Longitudinal dose patterns among patients newly initiated on long-term opioid therapy in the United States, 2018 to 2019: an observational cohort study and time-series cluster analysis.

ABSTRACT: Opioid prescribing varies widely, and prescribed opioid dosages for an individual can fluctuate over time. Patterns in daily opioid dosage among patients prescribed long-term opioid therapy have not been previously examined. This study uses a novel application of time-series cluster analysis to characterize and visualize daily opioid dosage trajectories and associated demographic characteristics of patients newly initiated on long-term opioid therapy. We used 2018 to 2019 data from the IQVIA Longitudinal Prescription (LRx) all-payer pharmacy database, which covers 92% of retail pharmacy prescriptions dispensed in the United States. We identified a cohort of 277,967 patients newly initiated on long-term opioid therapy during 2018. Patients were stratified into 4 categories based on their mean daily dosage during a 90-day baseline period (<50, 50-89, 90-149, and ≥150 morphine milligram equivalent [MME]) and followed for a 270-day follow-up period. Time-series cluster analysis identified 2 clusters for each of the 3 baseline dosage categories <150 MME and 3 clusters for the baseline dosage category ≥150 MME. One cluster in each baseline dosage category comprised opioid dosage trajectories with decreases in dosage at the end of the follow-up period (80.7%, 98.7%, 98.7%, and 99.0%, respectively), discontinuation (58.5%, 80.0%, 79.3%, and 81.7%, respectively), and rapid tapering (50.8%, 85.8%, 87.5%, and 92.9%, respectively). These findings indicate multiple clusters of patients newly initiated on long-term opioid therapy who experience discontinuation and rapid tapering and highlight potential areas for clinician training to advance evidence-based guideline-concordant opioid prescribing, including strategies to minimize sudden dosage changes, discontinuation, or rapid tapering, and the importance of shared decision-making.

Medical Costs of Substance Use Disorders in the US Employer-Sponsored Insurance Population.

Importance: Direct costs of substance use disorders (SUDs) in the United States are incurred primarily among the working-age population. Quantifying the medical cost of SUDs in the employer-sponsored insurance (ESI) population can improve understanding of how SUDs are affecting workplaces and inform decision-making on the value of prevention strategies. Objective: To estimate the annual attributable medical cost of SUDs in the ESI population from the health care payer perspective. Design, Setting, and Participants: In this economic evaluation, Merative MarketScan 2018 databases were weighted to represent the non-Medicare eligible ESI population. Regression and mathematical modeling of medical expenditures controlled for insurance enrollee demographic, clinical, and insurance factors to compare enrollees with and without an SUD diagnosis to identify the annual attributable medical cost of SUDs. Data analysis was conducted from January to March 2022. Exposures: International Statistical Classification of Diseases, Tenth Revision, Clinical Modification SUD diagnoses on inpatient or outpatient medical records according to Clinical Classifications Software categories (alcohol-, cannabis-, hallucinogen-, inhalant-, opioid-, sedative-, stimulant-, and other substance-related disorders). Main Outcomes and Measures: Annual SUD medical cost in the ESI population overall and by substance type (eg, alcohol). Number of enrollees with an SUD diagnosis and the annual mean cost per affected enrollee of SUD diagnosis (any and by substance type) are also reported. Results: Among 162 million ESI enrollees, 2.3 million (1.4%) had an SUD diagnosis in 2018. The regression analysis sample included 210 225 individuals with an SUD diagnosis (121 357 [57.7%] male individuals; 68 325 [32.5%] aged 25-44 years) and 1 049 539 individuals with no SUD diagnosis. The mean annual medical cost attributable to SUD diagnosis per affected enrollee was $15 640 (95% CI, $15 340-$15 940), and the total annual medical cost in the ESI population was $35.3 billion (2018 USD). Alcohol use disorder ($10.2 billion) and opioid use disorder ($7.3 billion) were the most costly. Conclusions and Relevance: In this economic evaluation of medical expenditures in the ESI population, the per-person and total medical costs of SUDs were substantial. Strategies to support employees and their health insurance dependents to prevent and treat SUDs can be considered in terms of potentially offsetting the existing high medical cost of SUDs. Medical expenditures for SUDs represent the minimum direct cost that employers and health insurers face because not all people with SUDs have a diagnosis, and costs related to absenteeism, presenteeism, job retention, and mortality are not addressed.

