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Interpreting results from deprescribing interventions to generate actionable evidence is challenging owing to inconsistent and heterogeneous outcome definitions between studies. We sought to characterize deprescribing intervention outcomes and recommend approaches to measure outcomes for future studies. A scoping literature review focused on deprescribing interventions for polypharmacy and informed a series of expert panel discussions and recommendations. Twelve experts in deprescribing research, policy, and clinical practice interventions participating in the Measures Workgroup of the US Deprescribing Research Network sought to characterize deprescribing outcomes and recommend approaches to measure outcomes for future studies. The scoping review identified 125 papers reflecting 107 deprescribing studies. Common outcomes included medication discontinuation, medication appropriateness, and a broad range of clinical outcomes potentially resulting from medication reduction. Panel recommendations included clearly defining clinically meaningful medication outcomes (e.g., number of chronic medications, dose reductions), ensuring adequate sample size and follow-up time to capture clinical outcomes resulting from medication discontinuation (e.g., quality of life [QOL]), and selecting appropriate and feasible data sources. A new conceptual model illustrates how downstream clinical outcomes (e.g., reduction in falls) should be interpreted in the context of initial changes in medication measures (e.g., reduction in mean total medications). Areas needing further development include implementation outcomes specific to deprescribing interventions and measures of adverse drug withdrawal events. Generating evidence to guide deprescribing is essential to address patient, caregiver, and clinician concerns about the benefits and harms of medication discontinuation. This article provides recommendations and an initial conceptual framework for selecting and applying appropriate intervention outcomes to support deprescribing research.

Interactive voice response and text message (IVR‐T) technology may improve hypertension control in under‐resourced settings. We conducted a randomized clinical trial to determine whether an IVR‐T intervention would improve blood pressure (BP), medication adherence and visit keeping among adults with hypertension from multiple racial and ethnic groups in primary care at an Urban Indian Health Organization in Albuquerque, New Mexico. Two hundred and ninety‐five participants were randomly assigned to IVR‐T (N = 148) or to usual care (N = 147). The IVR‐T arm received reminders for clinic visits, messages to reschedule missed clinic visits, monthly medication refill reminders, weekly motivational messages, and a blood pressure cuff. The usual care arm received no messages. The primary outcome was change in systolic BP (SBP) between baseline and 12 months. Secondary outcomes included change in SBP between baseline and 6 months, change in diastolic BP (DBP) at 6 and 12 months, self‐reported adherence at 6 months, and the proportion of missed primary care clinic appointments. The intervention did not affect SBP or DBP at 6 or 12 months. The 12‐month change in SBP/DBP was 1.66/1.10 mm Hg in usual care and 0.23/1.34 mm Hg in the intervention group (P values = .57 and .88, respectively). Self‐reported medication adherence improved comparably in both groups, and there was no difference in percentage of kept visits. Several features of study design, clinic operations, and data transfer were barriers to demonstrating effectiveness.

Context.— The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization. Cross-department, multidisciplinary collaboration to address gaps and improve patient and system outcomes is beneficial. Objective.— To demonstrate medical data warehouse utility for characterizing laboratory-associated quality gaps amenable to preanalytic or postanalytic interventions. Design.— A multidisciplinary team identified quality gaps. Medical data warehouse data were queried to characterize gaps. Organizational leaders were interviewed about quality improvement priorities. A decision aid with elements including national guidelines, local and national importance, and measurable outcomes was completed for each gap. Results.— Gaps identified included (1) test ordering; (2) diagnosis, detection, and documentation, and (3) high-risk medication monitoring. After examination of medical data warehouse data including enrollment, diagnoses, laboratory, pharmacy, and procedures for baseline performance, high-risk medication monitoring was selected, specifically alanine aminotransferase, aspartate aminotransferase, complete blood count, and creatinine testing among patients receiving disease-modifying antirheumatic drugs. The test utilization gap was in monitoring timeliness (eg, >60% of patients had a monitoring gap exceeding the guideline recommended frequency). Other contributors to selecting this gap were organizational enthusiasm, regulatory labeling, and feasibility of a significant laboratory role in addressing the gap. Conclusions.— A multidisciplinary process facilitated identification and selection of a laboratory medicine quality gap. Medical data warehouse data were instrumental in characterizing gaps.

