Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.

PURPOSE: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD). METHODS: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from four Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the Joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated. RESULTS: Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the four Data Partners. CONCLUSIONS: The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the Food and Drug Administration's MSDD.

Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database.

PURPOSE: The validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify diagnoses of severe acute liver injury (SALI) is not well known. We examined the positive predictive values (PPVs) of hospital ICD-9-CM diagnoses in identifying SALI among health plan members in the Mini-Sentinel Distributed Database (MSDD) for patients without liver/biliary disease and for those with chronic liver disease (CLD). METHODS: We selected random samples of members (149 without liver/biliary disease; 75 with CLD) with a principal hospital diagnosis suggestive of SALI (ICD-9-CM 570, 572.2, 572.4, 572.8, 573.3, 573.8, or V42.7) in the MSDD (2009-2010). Medical records were reviewed by hepatologists to confirm SALI events. PPVs of codes and code combinations for confirmed SALI were determined by CLD status. RESULTS: Among 105 members with available records and no liver/biliary disease, SALI was confirmed in 26 (PPV, 24.7%; 95%CI, 16.9-34.1%). Combined hospital diagnoses of acute hepatic necrosis (570) and liver disease sequelae (572.8) had high PPV (100%; 95%CI, 59.0-100%) and identified 7/26 (26.9%) events. Among 46 CLD members with available records, SALI was confirmed in 19 (PPV, 41.3%; 95%CI, 27.0-56.8%). Acute hepatic necrosis (570) or hepatorenal syndrome (572.4) plus any other SALI code had a PPV of 83.3% (95%CI, 51.6-97.9%) and identified 10/19 (52.6%) events. CONCLUSIONS: Most individual hospital ICD-9-CM diagnoses had low PPV for confirmed SALI events. Select code combinations had high PPV but did not capture all events.

Characterizing vaccine-associated risks using cubic smoothing splines.

Estimating risks associated with the use of childhood vaccines is challenging. The authors propose a new approach for studying short-term vaccine-related risks. The method uses a cubic smoothing spline to flexibly estimate the daily risk of an event after vaccination. The predicted incidence rates from the spline regression are then compared with the expected rates under a log-linear trend that excludes the days surrounding vaccination. The 2 models are then used to estimate the excess cumulative incidence attributable to the vaccination during the 42-day period after vaccination. Confidence intervals are obtained using a model-based bootstrap procedure. The method is applied to a study of known effects (positive controls) and expected noneffects (negative controls) of the measles, mumps, and rubella and measles, mumps, rubella, and varicella vaccines among children who are 1 year of age. The splines revealed well-resolved spikes in fever, rash, and adenopathy diagnoses, with the maximum incidence occurring between 9 and 11 days after vaccination. For the negative control outcomes, the spline model yielded a predicted incidence more consistent with the modeled day-specific risks, although there was evidence of increased risk of diagnoses of congenital malformations after vaccination, possibly because of a "provider visit effect." The proposed approach may be useful for vaccine safety surveillance.

Risk of myocardial infarction, stroke, and fracture in a cohort of community-based breast cancer patients.

Clinical trials suggest that increased risk of osteoporosis and fracture are the only serious side effects of adjuvant aromatase inhibitors (AIs), but little is known regarding toxicities of AIs in non-trial populations. We evaluated whether use of AIs was associated with myocardial infarction, stroke, and fracture in a community-based population. Using data from the HealthCore Integrated Research Database, 44,463 women aged ≥ 50 years with ≥ 2 breast cancer diagnosis codes between 2001 and 2007 were followed through 2008. Of these, 44,026 were matched using propensity score methods to women aged ≥ 50 years with no breast cancer codes. We assessed whether treatment with AIs was associated with myocardial infarction, stroke, and fracture using Cox proportional hazards models with time-varying treatment variables. Among breast cancer patients, 68.7% received no hormonal therapy, 20.6% received AIs (15.8% received only AIs, 4.8% were also treated with tamoxifen), and 10.7% received tamoxifen only. Breast cancer patients on AIs had a higher risk of any fracture (AHR = 1.13, 95% CI = 1.02-1.25) than breast cancer patients not receiving hormonal therapy. Patients on tamoxifen had a lower risk of hip fracture (AHR = 0.51, 95% CI = 0.32-0.81) than breast cancer patients not receiving hormonal therapy. Rates of myocardial infarction and stroke for patients on AIs or tamoxifen did not differ significantly from breast cancer patients not on therapy. The side effect profile of AIs in this community-based population was similar to that seen in clinical trials. These findings provide reassurance that AIs appear to be associated with few serious side effects.

