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.

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 evidence developed from population-level experience with targeted agents

Off-label drug use is common in oncology, due in part to significant unmet medical need, the rarity of many cancers, and the difficulty of conducting randomized controlled trials (RCTs) to support labeling of every drug in every disease setting. As new drugs are developed for use in tumors defined by genomic aberrations, it may be scientifically reasonable to expect that a targeted anti-cancer agent with efficacy in a biomarker-defined population within one tumor type may also have activity in another tumor type expressing the same biomarker. Such expectations also fuel off-label prescribing. However, the current approach to prescribing targeted agents off-label does not capture patient outcomes, thus missing an opportunity to gather data that could validate this approach. We explore the potential for collecting such data, highlight two proposals for oncology-specific patient registries, and put forward considerations that should be addressed to move toward better evidence development around off-label use.

Utilizing data consortia to monitor safety and effectiveness of biosimilars and their innovator products

BACKGROUND

The Biologics Price Competition and Innovation Act, introduced as part of the Affordable Care Act, directed the FDA to create an approval pathway for biologic products shown to be biosimilar or interchangeable with an FDA-approved innovator drug. These biosimilars will not be chemically identical to the reference agent. Investigational studies conducted with biosimilar agents will likely provide limited real-world evidence of their effectiveness and safety. How do we best monitor effectiveness and safety of biosimilar products once approved by the FDA and used more extensively by patients?

OBJECTIVE

To determine the feasibility of developing a distributed research network that will use health insurance plan and health delivery system data to detect biosimilar safety and effectiveness signals early and be able to answer important managed care pharmacy questions from both the government and managed care organizations.

METHODS

Twenty-one members of the AMCP Task Force on Biosimilar Collective Intelligence Systems met November 12, 2013, to discuss issues involved in designing this consortium and to explore next steps.

RESULTS

The task force concluded that a managed care biosimilars research consortium would be of significant value. Task force members agreed that it is best to use a distributed research network structurally similar to existing DARTNet, HMO Research Network, and Mini-Sentinel consortia. However, for some surveillance projects that it undertakes, the task force recognizes it may need supplemental data from managed care and other sources (i.e., a "hybrid" structure model).

CONCLUSIONS

The task force believes that AMCP is well positioned to lead the biosimilar-monitoring effort and that the next step to developing a biosimilar-innovator collective intelligence system is to convene an advisory council to address organizational governance.

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.

Amphetamines, atomoxetine and the risk of serious cardiovascular events in adults

Main Objective

To compare the incidence rates of serious cardiovascular events in adult initiators of amphetamines or atomoxetine to rates in non-users.

Methods

This was a retrospective cohort study of new amphetamines (n = 38,586) or atomoxetine (n = 20,995) users. Each medication user was matched to up to four non-users on age, gender, data source, and state (n = 238,183). The following events were primary outcomes of interest 1) sudden death or ventricular arrhythmia, 2) stroke, 3) myocardial infarction, 4) a composite endpoint of stroke or myocardial infarction. Cox proportional hazard regression was used to calculate propensity-adjusted hazard ratios for amphetamines versus matched non-users and atomoxetine versus matched non-users, with intracluster dependence within matched sets accounted for using a robust sandwich estimator.

Results

The propensity-score adjusted hazard ratio for amphetamines use versus non-use was 1.18 (95% CI: 0.55–2.54) for sudden death/ventricular arrhythmia, 0.80 (95% CI: 0.44–1.47) for stroke, 0.75 (95% CI: 0.42–1.35) for myocardial infarction, and 0.78 (95% CI: 0.51–1.19) for stroke/myocardial infarction. The propensity-score adjusted hazard ratio for atomoxetine use versus non-use was 0.41 (95% CI: 0.10–1.75) for sudden death/ventricular arrhythmia, 1.30 (95% CI: 0.52–3.29) for stroke, 0.56 (95% CI: 0.16–2.00) for myocardial infarction, and 0.92 (95% CI: 0.44–1.92) for stroke/myocardial infarction.

Conclusions

Initiation of amphetamines or atomoxetine was not associated with an elevated risk of serious cardiovascular events. However, some of the confidence intervals do not exclude modest elevated risks, e.g. for sudden death/ventricular arrhythmia.

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.

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 Hb_A1c 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.