BACKGROUND Efficient and effective strategies for treating chronic health conditions such as hypertension are particularly needed for under-resourced clinics such as Urban Indian Health Organizations (UIHOs). OBJECTIVE The objective of the Controlling Blood Pressure Trial is to assess the impact of an interactive voice response and text message (IVR-T) intervention compared with usual care among individuals with hypertension receiving care at a UIHO in Albuquerque, New Mexico. This manuscript presents the baseline characteristics of individuals enrolled in the trial and compares their characteristics with those in the hypertension registry who did not enroll in the trial. METHODS A hypertension registry developed from the clinic’s electronic health record was used for recruitment. Potentially eligible participants were contacted by letter and then by phone. Those who expressed interest completed an in-person baseline visit that included a baseline survey and blood pressure measurement using standardized procedures. Individuals randomized to the intervention group could opt to receive either automated text messages or automated phone calls in either English or Spanish. The messages include reminders of upcoming appointments at First Nations Community HealthSource, requests to reschedule recently missed appointments, monthly reminders to refill medications, and weekly motivational messages to encourage self-care, appointment keeping, and medication taking for hypertension. Individuals in the IVR-T arm could opt to nominate a care partner to also receive notices of upcoming and missed appointments. Individuals in the IVR-T arm were also offered a home blood pressure monitor. Follow-up visits will be conducted at 6 months and 12 months. RESULTS Over a 9.5-month period from April 2017 to January 2018, 295 participants were enrolled from a recruitment list of 1497 individuals. The enrolled cohort had a mean age of 53 years, was 25.1% (74/295) American Indian or Alaska Native and 51.9% (153/295) Hispanic, and 39.0% (115/295) had a baseline blood pressure greater than or equal to 140/90 mmHg. Overall, the differences between those enrolled in the trial and patients with hypertension who were ineligible, those who could not be reached, or those who chose not to enroll were minimal. Enrolled individuals had a slightly lower blood pressure (129/77 mmHg vs 132/79 mmHg; P=.04 for systolic blood pressure and P=.01 for diastolic blood pressure), were more likely to self-pay for their care (26% vs 10%; P CONCLUSIONS The Controlling Blood Pressure Trial has successfully enrolled a representative sample of individuals receiving health care at a UIHO. Trial follow-up will conclude in February 2019. CLINICALTRIAL ClinicalTrials.gov NCT03135405; http://clinicaltrials.gov/ct2/show/NCT03135405 (Archived by WebCite http://www.webcitation.org/76H2B4SO6) INTERNATIONAL REGISTERED REPOR DERR1-10.2196/11794

Background & Aims Reported prevalence of primary biliary cholangitis (PBC) varies widely. Demographic features and treatment patterns are not well characterized in the United States (US). We analyzed data from the Fibrotic Liver Disease (FOLD) Consortium, drawn from 11 geographically diverse health systems, to investigate epidemiologic factors and treatment of PBC in the US. Methods We developed a validated electronic health record-based classification model to identify patients with PBC in the FOLD database from 2003 through 2014. We used multivariable modeling to assess the effects of factors associated with PBC prevalence and treatment with ursodeoxycholic acid (UDCA). Results We identified 4241 PBC cases among over 14.5 million patients in FOLD health systems; median follow-up was 5 years. Accuracy of the classification model was excellent, with an area under the receiver operating characteristic curve value of 93%, 94% sensitivity, and 87% specificity. The average patient age at diagnosis was 60 years; 21% were Hispanic, 8% were African American, and 7% were Asian American/American Indian/Pacific Islander. Half of the cohort (49%) had elevated levels of alkaline phosphatase, and overall, 70% were treated with UDCA. The estimated 12-year prevalence of PBC was 29.3 per 100,000 persons. Adjusted prevalence values were highest among women (42.8 per 100,000), White patients (29.6 per 100,000), and patients 60–70 years old (44.7 per 100,000). Prevalence was significantly lower among men and African Americans (10.7 and 19.7 per 100,000, respectively) than women and whites; men and African Americans were also less likely to receive UDCA treatment (odds ratios, 0.6 and 0.5, respectively; P Conclusions In an analysis of a large cohort of patients with PBC receiving routine clinical care, we observed significant differences in PBC prevalence and treatment by gender, race, and age.

