Longitudinal analysis of antibody responses to Plasmodium vivax sporozoite antigens following natural infection.

BACKGROUND: P. vivax malaria is a major global health burden hindering social and economic development throughout many tropical and sub-tropical countries. Pre-erythrocytic (PE) vaccines emerge as an attractive approach for the control and elimination of malaria infection. Therefore, evaluating the magnitude, longevity and prevalence of naturally acquired IgG antibody responses against PE candidate antigens is useful for vaccine design. METHODOLOGY/PRINCIPAL FINDINGS: The antigenicity of five recombinant PE antigens (PvCSP-VK210, PvSSP3, PvM2-MAEBL, PvCelTOS and PvSPECT1) was evaluated in plasma samples from individuals residing in low transmission areas in Thailand (Ranong and Chumphon Provinces). The samples were collected at the time of acute vivax malaria and 90, 270 and 360 days later. The prevalence, magnitude and longevity of total IgG and IgG subclasses were determined for each antigen using the longitudinal data. Our results showed that seropositivity of all tested PE antigens was detected during infection in at least some subjects; anti-PvCSP-VK210 and anti-PvCelTOS antibodies were the most frequent. Titers of these antibodies declined during the year of follow up, but notably seropositivity persisted. Among seropositive subjects at post-infection, high number of subjects possessed antibodies against PvCSP-VK210. Anti-PvSSP3 antibody responses had the longest half-life. IgG subclass profiling showed that the predominant subclasses were IgG1 and IgG3 (cytophilic antibodies), tending to remain detectable for at least 360 days after infection. CONCLUSIONS/SIGNIFICANCE: The present study demonstrated the magnitude and longevity of serological responses to multiple PE antigens of P. vivax after natural infection. This knowledge could contribute to the design of an effective P. vivax vaccine.

Income-related disparities in Medicare advantage behavioral health care quality.

OBJECTIVE: To inform efforts to improve equity in the quality of behavioral health care by examining income-related differences in performance on HEDIS behavioral health measures in Medicare Advantage (MA) plans. DATA SOURCES AND STUDY SETTING: Reporting Year 2019 MA HEDIS data were obtained and analyzed. STUDY DESIGN: Logistic regression models were used to estimate differences in performance related to enrollee income, adjusting for sex, age, and race-and-ethnicity. Low-income enrollees were identified by Dual Eligibility for Medicare and Medicaid or receipt of the Low-Income Subsidy (DE/LIS). Models without and with random effects for plans were used to estimate overall and within-plan differences in measure performance. Heterogeneity by race-and-ethnicity in the associations of low-income with behavioral health quality were examined using models with interaction terms. DATA COLLECTION/EXTRACTION METHODS: Data were included for all MA contracts in the 50 states and the District of Columbia that collect HEDIS data. PRINCIPAL FINDINGS: For six of the eight measures, enrollees with DE/LIS coverage were more likely to have behavioral health conditions that qualify for HEDIS measures than higher income enrollees. In mixed-effects logistic regression models, DE/LIS coverage was associated with statistically significantly worse overall performance on five measures, with four large (>5 percentage point) differences (-7.5 to -11.1 percentage points) related to follow-up after hospitalization and avoidance of drug-disease interactions. Where the differences were large, they were primarily within-plan rather than between-plan. Interactions between DE/LIS and race-and-ethnicity were statistically significant (p < 0.05) for all measures; income-based quality gaps were larger for White enrollees than for Black or Hispanic enrollees. CONCLUSIONS: Low income is associated with lower performance on behavioral health HEDIS measures in MA, but these associations differ across racial-and-ethnic groups. Improving care integration and addressing barriers to care for low-income enrollees may improve equity across income levels in behavioral health care.

The Contribution of First-name Information to the Accuracy of Racial-and-Ethnic Imputations Varies by Sex and Race-and-Ethnicity Among Medicare Beneficiaries.