Factors That Affect Opioid Quality Improvement Initiatives in Primary Care: Insights from Ten Health Systems.

OBJECTIVE: To improve patient safety and pain management, the Centers for Disease Control and Prevention (CDC) released the Guideline for Prescribing Opioids for Chronic Pain (CDC Guideline). Recognizing that issuing a guideline alone is insufficient for transforming practice, CDC supported an Opioid Quality Improvement (QI) Collaborative, consisting of 10 health care systems that represented more than 120 practices across the United States. The research team identified factors related to implementation success using domains described by the integrated Promoting Action on Research Implementation in Health Services (iPARIHS) implementation science framework. METHODS: Data from interviews, notes from check-in calls, and documents provided by systems were used. The researchers collected data throughout the project through interviews, meeting notes, and documents. RESULTS: The iPARIHS framework was used to identify factors that affected implementation related to the context, innovation (implementing recommendations from the CDC Guideline), recipient (clinicians), and facilitation (QI team). Contextual characteristics were at the clinic, health system, and broader external context, including staffing and leadership support, previous QI experience, and state laws. Characteristics of the innovation were its adaptability and challenges operationalizing the measures. Recipient characteristics included belief in the importance of the innovation but challenges engaging in the initiative. Finally, facilitation characteristics driving differential outcomes included staffing and available time of the QI team, the ability to make changes, and experience with QI. CONCLUSION: As health care systems continue to implement the CDC Guideline, these insights can advance successful implementation efforts by describing common implementation challenges and identifying strategies to prepare for and overcome them.

Changes in Opioid Dispensing by Medical Specialties After the Release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain.

OBJECTIVE: To identify changes in opioid prescribing across a diverse array of medical specialties after the release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain. DESIGN: Interrupted time-series analysis of data from a commercial prescribing database. SUBJECTS: De-identified recipients of opioid prescriptions dispensed at U.S. retail pharmacies between 2015 and 2019. METHODS: Opioid dispensing data were obtained from the IQVIA Longitudinal Prescription (LRx) database, representing more than 800 million opioid prescriptions. Monthly dispensing rates, dosage in morphine milligram equivalents (MME), and mean prescription duration were calculated across 29 medical specialties. Changes in dispensing after the release of the 2016 CDC Guideline were assessed through interrupted time-series analysis. RESULTS: Declining trends in opioid dispensing accelerated in 24 of 29 specialty groups after the release of the CDC Guideline (P < 0.05 for 15 groups). Decreases were greatest among family medicine clinicians, where declines accelerated by 4.4 prescriptions per month per 100,000 persons (P = 0.005), and surgeons, where declines accelerated by 3.6 prescriptions per month per 100,000 (P = 0.003). CONCLUSIONS: These results illustrate that clinicians likely to provide primary care exhibited the greatest decreases in opioid dispensing. However, specialties outside the scope of the CDC Guideline (e.g., surgery) also exhibited accelerated decreases in prescribing. These declines illustrate that specialties beyond primary care could have interest in evaluating opioid prescribing practices, supporting the importance of specialty-specific guidance that balances the individualized risks and benefits of opioids and the role of non-opioid treatments.

Assessment of Annual Cost of Substance Use Disorder in US Hospitals.

