Multi-site medical record review for validation of intentional self-harm coding in emergency departments.

BACKGROUND: Codes in the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), are used for injury surveillance, including surveillance of intentional self-harm, as they appear in administrative billing records. This study estimated the positive predictive value of ICD-10-CM codes for intentional self-harm in emergency department (ED) billing records for patients aged 10 years and older who did not die and were not admitted to an inpatient medical service. METHODS: The study team in Maryland, Colorado, and Massachusetts selected all or a random sample of ED billing records with an ICD-10-CM code for intentional self-harm (specific codes that began with X71-X83, T36-T65, T71, T14.91). Positive predictive value (PPV) was determined by the number and percentage of records with a physician diagnosis of intentional self-harm, based on a retrospective review of the original medical record. RESULTS: The estimated PPV for the codes' capture of intentional self-harm based on physician diagnosis in the original medical record was 89.8% (95% CI 85.0-93.4) for Maryland records, 91.9% (95% CI 87.7-95.0) for Colorado records, and 97.3% (95% CI 95.1-98.7) for Massachusetts records. CONCLUSION: Given the high PPV of the codes, epidemiologists can use the codes for public health surveillance of intentional self-harm treated in the ED using ICD-10-CM coded administrative billing records. However, these codes and related variables in the billing database cannot definitively distinguish between suicidal and non-suicidal intentional self-harm.

Multisite medical record review of emergency department visits for unspecified injury of head following the ICD-10-CM coding transition.

INTRODUCTION: In 2016, a proposed International Classification of Diseases, Tenth Edition, Clinical Modification surveillance definition for traumatic brain injury (TBI) morbidity was introduced that excluded the unspecified injury of head (S09.90) diagnosis code. This study assessed emergency department (ED) medical records containing S09.90 for evidence of TBI based on medical documentation. METHODS: State health department representatives in Maryland, Kentucky, Colorado and Massachusetts reviewed a target of 385 randomly sampled ED records uniquely assigned the S09.90 diagnosis code (without proposed TBI codes), which were initial medical encounters among state residents discharged home during October 2015-December 2018. Using standardised abstraction procedures, reviewers recorded signs and symptoms of TBI, and head imaging results. A tiered case confirmation strategy was applied that assigned a level of certainty (high, medium, low, none) to each record based on the number and type of symptoms and imaging results present in the record. Positive predictive value (PPV) of S09.90 by level of TBI certainty was calculated by state. RESULTS: Wide variation in PPV of sampled ED records assigned S09.90: 36%-52% had medium or high evidence of TBI, while 48%-64% contained low or no evidence of a TBI. Loss of consciousness was mentioned in 8%-24% of sampled medical records. DISCUSSION: Exclusion of the S09.90 code in surveillance estimates may result in many missed TBI cases; inclusion may result in counting many false positives. Further, missed TBI cases influenced by incidence estimates, based on the TBI surveillance definition, may lead to inadequate allocation of public health resources.

Multisite medical record review of emergency department visits for traumatic brain injury.

BACKGROUND: In 2016, the CDC in the USA proposed codes from the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for identifying traumatic brain injury (TBI). This study estimated positive predictive value (PPV) of TBI for some of these codes. METHODS: Four study sites used emergency department or trauma records from 2015 to 2018 to identify two random samples within each site selected by ICD-10-CM TBI codes for (1) intracranial injury (S06) or (2) skull fracture only (S02.0, S02.1-, S02.8-, S02.91) with no other TBI codes. Using common protocols, reviewers abstracted TBI signs and symptoms and head imaging results that were then used to assign certainty of TBI (none, low, medium, high) to each sampled record. PPVs were estimated as a percentage of records with medium-certainty or high-certainty for TBI and reported with 95% confidence interval (CI). RESULTS: PPVs for intracranial injury codes ranged from 82% to 92% across the four samples. PPVs for skull fracture codes were 57% and 61% in the two university/trauma hospitals in each of two states with clinical reviewers, and 82% and 85% in the two states with professional coders reviewing statewide or nearly statewide samples. Margins of error for the 95% CI for all PPVs were under 5%. DISCUSSION: ICD-10-CM codes for traumatic intracranial injury demonstrated high PPVs for capturing true TBI in different healthcare settings. The algorithm for TBI certainty may need refinement, because it yielded moderate-to-high PPVs for records with skull fracture codes that lacked intracranial injury codes.