Patterns of bone density evaluation in a community population treated with aromatase inhibitors.

Aromatase inhibitors (AIs) increase the risk of bone loss and fracture. Guidelines recommend routine bone density screening for women on AIs, but there are few data regarding the incorporation of these guidelines into clinical practice. We assessed bone density testing in a community-based cohort of breast cancer patients treated with AIs. By means of encounter and pharmacy data from WellPoint plans in the HealthCore Integrated Research Database, we assessed bone density testing among 9,138 women aged ≥50 years with breast cancer who were treated with AIs between 2002 and 2008. We used multivariable logistic regression to identify factors associated with baseline bone density testing in women initiating an AI, and among a subset of 2,086 women treated with AIs for at least 2 years, with testing during the first 2 years of therapy. Only 41.6 % of women underwent bone density testing when initiating AI therapy. Rates of bone density testing increased over time, but were lower for women who were older, lived in the Northeast (vs. other regions), had been treated with prior proton pump inhibitor or tamoxifen therapy, lived in areas with lower educational attainment, or were enrolled in a health maintenance organization (vs. other insurance types) (all P < 0.05). Among women treated with AIs for at least 2 years, 59.9 % of women underwent bone density testing during the first 2 years of AI therapy. Rates of testing were lower for women living in the Midwest or West (vs. Northeast), living in areas with lower education levels, enrolled in health maintenance organizations (vs. other insurance types), and with prior tamoxifen use. In conclusion, most women initiating AI therapy, and 40 % of those on long-term therapy, did not undergo recommended bone density evaluation in this community-based population. Attention is needed to insure that unnecessary fractures are avoided in breast cancer patients taking AIs.

Immune globulins and thrombotic adverse events as recorded in a large administrative database in 2008 through 2010.

BACKGROUND: Thrombotic events (TEs) are rare but often serious adverse events that could occur after administration of immune globulin (IG) products. Our study objective was to assess occurrence of recorded TEs after administration of different US-licensed IG products and investigate potential risk factors using a large administrative database. STUDY DESIGN AND METHODS: This is a retrospective claims-based cohort study of individuals exposed to IG products from January 1, 2008, through September 30, 2010, using HealthCore's Integrated Research Database, a longitudinal health care database. IG products were identified by recorded Healthcare Common Procedure Coding System codes. TEs were ascertained via International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for same-day TEs by IG product, while controlling for confounders. RESULTS: Of 11,785 individuals exposed to IG products in the study period, 122 (1%) had TE(s) recorded on the same day as IG administration. TE rates per 1000 persons exposed ranged from 6.1 to 20.5 for different IG product groups. Vivaglobin users had an increased same-day TE risk compared to reference Gammagard Liquid users (OR, 3.56; 95% CI, 1.54-8.23). An increased TE risk was also found with older age (≥ 45 years), prior TE(s), and hypercoagulable state(s). CONCLUSION: The study suggests potentially elevated TE rates for different IG products, including subcutaneous. It also identifies important recipient TE risk factors and suggests that risk-benefit profiles should be weighed before IG administration. The observed differences may be due to various factors such as dosage, administration rates, and product manufacturing processes that warrant further evaluation.

Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments.

BACKGROUND: Adjusting for laboratory test results may result in better confounding control when added to administrative claims data in the study of treatment effects. However, missing values can arise through several mechanisms. METHODS: We studied the relationship between availability of outpatient lab test results, lab values, and patient and system characteristics in a large healthcare database using LDL, HDL, and HbA1c in a cohort of initiators of statins or Vytorin (ezetimibe & simvastatin) as examples. RESULTS: Among 703,484 patients 68% had at least one lab test performed in the 6 months before treatment. Performing an LDL test was negatively associated with several patient characteristics, including recent hospitalization (OR = 0.32, 95% CI: 0.29-0.34), MI (OR = 0.77, 95% CI: 0.69-0.85), or carotid revascularization (OR = 0.37, 95% CI: 0.25-0.53). Patient demographics, diagnoses, and procedures predicted well who would have a lab test performed (AUC = 0.89 to 0.93). Among those with test results available claims data explained only 14% of variation. CONCLUSIONS: In a claims database linked with outpatient lab test results, we found that lab tests are performed selectively corresponding to current treatment guidelines. Poor ability to predict lab values and the high proportion of missingness reduces the added value of lab tests for effectiveness research in this setting.