Importance: A persistently high US drug overdose death toll and increasing health care use associated with substance use disorder (SUD) create urgency for comprehensive estimates of attributable direct costs, which can assist in identifying cost-effective ways to prevent SUD and help people to receive effective treatment. Objective: To estimate the annual attributable medical cost of SUD in US hospitals from the health care payer perspective. Design, Setting, and Participants: This economic evaluation of observational data used multivariable regression analysis and mathematical modeling of hospital encounter costs, controlling for patient demographic, clinical, and insurance characteristics, and compared encounters with and without secondary SUD diagnosis to statistically identify the total attributable cost of SUD. Nationally representative hospital emergency department (ED) and inpatient encounters from the 2017 Healthcare Cost and Utilization Project Nationwide Emergency Department Sample and National Inpatient Sample were studied. Statistical analysis was performed from March to June 2020. Exposures: International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) principal or secondary SUD diagnosis on the hospital discharge record according to the Clinical Classifications Software categories (disorders related to alcohol, cannabis, hallucinogens, inhalants, opioids, sedatives, stimulants, and other substances). Main Outcomes and Measures: Annual attributable SUD medical cost in hospitals overall and by substance type (eg, alcohol). The number of encounters (ED and inpatient) with SUD diagnosis (principal or secondary) and the mean cost attributable to SUD per encounter by substance type are also reported. Results: This study examined a total of 124 573 175 hospital ED encounters and 33 648 910 hospital inpatient encounters from the 2017 Healthcare Cost and Utilization Project Nationwide Emergency Department Sample and National Inpatient Sample. Total annual estimated attributable SUD medical cost in hospitals was $13.2 billion. By substance type, the cost ranged from $4 million for inhalant-related disorders to $7.6 billion for alcohol-related disorders. Conclusions and Relevance: This study's results suggest that the cost of effective prevention and treatment may be substantially offset by a reduction in the high direct medical cost of SUD hospital care. The findings of this study may inform the treatment of patients with SUD during hospitalization, which presents a critical opportunity to engage patients who are at high risk for overdose. Aligning incentives such that prevention cost savings accrue to payers and practitioners that are otherwise responsible for SUD-related medical costs in hospitals and other health care settings may encourage prevention investment.

Indication-Specific Opioid Prescribing for US Patients With Medicaid or Private Insurance, 2017.

Importance: Although opioids can be effective medications in certain situations, they are associated with harms, including opioid use disorder and overdose. Studies have revealed unexplained prescribing variation and prescribing mismatched with patient-reported pain for many indications. Objective: To summarize opioid prescribing frequency, dosages, and durations, stratified across numerous painful medical indications. Design, Setting, and Participants: Retrospective cross-sectional analysis of 2017 US administrative claims data among outpatient clinical settings, including postsurgical discharge. Participants had any of 41 different indications associated with nonsurgical acute or chronic pain or postsurgical pain or pain associated with sickle cell disease or active cancer and were enrolled in either private insurance (including Medicare Advantage) in the OptumLabs Data Warehouse data set (n = 18 016 259) or Medicaid in the IBM MarketScan Multi-State Medicaid Database (n = 11 453 392). OptumLabs data were analyzed from October 2018 to March 2019; MarketScan data were analyzed from January to April 2019. Exposures: Nonsurgical acute or chronic pain or postsurgical pain; pain related to sickle cell disease or active cancer. Main Outcomes and Measures: Indication-specific opioid prescribing rates; days' supply per prescription; daily opioid dosage in morphine milligram equivalents; and for chronic pain indications, the number of opioid prescriptions. Results: During the study period, of 18 016 259 eligible patients with private insurance, the mean (95% CI) age was 42.7 (42.7-42.7) years, and 50.3% were female; of 11 453 392 eligible Medicaid enrollees, the mean (95% CI) age was 20.4 (20.4-20.4) years, and 56.1% were female. A pain-related indication under study occurred in at least 1 visit among 6 380 694 patients with private insurance (35.4%) and 3 169 831 Medicaid enrollees (27.7%); 2 270 596 (35.6% of 6 380 694) privately insured patients and 1 126 508 (35.5% of 3 169 831) Medicaid enrollees had 1 or more opioid prescriptions. Nonsurgical acute pain opioid prescribing rates were lowest for acute migraines (privately insured, 4.6% of visits; Medicaid, 6.6%) and highest for rib fractures (privately insured, 44.8% of visits; Medicaid, 56.3%), with variable days' supply but similar daily dosage across most indications. Opioid prescribing for a given chronic pain indication varied depending on a patient's opioid use history. Days' supply for postoperative prescriptions was longest for combined spinal decompression and fusion (privately insured, 9.5 days [95% CI, 9.4-9.7 days]) or spinal fusion (Medicaid, 9.1 days [95% CI, 8.9-9.2 days]) and was shortest for vaginal delivery (privately insured, 4.1 days [95% CI, 4.1-4.1 days] vs Medicaid, 4.2 days [95% CI, 4.2-4.2 days]). Conclusions and Relevance: Indication-specific opioid prescribing rates were not always aligned with existing guidelines. Potential inconsistencies between prescribing practice and clinical recommendations, such as for acute and chronic back pain, highlight opportunities to enhance pain management and patient safety.

