Reproducibility of the medical cost estimation from the Medicare Current Beneficiary Survey: Comparing claims and survey.

Background: The Medicare Current Beneficiary Survey (MCBS) limited-access data provides the unique opportunity to utilize administrative claims and adjusted survey data to investigate trends in utilization and medical expenditure across time. The adjusted survey data is a synthesized, matched version of the original survey data and claims. Researchers may choose adjusted survey data or original claims for cost evaluations according to their research purpose. However, limited research has examined methodological issues when estimating medical cost using different MCBS data sources. Objective: The study objective was to examine the reproducibility of individual-level medical cost using both MCBS data sources: adjusted survey and claims data. Methods: This serial cross-sectional study design analyzed 2006-2012 MCBS data. The sample included noninstitutionalized older Medicare beneficiaries (≥65 years old), with a cancer diagnosis and annually enrolled in Medicare Parts A, B, and D. The population was stratified by diabetes diagnosis. The primary outcome was annual medical cost. We investigated the discrepancies of medical cost estimated from the adjusted survey and original claims data. The agreement between cost estimates from the two sources in each year was determined using the Wilcoxon signed-rank test. Results: A total of 4918 eligible Medicare beneficiaries were included in this study, and 26% of beneficiaries also had diabetes (N = 1275). Significant disagreements in cost estimates between adjusted survey and claims data were present regardless of disease complexity (with or without diabetes). Significant disagreements in medical cost estimates were present in most years, except in 2010 (p = 0.467) and 2011 (p = 0.098), for beneficiaries with cancer and diabetes (p < 0.001 for all). Significant disagreements in medical cost estimates were present in all years for beneficiaries with cancer without diabetes (p < 0.001 for all). Conclusions: Based on discrepant cost estimates across data sources, researchers using MCBS to estimate costs should be cautious when using claims or adjusted survey data alone.

Pharmacogenomic Testing and Patient Perception Inform Pain Pharmacotherapy.

(1) Background: Chronic pain is one of the most common reasons for individuals to seek medications. Historically, opioids have been the mainstay of chronic pain management. However, in some patient populations, opioids fail to demonstrate therapeutic efficacy, whereas in other populations, opioids may cause toxic effects, even at lower doses. Response to pain medication is affected by many factors, including an individual's genetic variations. Pharmacogenomic testing has been designed to help achieve optimal treatment outcomes. This study aimed at assessing the impact of CYP2D6 pharmacogenomic testing on physicians' choice in prescribing chronic pain medications and patient pain control. (2) Methods: This retrospective study reviewed 107 patient charts from a single site pain management center. All 107 patients received pharmacogenomic testing. The outcomes of interest were confirmation that the optimal pain medication is being administered or a change in the chronic pain medication is warranted as a result of the pharmacogenomic testing. The main independent variable was the pharmacogenomic test result. Other independent variables included patient gender, race, and comorbidities. The retrospective study was reviewed and approved by the Touro College and University System IRB, HSIRB1653E. (3) Results: Patients self-reported pain intensity on a scale of 1-10 before and after pharmacogenomic testing. Then, 100% of patients in the retrospective study were tested for their pain pharmacogenomic profile. Of the 107 patients participating in the study, more than 50% had their medications altered as a result of the pharmacogenomic testing. The percentage of patients with intense pain were decreased post-pharmacogenomic testing (5.6%) as compared to pre-pharmacogenomic testing (10.5%). Patients with intense, moderate, and mild pain categories were more likely to receive changes in pain medications. In contrast, patients with severe pain were less likely to receive a change in pain medication. Hispanic ethnicity was associated with a statistically significantly decrease in a pain scale category. Illegal drug abuse was associated with a decrease in pain scale category. Change in medication dose was associated with a decrease in pain scale category. (4) Conclusion: In this retrospective study, implementation of pharmacogenomic testing demonstrated significant benefits to patients with intense pain undergoing treatment.

Can one or two simple questions predict poor medication adherence?

