East Africa, accounting for psychostimulant-related diagnosis in 16 of the 220 hospitalizations.

CONCLUSIONS

The high predictive values of psychostimulant codes for methamphetamine use support the application of administrative data in measuring methamphetamine-related healthcare use, as well as co-morbid health conditions and treatment patterns.

Low Back Pain and Substance Use: Diagnostic and Administrative Coding for Opioid Use and Dependence Increased in U.S. Older Adults with Low Back Pain

OBJECTIVE

Low back pain (LBP) is a leading cause of pain and disability. Substance use complicates the management of LBP, and potential risks increase with aging. Despite implications for an aging, diverse U.S. population, substance use and LBP comorbidity remain poorly defined. The objective of this study was to characterize LBP and substance use diagnoses in older U.S. adults by age, gender, and race.

DESIGN

Cross-sectional study of a random national sample.

SUBJECTS

Older adults including 1,477,594 U.S. Medicare Part B beneficiaries.

METHODS

Bayesian analysis of 37,634,210 claims, with 10,775,869 administrative and 92,903,649 diagnostic code assignments.

RESULTS

LBP was diagnosed in 14.8±0.06% of those more than 65 years of age, more in females than in males (15.8±0.08% vs. 13.4±0.09%), and slightly less in those more than 85 years of age (13.3±0.2%). Substance use diagnosis varied by substance: nicotine, 9.6±0.02%; opioid, 2.8±0.01%; and alcohol, 1.3±0.01%. Substance use diagnosis declined with advancing age cohort. Opioid use diagnosis was markedly higher for those in whom LBP was diagnosed (10.5%) than for those not diagnosed with LBP (1.5%). Most older adults (54.9%) with an opioid diagnosis were diagnosed with LBP. Gender differences were modest. Relative rates of substance use diagnoses in LBP were modest for nicotine and alcohol.

CONCLUSIONS

Older adults with LBP have high relative rates of opioid diagnoses, irrespective of gender or age. Most older adults with opioid-related diagnoses have LBP, compared with a minority of those not opioid diagnosed. In caring for older adults with LBP or opioid-related diagnoses, health systems must anticipate complexity and support clinicians, patients, and caregivers in managing pain comorbidities. Older adults may benefit from proactive incorporation of non-opioid pain treatments. Further study is needed.

Misclassification Error-Adjusted Prevalence of Injection Drug Use Among Infective Endocarditis Hospitalizations in the United States: A Serial Cross-Sectional Analysis of the 2007-2016 National Inpatient Sample

Administrative health databases have been used to monitor trends in infective endocarditis hospitalization related to nonprescription injection drug use (IDU) using International Classification of Diseases (ICD) code algorithms. Because no ICD code for IDU exists, drug dependence and hepatitis C virus (HCV) have been used as surrogate measures for IDU, making misclassification error (ME) a threat to the accuracy of existing estimates. In a serial cross-sectional analysis, we compared the unadjusted and ME-adjusted prevalences of IDU among 70,899 unweighted endocarditis hospitalizations in the 2007-2016 National Inpatient Sample. The unadjusted prevalence of IDU was estimated with a drug algorithm, an HCV algorithm, and a combination algorithm (drug and HCV). Bayesian latent class models were used to estimate the median IDU prevalence and 95% Bayesian credible intervals and ICD algorithm sensitivity and specificity. Sex- and age group-stratified IDU prevalences were also estimated. Compared with the misclassification-adjusted prevalence, unadjusted estimates were lower using the drug algorithm and higher using the combination algorithm. The median ME-adjusted IDU prevalence increased from 9.7% (95% Bayesian credible interval (BCI): 6.3, 14.8) in 2008 to 32.5% (95% BCI: 26.5, 38.2) in 2016. Among persons aged 18-34 years, IDU prevalence was higher in females than in males. ME adjustment in ICD-based studies of injection-related endocarditis is recommended.

Linkage to specialty care in the hepatitis C care cascade

Quality gaps exist in the hepatitis C virus (HCV) care process from diagnosis to cure. To better understand current gaps and to identify targets for quality improvement, we constructed an HCV care cascade in a patient-centered medical home (PCMH) with an emphasis on the specialty referral process. We performed a retrospective study of HCV-infected patients in a PCMH using electronic health record (EPIC) data. Patients with a first positive HCV RNA between 2012 and 2019 were included. With an adaptation to analyze linkage to specialty care, we created an HCV care cascade that included the following: (1) a positive HCV RNA, (2) referral to a specialty provider, (3) a scheduled specialty appointment, (4) attendance at a specialty visit, (5) prescription for HCV therapy, and (6) evidence of sustained virological response (SVR). Patient and referring clinician characteristics were analyzed at each step of the care pathway, and the proportion of patients completing each step was calculated. Of the 256 HCV RNA-positive patients, 229 (89.5%) received a specialty referral; 215 (84.0%) had an appointment scheduled; 178 (69.5%) attended the specialty appointment; 116 (45.3%) were prescribed antiviral therapy; and 87 (34.1%) had documented SVR during the study period. Of the 178 patients attending a specialty visit, 62 (34.8%) did not receive a prescription, and the barrier most often noted was the desire for further workup (40.3%). Gaps occur at all stages of the HCV care continuum, with drop-offs in care occurring both before and after linkage to specialty care.

Substance use disorders and risk of severe maternal morbidity in the United States

BACKGROUND

The contribution of substance use disorders to the burden of severe maternal morbidity in the United States is poorly understood. The objective was to estimate the independent association between substance use disorders during pregnancy and risk of severe maternal morbidity.

METHODS

Retrospective analysis of a weighted 53.4 million delivery hospitalizations from 2003 to 2016 among females aged>18 in the National Inpatient Sample. We constructed measures of substance use disorders using diagnostic codes for cannabis, opioids, and stimulants (amphetamines or cocaine) abuse or dependence during pregnancy. The outcome was the presence of any of the 21 CDC indicators of severe maternal morbidity. Using weighted multivariable logistic regression, we estimated the association between substance use disorders and adjusted risk of severe maternal morbidity. Because older age at delivery is predictive of severe maternal morbidity, we tested for effect modification between substance use and maternal age by age group (18-34 y vs >34 y).

RESULTS

Pregnant women with an opioid use disorder had an increased risk of severe maternal morbidity compared with women without an opioid use disorder (18-34 years: aOR: 1.51; 95 % CI: 1.41,1.61, >34 years: aOR: 1.17; 95 % CI: 1.00,1.38). Compared with their counterparts without stimulant use disorders, pregnant women with a simulant use disorder (amphetamines, cocaine) had an increased risk of severe maternal morbidity (18-34 years: aOR: 1.92; 95 % CI: 1.80,2.0, >34 years: aOR: 1.85; 95 % CI: 1.66,2.06). Cannabis use disorders were not associated with an increased risk of severe maternal morbidity.

CONCLUSION

Substance use disorders during pregnancy, particularly opioids, amphetamines, and cocaine use disorders, may contribute to severe maternal morbidity in the United States.