Validation of a claims-based diagnostic code for Stevens-Johnson syndrome in a commercially insured population.

PURPOSE: To validate the administrative claims identification of a diagnosis of Stevens-Johnson syndrome (SJS) using medical records as the "gold standard" in a large, commercially insured US population. METHODS: Patients with >1 medical claim with the International Classification of Diseases, Ninth Revision, Clinical Modification code 695.1x between 1 July 2000 and 31 May 2007 were queried in the HealthCore Integrated Research Database(SM) , which contains administrative claims data for 14 commercial health insurance plans. Trained nurses and pharmacists abstracted pertinent information from the identified patients' medical records, which were then reviewed by two independent dermatologists to identify criteria to determine SJS diagnosis. Positive predictive values (PPVs) based on the claims and chart data were computed for all the cases. RESULTS: Medical charts for 200 claims-identified cases, with the International Classification of Diseases, Ninth Revision, Clinical Modification code 695.1x, were abstracted and reviewed by the dermatologists. A total of five cases (PPV = 2.50%, 95%CI = 0.8%-5.7%) were determined to be SJS with clinical certainty. PPVs varied with data stratification: PPV for inpatient claims only (PPV = 2.00%, 95%CI = 0.24%-7.04%), inpatient claims with 695.1x in first diagnosis field (PPV = 4.11%, 95%CI = 0.86%-11.54%), and final decisions of either clinical certainty or probable cases of SJS (PPV = 6.00%, 95%CI = 3.14%-10.25%). CONCLUSION: These findings demonstrate the difficulties associated with identifying rare disorders, which lack specific diagnostic criteria, within administrative claims databases. They underscore the challenges of using claims data to monitor ill-defined clinical conditions as well as the need to validate claims-identified cases with information from other sources, such as medical charts. Copyright © 2012 John Wiley & Sons, Ltd.

Design considerations, architecture, and use of the Mini-Sentinel distributed data system.

PURPOSE: We describe the design, implementation, and use of a large, multiorganizational distributed database developed to support the Mini-Sentinel Pilot Program of the US Food and Drug Administration (FDA). As envisioned by the US FDA, this implementation will inform and facilitate the development of an active surveillance system for monitoring the safety of medical products (drugs, biologics, and devices) in the USA. METHODS: A common data model was designed to address the priorities of the Mini-Sentinel Pilot and to leverage the experience and data of participating organizations and data partners. A review of existing common data models informed the process. Each participating organization designed a process to extract, transform, and load its source data, applying the common data model to create the Mini-Sentinel Distributed Database. Transformed data were characterized and evaluated using a series of programs developed centrally and executed locally by participating organizations. A secure communications portal was designed to facilitate queries of the Mini-Sentinel Distributed Database and transfer of confidential data, analytic tools were developed to facilitate rapid response to common questions, and distributed querying software was implemented to facilitate rapid querying of summary data. RESULTS: As of July 2011, information on 99,260,976 health plan members was included in the Mini-Sentinel Distributed Database. The database includes 316,009,067 person-years of observation time, with members contributing, on average, 27.0 months of observation time. All data partners have successfully executed distributed code and returned findings to the Mini-Sentinel Operations Center. CONCLUSION: This work demonstrates the feasibility of building a large, multiorganizational distributed data system in which organizations retain possession of their data that are used in an active surveillance system.

A protocol for active surveillance of acute myocardial infarction in association with the use of a new antidiabetic pharmaceutical agent.

PURPOSE: To describe a protocol for active surveillance of acute myocardial infarction (AMI) in users of a recently approved oral antidiabetic medication, saxagliptin, and to provide the rationale for decisions made in drafting the protocol. METHODS: A new-user cohort design is planned for evaluating data from at least four Mini-Sentinel data partners from 1 August 2009 (following US Food and Drug Administration's approval of saxagliptin) through mid-2013. New users of saxagliptin will be compared in separate analyses with new users of sitagliptin, pioglitazone, long-acting insulins, and second-generation sulfonylureas. Two approaches to controlling for confounding will be evaluated: matching by exposure propensity score and stratification by AMI risk score. The primary analyses will use Cox regression models specified in a way that does not require pooling of patient-level data from the data partners. The Cox models are fit to summarized data on risk sets composed of saxagliptin users and similar comparator users at the time of an AMI. Secondary analyses will use alternative methods including Poisson regression and will explore whether further adjustment for covariates available only at some data partners (e.g., blood pressure) modifies results. RESULTS: The results of this study are pending. CONCLUSIONS: The proposed protocol describes a design for surveillance to evaluate the safety of a newly marketed agent as postmarket experience accrues. It uses data from multiple partner organizations without requiring sharing of patient-level data and compares alternative approaches to controlling for confounding. It is hoped that this initial active surveillance project of the Mini-Sentinel will provide insights that inform future population-based surveillance of medical product safety.