Pulmonary Illness Related to E-Cigarette Use in Illinois and Wisconsin - Final Report.

BACKGROUND: E-cigarettes are battery-operated devices that heat a liquid and deliver an aerosolized product to the user. Pulmonary illnesses related to e-cigarette use have been reported, but no large series has been described. In July 2019, the Wisconsin Department of Health Services and the Illinois Department of Public Health received reports of lung injury associated with the use of e-cigarettes (also called vaping) and launched a coordinated public health investigation. METHODS: We defined case patients as persons who reported use of e-cigarette devices and related products in the 90 days before symptom onset and had pulmonary infiltrates on imaging and whose illnesses were not attributed to other causes. Medical record abstraction and case patient interviews were conducted with the use of standardized tools. RESULTS: There were 98 case patients, 79% of whom were male; the median age of the patients was 21 years. The majority of patients presented with respiratory symptoms (97%), gastrointestinal symptoms (77%), and constitutional symptoms (100%). All case patients had bilateral infiltrates on chest imaging. A total of 95% of the patients were hospitalized, 26% underwent intubation and mechanical ventilation, and two deaths were reported. A total of 89% of the patients reported having used tetrahydrocannabinol products in e-cigarette devices, although a wide variety of products and devices was reported. Syndromic surveillance data from Illinois showed that the mean monthly rate of visits related to severe respiratory illness in June through August of 2019 was twice the rate that was observed in the same months in 2018. CONCLUSIONS: Case patients presented with similar clinical characteristics. Although the definitive substance or substances contributing to injury have not been determined, this initial cluster of illnesses represents an emerging clinical syndrome or syndromes. Additional work is needed to characterize the pathophysiology and to identify the definitive causes.

Severe Pulmonary Disease Associated with Electronic-Cigarette-Product Use - Interim Guidance.

On September 6, 2019, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr). As of August 27, 2019, 215 possible cases of severe pulmonary disease associated with the use of electronic cigarette (e-cigarette) products (e.g., devices, liquids, refill pods, and cartridges) had been reported to CDC by 25 state health departments. E-cigarettes are devices that produce an aerosol by heating a liquid containing various chemicals, including nicotine, flavorings, and other additives (e.g., propellants, solvents, and oils). Users inhale the aerosol, including any additives, into their lungs. Aerosols produced by e-cigarettes can contain harmful or potentially harmful substances, including heavy metals such as lead, volatile organic compounds, ultrafine particles, cancer-causing chemicals, or other agents such as chemicals used for cleaning the device (1). E-cigarettes also can be used to deliver tetrahydrocannabinol (THC), the principal psychoactive component of cannabis, or other drugs; for example, "dabbing" involves superheating substances that contain high concentrations of THC and other plant compounds (e.g., cannabidiol) with the intent of inhaling the aerosol. E-cigarette users could potentially add other substances to the devices. This report summarizes available information and provides interim case definitions and guidance for reporting possible cases of severe pulmonary disease. The guidance in this report reflects data available as of September 6, 2019; guidance will be updated as additional information becomes available.

