Utilization, user characteristics, and adverse outcomes of insulin glargine originators and follow-on drug in patients with diabetes in the United States.

BACKGROUND: The first follow-on drug (Basaglar) of the originator insulin glargine (Lantus), a long-acting insulin for treatment of type 1 and type 2 diabetes mellitus (T1DM, T2DM), was approved in 2015 in the United States. Information on the uptake, user characteristics, and outcomes of follow-on insulin remains sparse. OBJECTIVE: To describe the utilization, user characteristics, and health outcomes of the follow-on insulin glargine and insulin glargine originators in a large, distributed network of primarily commercially insured patients in the United States. METHODS: We used health care claims data in the US Food and Drug Administration's Sentinel common data model format across 5 research partners in the Biologics & Biosimilars Collective Intelligence Consortium distributed research network. Sentinel analytic tools were used to identify adult users of insulin glargine between January 1, 2011, and February 28, 2021, and describe patient demographics, baseline clinical characteristics, and adverse health events among users of the originators and the follow-on drug, stratified by diabetes type. RESULTS: We identified 508,438 users of originator drugs and 63,199 users of the follow-on drug. The proportions of the follow-on drug users among total insulin glargine users were 9.1% (n = 7,070) for T1DM and 11.4% (n=56,129) for T2DM. Follow-on use rose from 8.2% in 2017 to 24.8% in 2020, accompanied by a steady decrease in the use of originator drugs. Demographics of the users of the originators and follow-on drug were similar among the T1DM and T2DM groups. Overall, follow-on users had poorer baseline health profile and higher proportions of episodes with adverse events in the follow-up. CONCLUSIONS: We found evidence of increased uptake of the follow-on drug relative to the originator products in the post-2016 period. The differences in the base-line clinical characteristics between users of the originator products and the follow-on drug and their relationship with health outcomes merit further research. DISCLOSURES: Sengwee Toh consults for Pfizer, Inc., and TriNetX, LLC. This study was funded by the BBCIC.

Identification of cancer chemotherapy regimens and patient cohorts in administrative claims: challenges, opportunities, and a proposed algorithm.

BACKGROUND: Real-world evidence is a valuable source of information in healthcare. This study describes the challenges and successes during algorithm development to identify cancer cohorts and multi-agent chemotherapy regimens from claims data to perform a comparative effectiveness analysis of granulocyte colony stimulating factor (G-CSF) use. METHODS: Using the Biologics and Biosimilars Collective Intelligence Consortium's Distributed Research Network, we iteratively developed and tested a de novo algorithm to accurately identify patients by cancer diagnosis, then extract chemotherapy and G-CSF administrations for a retrospective study of prophylactic G-CSF. RESULTS: After identifying patients with cancer and subsequent chemotherapy exposures, we observed only 12% of patients with cancer received chemotherapy, which is fewer than expected based on prior analyses. Therefore, we reversed the initial inclusion criteria to identify chemotherapy receipt, then prior cancer diagnosis, which increased the number of patients from 2,814 to 3,645, or 68% of patients receiving chemotherapy had diagnoses of interest. Additionally, we excluded patients with cancer diagnoses that differed from those of interest in the 183 days before the index date of G-CSF receipt, including early-stage cancers without G-CSF or chemotherapy exposure. By removing this criterion, we retained 77 patients who were previously excluded. Finally, we incorporated a 5-day window to identify all chemotherapy drugs administered (excluding oral prednisone and methotrexate, as these medications may be used for other non-malignant conditions) as patients may fill oral prescriptions days to weeks prior to infusion. This increased the number of patients with chemotherapy exposures of interest to 6,010. The final cohort of included patients, based on G-CSF exposure, increased from 420 from the initial algorithm to 886 using the final algorithm. CONCLUSIONS: Medications used for multiple indications, sensitivity and specificity of administrative codes, and relative timing of medication exposure must all be evaluated to identify patient cohorts receiving chemotherapy from claims data.

Using the IMEDS distributed database for epidemiological studies in type 2 diabetes mellitus.