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.

Early steps in the development of a claims-based targeted healthcare safety monitoring system and application to three empirical examples

BACKGROUND

Several efforts are under way to develop and test methods for prospective drug safety monitoring using large, electronic claims databases. Prospective monitoring systems must incorporate signalling algorithms and techniques to mitigate confounding in order to minimize false positive and false negative signals due to chance and bias.

OBJECTIVE

The aim of the study was to describe a prototypical targeted active safety monitoring system and apply the framework to three empirical examples.

METHODS

We performed sequential, targeted safety monitoring in three known drug/adverse event (AE) pairs: (i) paroxetine/upper gastrointestinal (UGI) bleed; (ii) lisinopril/angioedema; (iii) ciprofloxacin/Achilles tendon rupture (ATR). Data on new users of the drugs of interest were extracted from the HealthCore Integrated Research Database. New users were matched by propensity score to new users of comparator drugs in each example. Analyses were conducted sequentially to emulate prospective monitoring. Two signalling rules--a maximum sequential probability ratio test and an effect estimate-based approach--were applied to sequential, matched cohorts to identify signals within the system.

RESULTS

Signals were identified for all three examples: paroxetine/UGI bleed in the seventh monitoring cycle, within 2 calendar years of sequential data; lisinopril/angioedema in the second cycle, within the first monitoring year; ciprofloxacin/ATR in the tenth cycle, within the fifth year.

CONCLUSION

In this proof of concept, our targeted, active monitoring system provides an alternative to systems currently in the literature. Our system employs a sequential, propensity score-matched framework and signalling rules for prospective drug safety monitoring and identified signals for all three adverse drug reactions evaluated.

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.

Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system

We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic health-care data. In a retrospective analysis, we show that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). Over >5 years of monitoring, rate differences (RDs) in comparisons of rosuvastatin with atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% confidence interval (CI): -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI: -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin with azithromycin was 0.3 cases per 1,000 person-years (95% CI: -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for the three drug-outcome pairs.

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.

Methylphenidate and risk of serious cardiovascular events in adults

OBJECTIVE

The authors sought to determine whether use of methylphenidate in adults is associated with elevated rates of serious cardiovascular events compared with rates in nonusers.

METHOD

This was a cohort study of new users of methylphenidate based on administrative data from a five-state Medicaid database and a 14-state commercial insurance database. All new methylphenidate users with at least 180 days of prior enrollment were identified. Users were matched on data source, state, sex, and age to as many as four comparison subjects who did not use methylphenidate, amphetamines, or atomoxetine. A total of 43,999 new methylphenidate users were identified and matched to 175,955 nonusers. Events of primary interest were 1) sudden death or ventricular arrhythmia, 2) stroke, 3) myocardial infarction, and 4) a composite endpoint of stroke or myocardial infarction.

RESULTS

The age-standardized incidence rate per 1,000 person-years of sudden death or ventricular arrhythmia was 2.17 (95% CI=1.63-2.83) in methylphenidate users and 0.98 (95% CI=0.89-1.08) in nonusers, for an adjusted hazard ratio of 1.84 (95% CI=1.33-2.55). Dosage was inversely associated with risk. Adjusted hazard ratios for stroke, myocardial infarction, and the composite endpoint of stroke or myocardial infarction did not differ statistically from 1.

CONCLUSIONS

Although initiation of methylphenidate was associated with a 1.8-fold increase in risk of sudden death or ventricular arrhythmia, the lack of a dose-response relationship suggests that this association may not be a causal one.

Cardiovascular events and death in children exposed and unexposed to ADHD agents

OBJECTIVE

The objective of this study was to compare the rate of severe cardiovascular events and death in children who use attention-deficit/hyperactivity disorder (ADHD) medications versus nonusers.

PATIENTS AND METHODS

We performed a large cohort study using data from 2 administrative databases. All children aged 3 to 17 years with a prescription for an amphetamine, atomoxetine, or methylphenidate were included and matched with up to 4 nonusers on the basis of data source, gender, state, and age. Cardiovascular events were validated using medical records. Proportional hazards regression was used to calculated hazard ratios.