U.S. National 90-Day Readmissions After Opioid Overdose Discharge.

INTRODUCTION: U.S. hospital discharges for opioid overdose increased substantially during the past two decades. This brief report describes 90-day readmissions among patients discharged from inpatient stays for opioid overdose. METHODS: In 2018, survey-weighted analysis of hospital stays in the 2016 Healthcare Cost and Utilization Project National Readmissions Database yielded the national estimated proportion of patients with opioid overdose stays that had all-cause readmissions within ≤90 days. A multivariable logistic regression model assessed index stay factors associated with readmission by type (opioid overdose or not). Number of readmissions per patient was assessed. RESULTS: More than 24% (n=14,351/58,850) of patients with non-fatal index stays for opioid overdose had at least one all-cause readmission ≤90 days of index stay discharge and 3% (n=1,658/58,850) of patients had at least one opioid overdose readmission. Less than 0.2% (n=104/58,850) of patients had more than one readmission for opioid overdose. Patient demographic characteristics (e.g., male, older age), comorbidities diagnosed during the index stay (e.g., drug use disorder, chronic pulmonary disease, psychoses), and other index stay factors (Medicare or Medicaid primary payer, discharge against medical advice) were significantly associated with both opioid overdose and non-opioid overdose readmissions. Nearly 30% of index stays for opioid overdose included heroin, which was significantly associated with opioid overdose readmissions. CONCLUSIONS: A quarter of opioid overdose patients have ≤90 days all-cause readmissions, although opioid overdose readmission is uncommon. Effective strategies to reduce readmissions will address substance use disorder as well as comorbid physical and mental health conditions.

Trends and Patterns of Geographic Variation in Opioid Prescribing Practices by State, United States, 2006-2017.

Importance: Risk of opioid use disorder, overdose, and death from prescription opioids increases as dosage, duration, and use of extended-release and long-acting formulations increase. States are well suited to respond to the opioid crisis through legislation, regulations, enforcement, surveillance, and other interventions. Objective: To estimate temporal trends and geographic variations in 6 key opioid prescribing measures in 50 US states and the District of Columbia. Design, Setting, and Participants: Population-based cross-sectional analysis of opioid prescriptions filled nationwide at US retail pharmacies between January 1, 2006, and December 31, 2017. Data were obtained from the IQVIA Xponent database. All US residents who had an opioid prescription filled at a US retail pharmacy were included. Main Outcomes and Measures: Primary outcomes were annual amount of opioids prescribed in morphine milligram equivalents (MME) per person; mean duration per prescription in days; and 4 separate prescribing rates-for prescriptions 3 or fewer days, those 30 days or longer, those with a high daily dosage (≥90 MME), and those with extended-release and long-acting formulations. Results: Between 2006 and 2017, an estimated 233.7 million opioid prescriptions were filled in retail pharmacies in the United States each year. For all states combined, 4 measures decreased: (1) mean (SD) amount of opioids prescribed (mean [SD] decrease, 12.8% [12.6%]) from 628.4 (178.0) to 543.4 (158.6) MME per person, a statistically significant decrease in 23 states; (2) high daily dosage (mean [SD] decrease, 53.1% [13.6%]) from 12.3 (3.4) to 5.6 (1.7) per 100 persons, a statistically significant decrease in 49 states; (3) short-term (≤3 days) duration (mean [SD] decrease, 43.1% [9.4%]) from 18.0 (5.4) to 10.0 (2.5) per 100 persons, a statistically significant decrease in 48 states; and (4) extended-release and long-acting formulations (mean [SD] decrease, 14.7% [13.7%]) from 7.2 (1.9) to 6.0 (1.7) per 100 persons, a statistically significant decrease in 27 states. Two measures increased, each associated with the duration of prescription dispensed: (1) mean (SD) prescription duration (mean [SD] increase, 37.6% [6.9%]) from 13.0 (1.2) to 17.9 (1.4) days, a statistically significant increase in every state; and (2) prescriptions for a term of 30 days or longer (mean [SD] increase, 37.7% [28.9%]) from 18.3 (7.7) to 24.9 (10.7) per 100 persons, a statistically significant increase in 39 states. Two- to 3-fold geographic differences were observed across states, measured by comparing the ratio of each state's 90th to 10th percentile for each measure. Conclusions and Relevance: In this study, across 12 years, the mean duration and prescribing rate for long-term prescriptions of opioids increased, whereas the amount of opioids prescribed per person and prescribing rate for high-dosage prescriptions, short-term prescriptions, and extended-release and long-acting formulations decreased. Some decreases were significant, but results were still high. Two- to 3-fold state variation in 5 measures occurred in most states. This information may help when state-specific intervention programs are being designed.