Accuracy of identifying neutropenia diagnoses in outpatient claims data.

PURPOSE: Diagnosis codes have been valid tools to identify severe neutropenia leading to hospitalization in claims data, but no data exist on the accuracy of outpatient diagnosis of neutropenia. We examined the validity and accuracy of claims-based algorithms to identify neutropenia from outpatient visits. METHODS: Adults with outpatient diagnosis of neutropenia in the HealthCore Integrated Research Database™ were identified by several algorithms using a combination of International Classification of Diseases, 9th Revision (ICD-9) codes and drug use data. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value of these algorithms using outpatient laboratory data within 3 months of the diagnosis as the gold standard to ascertain cases of mild (absolute neutrophil count (ANC) <1,500/µL) and severe (ANC <500/µL) neutropenia. RESULTS: Among 95,742 eligible subjects, 867 patients were identified with any ICD-9 codes for neutropenia. This algorithm had high specificity (99%), but low sensitivity (9%) and PPV (18%) for mild neutropenia. Among the subjects identified with the ICD-9 288.0 (N = 203), sensitivity was 4% and PPV was 33%. Specificity and PPV of the algorithm that combined any ICD-9 codes for neutropenia with dispensing of pegfilgrastim or filgrastim were 100 and 56% for mild neutropenia, respectively. Sensitivity was 1%. All algorithms had slightly higher sensitivity, but lower PPV for severe neutropenia. CONCLUSIONS: Use of ICD-9 codes for neutropenia in combination with drug use data did not appear to accurately identify outpatient diagnosis of neutropenia without using laboratory results, but it may be useful in determining the absence of neutropenia in claims data.

Cardiovascular safety of ADHD medications: rationale for and design of an investigator-initiated observational study.

PURPOSE: To describe the design and rationale of an investigator-initiated observational study to examine the cardiovascular safety of the following commonly-used medications to treat attention deficit hyperactivity disorder (ADHD): amphetamines, methylphenidate, and atomoxetine. METHODS: We are conducting an observational cohort study using data from five large Medicaid programs and the HealthCore Integrated Research Database (HIRD(SM)), which is derived from administrative data from commercial health plans. Our primary outcomes of interest are (1) sudden death/ventricular arrhythmia, (2) stroke, (3) myocardial infarction, and (4) stroke or myocardial infarction as a composite outcome. These claims diagnoses have been previously validated in adults, and the positive predictive value in children will be examined as part of this study. Secondary outcomes are (1) all-cause death, (2) non-suicide death, and (3) non-accident death. All design decisions have been made to minimize bias toward the null. Based on our pilot data, we expect to have at least 90% power to detect a minimum detectable hazard ratio (HR) of 3.0 in children and adolescents who initiate an ADHD medication for each outcome of interest (except for MI, for which the expected minimum detectable HR is 7.9). The expected minimum detectable HR is 1.7 for each outcome for adult incident ADHD medication users. RESULTS: Forthcoming. CONCLUSIONS: Potential limitations to this study include a low expected event rate in children and adolescents, potentially incomplete ascertainment of outcomes, and potential confounding by unmeasured variables. Nevertheless, this study will provide important information about the cardiovascular safety of ADHD medications.

Paying For Value From Costly Medical Technologies: A Framework For Applying Value-Based Payment Reforms.

Innovative medical products offer significant and potentially transformative impacts on health, but they create concerns about rising spending and whether this rise is translating into higher value. The result is increasing pressure to pay for therapies in a way that is tied to their value to stakeholders through improving outcomes, reducing disease complications, and addressing concerns about affordability. Policy responses include the growing application of health technology assessments based on available evidence to determine unit prices, as well as alternatives to volume-based payment that adjust product payments based on predictors or measures of value. Building on existing frameworks for value-based payment for health care providers, we developed an analogous framework for medical products, including drugs, devices, and diagnostic tools. We illustrate each of these types of alternative payment mechanisms and describe the conditions under which each may be useful. We discuss how the use of this framework can help track reforms, improve evidence, and advance policy analysis involving medical product payment.

