Interrupted time series analysis to evaluate the performance of drug overdose morbidity indicators shows discontinuities across the ICD-9-CM to ICD-10-CM transition.

INTRODUCTION: On 1 October 2015, the USA transitioned from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, 10th Revision (ICD-10-CM). Considering the major changes to drug overdose coding, we examined how using different approaches to define all-drug overdose and opioid overdose morbidity indicators in ICD-9-CM impacts longitudinal analyses that span the transition, using emergency department (ED) and hospitalisation data from six states' hospital discharge data systems. METHODS: We calculated monthly all-drug and opioid overdose ED visit rates and hospitalisation rates (per 100 000 population) by state, starting in January 2010. We applied three ICD-9-CM indicator definitions that included identical all-drug or opioid-related codes but restricted the number of fields searched to varying degrees. Under ICD-10-CM, all fields were searched for relevant codes. Adjusting for seasonality and autocorrelation, we used interrupted time series models with level and slope change parameters in October 2015 to compare trend continuity when employing different ICD-9-CM definitions. RESULTS: Most states observed consistent or increased capture of all-drug and opioid overdose cases in ICD-10-CM coded hospital discharge data compared with ICD-9-CM. More inclusive ICD-9-CM indicator definitions reduced the magnitude of significant level changes, but the effect of the transition was not eliminated. DISCUSSION: The coding change appears to have introduced systematic differences in measurement of drug overdoses before and after 1 October 2015. When using hospital discharge data for drug overdose surveillance, researchers and decision makers should be aware that trends spanning the transition may not reflect actual changes in drug overdose rates.

Defining indicators for drug overdose emergency department visits and hospitalisations in ICD-10-CM coded discharge data.

INTRODUCTION: The drug overdose epidemic has worsened over the past decade; however, efforts have been made to better understand and track nonfatal overdoses using various data sources including emergency department and hospital admission data from billing and discharge files. METHODS AND FINDINGS: The Centers for Disease Control and Prevention (CDC) has developed surveillance case definition guidance using standardised discharge diagnosis codes for public health practitioners and epidemiologists using lessons learnt from CDC's funded recipients and the Council for State and Territorial Epidemiologists (CSTE) International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) Drug Poisoning Indicators Workgroup and General Injury ICD-10-CM Workgroup. CDC's guidance was informed by health departments and CSTE's workgroups and included several key aspects for assessing drug overdose in emergency department and hospitalisation discharge data. These include: (1) searching all diagnosis fields to identify drug overdose cases; (2) estimating drug overdose incidence using visits for initial encounter but excluding subsequent encounters and sequelae; (3) excluding underdosing and adverse effects from drug overdose incidence indicators; and (4) using codes T36-T50 for overdose surveillance. CDC's guidance also suggests analysing intent separately for ICD-10-CM coding. CONCLUSIONS: CDC's guidance provides health departments a key tool to better monitor drug overdoses in their community. The implementation and validation of this standardised guidance across all CDC-funded health departments will be key to ensuring consistent and accurate reporting across all entities.

Descriptive exploration of overdose codes in hospital and emergency department discharge data to inform development of drug overdose morbidity surveillance indicator definitions in ICD-10-CM.

BACKGROUND: In October 2015, discharge data coding in the USA shifted to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), necessitating new indicator definitions for drug overdose morbidity. Amid the drug overdose crisis, characterising discharge records that have ICD-10-CM drug overdose codes can inform the development of standardised drug overdose morbidity indicator definitions for epidemiological surveillance. METHODS: Eight states submitted aggregated data involving hospital and emergency department (ED) discharge records with ICD-10-CM codes starting with T36-T50, for visits occurring from October 2015 to December 2016. Frequencies were calculated for (1) the position within the diagnosis billing fields where the drug overdose code occurred; (2) primary diagnosis code grouped by ICD-10-CM chapter; (3) encounter types; and (4) intents, underdosing and adverse effects. RESULTS: Among all records with a drug overdose code, the primary diagnosis field captured 70.6% of hospitalisations (median=69.5%, range=66.2%-76.8%) and 79.9% of ED visits (median=80.7%; range=69.8%-88.0%) on average across participating states. The most frequent primary diagnosis chapters included injury and mental disorder chapters. Among visits with codes for drug overdose initial encounters, subsequent encounters and sequelae, on average 94.6% of hospitalisation records (median=98.3%; range=68.8%-98.8%) and 95.5% of ED records (median=99.5%; range=79.2%-99.8%), represented initial encounters. Among records with drug overdose of any intent, adverse effect and underdosing codes, adverse effects comprised an average of 74.9% of hospitalisation records (median=76.3%; range=57.6%-81.1%) and 50.8% of ED records (median=48.9%; range=42.3%-66.8%), while unintentional intent comprised an average of 11.1% of hospitalisation records (median=11.0%; range=8.3%-14.5%) and 28.2% of ED records (median=25.6%; range=20.8%-40.7%). CONCLUSION: Results highlight considerations for adapting and standardising drug overdose indicator definitions in ICD-10-CM.