INTRODUCTION: This study aimed to assess data relevancy and data quality of the Innovation in Medical Evidence Development and Surveillance System Distributed Database (IMEDS-DD) for diabetes research and to evaluate comparability of its type 2 diabetes cohort to the general type 2 diabetes population. RESEARCH DESIGN AND METHODS: A retrospective study was conducted using the IMEDS-DD. Eligible members were adults with a medical encounter between April 1, 2018 and March 31, 2019 (index period). Type 2 diabetes and co-existing conditions were determined using all data available from April 1, 2016 to the most recent encounter within the index period. Type 2 diabetes patient characteristics, comorbidities and hemoglobin A1c (HbA1c) values were summarized and compared with those reported in national benchmarks and literature. RESULTS: Type 2 diabetes prevalence was 12.6% in the IMEDS-DD. Of 4 14 672 patients with type 2 diabetes, 52.8% were male, and the mean age was 65.0 (SD 13.3) years. Common comorbidities included hypertension (84.5%), hyperlipidemia (82.8%), obesity (45.3%), and cardiovascular disease (44.7%). Moderate-to-severe chronic kidney disease was observed in 20.2% patients. The most commonly used antihyperglycemic agents included metformin (35.7%), sulfonylureas (14.8%), and insulin (9.9%). Less than one-half (48.9%) had an HbA1c value recorded. These findings demonstrated the notable similarity in patient characteristics between type 2 diabetes populations identified within the IMEDS-DD and other large databases. CONCLUSIONS: Despite the limitations related to HbA1c data, our findings indicate that the IMEDS-DD contains robust information on key data elements to conduct pharmacoepidemiological studies in diabetes, including member demographic and clinical characteristics and health services utilization.

Healthcare claims-based Lyme disease case-finding algorithms in the United States: A systematic literature review.

BACKGROUND AND OBJECTIVE: Lyme disease (LD) is the fifth most commonly reported notifiable infectious disease in the United States (US) with approximately 35,000 cases reported in 2019 via public health surveillance. However, healthcare claims-based studies estimate that the number of LD cases is >10 times larger than reported through surveillance. To assess the burden of LD using healthcare claims data and the effectiveness of interventions for LD prevention and treatment, it is important to use validated well-performing LD case-finding algorithms ("LD algorithms"). We conducted a systematic literature review to identify LD algorithms used with US healthcare claims data and their validation status. METHODS: We searched PubMed and Embase for articles published in English since January 1, 2000 (search date: February 20, 2021), using the following search terms: (1) "Lyme disease"; and (2) "claim*" or "administrative* data"; and (3) "United States" or "the US*". We then reviewed the titles, abstracts, full texts, and bibliographies of the articles to select eligible articles, i.e., those describing LD algorithms used with US healthcare claims data. RESULTS: We identified 15 eligible articles. Of these, seven studies used LD algorithms with LD diagnosis codes only, four studies used LD diagnosis codes and antibiotic dispensing records, and the remaining four studies used serologic test order codes in combination with LD diagnosis codes and antibiotics records. Only one of the studies that provided data on algorithm performance: sensitivity 50% and positive predictive value 5%, and this was based on Lyme disease diagnosis code only. CONCLUSIONS: US claims-based LD case-finding algorithms have used diverse strategies. Only one algorithm was validated, and its performance was poor. Further studies are warranted to assess performance for different algorithm designs and inform efforts to better assess the true burden of LD.

The US Food and Drug Administration Sentinel System: a national resource for a learning health system.

The US Food and Drug Administration (FDA) created the Sentinel System in response to a requirement in the FDA Amendments Act of 2007 that the agency establish a system for monitoring risks associated with drug and biologic products using data from disparate sources. The Sentinel System has completed hundreds of analyses, including many that have directly informed regulatory decisions. The Sentinel System also was designed to support a national infrastructure for a learning health system. Sentinel governance and guiding principles were designed to facilitate Sentinel's role as a national resource. The Sentinel System infrastructure now supports multiple non-FDA projects for stakeholders ranging from regulated industry to other federal agencies, international regulators, and academics. The Sentinel System is a working example of a learning health system that is expanding with the potential to create a global learning health system that can support medical product safety assessments and other research.

Patient characteristics, pain treatment patterns, and incidence of total joint replacement in a US population with osteoarthritis.