Prevalence of Nonopioid and Opioid Prescriptions Among Commercially Insured Patients with Chronic Pain.

Objective The increased use of opioids to treat chronic pain in the past 20 years has led to a drastic increase in opioid prescribing in the United States. The Centers for Disease Control and Prevention's (CDC's) Guideline for Prescribing Opioids for Chronic Pain recommends the use of nonopioid therapy as the preferred treatment for chronic pain. This study analyzes the prevalence of nonopioid prescribing among commercially insured patients with chronic pain. Design Data from the 2014 IBM® MarketScan® databases representing claims for commercially insured patients were used. International Classification of Diseases, Ninth Revision, codes were used to identify patients with chronic pain. Nonopioid prescriptions included nonsteroidal anti-inflammatory drugs (NSAIDs), analgesics/antipyretics (e.g., acetaminophen), anticonvulsants, and antidepressant medications. The prevalence of nonopioid and opioid prescriptions was calculated by age, sex, insurance plan type, presence of a depressive or seizure disorder, and region. Results In 2014, among patients with chronic pain, 16% filled only an opioid, 17% filled only a nonopioid prescription, and 28% filled both a nonopioid and an opioid. NSAIDs and antidepressants were the most commonly prescribed nonopioids among patients with chronic pain. Having prescriptions for only nonopioids was more common among patients aged 50-64 years and among female patients. Conclusions This study provides a baseline snapshot of nonopioid prescriptions before the release of the CDC Guideline and can be used to examine the impact of the CDC Guideline and other evidence-based guidelines on nonopioid use among commercially insured patients with chronic pain.

US hospital discharges documenting patient opioid use disorder without opioid overdose or treatment services, 2011-2015.

BACKGROUND: Understanding more about circumstances in which patients receive an opioid use disorder (OUD) diagnosis might illuminate opportunities for intervention and ultimately prevent opioid overdoses. This study aimed to describe patient and clinical characteristics of hospital discharges documenting OUD among patients not being treated for opioid overdose, detoxification, or rehabilitation. METHODS: We assessed patient, payer, and clinical characteristics of nationally-representative 2011-2015 National Inpatient Sample discharges documenting OUD, excluding opioid overdose, detoxification, and rehabilitation. Discharges were clinically classified by Diagnostic Related Group (DRG) for analysis. RESULTS: Annual discharges grew 38%, from 347,137 (2011) to 478,260 (2015), totaling 2 million discharges during the study period. The annual discharge rate increased among all racial/ethnic groups, but was highest among the non-Hispanic black population until 2015, when non-Hispanic whites had a slightly higher rate (164 versus 162 per 100,000 population). Female patients and Medicaid and Medicare as primary payer accounted for an increasing annual proportion of discharges. Just 14 DRGs accounted for nearly 50% of discharges over the study period. The most prevalent primary treatment received during OUD inpatient stays was for psychoses (DRG 885; 16% of discharges) and drug and alcohol abuse or dependence symptoms (including withdrawal) or (non-opioid) poisoning (DRG 894, 897, 917, 918; 12% of discharges). CONCLUSIONS: Now nearly half a million yearly US hospital discharges for a range of primary treatment include patients' diagnosis of OUD without opioid overdose, detoxification, or rehabilitation services. Inpatient stays present an important opportunity to link OUD patients to treatment to reduce opioid-related morbidity and mortality.

