Use of Real-World Evidence for Regulatory Approval and Coverage of Medical Devices: A Landscape Assessment.

OBJECTIVES: To enhance the generalizability of the evidence it reviews, the US Food and Drug Administration (FDA) has encouraged manufacturers to expand the submission of real-world evidence (RWE). The extent to which this evidence, which is generated outside of research settings, can support decision making remains unclear. We described the current use of RWE for medical devices, assessed manufacturers' challenges in generating and using it for regulatory and coverage decisions, and identified opportunities to expand its use. METHODS: We conducted 27 solo and group interviews with FDA officials and representatives of device manufacturers, payers, and health technology assessment organizations. All interviews used a semistructured protocol and were transcribed to allow thematic analysis. RESULTS: Accessing and linking real-world data sources, identifying unique devices, capturing longitudinal data, limited staff expertise, and uncertain return on investment have hampered efforts to use real-world data. Many companies in our sample were conducting research using real-world data, but none had submitted RWE as the primary evidence supporting a premarket approval. FDA guidance was helpful, but regulatory requirements remained ambiguous and examples of successful regulatory decisions based on RWE were limited. Payers mainly used RWE to supplement experimental evidence in coverage decisions, evaluated both types of evidence in similar ways, and had concerns about the rigor of RWE. CONCLUSIONS: Technical challenges may slow efforts to generate and use RWE in the near term. Additional regulatory guidance and examples, greater use of rigorous study designs and analytic methods, and continued stakeholder engagement could accelerate the use of RWE.

Health system affiliation of physician organizations and quality of care for Medicare beneficiaries who have high needs.

OBJECTIVE: To test the hypothesis that health systems provide better care to patients with high needs by comparing differences in quality between system-affiliated and nonaffiliated physician organizations (POs) and to examine variability in quality across health systems. DATA SOURCES: 2015 Medicare Data on Provider Practice and Specialty linked physicians to POs. Medicare Provider Enrollment, Chain, and Ownership System (PECOS) and IRS Form 990 data identified health system affiliations. Fee-for-service Medicare enrollment and claims data were used to examine quality. STUDY DESIGN: This cross-sectional analysis of beneficiaries with high needs, defined as having more than twice the expected spending of an average beneficiary, examined six quality measures: continuity of care, follow-up visits after hospitalizations and emergency department (ED) visits, ED visits, all-cause readmissions, and ambulatory care-sensitive hospitalizations. Using a matched-pair design, we estimated beneficiary-level regression models with PO random effects to compare quality of care in system-affiliated and nonaffiliated POs. We then limited the sample to system-affiliated POs and estimated models with system random effects to examine variability in quality across systems. PRINCIPAL FINDINGS: Among 2 323 301 beneficiaries with high needs, 52.3% received care from system-affiliated POs. Rates of ED visits were statistically significantly different in system-affiliated POs (117.5 per 100) and nonaffiliated POs (106.8 per 100, P < .0001). Small differences in the other five quality measures were observed across a range of sensitivity analyses. Among systems, substantial variation was observed for rates of continuity of care (90% of systems had rates between 70.8% and 89.4%) and follow-up after ED visits (90% of systems had rates between 56.9% and 73.5%). CONCLUSIONS: Small differences in quality of care were observed among beneficiaries with high needs receiving care from system POs and nonsystem POs. Health systems may not confer hypothesized quality advantages to patients with high needs.

Racial and ethnic disparities in care for health system-affiliated physician organizations and non-affiliated physician organizations.