BACKGROUND: Currently available medications for chronic osteoarthritis pain are only moderately effective, and their use is limited in many patients because of serious adverse effects and contraindications. The primary surgical option for osteoarthritis is total joint replacement (TJR). The objectives of this study were to describe the treatment history of patients with osteoarthritis receiving prescription pain medications and/or intra-articular corticosteroid injections, and to estimate the incidence of TJR in these patients. METHODS: This retrospective, multicenter, cohort study utilized health plan administrative claims data (January 1, 2013, through December 31, 2019) of adult patients with osteoarthritis in the Innovation in Medical Evidence Development and Surveillance Distributed Database, a subset of the US FDA Sentinel Distributed Database. Patients were analyzed in two cohorts: those with prevalent use of "any pain medication" (prescription non-steroidal anti-inflammatory drugs [NSAIDs], opioids, and/or intra-articular corticosteroid injections) using only the first qualifying dispensing (index date); and those with prevalent use of "each specific pain medication class" with all qualifying treatment episodes identified. RESULTS: Among 1 992 670 prevalent users of "any pain medication", pain medications prescribed on the index date were NSAIDs (596 624 [29.9%] patients), opioids (1 161 806 [58.3%]), and intra-articular corticosteroids (323 459 [16.2%]). Further, 92 026 patients received multiple pain medications on the index date, including 71 632 (3.6%) receiving both NSAIDs and opioids. Altogether, 20.6% of patients used an NSAID at any time following an opioid index dispensing and 17.2% used an opioid following an NSAID index dispensing. The TJR incidence rates per 100 person-years (95% confidence interval [CI]) were 3.21 (95% CI: 3.20-3.23) in the "any pain medication" user cohort, and among those receiving "each specific pain medication class" were NSAIDs, 4.63 (95% CI: 4.58-4.67); opioids, 7.45 (95% CI: 7.40-7.49); and intra-articular corticosteroids, 8.05 (95% CI: 7.97-8.13). CONCLUSIONS: In patients treated with prescription medications for osteoarthritis pain, opioids were more commonly prescribed at index than NSAIDs and intra-articular corticosteroid injections. Of the pain medication classes examined, the incidence of TJR was highest in patients receiving intra-articular corticosteroids and lowest in patients receiving NSAIDs.

Health outcomes coding trends in the US Food and Drug Administration's Sentinel System during transition to International Classification of Diseases-10 coding system: A brief review.

BACKGROUND AND PURPOSE: The transition from International Classification of Diseases, 9th revision, clinical modification (ICD-9-CM) to ICD-10-CM poses a challenge to epidemiologic studies that use diagnostic codes to identify health outcomes and covariates. We evaluated coding trends in health outcomes in the US Food and Drug Administration's Sentinel System during the transition. METHODS: We reviewed all health outcomes coding trends reports on the Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the ICD-9-CM and ICD-10-CM eras by visual inspection. RESULTS: We identified 78 unique health outcomes (22 acute, 32 chronic, and 24 acute or chronic) and 140 time-series graphs of incidence and prevalence. The reports also included code lists and code mapping methods used. Of the 140 graphs reviewed, 81 (57.9%) showed consistent trends across the ICD-9-CM and ICD-10-CM eras, while 51 (36.4%) and 8 (5.7%) graphs showed inconsistent and uncertain trends, respectively. Chronic HOIs and acute/chronic HOIs had higher proportions of consistent trends in prevalence definitions (83.9% and 78.3%, respectively) than acute HOIs (28.6%). For incidence, 55.6% of acute HOIs showed consistent trends, while 41.2% of chronic HOIs and 39.3% of acute/chronic HOIs showed consistency. CONCLUSIONS: Researchers using ICD-10-CM algorithms obtained by standardized mappings from ICD-9-CM algorithms should assess the mapping performance before use. The Sentinel reports provide a valuable resource for researchers who need to develop and assess mapping strategies. The reports could benefit from additional information about the algorithm selection process and additional details on monthly incidence and prevalence rates. KEY POINTS: We reviewed health outcomes coding trends reports on the US FDA Sentinel website through November 30, 2019 and analyzed trends in incidence and prevalence across the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) and ICD-10-CM eras by code mapping method and the type of health outcomes of interest (acute, chronic, acute or chronic). More than a third of the 140 time-series graphs of incidence and prevalence of health outcomes showed inconsistent or uncertain trends. Consistency in trends varied by code mapping method, type of health outcomes of interest, and whether the measurement was incidence or prevalence. Studies using ICD-9-CM-based algorithms mapped to ICD-10-CM codes need to assess the performance of the mappings and conduct manual refinement of the algorithms as needed before using them.

Patient Characteristics and Utilization Patterns of Short-Acting Recombinant Granulocyte Colony-Stimulating Factor (G-CSF) Biosimilars Compared to Their Reference Product.