RATIONALE, AIMS, AND OBJECTIVES: Poor adherence to evidence-based medications is a major problem in conventional clinical practise. Better prognostic tools are needed to identify those with the highest likelihood of being non-adherent. The objective of this study is to determine if a 2-item patient activation status (PAS) measure identifies Medicare beneficiaries at risk of poor adherence to drugs typically recommended in treating type 2 diabetes. METHODS: PAS and medication adherence were assessed for respondents to the 2009 Medicare Current Beneficiary Survey and then compared using bivariate and multivariate tests. Participants' PAS was classified as "active," "high effort," "complacent," or "passive" based on how confident they were in identifying needed medical care and whether they brought medication lists to their doctors' visits. Adherence with oral antidiabetic drugs, angiotensin-converting enzyme-inhibitors/angiotensin receptor blockers, and statins was assessed using proportion of days covered (PDC). RESULTS: A total of 940 Medicare beneficiaries with diabetes enrolled in Part D plans in 2009. The overall effect of PAS on medication adherence was small (3% lower PDC for complacent/passive vs active/high effort beneficiaries, P < 0.10). However, interactions of complacent/passive PAS with other characteristics associated with poor adherence identified certain subgroups as especially prone to problematic adherence: age < 65 (PDC -11%, P < 0.05), non-Hispanic black (PDC -13%, P < 0.05), and morbidly obese (-9%, P < 0.10). CONCLUSION: A single question relating to taking medication lists to doctor visits may help identify patient subgroups prone to poor adherence in conventional practise, but larger samples are necessary to validate and extend these findings.

Global health research partnerships in the context of the Sustainable Development Goals (SDGs).

This themed issue on global health research has come at an opportune time in the middle of the ongoing global public health crisis arising from the coronavirus disease (COVID-19) pandemic which has claimed nearly 756,000 lives in 210 countries and territories around the world as of August 15, 2020. The public health crisis underscores the importance of global health research partnerships and collaborations to develop and evaluate the requisite health technologies to assist in containing COVID-19, other diseases, and health-related concerns that defy national borders. The 17 Sustainable Development Goals (SDGs), adopted by the member countries of the United Nations in September 2015, provide a framework for global development efforts including global health research. SDG3, which promotes health and well-being for the world populations across the age spectrum, highlights disease areas for special focus which can be adapted in specific global health research programs to serve local health needs. SDG17 promotes partnerships between high income (HIC) and low and middle-income countries (LMIC) for sustainable and equitable global development. However, given the wide disparities in fiscal and overall capacity for research between researchers in HIC and their counterparts in LMIC as well as the greater vulnerabilities of the LMIC communities when serving as research locations, a spotlight on the nature of such global health research partnerships in the context of the SDGs is desirable. This is to ensure that they are meaningful and mutually-beneficial partnerships which address local health concerns and promote long-term value for the communities involved. The objective of this commentary is, therefore, to provide a brief overview of the SDGs by way of context; explore the power differences at play when researchers from HIC are seeking research opportunities in LMIC; examine the social determinants of health and the disproportionate burden of global diseases carried by populations in LMIC to establish their vulnerability; discuss global research partnerships; and attempt to make a case for why community-based participatory research may be the preferred type of global health research partnership in the context of the SDGs.

Does good medication adherence really save payers money?

BACKGROUND: Despite a growing consensus that better adherence with evidence-based medications can save payers money, assertions of cost offsets may be incomplete if they fail to consider additional drug costs and/or are biased by healthy adherer behaviors unobserved in typical medical claims-based analyses. OBJECTIVES: The objective of this study was to determine whether controlling for healthy adherer bias (HAB) materially affected estimated medical cost offsets and additional drug spending associated with higher adherence. SUBJECTS: A total of 1273 Medicare beneficiaries with diabetes enrolled in Part D plans between 2006 and 2009. RESEARCH DESIGN: Using survey and claims data from the Medicare Current Beneficiary Survey, we measured medical and drug costs associated with good and poor adherence (proportion of days covered ≥ 80% and <80%, respectively) to oral antidiabetic drugs, ACE inhibitors/ARBs, and statins over 2 years. To test for HAB, we estimated pairs of regression models, one set containing variables typically controlled for in conventional claims analysis and a second set with survey-based variables selected to capture HAB effects. RESULTS: We found consistent evidence that controlling for HAB reduces estimated savings in medical costs from better adherence, and likewise, reduces estimates of additional adherence-related drug spending. For ACE inhibitors/ARBs we estimate that controlling for HAB reduced adherence-related medical cost offsets from $6389 to $4920 per person (P<0.05). Estimates of additional adherence-related drug costs were 26% and 14% lower in HAB-controlled models (P < 0.05). CONCLUSIONS: These results buttress the economic case for action by health care payers to improve medication adherence among insured persons with chronic disease. However, given the limitations of our research design, further research on larger samples with other disease states is clearly warranted.