Value-based arrangements may be more prevalent than assumed.

OBJECTIVES: To better understand the prevalence of US value-based payment arrangements (VBAs), their characteristics, and the factors that facilitate their success or act as barriers to their implementation. STUDY DESIGN: Surveys were administered to a convenience sample of subject matter experts who were senior representatives from payer organizations and biopharmaceutical manufacturers. These data were supplemented with qualitative interviews in a subsample of survey respondents. METHODS: Descriptive statistics, including percentages for categorical values and mean (SD) and median (interquartile range) for continuous variables, were assessed for quantitative questions. Trained reviewers collated responses to free-text survey questions and the qualitative interviews to identify themes. RESULTS: Of the 25 respondents, 1 manufacturer and 4 payers reported not having explored or negotiated any VBAs. Subsequently, questionnaire results from 11 biopharmaceutical manufacturers and 9 payers who had experience with VBAs were analyzed. More than 70% of VBAs implemented between 2014 and 2017 were not publicly disclosed. Furthermore, although consideration of VBAs as a coverage and payment tool is increasing, VBA implementation is relatively low, with manufacturers and payers reporting that approximately 33% and 60% of early dialogues translate into signed VBA contracts, respectively. Respondents' reasoning for VBA negotiation process breakdowns generally differed by sector and reflected each sector's respective priorities. CONCLUSIONS: This study reveals that the majority of VBAs are not publicly disclosed, which could underestimate their true prevalence and impact. Given the effort required to implement a VBA, future arrangements would likely benefit from a framework or other evaluative tool to help assess VBA pursuit desirability and guide the negotiation and implementation process.

Implementation of a Market Entry Reward within the United States.

As part of a multifactorial approach to address weak incentives for innovative antimicrobial drug development, market entry rewards (MERs) are an emerging solution. Recently, the Duke-Margolis Center for Health Policy released the Priority Antimicrobial Value and Entry (PAVE) Award proposal, which combines a MER with payment reforms, transitioning from volume-based to "value-based" payments for antimicrobials. Here, the PAVE Award and similar MERs are reviewed, focusing on further refinement and avenues for implementation.

Characteristics of older adults who meet the annual prescription drug expenditure threshold for medicare medication therapy management programs.