BACKGROUND: Data on short-acting recombinant granulocyte colony-stimulating factor (G-CSF) biosimilar utilization from claims data in the USA are limited. OBJECTIVE: To evaluate patient baseline characteristics and utilization patterns for short-acting G-CSF products with particular focus on the assessment of filgrastim biosimilar usage relative to the originator product. PATIENTS AND METHODS: We examined filgrastim, filgrastim-sndz, and tbo-filgrastim use among adult patients between January 2012 and March 2019 across the five health-plan research partners in the BBCIC Distributed Research Network. The publicly available Sentinel System analytic toolkit was used to perform the distributed analyses. RESULTS: We evaluated over 38 million eligible health-plan members representing more than 88 million person-years of data. We identified 45,204 incident treatment episodes, including 33,118 episodes with filgrastim, 6525 episodes with filgrastim-sndz, and 5,561 episodes with tbo-filgrastim. We observed that the demographic and clinical characteristics of users were comparable across products. While total use of all filgrastim products remained consistent, the proportion of incident episodes of the originator filgrastim steadily decreased since 2014, with filgrastim-sndz and tbo-filgrastim making up the difference. Utilization for the G-CSF biosimilar, filgrastim-sndz, increased from 40 (1%) of 6823 total filgrastim product episodes in 2015, to 2486 (44%) of a total 5668 episodes of filgrastim products in 2018 (partial data for 2018). CONCLUSION: New episodes of short-acting biosimilar filgrastim products have increased over time while the overall number of new users remained flat. Although barriers to biosimilar use in oncology have been noted, uptake has begun and continues to grow.

Utilization patterns and characteristics of users of biologic anti-inflammatory agents in a large, US commercially insured population.

We report utilization patterns and characteristics of patients treated with biologic anti-inflammatory agents in a large commercially insured patient population in the United States. We identified adult (age ≥18 years) patients receiving biologic anti-inflammatory agents between 1 January 2012 and 31 March 2019 across the five Research Partners in the Biologic and Biosimilars Collective Intelligence Consortium's Distributed Research Network. We examined the number of incident use episodes for each biologic, as well as patient demographic and clinical characteristics. Curated data and analytic tools from the Food and Drug Administration's Sentinel System were used to perform the analyses. We identified 90,360 incident episodes of tumor necrosis factor-alpha inhibitors (TNFi) and 70,506 incident episodes of non-TNFi medications. Adalimumab was the most common TNFi drug (47% of all TNFi episodes) and showed a steady increase in utilization during the study period compared to other TNFi agents. Rituximab was the most commonly initiated non-TNFi medication (44% of non-TNFi episodes). Other non-TNFi agents, namely, ustekinumab, vedolizumab, and secukinumab, demonstrated notable increases in utilization over time. Biosimilar use was limited; we observed 653 incident episodes for infliximab-dyyb and 39 incident episodes for infliximab-abda. As more biologics enter the market, greater variation in the use of biologics with similar indications and between biologic originators and biosimilars is anticipated. Because information on efficacy and safety at the time of drug approval is limited, post-marketing surveillance and research is needed to monitor medication safety and evaluate effectiveness between biologic drugs using real-world data.

Capture of biologic and biosimilar dispensings in a consortium of U.S.-based claims databases: Utilization of national drug codes and Healthcare Common Procedure Coding System modifiers in medical claims.

PURPOSE: To assess the capture of biologics (originator and biosimilar) in the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN), with a focus on medical claim National Drug Code (NDC), a new data field, and Healthcare Common Procedure Coding System (HCPCS) modifier. METHODS: We conducted a repeated cross-sectional study among patients with medical and pharmacy benefits enrolled in insurance plans participating in the BBCIC DRN between 1 January 2013 and 30 September 2017. We calculated the proportion of medical claims with ≥1 NDC and identified select biologics using four different approaches: (a) specific HCPCS alone, (b) specific HCPCS and NDC, (c) non-specific HCPCS with NDC, and (d) HCPCS with modifiers (applicable to biosimilars). Numbers of dispensings were calculated for each biologic by approach and select patient and claim characteristics. RESULTS: More than 1.5 million eligible participants contributed approximately 4 million person-years of data, including 1.2 billion medical claims. The proportion of medical claims with ≥1 NDC increased from 1.2% in 2013 to 3.0% in 2017. Medical claim NDCs identified 39% and 28% of vedolizumab dispensed in 2014 and 2015 and 30% of Epogen/Procrit dispensed overall. Out of 26,381 filgrastim biosimilar dispensings identified, 51% had a HCPCS modifier and 12% had a medical claim NDC for Zarxio. HCPCS modifiers and medical claim NDCs were present for 38% and 3% of all infliximab biosimilars dispensed (total n = 1,244). CONCLUSIONS: Medical claim NDC and HCPCS modifier improves identification of select biologics without product-specific HCPCS code, thereby facilitating product-specific biologic research.