OBJECTIVE: To assess racial and ethnic disparities in care for Medicare fee-for-service (FFS) beneficiaries and whether disparities differ between health system-affiliated physician organizations (POs) and nonaffiliated POs. DATA SOURCES: We used Medicare Data on Provider Practice and Specialty (MD-PPAS), Medicare Provider Enrollment, Chain, and Ownership System (PECOS), IRS Form 990, 100% Medicare FFS claims, and race/ethnicity estimated using the Medicare Bayesian Improved Surname Geocoding 2.0 algorithm. STUDY DESIGN: Using a sample of 16 007 POs providing primary care in 2015, we assessed racial/ethnic disparities on 12 measures derived from claims (2 cancer screenings; diabetic eye examinations; continuity of care; two medication adherence measures; three measures of follow-up visits after acute care; all-cause emergency department (ED) visits, all-cause readmissions, and ambulatory care-sensitive admissions). We decomposed these "total" disparities into within-PO and between-PO components using models with PO random effects. We then pair-matched 1853 of these POs that were affiliated with health systems to similar nonaffiliated POs. We examined differences in within-PO disparities by affiliation status by interacting each nonwhite race/ethnicity with an affiliation indicator. DATA COLLECTION/EXTRACTION METHODS: Medicare Data on Provider Practice and Specialty identified POs billing Medicare; PECOS and IRS Form 990 identified health system affiliations. Beneficiaries age 18 and older were attributed to POs using a plurality visit rule. PRINCIPAL FINDINGS: We observed total disparities in 12 of 36 comparisons between white and nonwhite beneficiaries; nonwhites received worse care in 10. Within-PO disparities exceeded between-PO disparities and were substantively important (>=5 percentage points or>=0.2 standardized differences) in nine of the 12 comparisons. Among these 12, nonaffiliated POs had smaller disparities than affiliated POs in two comparisons (P < .05): 1.6 percentage points smaller black-white disparities in follow-up after ED visits and 0.6 percentage points smaller Hispanic-white disparities in breast cancer screening. CONCLUSIONS: We find no evidence that system-affiliated POs have smaller racial and ethnic disparities than nonaffiliated POs. Where differences existed, disparities were slightly larger in affiliated POs.

Specialty care access for Medicaid enrollees in expansion states.

OBJECTIVES: Community health centers (CHCs) historically have reported challenges obtaining specialty care for their patients, but recent policy changes, including Medicaid eligibility expansions under the Affordable Care Act, may have improved access to specialty care. The objective of this study was to assess current levels of difficulty accessing specialty care for CHC patients, by insurance type, and to identify specific barriers and strategies that CHCs are using to overcome these barriers. STUDY DESIGN: Cross-sectional survey, administered during summer 2017, of medical directors at CHCs in 9 states and the District of Columbia, all of which expanded Medicaid. METHODS: Surveys were administered to medical directors at 361 CHCs (response rate, 55%) to assess the difficulty of accessing specialty care by insurance type and to identify the specialties for which it was most difficult to obtain new patient visits. The survey also elicited ratings of commonly reported barriers to obtaining specialty care and identified strategies used by CHCs to access specialty care for patients. Descriptive results are presented. RESULTS: Nearly 60% of CHCs reported difficulty obtaining new patient specialty visits for their Medicaid patients, most often for orthopedists. Barriers to specialty care reported by CHCs included that few specialists in Medicaid managed care organization (MCO) networks were accepting new patients (69.4%) and MCO administrative requirements for obtaining specialist consults (49.0%). To enhance access to specialists, CHCs reported that they entered into referral agreements, developed appointment reminder systems, and participated in data exchange and other community-based initiatives. CONCLUSIONS: Medicaid patients at CHCs face many barriers to accessing specialty care. Payment policies and network adequacy rules may need to be reexamined to address these challenges.

Primary Care Visit Regularity and Patient Outcomes: an Observational Study.

BACKGROUND: Regular primary care visits may allow an opportunity to deliver high-value, proactive care. However, no previous study has examined whether more temporally regular primary care visits predict better outcomes. OBJECTIVE: To examine the relationship between the temporal regularity of primary care (PC) visits and outcomes. DESIGN: Retrospective cohort study. PARTICIPANTS: We used Medicare claims for 378,862 fee-for-service Medicare beneficiaries, who received PC at 1328 federally qualified health centers from 2010 to 2014. MAIN MEASURES: We created five beneficiary groups based upon their annual number of PC visits. We further subdivided those groups according to whether PC visits occurred with more or less regularity than the median value. We compared these 10 subgroups on three outcomes, adjusting for beneficiary characteristics: emergency department (ED) visits, hospitalizations, and total Medicare expenditures. We also aggregated to the clinic level and divided clinics into tertiles of more, less, and similarly regular to predicted. We compared these three groups of clinics on the same three outcomes of care. KEY RESULTS: Within each visit frequency group, beneficiaries in the subgroup with fewer regular visits had more ED visits, more hospitalizations, and higher costs. Among beneficiaries with the most frequent PC visits, the less regular subgroup had more ED visits (1.70 vs. 1.31 per person-year), more hospitalizations (0.69 vs. 0.57), and greater Medicare expenditures ($20,731 vs. $17,430, p < 0.001 for all comparisons). Clinics whose PC visits were more regular than predicted also had better outcomes than other clinics, although the effect sizes were smaller. CONCLUSIONS: Temporal patterns of PC visits are correlated with outcomes, even among beneficiaries who appear otherwise similar. Measuring the temporal regularity of PC visits may be useful for identifying beneficiaries at risk for adverse events, and as a barometer for and an impetus to clinic-level quality improvement.