BACKGROUND: The Medicare Modernization Act of 2003 requires drug plan sponsors to provide medication therapy management programs (MTMPs) to beneficiaries with (1) drug expenditures above $4,000, (2) multiple comorbidities, and (3) multiple prescription drugs. The Medical Expenditure Panel Survey (MEPS) is a national probability survey conducted annually by the Agency for Healthcare Research and Quality and the National Center for Health Statistics to provide nationally representative estimates of health care use, expenditures, sources of payments, and insurance coverage for the U.S. civilian noninstitutionalized population. MEPS comprises 3 components, including the household component (HC) in which households and individuals within households are sampled. The medical provider component (MPC) supplements the HC by contacting providers (hospitals, outpatient offices, home health agencies, and pharmacies) reported in the HC, and the insurance component collects data on health insurance plans and is separate from the HC. OBJECTIVE: The purpose of this study was to estimate from MEPS data for 2002-2003 (1) the proportion of older adults who may have met the $4,000 expenditure component of the MTMP criteria and (2) the patient-specific risk factors associated with meeting the $4,000 expenditure threshold. METHODS: This study is a cross-sectional analysis of MEPS respondents aged 65 years or older. Data came from both the MEPS-HC and the supplemental MEPS-MPC for 2002 and 2003. Specific data files were pooled and included the Full Year Consolidated files, Prescribed Medicines files, and the Medical Conditions files for both the 2002 and the 2003 MEPS-HC. Variables extracted from the MEPS data files included demographics, socioeconomic status, functional limitations, health status, presence and number of chronic conditions, body mass index, medical and prescription drug insurance, and health care utilization measures. The expenditure threshold of $4,000 was adjusted to $3,810 in 2003 U.S. dollars. Survey-weighted logistic regression identified factors associated with meeting the expenditure threshold. Unbiased population point estimates were obtained by adjusting for survey nonresponse, poststratification, and oversampling of blacks and Hispanics using MEPS person-level weights. In all analyses, standard errors were adjusted for nonindependence of observations due to complex multistage sampling by specifying the strata and primary sampling units for each respondent. RESULTS: Based on a sample of 8,035 noninstitutionalized persons aged 65 years or older in the United States, representing a population of 36.5 million older adults, MEPS data estimate that approximately 3.3 million (9.2%) incurred annual drug expenditures greater than $3,810, accounting for 35% of $55.3 billion in drug expenditures among all older adults. Older adults meeting the $3,810 prescription expenditure threshold reported an average 10.8 (SE=0.2) unique medications, 82.2 (SE=1.8) prescriptions, and 5.2 (SE=0.1) chronic conditions. Prescription expenditures accounted for 33.9% of total health care expenditures compared with 15.8% for persons who did not meet the $3,810 criterion and an average 19.5% for all persons aged 65 years or older (n=8,035). Factors that predicted meeting the expenditure threshold included age in 10-year increments (odds ratio [OR]=0.81; 95% confidence interval [CI], 0.68-0.97), requiring help with activities of daily living (OR=1.53; 95% CI, 1.19-1.97), having functional limitations (OR=1.67; 95% CI, 1.30-2.14), having TRICARE (military health care services) benefits (OR=0.54; 95% CI, 0.33-0.86), and being on Medicaid (OR=1.36; 95% CI, 1.02-1.81). Other factors that were also predictive of meeting the expenditure threshold included mental health disorders, ulcers, diabetes, dyslipidemia, cardiac disease, chronic obstructive pulmonary disorder, and the number of chronic conditions. CONCLUSIONS: MEPS survey respondents aged 65 years or older with drug expenditures exceeding the MTMP threshold of $4,000 per year obtain substantially more drugs and have a higher disease burden than those with lower drug expenditures. Characteristics other than drug use, such as having functional limitations or requiring help with activities of daily living, can be used to identify potential MTMP candidates.

LDL-C goal attainment among patients newly diagnosed with coronary heart disease or diabetes in a commercial HMO.