Mapping from the International Classification of Diseases (ICD) 9th to 10th Revision for Research in Biologics and Biosimilars Using Administrative Healthcare Data.

PURPOSE: The Centers for Medicare and Medicaid Services (CMS) mandated the transition from ICD-9 to ICD-10 codes on October 1, 2015. Postmarketing surveillance of newly marketed drugs, including novel biologics and biosimilars, requires a robust approach to convert ICD-9 to ICD-10 codes for study variables. We examined three mapping methods for health conditions (HCs) of interest to the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) and compared their prevalence. METHODS: Using CMS General Equivalence Mappings, we applied forward-backward mapping (FBM) to 108 HCs and secondary mapping (SM) and tertiary mapping (TM) to seven preselected HCs. A physician reviewed the mapped ICD-10 codes. The prevalence of the 108 HCs defined by ICD-9 versus ICD-10 codes was examined in BBCIC's distributed research network (September 1, 2012 to March 31, 2018). We visually assessed prevalence trends of these HCs and applied a threshold of 20% level change in ICD-9 versus ICD-10 prevalence. RESULTS: Nearly four times more ICD-10 codes were mapped by SM and TM than FBM, but most were irrelevant or nonspecific. For conditions like myocardial infarction, SM or TM did not generate additional ICD-10 codes. Through visual inspection, one-fifth of the HCs had inconsistent ICD-9 versus ICD-10 prevalence trends. 13% of HCs had a level change greater than +/-20%. CONCLUSION: FBM is generally the most efficient way to convert ICD-9 to ICD-10 codes, yet manual review of converted ICD-10 codes is recommended even for FBM. The lack of existing guidance to compare the performance of ICD-9 with ICD-10 codes led to challenges in empirically determining the quality of conversions.

Risk Factors for Bloodstream Infections Among an Urban Population with Skin and Soft Tissue Infections: A Retrospective Unmatched Case-Control Study.

INTRODUCTION: The prevalence of acute bacterial skin and skin structure infections (ABSSSIs) continues to increase. Bloodstream infection (BSI) is a severe secondary complication of ABSSSI. The objective of this study was to determine clinical and sociodemographic risk factors for BSI in patients with acute bacterial skin and skin structure infections (ABSSSIs) and to determine if sociodemographic factors impact severity at presentation. METHODS: This was a retrospective unmatched (1:1) case-control study. Predictors of BSI and severe infection were sought through multivariable logistic regression analyses. Cases and controls were collected from two major medical centers located in downtown Detroit, Michigan: the Detroit Medical Center and the Henry Ford Health System. The population of interest included adult patients with community-onset (CO) ABSSSI treated at a participating hospital between January 2010 and December 2015. Cases were defined as those developing BSI within 48 h of admission with CO-ABSSSI as the primary source, while controls were those with CO-ABSSSI without BSI. RESULTS: A total of 392 patients (196 cases, 196 controls) were included. Independent predictors of BSI were male gender (aOR 1.85: 95% CI 1.11, 3.66), acute renal failure (aOR 2.08: 95% CI 1.18, 3.66), intravenous drug use (aOR 4.38, 95% CI 2.22, 8.62), and prior hospitalization (aOR 2.41, 95% CI 1.24, 4.93). African American race (aOR 2.18, 95% CI 1.38, 3.4), leukocytosis (aOR 2.24, 95% CI 1.41, 3.55), and prior hospitalization (aOR 2.07, 95% CI 1.19, 3.00) were significantly associated with infection severity. CONCLUSION: Both clinical and sociodemographic factors were associated with BSI and severe infection underscoring the importance of social determinants of health in outcomes among underserved populations.

Comparative effectiveness of uterine fibroids procedures using linked medical record and claims data.

