Justin W. Timbie

Health-related quality of life among patients with breast cancer receiving zoledronic acid or pamidronate disodium for metastatic bone lesions

BackgroundResearch on individual differences in health-related quality of life (HRQOL) can identify intervention targets and important covariates in analyses of treatment outcomes. ObjectivesThe objectives of this study were to describe HRQOL trajectories for women with metastatic breast cancer in a randomized trial of bisphosphonates and to identify characteristics associated with variations in HRQOL. Research DesignWe conducted a prospective quality-of-life study within a randomized, controlled trial. SubjectsWe studied women with metastatic breast cancer receiving zoledronic acid or pamidronate disodium to reduce the incidence of skeletal-related events (SREs). Main Outcome MeasuresHRQOL was measured at fixed time points during the trial. Individual growth-curve modeling was used to describe longitudinal trajectories and to identify predictors of trajectories. ResultsFor most domains of HRQOL, the mean trajectory reflected a mild increase, which leveled off later in the trial. Older age and full-time employment were associated with higher baseline HRQOL. Longer time from cancer diagnosis to randomization, lower Eastern Cooperative Oncology Group (ECOG) status (score of 2 [“inactive”]), and a history of SREs were associated with lower baseline HRQOL. Significant differences across geographic regions were observed for all domains. Active ECOG status (score of 0–1) at baseline was predictive of greater increases in all domains of HRQOL except Social/Family Well-Being. Age, geographic region, and time from first bone metastases to randomization were associated with longitudinal changes in some domains. ConclusionsWomen with metastatic breast cancer receiving bisphosphonates for prevention of SREs experienced an overall increase in HRQOL. Variations among women’s experiences are explained partly by such characteristics as a history of SREs.

Five reasons that many comparative effectiveness studies fail to change patient care and clinical practice

Despite widespread enthusiasm about the potential impact of new investments in comparative effectiveness research, recent history suggests that scientific evidence may be slow to change clinical practice. Reflecting on studies conducted over the past decade, we identify five causes that underlie the failure of many comparative effectiveness studies to alter patient care. These are financial incentives, such as fee-for-service payment, that may militate against the adoption of new clinical practices; ambiguity of study results that hamper decision making; cognitive biases in the interpretation of new information; failure of the research to address the needs of end users; and limited use of decision support by patients and clinicians. Policies that encourage the development of consensus objectives, methods, and evidentiary standards before studies get under way and that provide strong incentives for patients and providers to use resources efficiently may help overcome at least some of these barriers and enable comparative effectiveness results to alter medical practice more quickly.

Variation in the Net Benefit of Aggressive Cardiovascular Risk Factor Control Across the US Population of Patients With Diabetes Mellitus

BACKGROUND Lowering low-density lipoprotein cholesterol (LDL-C) and blood pressure (BP) in patients with diabetes mellitus (DM) can significantly reduce the risk of cardiovascular disease (CVD). However, to our knowledge, previous studies have not assessed variability in both the benefit and harm from pursuing LDL-C and BP target levels. METHODS Our sample comprised individuals 30 to 75 years old with DM participating in the National Health and Nutrition Examination Survey III. We used Monte Carlo methods to simulate a treat-to-target strategy, in which patients underwent treatment intensification with the goal of achieving LDL-C and BP target levels of 100 mg/dL and 130/80 mm Hg, respectively. Patients received up to 5 titrations of statin therapy and 8 titrations of antihypertensive therapy. Treatment adverse effects and polypharmacy risks and burdens were incorporated using disutilities. Health outcomes were simulated using a Markov model. RESULTS Treating to targets resulted in gains of 1.50 (for LDL-C) and 1.35 (for BP) quality-adjusted life-years (QALYs) of lifetime treatment-related benefit, which declined to 1.42 and 1.16 QALYs after accounting for treatment-related harms. Most of the total benefit was limited to the first few steps of medication intensification or to tight control for a limited group of very high-risk patients. However, because of treatment-related disutility, intensifying beyond the first step (LDL-C) or third step (BP) resulted in either limited benefit or net harm for patients with below-average risk. CONCLUSION The benefits and harms from aggressive risk factor modification vary widely across the US population of individuals with DM, depending on a patients underlying CVD risk, suggesting that a personalized approach could maximize a patients net benefit from treatment.

Systematic review of strategies to manage and allocate scarce resources during mass casualty events.

STUDY OBJECTIVE Efficient management and allocation of scarce medical resources can improve outcomes for victims of mass casualty events. However, the effectiveness of specific strategies has never been systematically reviewed. We analyze published evidence on strategies to optimize the management and allocation of scarce resources across a wide range of mass casualty event contexts and study designs. METHODS Our literature search included MEDLINE, Scopus, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Global Health, Web of Science, and the Cochrane Database of Systematic Reviews, from 1990 through late 2011. We also searched the gray literature, using the New York Academy of Medicines Grey Literature Report and key Web sites. We included both English- and foreign-language articles. We included studies that evaluated strategies used in actual mass casualty events or tested through drills, exercises, or computer simulations. We excluded studies that lacked a comparison group or did not report quantitative outcomes. Data extraction, quality assessment, and strength of evidence ratings were conducted by a single researcher and reviewed by a second; discrepancies were reconciled by the 2 reviewers. Because of heterogeneity in outcome measures, we qualitatively synthesized findings within categories of strategies. RESULTS From 5,716 potentially relevant citations, 74 studies met inclusion criteria. Strategies included reducing demand for health care services (18 studies), optimizing use of existing resources (50), augmenting existing resources (5), implementing crisis standards of care (5), and multiple categories (4). The evidence was sufficient to form conclusions on 2 strategies, although the strength of evidence was rated as low. First, as a strategy to reduce demand for health care services, points of dispensing can be used to efficiently distribute biological countermeasures after a bioterrorism attack or influenza pandemic, and their organization influences speed of distribution. Second, as a strategy to optimize use of existing resources, commonly used field triage systems do not perform consistently during actual mass casualty events. The number of high-quality studies addressing other strategies was insufficient to support conclusions about their effectiveness because of differences in study context, comparison groups, and outcome measures. Our literature search may have missed key resource management and allocation strategies because of their extreme heterogeneity. Interrater reliability was not assessed for quality assessments or strength of evidence ratings. Publication bias is likely, given the large number of studies reporting positive findings. CONCLUSION The current evidence base is inadequate to inform providers and policymakers about the most effective strategies for managing or allocating scarce resources during mass casualty events. Consensus on methodological standards that encompass a range of study designs is needed to guide future research and strengthen the evidence base. Evidentiary standards should be developed to promote consensus interpretations of the evidence supporting individual strategies.