Using Health IT to Coordinate Care and Improve Quality in Safety-Net Clinics.

BACKGROUND: Health centers provide care to vulnerable and high-need populations. Recent investments have promoted use of health information technology (HIT) capabilities for improving care coordination and quality of care in health centers. This study examined factors associated with use of these HIT capabilities and the association between these capabilities and quality of care in a census of health centers in the United States. METHODS: Cross-sectional secondary data from the 2015 Health Resources and Services Administration's Uniform Data System was used to examine 6 measures of HIT capability related to care coordination and clinical decision support and 16 measures of quality (12 process measures, 3 outcome measures, 1 composite measure) for health centers in the United States. Adjusted logistic regressions were used to examine health center characteristics associated with use of HIT capabilities, and adjusted linear regressions were used to examine associations between HIT capabilities and quality of care. RESULTS: Many health centers reported using HIT for care coordination activities, including coordinating enabling services (67.3%) or engaging patients (81.0%). Health center size and medical home recognition were associated with significantly greater odds of using HIT for enabling services and engaging patients. These HIT capabilities were associated with higher overall quality and higher rates of six process measures (adult screening and maternal and child health) and hemoglobin A1c control. CONCLUSION: Use of HIT for such activities as arranging enabling services and engaging patients are underleveraged tools for care coordination. There may be opportunities to further improve quality of care for vulnerable patients by promoting health centers' use of these HIT capabilities.

Examining differential performance of 3 medical home recognition programs.

OBJECTIVES: We examined differences in patient outcomes associated with 3 patient-centered medical home (PCMH) recognition programs-National Committee for Quality Assurance (NCQA) Level 3, The Joint Commission (TJC), and Accreditation Association for Ambulatory Health Care (AAAHC)-among Medicare beneficiaries receiving care at federally qualified health centers (FQHCs). STUDY DESIGN: We used data from CMS' FQHC Advanced Primary Care Practice Demonstration, in which participating FQHCs received assistance to achieve NCQA Level 3 PCMH recognition. We assessed the impact of the 3 recognition programs on utilization, quality, and Medicare expenditures using a sample of 1108 demonstration and comparison FQHCs. METHODS: Using propensity-weighted difference-in-differences analyses, we compared changes in outcomes over 3 years for beneficiaries attributed to FQHCs that achieved each type of recognition relative to beneficiaries attributed to FQHCs that did not achieve recognition. RESULTS: Recognized FQHCs, compared with nonrecognized FQHCs, were associated with significant 3-year changes in FQHC visits, non-FQHC primary care visits, specialty visits, emergency department (ED) visits, hospitalizations, a composite diabetes process measure, and Medicare expenditures. Changes varied in direction and strength by recognition type. In year 3, compared with nonrecognized sites, NCQA Level 3 sites were associated with greater increases in ambulatory visits and quality and greater reductions in hospitalizations and expenditures (P <.01), TJC sites were associated with significant reductions in ED visits and hospitalizations (P <.01), and AAAHC sites had changes in the opposite direction of what we anticipated. CONCLUSIONS: Heterogeneous changes in beneficiary utilization, quality, and expenditures by recognition type may be explained by differences in recognition criteria, evaluation processes, and documentation requirements.

Utilization of health care services among Medicare beneficiaries who visit federally qualified health centers.