BACKGROUND: Data on race-and-ethnicity that are needed to measure health equity are often limited or missing. The importance of first name and sex in predicting race-and-ethnicity is not well understood. OBJECTIVE: The objective of this study was to compare the contribution of first-name information to the accuracy of basic and more complex racial-and-ethnic imputations that incorporate surname information. RESEARCH DESIGN: We imputed race-and-ethnicity in a sample of Medicare beneficiaries under 2 scenarios: (1) with only sparse predictors (name, address, sex) and (2) with a rich set (adding limited administrative race-and-ethnicity, demographics, and insurance). SUBJECTS: A total of 284,627 Medicare beneficiaries who completed the 2014 Medicare Consumer Assessment of Healthcare Providers and Systems survey and reported race-and-ethnicity were included. RESULTS: Hispanic, non-Hispanic Asian/Pacific Islander, and non-Hispanic White racial-and-ethnic imputations are more accurate for males than females under both sparse-predictor and rich-predictor scenarios; adding first-name information increases accuracy more for females than males. In contrast, imputations of non-Hispanic Black race-and-ethnicity are similarly accurate for females and males, and first names increase accuracy equally for each sex in both sparse-predictor and rich-predictor scenarios. For all 4 racial-and-ethnic groups, incorporating first-name information improves prediction accuracy more under the sparse-predictor scenario than under the rich-predictor scenario. CONCLUSION: First-name information contributes more to the accuracy of racial-and-ethnic imputations in a sparse-predictor scenario than in a rich-predictor scenario and generally narrows sex gaps in accuracy of imputations.

Disparities In The Quality Of Clinical Care Delivered To American Indian/Alaska Native Medicare Advantage Enrollees.

This study used data from the 2019 Healthcare Effectiveness Data and Information Set (HEDIS) to examine differences in the quality of care received by American Indian/Alaska Native beneficiaries versus care received by non-Hispanic White beneficiaries enrolled in Medicare Advantage (managed care) plans. American Indian/Alaska Native beneficiaries were more likely than White beneficiaries to receive care that meets clinical standards for eight of twenty-six HEDIS measures and were less likely than White beneficiaries to receive care that meets clinical standards for five of twenty-six measures. Measures for which American Indian/Alaska Native beneficiaries were less likely to receive care meeting clinical standards were mainly ones pertaining to appropriate treatment of diagnosed conditions. In all cases, differences in care for American Indian/Alaska Native and White beneficiaries were largely within-plan differences. These findings indicate the need for improved clinical care for all beneficiaries. For American Indian/Alaska Native beneficiaries, there is a particular need for improvement in the treatment of diagnosed conditions, including diabetes, chronic obstructive pulmonary disease, and alcohol and other forms of substance abuse.

Patient-Reported Care Coordination is Associated with Better Performance on Clinical Care Measures.

BACKGROUND: Prior studies using aggregated data suggest that better care coordination is associated with higher performance on measures of clinical care process; it is unclear whether this relationship reflects care coordination activities of health plans or physician practices. OBJECTIVE: Estimate within-plan relationships between beneficiary-reported care coordination measures and HEDIS measures of clinical process for the same individuals. DESIGN: Mixed-effect regression models in cross-sectional data. PARTICIPANTS: 2013 Medicare Advantage CAHPS respondents (n=152,069) with care coordination items linked to independently collected HEDIS data on clinical processes. MAIN MEASURES: Care coordination measures assessed follow-up, whether doctors had medical records during visits, whether doctors discussed medicines being taken, how informed doctors seemed about specialist care, and help received with managing care among different providers. HEDIS measures included mammography, colorectal cancer screening, cardiovascular LDL-C screening, controlling blood pressure, 5 diabetes care measures (LDL-C screening, retinal eye exam, nephropathy, blood sugar/HbA1c <9%, LCL-C<100 mg/dL), glaucoma screening in older adults, BMI assessment, osteoporosis management for women with a fracture, and rheumatoid arthritis therapy. KEY RESULTS: For 9 of the 13 HEDIS measures, within health plans, beneficiaries who reported better care coordination also received better clinical care (p<0.05) and none of the associations went in the opposite direction; HEDIS differences between those with excellent and poor coordination exceeded 5 percentage points for 7 measures. Nine measures had positive associations (breast cancer screening, colorectal cancer screening, cardiovascular care LDL-C screening, 4 of 5 diabetes care measures, osteoporosis management, and rheumatoid arthritis therapy). CONCLUSIONS: Within health plans, beneficiaries who report better care coordination also received higher-quality clinical care, particularly for care processes that entail organizing patient care activities and sharing information among different healthcare providers. These results extend prior research showing that health plans with better beneficiary-reported care coordination achieved higher HEDIS performance scores.

Defining the 90-day cost structure of lower extremity revascularization for alternative payment model assessment.

