Instrumental variable analysis is an increasingly popular method in comparative effectiveness research (CER). In theory, the instrument controls for unobserved and observed patient characteristics that affect the outcome. However, the results of instrumental variable analyses in observational settings may be biased if the instrument and outcome are related through an unadjusted third variable: an "instrument-outcome confounder." The authors identified published CER studies that used instrumental variable analysis and searched the literature for potential confounders of the most common instrument-outcome pairs. Of the 187 studies identified, 114 used 1 or more of the 4 most common instrument categories: distance to facility, regional variation, facility variation, and physician variation. Of these, 65 used mortality as an outcome. Potential unadjusted instrument-outcome confounders were observed in all studies, including patient race, socioeconomic status, clinical risk factors, health status, and urban or rural residency; facility and procedure volume; and co-occurring treatments. Only 4 (6%) instrumental variable CER studies considered potential instrument-outcome confounders outside the study data. Many effect estimates may be biased by the failure to adjust for instrument-outcome confounding. The authors caution against overreliance on instrumental variable studies for CER.

Mobile and smartphone (mHealth) technologies have the potential to improve diabetes care and self-management, but little is known about their effectiveness and how patients, providers, and payers currently interact with them. We conducted a systematic review and found only 20 peer-reviewed articles, published since 2010, with robust evidence about the effectiveness of mHealth interventions for diabetes. The majority of these interventions showed improvement on primary endpoints, such as HbA1c; mHealth technologies that interacted with both patients and providers were more likely to be effective. There was little evidence about persistent use by patients, use by a patient's health care provider, or long-term effectiveness. None of the studies discussed regulatory oversight of mHealth technologies or payer reimbursement for them. No robust studies evaluated the more than 1100 publicly available smartphone apps for diabetes. More research with valid study designs and longer follow-up is needed to evaluate the impact of mHealth technologies for diabetes care and self-management.

Background:High deductible health plans linked to Health Savings Accounts (HSA-HDHPs) must include all care under the deductible except for select preventive services. Some employers and insurers have adopted Preventive Drug Lists (PDLs) that exempt specific classes of medications from deductibles.Objective:The objective of this study was to examine the association between shifts to PDL coverage and medication utilization among patients with diabetes in HSA-HDHPs.Research Design:A natural experiment comparing pre-post changes in monthly and annual outcomes in matched study groups.Subjects:The intervention group included 1744 commercially-insured HSA-HDHP patients with diabetes age 12–64 years switched by employers to PDL coverage; the control group included 3349 propensity-matched HSA-HDHP patients whose employers offered no PDL.Measures:Outcomes were out-of-pocket (OOP) costs for medications and the number of pharmacy fills converted to 30-day equivalents.Results:Transition to the PDL was associated with a relative pre-post decrease of $612 (−35%,P<0.001) per member OOP medication expenditures; OOP reductions were higher for key classes of antidiabetic and cardiovascular medicines listed on the PDL; the policy did not affect unlisted classes. The PDL group experienced relative increases in medication use of 6.0 30-day fills per person during the year (+11.2%,P<0.001); the increase was more than twice as large for lower-income (+6.6 fills, +12.6%,P<0.001) than higher-income (+3.0 fills, +5.1%,P=0.024) patients.Conclusion:Transition to a PDL which covers important classes of medication to manage diabetes and cardiovascular conditions is associated with substantial annual OOP cost savings for patients with diabetes and increased utilization of important classes of medications, especially for lower-income patients.