BACKGROUND: Previous studies have disagreed on whether patients who receive primary care from federally qualified health centers (FQHCs) have different utilization patterns than patients who receive care elsewhere. Our objective was to compare patterns of healthcare utilization between Medicare beneficiaries who received primary care from FQHCs and Medicare beneficiaries who received primary care from another source. METHODS: We compared characteristics and ambulatory, emergency department (ED), and inpatient utilization during 2013 between 130,637 Medicare beneficiaries who visited an FQHC for the majority of their primary care in 2013 (FQHC users) and a random sample of 1,000,000 Medicare fee-for-service (FFS) beneficiaries who did not visit an FQHC (FQHC non-users). We then created a propensity-matched sample of 130,569 FQHC users and 130,569 FQHC non-users to account for differences in observable patient characteristics between the two groups and repeated all comparisons. RESULTS: Before matching, the two samples differed in terms of age (42% below age 65 for FQHC users vs. 16% among FQHC non-users, p < 0.001 for all comparisons), disability (52% vs. 24%), eligibility for Medicaid (56% vs. 21%), severe mental health disorders (17% vs. 10%), and substance abuse disorders (6% vs. 3%). FQHC users had fewer ambulatory visits to primary care or specialist providers (10.0 vs. 12.0 per year), more ED visits (1.2 vs. 0.8), and fewer hospitalizations (0.3 vs. 0.4). In the matched sample, FQHC users still had slightly lower utilization of ambulatory visits to primary care or specialist providers (10.0 vs. 11.2) and slightly higher utilization of ED visits (1.2 vs. 1.0), compared to FQHC users. Hospitalization rates between the two groups were similar (0.3 vs. 0.3). CONCLUSIONS: In this population of Medicare FFS beneficiaries, FQHC users had slightly lower utilization of ambulatory visits and slightly higher utilization of ED visits, compared to FQHC non-users, after accounting for differences in case mix. This study suggests that FQHC care and non-FQHC care are associated with broadly similar levels of healthcare utilization among Medicare FFS beneficiaries.

Medicare Advantage and Fee-for-Service Performance on Clinical Quality and Patient Experience Measures: Comparisons from Three Large States.

OBJECTIVE: To compare performance between Medicare Advantage (MA) and Fee-for-Service (FFS) Medicare during a time of policy changes affecting both programs. DATA SOURCES/STUDY SETTING: Performance data for 16 clinical quality measures and 6 patient experience measures for 9.9 million beneficiaries living in California, New York, and Florida. STUDY DESIGN: We compared MA and FFS performance overall, by plan type, and within service areas associated with contracts between CMS and MA organizations. Case mix-adjusted analyses (for measures not typically adjusted) were used to explore the effect of case mix on MA/FFS differences. DATA COLLECTION/EXTRACTION METHODS: Performance measures were submitted by MA organizations, obtained from the nationwide fielding of the Medicare Consumer Assessment of Healthcare Providers and Systems (MCAHPS) Survey, or derived from claims. PRINCIPAL FINDINGS: Overall, MA outperformed FFS on all 16 clinical quality measures. Differences were large for HEDIS measures and small for Part D measures and remained after case mix adjustment. MA enrollees reported better experiences overall, but FFS beneficiaries reported better access to care. Relative to FFS, performance gaps were much wider for HMOs than PPOs. Excluding HEDIS measures, MA/FFS differences were much smaller in contract-level comparisons. CONCLUSIONS: Medicare Advantage/Fee-for-Service differences are often large but vary in important ways across types of measures and contracts.

Implementation of Medical Homes in 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 ($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.).