BACKGROUND: The U.S. healthcare system is undergoing a broad transformation from the traditional fee-for-service model to value-based payments. The changes introduced by the Medicare Quality Payment Program, including the establishment of Alternative Payment Models, ensure that the practice of vascular surgery is likely to face significant reimbursement changes as payments transition to favor these models. The Society for Vascular Surgery Alternative Payment Model taskforce was formed to explore the opportunities to develop a physician-focused payment model that will allow vascular surgeons to continue to deliver the complex care required for peripheral arterial disease (PAD). METHODS: A financial analysis was performed based on Medicare beneficiaries who had undergone qualifying index procedures during fiscal year 2016 through the third quarter of 2017. Index procedures were defined using a list of Healthcare Common Procedural Coding (HCPC) procedure codes that represent open and endovascular PAD interventions. Inpatient procedures were mapped to three diagnosis-related group (DRG) families consistent with PAD conditions: other vascular procedures (codes, 252-254), aortic and heart assist procedures (codes, 268, 269), and other major vascular procedures (codes, 270-272). Patients undergoing outpatient or office-based procedures were included if the claims data were inclusive of the HCPC procedure codes. Emergent procedures, patients with end-stage renal disease, and patients undergoing interventions within the 30 days preceding the index procedure were excluded. The analysis included usage of postacute care services (PACS) and 90-day postdischarge events (PDEs). PACS are defined as rehabilitation, skilled nursing facility, and home health services. PDEs included emergency department visits, observation stays, inpatient readmissions, and reinterventions. RESULTS: A total of 123,180 cases were included. Of these 123,180 cases, 82% had been performed in the outpatient setting. The Medicare expenditures for all periprocedural services provided at the index procedure (ie, professional, technical, and facility fees) were higher in the inpatient setting, with an average reimbursement per index case of $18,755, $34,600, and $25,245 for DRG codes 252 to 254, DRG codes 268 and 269, and DRG codes 270 to 272, respectively. Outpatient facility interventions had an average reimbursement of $11,458, and office-based index procedures had costs of $11,533. PACS were more commonly used after inpatient index procedures. In the inpatient setting, PACS usage and reimbursement were 58.6% ($5338), 57.2% ($4192), and 55.9% ($5275) for DRG codes 252 to 254, DRG codes 268 and 269, and DRG codes 270 to 272, respectively. Outpatient facility cases required PACS for 13.7% of cases (average cost, $1352), and office-based procedures required PACS in 15% of cases (average cost, $1467). The 90-day PDEs were frequent across all sites of service (range, 38.9%-50.2%) and carried significant costs. Readmission was associated with the highest average PDE expenditure (range, $13,950-$18.934). The average readmission Medicare reimbursement exceeded that of the index procedures performed in the outpatient setting. CONCLUSIONS: The cost of PAD interventions extends beyond the index procedure and includes relevant spending during the long postoperative period. Despite the analysis challenges related to the breadth of vascular procedures and the site of service variability, the data identified potential cost-saving opportunities in the management of costly PDEs. Because of the vulnerability of the PAD patient population, alternative payment modeling using a bundled value-based approach will require reallocation of resources to provide longitudinal patient care extending beyond the initial intervention.

The Society for Vascular Surgery Alternative Payment Model Task Force report on opportunities for value-based reimbursement in care for patients with peripheral artery disease.

The Society for Vascular Surgery Alternative Payment Model (APM) Taskforce document explores the drivers and implications for developing objective value-based reimbursement plans for the care of patients with peripheral arterial disease (PAD). The APM is a payment approach that highlights high-quality and cost-efficient care and is a financially incentivized pathway for participation in the Quality Payment Program, which aims to replace the traditional fee-for-service payment method. At present, the participation of vascular specialists in APMs is hampered owing to the absence of dedicated models. The increasing prevalence of PAD diagnosis, technological advances in therapeutic devices, and the increasing cost of care of the affected patients have financial consequences on care delivery models and population health. The document summarizes the existing measurement methods of cost, care processes, and outcomes using payor data, patient-reported outcomes, and registry participation. The document also evaluates the existing challenges in the evaluation of PAD care, including intervention overuse, treatment disparities, varied clinical presentations, and the effects of multiple comorbid conditions on the cost potentially attributable to the vascular interventionalist. Medicare reimbursement data analysis also confirmed the prolonged need for additional healthcare services after vascular interventions. The Society for Vascular Surgery proposes that a PAD APM should provide patients with comprehensive care using a longitudinal approach with integration of multiple key medical and surgical services. It should maintain appropriate access to diagnostic and therapeutic advancements and eliminate unnecessary interventions. It should also decrease the variability in care but must also consider the varying complexity of the presenting PAD conditions. Enhanced quality of care and physician innovation should be rewarded. In addition, provisions should be present within an APM for high-risk patients who carry the risk of exclusion from care because of the naturally associated high costs. Although the document demonstrates clear opportunities for quality improvement and cost savings in PAD care, continued PAD APM development requires the assessment of more granular data for accurate risk adjustment, in addition to largescale testing before public release. Collaboration between payors and physician specialty societies remains key.