RESULTS

We identified 241 417 incident users (primary cohort). No statistically significant difference between incident users and nonusers was observed in the rate of validated sudden death or ventricular arrhythmia (hazard ratio: 1.60 [95% confidence interval (CI): 0.19-13.60]) or all-cause death (hazard ratio: 0.76 [95% CI: 0.52-1.12]). None of the strokes identified during exposed time to ADHD medications were validated. No myocardial infarctions were identified in ADHD medication users. No statistically significant difference between prevalent users and nonusers (secondary cohort) was observed (hazard ratios for validated sudden death or ventricular arrhythmia: 1.43 [95% CI: 0.31-6.61]; stroke: 0.89 [95% CI: 0.11-7.11]; stroke/myocardial infarction: 0.72 [95% CI: 0.09-5.57]; and all-cause death: 0.77 [95% CI: 0.56-1.07).

CONCLUSIONS

The rate of cardiovascular events in exposed children was very low and in general no higher than that in unexposed control subjects. Because of the low number of events, we have limited ability to rule out relative increases in rate.

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.

Risk of osteoporotic fracture in a large population-based cohort of patients with rheumatoid arthritis

Introduction

Although osteoporosis has been reported to be more common in patients with rheumatoid arthritis (RA), little is known whether the risk of osteoporotic fractures in these patients differs by age, sex, and anatomic site.

Methods

A retrospective cohort study was conducted using a health care utilization database. Incidence rates (IRs) and rate ratios (RRs) of osteoporotic fractures with 95% confidence intervals (CIs) were calculated. Multivariable Cox proportional hazards models compared the risk of osteoporotic fracture at typical sites between RA and non-RA patients.

Results

During a median 1.63-year follow-up, 872 (1.9%) of 47,034 RA patients experienced a fracture. The IR for osteoporotic fracture at typical sites among RA patients was 9.6 per 1,000 person-years, 1.5 times higher than the rate of non-RA patients. The IR was highest for hip fracture (3.4 per 1,000 person-years) in RA. The IRs across all age groups were higher for women than men and increased with older age in both groups. The RRs were elevated in RA patients across all common sites of osteoporotic fracture: hip (1.62, 95% CI 1.43 to 1.84), wrist (1.15, 95% CI 1.00 to 1.32), pelvis (2.02, 95% CI 1.77 to 2.30), and humerus (1.51, 95% CI 1.27 to 1.84). After confounding adjustment, a modest increase in risk for fracture was noted with RA (hazard ratio 1.26, 95% CI 1.15 to 1.38).

Conclusions

Our study showed an increased risk of osteoporotic fractures for RA patients across all age groups, sex and various anatomic sites, compared with non-RA patients.

Efficiency and economic benefits of a payer-based electronic health record in an emergency department

OBJECTIVES

The objective was to evaluate the use of a payer-based electronic health record (P-EHR), which is a clinical summary of a patient's medical and pharmacy claims history, in an emergency department (ED) on length of stay (LOS) and plan payments.

METHODS

A large urban ED partnered with the dominant health plan in the region and implemented P-EHR technology in September 2005 for widespread use for health plan members presenting to the ED. A retrospective observational study design was used to evaluate this previously implemented P-EHR. Health plan and electronic hospital data were used to identify 2,288 ED encounters. Encounters with P-EHR use (n = 779) were identified between September 1, 2005, and February 17, 2006; encounters from the same health plan (n = 1,509) between November 1, 2004, and March 31, 2005, were compared. Outcomes were ED LOS and plan payment for the ED encounter. Analyses evaluated the effect of using the P-EHR in the ED setting on study outcomes using multivariate regressions and the nonparametric bootstrap.

RESULTS

After covariate adjustment, among visits resulting in discharge (ED-only), P-EHR visits were 19 minutes shorter (95% confidence interval [CI] = 5 to 33 minutes) than non-P-EHR visits. Among visits resulting in hospitalization, the P-EHR was associated with an average 77-minute shorter ED LOS (95% CI = 28 to 126 minutes), compared to non-P-EHR visits. The P-EHR was associated with an average of $1,560 (95% CI = $43 to $2,910) lower total plan expenditures for hospitalized visits. No significant difference in total payments was observed among discharged visits.

CONCLUSIONS

In the study ED, the P-EHR was associated with a significant reduction in ED LOS overall and was associated with lower plan payments for visits that resulted in hospitalization.

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.

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.