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

BACKGROUND: Patient-centered medical home (PCMH) models of primary care have the potential to expand access, improve population health, and lower costs. Federally qualified health centers (FQHCs) were early adopters of PCMH models. OBJECTIVE: We measured PCMH capabilities in a diverse nationwide sample of FQHCs and assessed the relationship between PCMH capabilities and Medicare beneficiary outcomes. DESIGN: Cross-sectional, propensity score-weighted, multivariable regression analysis. PARTICIPANTS: A convenience sample of 804 FQHC sites that applied to a nationwide FQHC PCMH initiative and 231,163 Medicare fee-for-service beneficiaries who received a plurality of their primary care services from these sites. MAIN MEASURES: PCMH capabilities were self-reported using the National Committee for Quality Assurance's (NCQA's) 2011 application for PCMH recognition. Measures of utilization, continuity of care, quality, and Medicare expenditures were derived from Medicare claims covering a 1-year period ending October 2011. KEY RESULTS: Nearly 88% of sites were classified as having PCMH capabilities equivalent to NCQA Level 1, 2, or 3 PCMH recognition. These more advanced sites were associated with 228 additional FQHC visits per 1000 Medicare beneficiaries (95% CI: 176, 278), compared with less advanced sites; 0.02 points higher practice-level continuity of care (95% CI: 0.01, 0.03); and a greater likelihood of administering two of four recommended diabetes tests. However, more advanced sites were also associated with 181 additional visits to specialists per 1000 beneficiaries (95% CI: 124, 232) and 64 additional visits to emergency departments (95% CI: 35, 89)-but with no differences in inpatient utilization. More advanced sites had higher Part B expenditures ($111 per beneficiary [95% CI: $61, $158]) and total Medicare expenditures of $353 [95% CI: $65, $614]). CONCLUSIONS: Implementation of PCMH models in FQHCs may be associated with improved primary care for Medicare beneficiaries. Expanded access to care, in combination with slower development of key PCMH capabilities, may explain higher Medicare expenditures and other types of utilization.

JOURNAL CLUB: Radiologists' Perceptions of Computerized Decision Support: A Focus Group Study From the Medicare Imaging Demonstration Project.

OBJECTIVE: The purpose of this study was to discern radiologists' perceptions regarding the implementation of a decision support system intervention as part of the Medicare Imaging Demonstration project and the effect of decision support on radiologists' interactions with ordering clinicians, their radiology work flow, and appropriateness of advanced imaging. SUBJECTS AND METHODS: A focus group study was conducted with a diverse sample of radiologists involved in interpreting advanced imaging studies at Medicare Imaging Demonstration project sites. A semistructured moderator guide was used, and all focus group discussions were recorded and transcribed verbatim. Qualitative data analysis software was used to code thematic content and identify representative segments of text. Participating radiologists also completed an accompanying survey designed to supplement focus group discussions. RESULTS: Twenty-six radiologists participated in four focus group discussions. The following major themes related to the radiologists' perceptions after decision support implementation were identified: no substantial change in radiologists' interactions with referring clinicians; no substantial change in radiologist work flow, including protocol-writing time; and no perceived increase in imaging appropriateness. Radiologists provided suggestions for improvements in the decision support system, including increasing the usability of clinical data captured, and expressed a desire to have greater involvement in future development and implementation efforts. CONCLUSION: Overall, radiologists from health care systems involved in the Medicare Imaging Demonstration did not perceive that decision support had a substantial effect, either positive or negative, on their professional roles and responsibilities. Radiologists expressed a desire to improve efficiencies and quality of care by having greater involvement in future efforts.

Specialty Payment Model Opportunities and Assessment: Gastroenterology and Cardiology Model Design Report.

Gastroenterology and cardiology services are common and costly among Medicare beneficiaries. Episode-based payment, which aims to create incentives for high-quality, low-cost care, has been identified as a promising alternative payment model. This article describes research related to the design of episode-based payment models for ambulatory gastroenterology and cardiology services for possible testing by the Center for Medicare and Medicaid Innovation at the Centers for Medicare and Medicaid Services (CMS). The authors analyzed Medicare claims data to describe the frequency and characteristics of gastroenterology and cardiology index procedures, the practices that delivered index procedures, and the patients that received index procedures. The results of these analyses can help inform CMS decisions about the definition of episodes in an episode-based payment model; payment adjustments for service setting, multiple procedures, or other factors; and eligibility for the payment model.

Specialty Payment Model Opportunities and Assessment: Oncology Model Design Report.