Preoperative Vitamin D Repletion in Total Knee Arthroplasty: A Cost-Effectiveness Model.

BACKGROUND: Recent studies have identified vitamin D deficiency (serum 25-hydroxyvitamin D [25(OH)D] < 20 ng/L) as a potentially modifiable risk factor for prosthetic joint infection (PJI) in arthroplasty. The purpose of this study is to determine whether implementation of preoperative 25(OH)D repletion is cost-effective for reducing PJI following total knee arthroplasty (TKA). METHODS: A cost estimation predictive model was generated to determine the utility of both selective and nonselective 25(OH)D repletion in primary TKA to prevent PJI. Input data on the incidence of 25(OH)D deficiency, relative complication rates, and costs of serum 25(OH)D repletion and 2-stage revision for PJI were derived from previously published literature identified using systematic review and publicly available data from Medicare reimbursement schedules. Mean, lower, and upper bounds of 1-year cost savings were computed for nonselective and selective repletion relative to no repletion. RESULTS: Selective preoperative 25(OH)D screening and repletion were projected to result in $1,504,857 (range, $215,084-$4,256,388) in cost savings per 10,000 cases. Nonselective 25(OH)D repletion was projected to result in $1,906,077 (range, $616,304-$4,657,608) in cost savings per 10,000 cases. With univariate adjustment, nonselective repletion is projected to be cost-effective in scenarios where revision for PJI costs ≥$10,636, incidence of deficiency is ≥1.1%, and when repletion has a relative risk reduction ≥4.2%. CONCLUSION: This predictive model supports the potential role of 25(OH)D repletion as a cost-effective mechanism of reducing PJI risk in TKA. Given the low cost of 25(OH)D repletion relative to serum laboratory testing, nonselective repletion appears to be more cost-effective than selective repletion. Further prospective investigation to assess this modifiable risk factor is warranted.

Impact of Social Needs Navigation on Utilization Among High Utilizers in a Large Integrated Health System: a Quasi-experimental Study.

BACKGROUND: Programs addressing social determinants of health for high-utilizing patients are gaining interest among health systems as an avenue to promote health and decrease utilization. OBJECTIVE: To evaluate impacts of a social needs screening and navigation program for adult predicted high utilizers on total medical visit utilization. DESIGN: A prospective, quasi-experimental study using an intent-to-treat propensity-weighted difference-in-differences approach. Stratified analyses assessed intervention effects among three low-socioeconomic status sub-samples: patients in low-income areas, in low-education areas, and with Medicaid insurance. PARTICIPANTS: Predicted high utilizers-patients predicted to be in the highest 1% for total utilization in a large integrated health system. INTERVENTION: A telephonic social needs screening and navigation program. MAIN MEASURES: Primary difference-in-difference analyses compared total visit count utilization, including outpatient, emergency department (ED), and inpatient utilization, between the intervention and control groups at both in-network and out-of-network facilities. Prevalence of social needs among sample patients and their connection rates to social needs resources are also described. KEY RESULTS: The study included 34,225 patients (7107 intervention, 27,118 control). Most (53%) patients screened reported social needs, but only a minority (10%) of those with a need were able to connect with resources to address these needs. Primary analysis found total utilization visits decreased 2.2% (95% CI - 4.5%, 0.1%; p = 0.058) in the intervention group. Stratified analyses showed decreases in total utilization for all low-socioeconomic status subgroups receiving the intervention compared with controls: - 7.0% (95% CI - 11.9%, - 1.9%; p = 0.008) in the low-income area group, - 11.5% (- 17.6%, 5.0%; p < 0.001) in the low-education area group, and - 12.1% (- 18.1%, - 5.6%; p < 0.001) in the Medicaid group. CONCLUSIONS: Social needs navigation programs for high-utilizing patients may have modest effects on utilization for the population overall. However, significant decreases in utilization were found among low-socioeconomic status patients more likely to experience social needs.

Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity.

OBJECTIVE: To improve an existing method, Medicare Bayesian Improved Surname Geocoding (MBISG) 1.0 that augments the Centers for Medicare & Medicaid Services' (CMS) administrative measure of race/ethnicity with surname and geographic data to estimate race/ethnicity. DATA SOURCES/STUDY SETTING: Data from 284 627 respondents to the 2014 Medicare CAHPS survey. STUDY DESIGN: We compared performance (cross-validated Pearson correlation of estimates and self-reported race/ethnicity) for several alternative models predicting self-reported race/ethnicity in cross-sectional observational data to assess accuracy of estimates, resulting in MBISG 2.0. MBISG 2.0 adds to MBISG 1.0 first name, demographic, and coverage predictors of race/ethnicity and uses a more flexible data aggregation framework. DATA COLLECTION/EXTRACTION METHODS: We linked survey-reported race/ethnicity to CMS administrative and US census data. PRINCIPAL FINDINGS: MBISG 2.0 removed 25-39 percent of the remaining MBISG 1.0 error for Hispanics, Whites, and Asian/Pacific Islanders (API), and 9 percent for Blacks, resulting in correlations of 0.88 to 0.95 with self-reported race/ethnicity for these groups. CONCLUSIONS: MBISG 2.0 represents a substantial improvement over MBISG 1.0 and the use of CMS administrative data on race/ethnicity alone. MBISG 2.0 is used in CMS' public reporting of Medicare Advantage contract HEDIS measures stratified by race/ethnicity for Hispanics, Whites, API, and Blacks.

Racial And Ethnic Differences In The Attainment Of Behavioral Health Quality Measures In Medicare Advantage Plans.

As the Medicare population becomes more diverse and its demand for behavioral health care grows, a better understanding of racial/ethnic disparities in the quality of behavioral health care is crucial. Medicare Advantage (MA) plans are accountable through the public reporting of quality performance on measures, including the Healthcare Effectiveness Data and Information Set (HEDIS). We examined HEDIS data on eight MA behavioral health care quality measures, using mixed-effects logistic regressions to distinguish racial/ethnic differences within and between MA health plans. We found that performance differed across racial/ethnic groups by more than 10 percentage points on most quality measures. Significant within-plan disparities were found in twenty of twenty-four comparisons of racial/ethnic minority groups with whites. Within-plan disparities varied widely across plans, with performance being equivalent across racial/ethnic groups in some plans and widely divergent in others. Unlike other types of medical care, in behavioral health within-plan quality disparities are prominent in MA plans, which suggests a role for stratified reporting by racial/ethnic group.

How Do Gender Differences in Quality of Care Vary Across Medicare Advantage Plans?

BACKGROUND: Healthcare Effectiveness Data and Information Set (HEDIS) quality measures have long been used to compare care across health plans and to study racial/ethnic and socioeconomic disparities among Medicare Advantage (MA) beneficiaries. However, possible gender differences in seniors' quality of care have received less attention. OBJECTIVE: To test for the presence and nature of any gender differences in quality of care across MA Plans, overall and by domain; to identify those most at risk of poor care. DESIGN: Cross-sectional analysis of individual-level HEDIS measure scores from 23.8 million records using binomial mixed-effect models to estimate the effect of gender on performance. For each measure, we assess variation in gender gaps and their correlation with plan performance. PARTICIPANTS: Beneficiaries from 456 MA plans in 2011-2012 HEDIS data. MAIN MEASURES: Performance on 32 of 34 HEDIS measures which were available in both measurement years. The two excluded measures had mean performance scores below 10%. KEY RESULTS: Women experienced better quality of care than men for 22/32 measures, with most pertaining to screening or treatment. Men experienced better quality on nine measures, including four related to cardiovascular disease and three to potentially harmful drug-disease interactions. Plans varied substantially in the magnitude of gender gaps for 21/32 measures; in general, the gender gap in quality of care was least favorable to men in low-performing plans. CONCLUSIONS: Women generally experienced better quality of care than men. However, women experienced poorer care for cardiovascular disease-related intermediate outcomes and potentially harmful drug-disease interactions. Quality improvement may be especially important for men in low-performing plans and for cardiovascular-related care and drug-disease interactions for women. Gender-stratified reporting could reveal gender gaps, identify plans for which care varies by gender, and motivate efforts to address faults and close the gaps in the delivery system.