ICD-10-CM-Based Definitions for Emergency Department Opioid Poisoning Surveillance: Electronic Health Record Case Confirmation Study.

OBJECTIVES: Valid opioid poisoning morbidity definitions are essential to the accuracy of national surveillance. The goal of our study was to estimate the positive predictive value (PPV) of case definitions identifying emergency department (ED) visits for heroin or other opioid poisonings, using billing records with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. METHODS: We examined billing records for ED visits from 4 health care networks (12 EDs) from October 2015 through December 2016. We conducted medical record reviews of representative samples to estimate the PPVs and 95% confidence intervals (CIs) of (1) first-listed heroin poisoning diagnoses (n = 398), (2) secondary heroin poisoning diagnoses (n = 102), (3) first-listed other opioid poisoning diagnoses (n = 452), and (4) secondary other opioid poisoning diagnoses (n = 103). RESULTS: First-listed heroin poisoning diagnoses had an estimated PPV of 93.2% (95% CI, 90.0%-96.3%), higher than secondary heroin poisoning diagnoses (76.5%; 95% CI, 68.1%-84.8%). Among other opioid poisoning diagnoses, the estimated PPV was 79.4% (95% CI, 75.7%-83.1%) for first-listed diagnoses and 67.0% (95% CI, 57.8%-76.2%) for secondary diagnoses. Naloxone was administered in 867 of 1055 (82.2%) cases; 254 patients received multiple doses. One-third of all patients had a previous drug poisoning. Drug testing was ordered in only 354 cases. CONCLUSIONS: The study findings suggest that heroin or other opioid poisoning surveillance definitions that include multiple diagnoses (first-listed and secondary) would identify a high percentage of true-positive cases.

Building U.S. Capacity to Review and Prevent Maternal Deaths.

In the United States, the risk of death during and up to a year after pregnancy from pregnancy-related causes increased from ∼10 deaths per 100,000 live births in the early 1990s to 17 deaths per 100,000 live births in 2013. While vital statistics-based surveillance systems are useful for monitoring trends and disparities, state and local maternal mortality review committees (MMRCs) are best positioned to both comprehensively assess deaths to women during pregnancy and the year after the end of pregnancy, and identify opportunities for prevention. Although the number of committees that exist has increased over the last several years, both newly formed and long-established committees struggle to achieve and sustain progress toward reviewing and preventing deaths. We describe the key elements of a MMRC; review a logic model that represents the general inputs, activities, and outcomes of a fully functional MMRC; and describe Building U.S. Capacity to Review and Prevent Maternal Deaths, a recent multisector initiative working to remove barriers to fully functional MMRCs. Increased standardization of review committee processes allows for better data to understand the multiple factors that contribute to maternal deaths and facilitates the collaboration that is necessary to eliminate preventable maternal deaths in the United States.

Air pollution, physical activity, and markers of acute airway oxidative stress and inflammation in adolescents.

BACKGROUND: The airway inflammatory response is likely the mechanism for adverse health effects related to exposure to air pollution. Increased ventilation rates during physical activity in the presence of air pollution increases the inhaled dose of pollutants. However, physical activity may moderate the relationship between air pollution and the inflammatory response. The present study aimed to characterize, among healthy adolescents, the relationship between dose of inhaled air pollution, physical activity, and markers of lung function, oxidative stress, and airway inflammation. METHODS: With a non-probability sample of adolescents, this observational study estimated the association between air pollution dose and outcome measures by use of general linear mixed models with an unstructured covariance structure and a random intercept for subjects to account for repeated measures within subjects. RESULTS: A one interquartile range (IQR) (i.e., 345.64 µg) increase in ozone (O3) inhaled dose was associated with a 29.16% average decrease in the percentage of total oxidized compounds (%Oxidized). A one IQR (i.e., 2.368E+10 particle) increase in total particle number count in the inhaled dose (PNT) was associated with an average decrease in forced expiratory flow (FEF25-75) of 0.168 L/second. Increasing activity levels attenuated the relationship between PNT inhaled dose and exhaled nitric oxide (eNO). The relationship between O3 inhaled dose and percent oxidized exhaled breath condensate cystine (%CYSS) was attenuated by activity level, with increasing activity levels corresponding to smaller changes from baseline for a constant O3 inhaled dose. CONCLUSIONS: The moderating effects of activity level suggest that peaks of high concentration doses of air pollution may overwhelm the endogenous redox balance of cells, resulting in increased airway inflammation. Further research that examines the relationships between dose peaks over time and inflammation could help to determine whether a high concentration dose over a short period of time has a different effect than a lower concentration dose over a longer period of time.