This article describes research related to the design of a payment model for specialty oncology services for possible testing by the Center for Medicare and Medicaid Innovation at the Centers for Medicare & Medicaid Services (CMS). Cancer is a common and costly condition. Episode-based payment, which aims to create incentives for high-quality, low-cost care, has been identified as a promising alternative payment model for oncology care. Episode-based payment systems can provide flexibility to health care providers to select among the most effective and efficient treatment alternatives, including activities that are not currently reimbursed under Medicare payment policies. However, the model design also needs to ensure that high-quality care is delivered and that beneficial treatments are not withheld from patients. CMS asked MITRE and RAND to conduct analyses to inform design decisions related to an episode-based oncology model for Medicare beneficiaries undergoing chemotherapy treatment for cancer. In particular, this study focuses on analyses of Medicare claims data related to the definition of the initiation of an episode of chemotherapy, patterns of spending during and surrounding episodes of chemotherapy, and attribution of episodes of chemotherapy to physician practices. We found that the time between the primary cancer diagnosis and chemotherapy initiation varied widely across patients, ranging from one day to over seven years, with a median of 2.4 months. The average level of total monthly payments varied considerably across cancers, with the highest spending peak of $9,972 for lymphoma, and peaks of $3,109 for breast cancer and $2,135 for prostate cancer.

Specialty Payment Model Opportunities and Assessment: Oncology Simulation Report.

This article describes the results of a simulation analysis of a payment model for specialty oncology services that is being developed for possible testing by the Center for Medicare and Medicaid Innovation at the Centers for Medicare & Medicaid Services (CMS). CMS asked MITRE and RAND to conduct simulation analyses to preview some of the possible impacts of the payment model and to inform design decisions related to the model. The simulation analysis used an episode-level dataset based on Medicare fee-for-service (FFS) claims for historical oncology episodes provided to Medicare FFS beneficiaries in 2010. Under the proposed model, participating practices would continue to receive FFS payments, would also receive per-beneficiary per-month care management payments for episodes lasting up to six months, and would be eligible for performance-based payments based on per-episode spending for attributed episodes relative to a per-episode spending target. The simulation offers several insights into the proposed payment model for oncology: (1) The care management payments used in the simulation analysis-$960 total per six-month episode-represent only 4 percent of projected average total spending per episode (around $27,000 in 2016), but they are large relative to the FFS revenues of participating oncology practices, which are projected to be around $2,000 per oncology episode. By themselves, the care management payments would increase physician practices' Medicare revenues by roughly 50 percent on average. This represents a substantial new outlay for the Medicare program and a substantial new source of revenues for oncology practices. (2) For the Medicare program to break even, participating oncology practices would have to reduce utilization and intensity by roughly 4 percent. (3) The break-even point can be reduced if the care management payments are reduced or if the performance-based payments are reduced.

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 $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.

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 Medicine's 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.

Diminishing efficacy of combination therapy, response-heterogeneity, and treatment intolerance limit the attainability of tight risk factor control in patients with diabetes.

OBJECTIVE: To evaluate the attainability of tight risk factor control targets for three diabetes risk factors and to assess the degree of polypharmacy required. DATA SOURCES/STUDY SETTING: National Health and Nutrition Examination Survey-III. STUDY DESIGN: We simulated a strategy of "treating to targets," exposing subjects to a battery of treatments until low-density lipoprotein (LDL)-cholesterol (100 mg/dL), hemoglobin A1c (7 percent), and blood pressure (130/80 mm Hg) targets were achieved or until all treatments had been exhausted. Regimens included five statins of increasing potency, four A1c-lowering therapies, and eight steps of antihypertensive therapy. DATA COLLECTION/EXTRACTION METHODS: We selected parameter estimates from placebo-controlled trials and meta-analyses. PRINCIPAL FINDINGS: Under ideal efficacy conditions, 77, 64, and 58 percent of subjects achieved the LDL, A1c, and blood pressure targets, respectively. Successful control depended highly on a subject's baseline number of treatments. Using the least favorable assumptions of treatment tolerance, success rates were 11-17 percentage points lower. Approximately 57 percent of subjects required five or more medication classes. CONCLUSIONS: A significant proportion of people with diabetes will fail to achieve targets despite using high doses of multiple, conventional treatments. These findings raise concerns about the feasibility and polypharmacy burden needed for tight risk factor control, and the use of measures of tight control to assess the quality of care for diabetes.