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

OBJECTIVES: In 2012, a consensus document was developed on drug overdose poisoning definitions. We took the opportunity to apply these new definitions to health care administrative data in 4 states. Our objective was to calculate and compare drug (particularly opioid) poisoning rates in these 4 states for 4 selected Injury Surveillance Workgroup 7 (ISW7) drug poisoning indicators, using 2 ISW7 surveillance definitions, Option A and Option B. We also identified factors related to the health care administrative data used by each state that might contribute to poisoning rate variations. METHODS: We used state-level hospital and emergency department (ED) discharge data to calculate age-adjusted rates for 4 drug poisoning indicators (acute drug poisonings, acute opioid poisonings, acute opioid analgesic poisonings, and acute or chronic opioid poisonings) using just the principal diagnosis or first-listed external cause-of-injury fields (Option A) or using all diagnosis or external cause-of-injury fields (Option B). We also calculated the high-to-low poisoning rate ratios to measure rate variations. RESULTS: The average poisoning rates per 100 000 population for the 4 ISW7 poisoning indicators ranged from 11.2 to 216.4 (ED) and from 14.2 to 212.8 (hospital). For each indicator, ED rates were usually higher than were hospital rates. High-to-low rate ratios between states were lowest for the acute drug poisoning indicator (range, 1.5-1.6). Factors potentially contributing to rate variations included administrative data structure, accessibility, and submission regulations. CONCLUSIONS: The ISW7 Option B surveillance definition is needed to fully capture the state burden of opioid poisonings. Efforts to control for factors related to administrative data, standardize data sources on a national level, and improve data source accessibility for state health departments would improve the accuracy of drug poisoning surveillance.

Increases in heroin overdose deaths - 28 States, 2010 to 2012.

Nationally, death rates from prescription opioid pain reliever (OPR) overdoses quadrupled during 1999-2010, whereas rates from heroin overdoses increased by <50%. Individual states and cities have reported substantial increases in deaths from heroin overdose since 2010. CDC analyzed recent mortality data from 28 states to determine the scope of the heroin overdose death increase and to determine whether increases were associated with changes in OPR overdose death rates since 2010. This report summarizes the results of that analysis, which found that, from 2010 to 2012, the death rate from heroin overdose for the 28 states increased from 1.0 to 2.1 per 100,000, whereas the death rate from OPR overdose declined from 6.0 per 100,000 in 2010 to 5.6 per 100,000 in 2012. Heroin overdose death rates increased significantly for both sexes, all age groups, all census regions, and all racial/ethnic groups other than American Indians/Alaska Natives. OPR overdose mortality declined significantly among males, persons aged <45 years, persons in the South, and non-Hispanic whites. Five states had increases in the OPR death rate, seven states had decreases, and 16 states had no change. Of the 18 states with statistically reliable heroin overdose death rates (i.e., rates based on at least 20 deaths), 15 states reported increases. Decreases in OPR death rates were not associated with increases in heroin death rates. The findings indicate a need for intensified prevention efforts aimed at reducing overdose deaths from all types of opioids while recognizing the demographic differences between the heroin and OPR-using populations. Efforts to prevent expansion of the number of OPR users who might use heroin when it is available should continue.

Trends in opioid-related fatal overdoses in Massachusetts, 1990-2003.

UNLABELLED: Since 1997, poisoning, particularly from heroin and other opioids, has been the leading cause of injury mortality in Massachusetts. Our aim was to describe recent trends in opioid-related poisoning deaths among Massachusetts residents. METHODS: Massachusetts death files for the years 1990-2003, as coded by International Classification of Disease, Ninth Revision and International Classification of Disease, Tenth Revision, were used to identify all poisoning deaths and opioid-related poisoning deaths; rates were age-adjusted and grouped by year, sex, and race/ethnicity. RESULTS: From 1990 to 2003, opioid-related fatal poisoning rates increased by 529% from 1.4 per 100,000 in 1990 to 8.8 per 100,000 in 2003. The proportion of total poisoning deaths associated with opioids rose from 28% in 1990 to 69% in 2003. CONCLUSIONS: Massachusetts experienced a significant increase in opioid-related poisoning death rates. To guide future public health interventions, further investigation is necessary to better delineate the specific opioids involved, the circumstances surrounding these deaths, and the medical and behavioral health care options available.