BACKGROUND: Patients beginning treatment with lipid-modifying drugs should have their serum lipid levels monitored and, if necessary, their drug therapy adjusted to reach and maintain their treatment goals. Patients with coronary heart disease or diabetes are at high risk of coronary events and are particularly important target groups for monitoring and dose adjustment of lipid-modifying drug therapy. OBJECTIVE: to determine from administrative claims the rates of lipid testing, treatment with low-density lipoprotein cholesterol (LDL-C)-lowering drug therapy, and LDL-C goal attainment defined as LDL-C < 100 mg per DL in the time period after a new diagnosis of coronary heart disease or diabetes among patients who had not previously received lipid-modifying drug therapy. METHODS: an index date was defined by a new diagnosis of coronary heart disease or diabetes between January 1, 1999 and December 31, 2000, preceded by a 12-month pre-index period without lipid-modifying drug treatment in a commercial health maintenance organization (HMO) database for the southeastern united states. coronary heart disease (CHD) was defined by a diagnosis code for myocardial infarction (International Classification of Diseases, Ninth Edition, Clinical Modification [ICD-9-CM] code 410.xx) or angina/ischemic heart disease (411.xx), or a procedural code for angioplasty (icd-9-cM 36.1x-36.3x; Current Procedural Terminology [CPT] 92980-92984, 92995-92996) or coronary artery bypass graft (icd-9-cM 36.01, 36.02, 36.05, 36.09; CPT 33510-33545). diabetes was identified either by an icd-9-cM diagnosis code 250.xx or a pharmacy claim for an antihyperglycemic medication. Patients were followed in the post-index period until loss of eligibility or a maximum of 42 months (mean = 26 months, range=12-42 months). We calculated the proportion of patients with lipids treated and at LDL-C goal (defined as V < 100 mg per DL) in months 1-6 after the index date. among those not at goal in months 1-6, we estimated the proportion treated to goal in months 7-12 and in month 7 to the end of the post-index period. Logistic regression was used to estimate the odds of goal attainment in months 7-12 and in month 7 to the end of the post-index period among patients who were not at goal in months 1-6. RESULTS: Laboratory lipid values were available for 4,676 (40.4%) of 11,552 patients who had not previously received lipid-modifying drug therapy in months 1-6 after the index date, of whom 72.7% (n = 3,400) had an LDL-C > or =100 mg per DL (63.5% for CHD and 76.7% for diabetes). Of 1,245 patients tested and treated with lipid-modifying therapy in months 1-6, 485 (39.0%) were at LDL-C goal in months 1-6 (48.2% of CHD and 28.8% of diabetes patients), and 760 (61.0%) were not at LDL-C goal (51.8% of those with CHD and 71.2% of those with diabetes). Goal attainment (cumulative) among those treated improved to 50.1% in months 7-12 and 58.4% in month 7 to the end of the post-index period. Patients not attaining goal in months 1-6, and who continued treatment in months 7-12 and month 13 to the end of the post-index period, had a 48.8% (95% confidence interval [CI], 44.0%-53.6%) predicted probability of attaining their goals. The odds of goal attainment in month 7 to the end of post-index period (among those not at goal in months 1-6) were greater for (a) age e 65 years (odds ratio [or] = 2.45, 95% CI, 1.62-3.72), (b) history of hypertension (or = 1.91, 95% CI, 1.20-3.03), (c) greater number of distinct medications (or = 1.07, 95% CI, 1.01-1.14 per additional medication), (d) months of observation post-index (or = 1.04, 95% CI = 1.01-1.08 per additional month), and (e) months supply of lipid-modifying medication (or = 1.04, 95% CI, 1.01-1.07 per additional month), and were lower for LDL-C > or = 130 mg per DL in months 1-6 (or = 0.53, 95% CI, 0.35-0.82) and a history of dyslipidemia (or = 0.54, 95% CI, 0.35-0.83). The odds of LDL-C goal attainment were not affected by diagnosis (CHD vs. diabetes), gender, statin titration (34% of patients), lipid-modifying drug switching (39% of patients), or treatment with a high-potency LDL-C-lowering drug dosage (one of sufficient strength to reduce LDL-C by > 40%). CONCLUSION: of patients receiving lipid testing and lipid drug treatment in the 6 months after an initial diagnosis of CHD or diabetes, 61% were not at the LDL-C goal of < 100 mg per DL. Among those not at LDL-C goal in the first 6 months of treatment, only about half who continued treatment subsequently attained their LDL-C goal, despite statin titration or switching of their lipid-modifying drug therapy.

Repairing the broken market for antibiotic innovation.

Multidrug-resistant bacterial diseases pose serious and growing threats to human health. While innovation is important to all areas of health research, it is uniquely important in antibiotics. Resistance destroys the fruit of prior research, making it necessary to constantly innovate to avoid falling back into a pre-antibiotic era. But investment is declining in antibiotics, driven by competition from older antibiotics, the cost and uncertainty of the development process, and limited reimbursement incentives. Good public health practices curb inappropriate antibiotic use, making return on investment challenging in payment systems based on sales volume. We assess the impact of recent initiatives to improve antibiotic innovation, reflecting experience with all sixty-seven new molecular entity antibiotics approved by the Food and Drug Administration since 1980. Our analysis incorporates data and insights derived from several multistakeholder initiatives under way involving governments and the private sector on both sides of the Atlantic. We propose three specific reforms that could revitalize innovations that protect public health, while promoting long-term sustainability: increased incentives for antibiotic research and development, surveillance, and stewardship; greater targeting of incentives to high-priority public health needs, including reimbursement that is delinked from volume of drug use; and enhanced global collaboration, including a global treaty.

Improving pharmaceutical innovation by building a more comprehensive database on drug development and use.

New drugs and biologics have had a tremendous impact on the treatment of many diseases. However, available measures suggest that pharmaceutical innovation has remained relatively flat, despite substantial growth in research and development spending. We review recent literature on pharmaceutical innovation to identify limitations in measuring and assessing innovation, and we describe the framework and collaborative approach we are using to develop more comprehensive, publicly available metrics for innovation. Our research teams at the Brookings Institution and Deerfield Institute are collaborating with experts from multiple areas of drug development and regulatory review to identify and collect comprehensive data elements related to key development and regulatory characteristics for each new molecular entity approved over the past several decades in the United States and the European Union. Subsequent phases of our effort will add data on downstream product use and patient outcomes and will also include drugs that have failed or been abandoned in development. Such a database will enable researchers to better analyze the drivers of drug innovation, trends in the output of new medicines, and the effect of policy efforts designed to improve innovation.