Author Correction: A comprehensive model for assessment of liver stage therapies targeting Plasmodium vivax and Plasmodium falciparum.

The original version of this Article contained an error in the spelling of Richard Thomson-Luque, which was incorrectly given as Richard Thomson Luque. This error has now been corrected in both the PDF and HTML versions of the Article.

A comprehensive model for assessment of liver stage therapies targeting Plasmodium vivax and Plasmodium falciparum.

Malaria liver stages represent an ideal therapeutic target with a bottleneck in parasite load and reduced clinical symptoms; however, current in vitro pre-erythrocytic (PE) models for Plasmodium vivax and P. falciparum lack the efficiency necessary for rapid identification and effective evaluation of new vaccines and drugs, especially targeting late liver-stage development and hypnozoites. Herein we report the development of a 384-well plate culture system using commercially available materials, including cryopreserved primary human hepatocytes. Hepatocyte physiology is maintained for at least 30 days and supports development of P. vivax hypnozoites and complete maturation of P. vivax and P. falciparum schizonts. Our multimodal analysis in antimalarial therapeutic research identifies important PE inhibition mechanisms: immune antibodies against sporozoite surface proteins functionally inhibit liver stage development and ion homeostasis is essential for schizont and hypnozoite viability. This model can be implemented in laboratories in disease-endemic areas to accelerate vaccine and drug discovery research.

Do reimbursement recommendation processes used by government drug plans in Canada adhere to good governance principles?

In democratic societies, good governance is the key to assuring the confidence of stakeholders and other citizens in how governments and organizations interact with and relate to them and how decisions are taken. Although defining good governance can be debatable, the United Nations Development Program (UNDP) set of principles is commonly used. The reimbursement recommendation processes of the Canadian Agency for Drugs and Technologies in Health (CADTH), which carries out assessments for all public drug plans outside Quebec, are examined in the light of the UNDP governance principles and compared with the National Institute for Health and Care Excellence system in England. The adherence of CADTH's processes to the principles of accountability, transparency, participatory, equity, responsiveness and consensus is poor, especially when compared with the English system, due in part to CADTH's lack of genuine independence. CADTH's overriding responsibility is toward the governments that "own," fund and manage it, while the agency's status as a not-for-profit corporation under federal law protects it from standard government forms of accountability. The recent integration of CADTH's reimbursement recommendation processes with the provincial public drug plans' collective system for price negotiation with pharmaceutical companies reinforces CADTH's role as a nonindependent partner in the pursuit of governments' cost-containment objectives, which should not be part of its function. Canadians need a national organization for evaluating drugs for reimbursement in the public interest that fully embraces the principles of good governance - one that is publicly accountable, transparent and fair and includes all stakeholders throughout its processes.

What Role Does Efficiency Play in Understanding the Relationship Between Cost and Quality in Physician Organizations?

BACKGROUND: The belief that there is inefficiency, or the potential to improve patient health at current levels of spending, is driving the push for greater value in health care. Previous studies demonstrate overuse of a narrow set of services, suggesting provider inefficiency, but existing studies neither quantify inefficiency more broadly nor assess its variation across physician organizations (POs). DATA AND METHODS: We used data on quality of care and total cost of care from 129 California POs participating in a statewide value-based pay-for-performance program. We estimated a production function with quality as the output and cost as the input, using a stochastic frontier model, to develop a measure of relative efficiency for each PO. To validate the efficiency measure, we examined correlations of PO efficiency estimates with indicators representing overuse of services. RESULTS: The estimated production function showed that PO quality was positively associated with costs, although there were diminishing marginal returns to spending. A certain minimum level of spending was associated with high quality even among efficient POs. Most strikingly, however, POs had substantial variation in efficiency, producing widely differing levels of quality for the same cost. CONCLUSIONS: Differences among POs in the efficiency with which they produce quality suggest opportunities for improvements in care delivery that increase quality without increasing spending.