AIMS: To compare durability of uterus-conserving procedures for symptomatic fibroids in terms of incidence and time to subsequent procedures. PATIENTS & METHODS: We conducted a retrospective database study of 2648 patients having a uterus-conserving procedure for uterine fibroids from 2005 to 2011 with a minimum of 2 years follow-up. RESULTS: Patients with myomectomy or uterine artery embolization as their index procedure had lower risk of a subsequent procedure during the study compared with patients who underwent endometrial ablation. CONCLUSION: While subject to known limitations of using electronic medical record and administrative claims data, this research provides additional evidence regarding expectations for time to subsequent procedures that may be helpful for women and their healthcare providers to consider when making treatment choices.

Characterization of Missing Data in Clinical Registry Studies.

Patterns of missing data are seldom well-characterized in observational research. This study examined the magnitude of, and factors associated with, missing data across multiple observational studies. Missingness was evaluated for demographic, clinical, and patient-reported outcome (PRO) data from a procedure registry (TOPS), a rare disease (cystic fibrosis) registry (Port-CF), and a comparative effectiveness registry (glaucoma, RiGOR). Generalized linear mixed effects models were fit to assess whether patient characteristics or follow-up methods predicted missingness. Data from 156,707 surgical procedures, 32,118 cystic fibrosis patients, and 2373 glaucoma patients were analyzed. Data were rarely missing for demographics, treatments, and outcomes. Missingness for clinical variables varied by registry and measure and depended on whether a variable was required. Within RiGOR, PRO forms were missing more often when collected by e-mail compared with office-based paper data collection. In Port-CF, missingness varied based on insurance status and sex. Strategic consideration of operational approaches affecting missing data should be performed prior to data collection and assessed periodically during study conduct.

Radon-contaminated drinking water from private wells: an environmental health assessment examining a rural Colorado mountain community's exposure.

In the study discussed in this article, 27 private drinking water wells located in a rural Colorado mountain community were sampled for radon contamination and compared against (a) the U.S. Environmental Protection Agency's (U.S. EPA's) proposed maximum contaminant level (MCL), (b) the U.S. EPA proposed alternate maximum contaminate level (AMCL), and (c) the average radon level measured in the local municipal drinking water system. The data from the authors' study found that 100% of the wells within the study population had radon levels in excess of the U.S. EPA MCL, 37% were in excess of the U.S. EPA AMCL, and 100% of wells had radon levels greater than that found in the local municipal drinking water system. Radon contamination in one well was found to be 715 times greater than the U.S. EPA MCL, 54 times greater than the U.S. EPA AMLC, and 36,983 times greater than that found in the local municipal drinking water system. According to the research data and the reviewed literature, the results indicate that this population has a unique and elevated contamination profile and suggest that radon-contaminated drinking water from private wells can present a significant public health concern.

Evaluation and overview of the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance Project (NEISS-CADES).

BACKGROUND: Adverse drug events (ADEs) are an important cause of patient injury. Although most medications are prescribed and used in the outpatient setting, prevention efforts focus on the inpatient setting, partly because of limited data on outpatient events. We describe and evaluate a new system for surveillance of outpatient ADEs treated in hospital emergency departments (EDs). METHODS: We used guidelines for evaluating public health surveillance systems, developed by the Centers for Disease Control and Prevention, to assess the performance of the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance project (NEISS-CADES) from January 1, 2004 through December 31, 2004. RESULTS: NEISS-CADES is a nationally representative surveillance system that identifies ADEs using ED clinical records. Of 10,383 reports in 2004, 100% listed patient age, sex, and disposition; 98% listed the implicated drugs. A 6-hospital evaluation of data quality, completeness, and other system attributes showed that NEISS-CADES data accurately reflected clinical records with respect to patient age and sex (100%), primary diagnosis (93%), implicated drugs (93%), primary treatments (80%), and diagnostic testing (61%). Sensitivity of case identification was estimated to be at least 0.33; estimated positive predictive value was 0.92. Data collection does not require additional work by clinical staff and has been well accepted by participating institutions. CONCLUSIONS: NEISS-CADES provides detailed and timely information on outpatient ADEs treated in EDs and identifies specific drugs and circumstances associated with these injuries. Findings from NEISS-CADES can help design and prioritize patient safety interventions for outpatient ADEs.

National surveillance of emergency department visits for outpatient adverse drug events.

