Matthew J Crowley

Benefits and Harms of Breast Cancer Screening A Systematic Review

IMPORTANCE Patients need to consider both benefits and harms of breast cancer screening. OBJECTIVE To systematically synthesize available evidence on the association of mammographic screening and clinical breast examination (CBE) at different ages and intervals with breast cancer mortality, overdiagnosis, false-positive biopsy findings, life expectancy, and quality-adjusted life expectancy. EVIDENCE REVIEW We searched PubMed (to March 6, 2014), CINAHL (to September 10, 2013), and PsycINFO (to September 10, 2013) for systematic reviews, randomized clinical trials (RCTs) (with no limit to publication date), and observational and modeling studies published after January 1, 2000, as well as systematic reviews of all study designs. Included studies (7 reviews, 10 RCTs, 72 observational, 1 modeling) provided evidence on the association between screening with mammography, CBE, or both and prespecified critical outcomes among women at average risk of breast cancer (no known genetic susceptibility, family history, previous breast neoplasia, or chest irradiation). We used summary estimates from existing reviews, supplemented by qualitative synthesis of studies not included in those reviews. FINDINGS Across all ages of women at average risk, pooled estimates of association between mammography screening and mortality reduction after 13 years of follow-up were similar for 3 meta-analyses of clinical trials (UK Independent Panel: relative risk [RR], 0.80 [95% CI, 0.73-0.89]; Canadian Task Force: RR, 0.82 [95% CI, 0.74-0.94]; Cochrane: RR, 0.81 [95% CI, 0.74-0.87]); were greater in a meta-analysis of cohort studies (RR, 0.75 [95% CI, 0.69 to 0.81]); and were comparable in a modeling study (CISNET; median RR equivalent among 7 models, 0.85 [range, 0.77-0.93]). Uncertainty remains about the magnitude of associated mortality reduction in the entire US population, among women 40 to 49 years, and with annual screening compared with biennial screening. There is uncertainty about the magnitude of overdiagnosis associated with different screening strategies, attributable in part to lack of consensus on methods of estimation and the importance of ductal carcinoma in situ in overdiagnosis. For women with a first mammography screening at age 40 years, estimated 10-year cumulative risk of a false-positive biopsy result was higher (7.0% [95% CI, 6.1%-7.8%]) for annual compared with biennial (4.8% [95% CI, 4.4%-5.2%]) screening. Although 10-year probabilities of false-positive biopsy results were similar for women beginning screening at age 50 years, indirect estimates of lifetime probability of false-positive results were lower. Evidence for the relationship between screening and life expectancy and quality-adjusted life expectancy was low in quality. There was no direct evidence for any additional mortality benefit associated with the addition of CBE to mammography, but observational evidence from the United States and Canada suggested an increase in false-positive findings compared with mammography alone, with both studies finding an estimated 55 additional false-positive findings per extra breast cancer detected with the addition of CBE. CONCLUSIONS AND RELEVANCE For women of all ages at average risk, screening was associated with a reduction in breast cancer mortality of approximately 20%, although there was uncertainty about quantitative estimates of outcomes for different breast cancer screening strategies in the United States. These findings and the related uncertainty should be considered when making recommendations based on judgments about the balance of benefits and harms of breast cancer screening.

Rate- and Rhythm-Control Therapies in Patients With Atrial Fibrillation: A Systematic Review

Atrial fibrillation (AF) is a major public health problem in the United States. More than 2.3 million Americans are estimated to have AF (1). The known association between AF and substantial mortality, morbidity, and health care costs compounds the effect of this condition. Not only is the risk for death in patients with AF twice that of patients without it, but AF can result in myocardial ischemia and infarction, exacerbate heart failure (HF), and cause tachycardia-induced cardiomyopathy if the ventricular rate is not well-controlled (25). The most dreaded complication of AF is thromboembolism, especially stroke (6). In some patients, AF or therapies to manage this condition can severely depreciate quality of life (710). Furthermore, the management of AF and its complications is responsible for nearly

Clinical outcomes of metformin use in populations with chronic kidney disease, congestive heart failure, or chronic liver disease: A systematic review