Appropriateness of Advanced Diagnostic Imaging Ordering Before and After Implementation of Clinical Decision Support Systems

Appropriateness of Advanced Diagnostic Imaging Ordering Before and After Implementation of Clinical Decision Support Systems Computerized clinical decision support (CDS) systems that match patient characteristics against appropriateness criteria to produce algorithmic treatment recommendations are a potential means of improving care.1,2 The Protecting Access to Medicare Act of 2014 mandates use of CDS systems for the ordering of advanced diagnostic imaging in the Medicare program starting in 2017.3 In a descriptive observational study, we used data from the Medicare Imaging Demonstration to evaluate the relationship of CDS system use with the proportion of imaging orders matched to appropriateness criteria, the appropriateness of ordered images, and the proportion of orders changed following feedback.

A conceptual framework and protocol for defining clinical decision support objectives applicable to medical specialties

BackgroundThe U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.DesignWe developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as “CDS opportunities,” might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists’ clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics.

Impact of Socioeconomic Adjustment on Physicians' Relative Cost of Care

Background:Ongoing efforts to profile physicians on their relative cost of care have been criticized because they do not account for differences in patients’ socioeconomic status (SES). The importance of SES adjustment has not been explored in cost-profiling applications that measure costs using an episode of care framework. Objectives:We assessed the relationship between SES and episode costs and the impact of adjusting for SES on physicians’ relative cost rankings. Research design:We analyzed claims submitted to 3 Massachusetts commercial health plans during calendar years 2004 and 2005. We grouped patients’ care into episodes, attributed episodes to individual physicians, and standardized costs for price differences across plans. We accounted for differences in physicians’ case mix using indicators for episode type and a patient’s severity of illness. A patient’s SES was measured using an index of 6 indicators based on the zip code in which the patient lived. We estimated each physician’s case mix-adjusted average episode cost and percentile rankings with and without adjustment for SES. Results:Patients in the lowest SES quintile had

Implementation of Medical Homes in Federally Qualified Health Centers

80 higher unadjusted episode costs, on average, than patients in the highest quintile. Nearly 70% of the variation in a physician’s average episode cost was explained by case mix of their patients, whereas the contribution of SES was negligible. After adjustment for SES, only 1.1% of physicians changed relative cost rankings >2 percentiles. Conclusions:Accounting for patients’ SES has little impact on physicians’ relative cost rankings within an episode cost framework.

Association Between Patient-Centered Medical Home Capabilities and Outcomes for Medicare Beneficiaries Seeking Care from Federally Qualified Health Centers

BACKGROUND From 2011 through 2014, the Federally Qualified Health Center Advanced Primary Care Practice Demonstration provided care management fees and technical assistance to a nationwide sample of 503 federally qualified health centers to help them achieve the highest (level 3) medical‐home recognition by the National Committee for Quality Assurance, a designation that requires the implementation of processes to improve access, continuity, and coordination. METHODS We examined the achievement of medical‐home recognition and used Medicare claims and beneficiary surveys to measure utilization of services, quality of care, patients’ experiences, and Medicare expenditures in demonstration sites versus comparison sites. Using difference‐in‐differences analyses, we compared changes in outcomes in the two groups of sites during a 3‐year period. RESULTS Level 3 medical‐home recognition was awarded to 70% of demonstration sites and to 11% of comparison sites. Although the number of visits to federally qualified health centers decreased in the two groups, smaller reductions among demonstration sites than among comparison sites led to a relative increase of 83 visits per 1000 beneficiaries per year at demonstration sites (P<0.001). Similar trends explained the higher performance of demonstration sites with respect to annual eye examinations and nephropathy tests (P<0.001 for both comparisons); there were no significant differences with respect to three other process measures. Demonstration sites had larger increases than comparison sites in emergency department visits (30.3 more per 1000 beneficiaries per year, P<0.001), inpatient admissions (5.7 more per 1000 beneficiaries per year, P=0.02), and Medicare Part B expenditures (

Evaluation of CMS' FQHC APCP Demonstration: Final First Annual Report

37 more per beneficiary per year, P=0.02). Demonstration‐site participation was not associated with relative improvements in most measures of patients’ experiences. CONCLUSIONS Demonstration sites had higher rates of medical‐home recognition and smaller decreases in the number of patients’ visits to federally qualified health centers than did comparison sites, findings that may reflect better access to primary care relative to comparison sites. Demonstration sites had larger increases in emergency department visits, inpatient admissions, and Medicare Part B expenditures. (Funded by the Centers for Medicare and Medicaid Services.)