CONTEXT: Adverse drug events are common and often preventable causes of medical injuries. However, timely, nationally representative information on outpatient adverse drug events is limited. OBJECTIVE: To describe the frequency and characteristics of adverse drug events that lead to emergency department visits in the United States. DESIGN, SETTING, AND PARTICIPANTS: Active surveillance from January 1, 2004, through December 31, 2005, through the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance project. MAIN OUTCOME MEASURES: National estimates of the numbers, population rates, and severity (measured by hospitalization) of individuals with adverse drug events treated in emergency departments. RESULTS: Over the 2-year study period, 21,298 adverse drug event cases were reported, producing weighted annual estimates of 701,547 individuals (95% confidence interval [CI], 509,642-893,452) or 2.4 individuals per 1000 population (95% CI, 1.7-3.0) treated in emergency departments. Of these cases, 3487 individuals required hospitalization (annual estimate, 117,318 [16.7%]; 95% CI, 13.1%-20.3%). Adverse drug events accounted for 2.5% (95% CI, 2.0%-3.1%) of estimated emergency department visits for all unintentional injuries and 6.7% (95% CI, 4.7%-8.7%) of those leading to hospitalization and accounted for 0.6% of estimated emergency department visits for all causes. Individuals aged 65 years or older were more likely than younger individuals to sustain adverse drug events (annual estimate, 4.9 vs 2.0 per 1000; rate ratio [RR], 2.4; 95% CI, 1.8-3.0) and more likely to require hospitalization (annual estimate, 1.6 vs 0.23 per 1000; RR, 6.8; 95% CI, 4.3-9.2). Drugs for which regular outpatient monitoring is used to prevent acute toxicity accounted for 41.5% of estimated hospitalizations overall (1381 cases; 95% CI, 30.9%-52.1%) and 54.4% of estimated hospitalizations among individuals aged 65 years or older (829 cases; 95% CI, 45.0%-63.7%). CONCLUSIONS: Adverse drug events among outpatients that lead to emergency department visits are an important cause of morbidity in the United States, particularly among individuals aged 65 years or older. Ongoing, population-based surveillance can help monitor these events and target prevention strategies.

Preferences for mechanical ventilation among survivors of prolonged mechanical ventilation and tracheostomy.

BACKGROUND: Among survivors of prolonged mechanical ventilation, preferences for this treatment have rarely been explored. OBJECTIVES: To elicit preferences of survivors of prolonged mechanical ventilation (>or=7 days) and factors influencing these preferences. METHODS: A descriptive, cross-sectional survey design was used. Subjects were recruited from intensive care units in a tertiary care hospital and from long-term care facilities. Each subject (n = 30) was asked to reflect on the decision to use mechanical ventilation; rate current health, pain/discomfort in the intensive care unit and from mechanical ventilation, perceived family financial burden, and emotional/physical stress related to mechanical ventilation; identify changes that would influence preference for mechanical ventilation; and answer questions about quality of life, functional status, depressive symptoms, and communication. RESULTS: Most subjects (75.9%) would have chosen mechanical ventilation. Median days of mechanical ventilation and tracheostomy were greater for subjects who would have chosen mechanical ventilation (98.5 vs 70), as were median days of tracheostomy (102 vs 64). Patients who would not have chosen mechanical ventilation had more depressive symptoms and were more likely to be insured by Medicare. No other variables differed between groups. Patients who preferred mechanical ventilation would change their preference on the basis of their families' emotional/physical stress and financial burden. Patients who did not prefer mechanical ventilation would change their preference if the family financial burden and emotional/physical stress were reduced and current health improved. CONCLUSIONS: Most patients would have chosen mechanical ventilation. Survivors' preferences were influenced by their current health and families' financial burden and stress.

The evidence base for public health informing policy at the Centers for Disease Control and Prevention.

BACKGROUND: As part of a major re-examination of its organization, in 2004, the Centers for Disease Control and Prevention (CDC) assessed the evidence base for the effectiveness of population-based public health intervention programs. METHODS: For the leading causes of disease, injury, and disability, evidence was systematically reviewed for modifiable risk factors and their attributable fractions, and for public health interventions and their preventable fractions. RESULTS: For 31 conditions, 194 modifiable risk factors were identified, and attributable fractions were found for 65 (33.5%). For 137 (70.6%) of the risk factors, 702 population-based interventions were found. Preventable fractions were found for 31 (4.4%) of the interventions. CONCLUSIONS: Despite considerable information about both modifiable risk factors and interventions designed to reduce the risks of the major causes of disease, injury, and disability, the evidence base that describes the effectiveness of these interventions is limited. The CDC is committed to support research that will set priorities for program development and identify effective public health interventions.