Misclassification Risk of Tier-Based Physician Quality Performance Systems.

OBJECTIVE: There is increasing interest in identifying high-quality physicians, such as whether physicians perform above or below a threshold level. To evaluate whether current methods accurately distinguish above- versus below-threshold physicians, we estimate misclassification rates for two-category identification systems. DATA SOURCES: Claims data for Medicare fee-for-service beneficiaries residing in Florida or New York in 2010. STUDY DESIGN: Estimate colorectal cancer, glaucoma, and diabetes quality scores for 23,085 physicians. Use a beta-binomial model to estimate physician score reliabilities. Compute the proportion of physicians whose performance tier would be misclassified under three scoring systems. PRINCIPAL FINDINGS: In the three scoring systems, misclassification ranges were 8.6-25.7 percent, 6.4-22.8 percent, and 4.5-21.7%. True positive rate ranges were 72.9-97.0 percent, 83.4-100.0 percent, and 34.7-88.2 percent. True negative rate ranges were 68.5-91.6 percent, 10.5-92.4 percent, and 81.1-99.9 percent. Positive predictive value ranges were 70.5-91.6 percent, 77.0-97.3 percent, and 55.2-99.1 percent. CONCLUSIONS: Current methods for profiling physicians on quality may produce misleading results, as the number of eligible events is typically small. Misclassification is a policy-relevant measure of the potential impact of tiering on providers, payers, and patients. Quantifying misclassification rates should inform the construction of high-performance networks and quality improvement initiatives.

The Comparison of Matching Methods Using Different Measures of Balance: Benefits and Risks Exemplified within a Study to Evaluate the Effects of German Disease Management Programs on Long-Term Outcomes of Patients with Type 2 Diabetes.

OBJECTIVE: To present a case study on how to compare various matching methods applying different measures of balance and to point out some pitfalls involved in relying on such measures. DATA SOURCES: Administrative claims data from a German statutory health insurance fund covering the years 2004-2008. STUDY DESIGN: We applied three different covariance balance diagnostics to a choice of 12 different matching methods used to evaluate the effectiveness of the German disease management program for type 2 diabetes (DMPDM2). We further compared the effect estimates resulting from applying these different matching techniques in the evaluation of the DMPDM2. PRINCIPAL FINDINGS: The choice of balance measure leads to different results on the performance of the applied matching methods. Exact matching methods performed well across all measures of balance, but resulted in the exclusion of many observations, leading to a change of the baseline characteristics of the study sample and also the effect estimate of the DMPDM2. All PS-based methods showed similar effect estimates. Applying a higher matching ratio and using a larger variable set generally resulted in better balance. Using a generalized boosted instead of a logistic regression model showed slightly better performance for balance diagnostics taking into account imbalances at higher moments. CONCLUSION: Best practice should include the application of several matching methods and thorough balance diagnostics. Applying matching techniques can provide a useful preprocessing step to reveal areas of the data that lack common support. The use of different balance diagnostics can be helpful for the interpretation of different effect estimates found with different matching methods.

Estimating causal effects for multivalued treatments: a comparison of approaches.

Interventions with multivalued treatments are common in medical and health research, such as when comparing the efficacy of competing drugs or interventions, or comparing between various doses of a particular drug. In recent years, there has been a growing interest in the development of multivalued treatment effect estimators using observational data. In this paper, we compare the performance of commonly used regression-based methods that estimate multivalued treatment effects based on the unconfoundedness assumption. These estimation methods fall into three general categories: (i) estimators based on a model for the outcome variable using conventional regression adjustment; (ii) weighted estimators based on a model for the treatment assignment; and (iii) 'doubly-robust' estimators that model both the treatment assignment and outcome variable within the same framework. We assess the performance of these models using Monte Carlo simulation and demonstrate their application with empirical data. Our results show that (i) when models estimating both the treatment and outcome are correctly specified, all adjustment methods provide similar unbiased estimates; (ii) when the outcome model is misspecified, regression adjustment performs poorly, while all the weighting methods provide unbiased estimates; (iii) when the treatment model is misspecified, methods based solely on modeling the treatment perform poorly, while regression adjustment and the doubly robust models provide unbiased estimates; and (iv) when both the treatment and outcome models are misspecified, all methods perform poorly. Given that researchers will rarely know which of the two models is misspecified, our results support the use of doubly robust estimation.