Background: Efficient and effective strategies for treating chronic health conditions such as hypertension are particularly needed for under-resourced clinics such as Urban Indian Health Organizations (UIHOs). Objective: The objective of the Controlling Blood Pressure Trial is to assess the impact of an interactive voice response and text message (IVR-T) intervention compared with usual care among individuals with hypertension receiving care at a UIHO in Albuquerque, New Mexico. This manuscript presents the baseline characteristics of individuals enrolled in the trial and compares their characteristics with those in the hypertension registry who did not enroll in the trial. Methods: A hypertension registry developed from the clinic’s electronic health record was used for recruitment. Potentially eligible participants were contacted by letter and then by phone. Those who expressed interest completed an in-person baseline visit that included a baseline survey and blood pressure measurement using standardized procedures. Individuals randomized to the intervention group could opt to receive either automated text messages or automated phone calls in either English or Spanish. The messages include reminders of upcoming appointments at First Nations Community HealthSource, requests to reschedule recently missed appointments, monthly reminders to refill medications, and weekly motivational messages to encourage self-care, appointment keeping, and medication taking for hypertension. Individuals in the IVR-T arm could opt to nominate a care partner to also receive notices of upcoming and missed appointments. Individuals in the IVR-T arm were also offered a home blood pressure monitor. Follow-up visits will be conducted at 6 months and 12 months. Results: Over a 9.5-month period from April 2017 to January 2018, 295 participants were enrolled from a recruitment list of 1497 individuals. The enrolled cohort had a mean age of 53 years, was 25.1% (74/295) American Indian or Alaska Native and 51.9% (153/295) Hispanic, and 39.0% (115/295) had a baseline blood pressure greater than or equal to 140/90 mmHg. Overall, the differences between those enrolled in the trial and patients with hypertension who were ineligible, those who could not be reached, or those who chose not to enroll were minimal. Enrolled individuals had a slightly lower blood pressure (129/77 mmHg vs 132/79 mmHg; P=.04 for systolic blood pressure and P=.01 for diastolic blood pressure), were more likely to self-pay for their care (26% vs 10%; P

Background/Aims Multi-site collaborations offer opportunities to engage diverse research expertise to answer important public health questions. Many of these collaborations have, at their core, large, robust data sources that are critical to achieving research goals. Before scientific work can begin, however, there is a complex maze of administrative and regulatory requirements that must be efficiently navigated in order to avoid project delays. As funders’ interest in comparative effective research (CER), research networks, and ‘big data’ increases, funding periods appear to be shrinking, making administrative and regulatory efficiencies more critical than ever. The current effort documents best practices in these areas.

Purpose: Multi-institutional collaborations are necessary in order to create large and robust data sets that are needed to answer important comparative effectiveness research (CER) questions. Before scientific work can begin, a complex maze of administrative and regulatory requirements must be efficiently navigated to avoid project delays.Innovation: Staff from research, regulatory, and administrative teams involved in three HMO Research Network (HMORN) multi-institutional collaborations developed and employed novel approaches: to secure and maintain Institutional Review Board (IRB) approvals; to enable data sharing, and to expedite subawards for two data-only minimal risk studies. These novel approaches accelerated required processes and approvals while maintaining regulatory, human subjects, and institutional protections.Credibility: Outcomes from the processes described here are compared with processes outlined in the research and regulatory literature and with processes that have been used in previous multisite research collaborations.Conclusion and Discussion: Research, regulatory, and administrative staff are essential contributors to the success of multi-institutional collaborations. Their flexibility, creativity, and effective communication skills can lead to the development of efficient approaches to achieving the necessary oversight for these complex projects. Elements of these specific strategies can be adapted and used by other research networks. Other efforts in these areas should be evaluated and shared. The processes that help develop a “learning research system” play an important and complementary role in sustaining multi-institutional research collaborations.

Objective: To assess the accuracy of electronic health record (EHR)–derived diagnoses in identifying children with incident (i.e., newly diagnosed) ADHD. Method: In 10 large health care organizations, electronic diagnoses data were used to identify all potential cases of incident ADHD among 3- through 9-year-old children. A random sample of records was manually reviewed to determine whether a diagnosis of ADHD was documented in clinician notes. Results: From electronic diagnoses data, a total of 7,362 children with incident ADHD were identified. Upon manual review of 500 records, the diagnosis of incident ADHD was confirmed in clinician notes for 71.5% (95% confidence interval [CI] = [56.5, 86.4]) of records for 3- through 5-year-old children and 73.6% (95% CI = [65.6, 81.6]) of records for 6- through 9-year-old children. Conclusion: Studies predicated on the identification of incident ADHD cases will need to carefully consider study designs that minimize the likelihood of case misclassification.

Measuring productivity is important for determining appropriate physician compensation, as indicated by the current emphasis on benchmarking. A combination of benchmarking and individual profiling data may prove useful for developing productivity-based compensation plans. However, while tying physician compensation to multiple indicators is prudent, it is also cumbersome, since indicator values may not be comparable. A compensation model that scales indicators to a common measure, such as a relative value scale, may allow the visual representation of resource utilization, and peer comparisons can assist in adjusting to the accountability demanded by managed care.