Fungal endophthalmitis associated with compounded products.

Fungal endophthalmitis is a rare but serious infection. In March 2012, several cases of probable and laboratory-confirmed fungal endophthalmitis occurring after invasive ocular procedures were reported nationwide. We identified 47 cases in 9 states: 21 patients had been exposed to the intraocular dye Brilliant Blue G (BBG) during retinal surgery, and the other 26 had received an intravitreal injection containing triamcinolone acetonide. Both drugs were produced by Franck's Compounding Lab (Ocala, FL, USA). Fusarium incarnatum-equiseti species complex mold was identified in specimens from BBG-exposed case-patients and an unopened BBG vial. Bipolaris hawaiiensis mold was identified in specimens from triamcinolone-exposed case-patients. Exposure to either product was the only factor associated with case status. Of 40 case-patients for whom data were available, 39 (98%) lost vision. These concurrent outbreaks, associated with 1 compounding pharmacy, resulted in a product recall. Ensuring safety and integrity of compounded medications is critical for preventing further outbreaks associated with compounded products.

Rocky mountain spotted fever hospitalizations among American Indians.

To describe the epidemiology of Rocky Mountain spotted fever (RMSF) among American Indians/Alaska Natives (AI/ANs), we conducted a retrospective analysis of hospitalization records with an RMSF diagnosis using Indian Health Service (IHS) hospital discharge data for calendar years 1980-2003. A total of 261 RMSF hospitalizations were reported among AIs, for an average annual hospitalization rate of 1.21 per 100,000 persons; two deaths were reported (0.8%). Most hospitalizations (88.5%) occurred in the Southern Plains region, where the rate was 4.23 per 100,000 persons. Children 1-4 years of age had the highest age-specific hospitalization rate of 2.50 per 100,000 persons. The overall annual RMSF hospitalization rate declined during the study period. Understanding the epidemiology of RMSF among AI/ANs and educating IHS/tribal physicians on the diagnosis of tick-borne diseases remain important for the prompt treatment of RMSF and the reduction of the disease occurrence among AI/ANs, particularly in high-risk areas.

Comparison of two major emergency department-based free-text chief-complaint coding systems.

INTRODUCTION: Emergency departments (EDs) using free-text chief-complaint data for syndromic surveillance face a unique challenge because a complaint might be described and coded in multiple ways. OBJECTIVE: Two major ED-based free-text chief-complaint coding systems were compared for agreement between free-text interpretation and syndrome coding. METHODS: Chief-complaint data from 21,736 patients at an urban ED were processed through both the New York City Department of Health and Mental Hygiene (DOHMH) syndrome coding system as modified by the Chicago Department of Public Health and the Real-Time Outbreak Detection System Complaint Coder (CoCo, version 2.1, University of Pittsburgh). To account for differences in each system's specified syndromes, relevant syndromes from the DOHMH system were collapsed into the corresponding CoCo categories so that a descriptive comparison could be made. DOHMH classifications were combined to match existing CoCo categories as follows: 1) vomit+diarrhea = Gastrointestinal; 2) cold+respiratory+asthma = Respiratory; 3) fevflu = Constitutional; 4) rash = Rash; 5) sepsis+other = Other, 6) unknown = Unknown. RESULTS: Overall agreement between DOHMH and CoCo syndrome coding was optimal (0.614 kappa). However, agreement between individual syndromes varied substantially. Rash and Respiratory had the highest agreement (0.711 and 0.594 kappa, respectively). Other and Constitutional had an intermediate level of agreement (0.453 and 0.419 kappa, respectively), but less than optimal agreement was identified for Gastrointestinal and Unknown (0.270 and 0.002 kappa, respectively). CONCLUSIONS: Although this analysis revealed optimal overall agreement between the two systems evaluated, substantial differences in classification schemes existed, highlighting the need for a consensus regarding chief-complaint classification.