16 billion in additional costs to the U.S. health care system per year (11). Despite the substantial public health effect of AF, uncertainties around its management remain. In particular, the comparative safety and effectiveness of different rate- and rhythm-control therapies for patients with AF are unclear. We conducted this systematic review to evaluate the comparative safety and effectiveness of rate- versus rhythm-control strategies; medications used for ventricular rate control; strict versus more lenient rate-control strategies; nonpharmacologic rate-control therapies versus medications; electrical cardioversion and antiarrhythmic medications for restoration of sinus rhythm; and catheter ablation, surgical ablation, and antiarrhythmic medications for maintenance of sinus rhythm. Methods We developed and followed a standard protocol for our review. Full details of our methods, search strategies, results, and conclusions are presented in a comparative effectiveness review commissioned by the Agency for Healthcare Research and Quality (AHRQ) and are available at www.effectivehealthcare.ahrq.gov (12). Data Sources and Searches We searched PubMed, EMBASE, and the Cochrane Database of Systematic Reviews for studies published between 1 January 2000 and 12 November 2013. Data before 2000 have been summarized in an AHRQ report on the management of new-onset AF published in 2001 (1315). Study Selection We identified randomized, controlled trials (RCTs) published in English that were comparative assessments of pharmacologic or nonpharmacologic rate- or rhythm-control therapies aimed at treating adults with AF. Observational studies were also allowed for comparisons of strict versus lenient rate control or cardiac resynchronization therapy versus other rhythm-control therapies. The following outcomes were considered: restoration of sinus rhythm (conversion), maintenance of sinus rhythm, recurrence of AF at 12 months, development of cardiomyopathy, death (all-cause and cardiac), myocardial infarction, cardiovascular hospitalizations, HF symptoms, control of AF symptoms, quality of life, functional status, stroke and other embolic events, bleeding events, and adverse effects of therapy. Data Extraction and Quality Assessment One investigator abstracted and another confirmed data related to study setting and design, patient characteristics, details of treatment, comparators, and relevant outcomes. The quality of individual studies was evaluated using the approach described in AHRQs Methods Guide for Effectiveness and Comparative Effectiveness Reviews (16). Investigators also assessed factors that limited applicability of the evidence. Data Synthesis and Analysis For each treatment comparison and outcome of interest, we determined the feasibility of completing a quantitative synthesis (meta-analysis) based on the volume of relevant literature, conceptual homogeneity of the studies (both in terms of study population and outcomes), and completeness of the reporting of results. We considered meta-analysis for outcomes that at least 3 studies reported. For our evaluation of rate- versus rhythm-control strategies, we grouped all rate-control strategies together and all rhythm-control strategies together, regardless of the specific medication or procedure. We grouped pharmacologic interventions by class, considering rate-controlling calcium-channel blockers and all -blockers each to be similar enough to be grouped together. We categorized procedures into electrical cardioversion, atrioventricular node (AVN) ablation, AF ablation by pulmonary vein isolation (PVI) (by open surgical, minimally invasive, or transcatheter procedures), and different types of surgical maze procedures and explored comparisons among these categories. In addition, for the comparisons focusing on medications versus procedures, we also explored grouping all medications together and comparing them with all procedures. When a meta-analysis was appropriate, we used a random-effects model to synthesize the available evidence quantitatively using Comprehensive Meta-Analysis, version 2 (Biostat, Englewood, New Jersey). We used a standardized approach to rank the overall strength of evidence (SOE) for each outcome (16). Role of the Funding Source Primary funding was provided by AHRQ. Neither the technical experts nor AHRQ representatives had a role in the literature search, data analysis, interpretation of the data, or decision to submit the manuscript for publication. Results We screened 10495 abstracts, evaluated 570 full-text articles, and included 200 articles representing 162 studies involving 28836 patients (Figure 1). Tables 1 to 6 of the Supplement provide details about these studies and their populations for each topic described here. Table 7 of the Supplement lists identified and potential limitations of the studies. The full AHRQ report highlights additional findings (12). Figure 1. Summary of evidence search and selection. AAD = antiarrhythmic drug; CRT = cardiac resynchronization therapy; RCT = randomized, controlled trial. * Some studies were relevant to more than 1 topic. Supplement. Tables Rate- Versus Rhythm-Control Strategies We included 16 RCTs in this analysis: 13 compared pharmacologic rhythm-control versus rate-control strategies (1729) and 3 compared a rhythm-control strategy with PVI versus a rate-control strategy that involved AVN ablation and implantation of a pacemaker in 1 study (30) and rate-controlling medications in the other 2 (31, 32). Ten RCTs (17, 18, 2022, 2428) provided information on outcomes of interest and were combined quantitatively (Figure 2). Of these, 5 included only patients with persistent AF (2022, 25, 28), 1 included only patients with paroxysmal AF (17), and 4 included patients with paroxysmal or persistent AF (18, 24, 26, 27). Two studies (17, 22) compared a single-chamber pacemaker plus AVN ablation versus a dual-chamber pacemaker plus AVN ablation plus an antiarrhythmic medication; all others compared largely unspecified rate-control with rhythm-control strategies. Figure 2. Meta-analysis forest plots. AAD = antiarrhythmic drug; PVI = pulmonary vein isolation. A. All-cause mortality for rate- vs. rhythm-control strategies. B. Cardiovascular mortality for rate- vs. rhythm-control strategies. C. Stroke for rate- vs. rhythm-control strategies. D. Restoration of sinus rhythm for monophasic vs. biphasic waveforms. E. Maintenance of sinus rhythm for PVI vs. AAD therapy. Figure 2. Continued. Data from the included studies showed moderate SOE that pharmacologic rate- and rhythm-control strategies are of comparable efficacy with regard to their effect on all-cause mortality (odds ratio [OR], 1.34 [95% CI, 0.89 to 2.02]; Q= 21.71; P= 0.003) (Figure 2, A) (18, 2022, 24, 2628), cardiac mortality (OR, 0.96 [CI, 0.77 to 1.20]; Q= 3.55; P= 0.47) (Figure 2, B) (18, 21, 22, 24, 25), and stroke (OR, 0.99 [CI, 0.76 to 1.30]; Q= 7.02; P= 0.43) (Figure 2, C) (17, 18, 2022, 24, 27, 28). Although the meta-analysis for all-cause mortality showed a potential benefit, it did not reach statistical significance and 6 of the 8 studies (6069 patients [95%]) had ORs that crossed 1, resulting in a final moderate SOE. For cardiac mortality (Figure 2, B), point estimates were inconsistent and CIs were wide for 2 of the 5 studies (18, 21), but there was no evidence of heterogeneity; therefore, our SOE rating was not affected. For the outcome of stroke, there was no evidence of heterogeneity, but the findings were mostly driven by 1 large, good-quality RCT (4060 patients), which was inconsistent with several of the smaller studies, reducing our confidence in the finding and in the SOE. These studies largely included older patients with mild AF symptoms. Three RCTs compared pharmacologic rate-control strategies with rhythm-control strategies using antiarrhythmic medications (17, 18, 22). These RCTs showed fewer cardiovascular hospitalizations with the rhythm-control strategies (17, 18, 22). Although data from 5 RCTs suggest that there is no difference between pharmacologic rate- and rhythm-control strategies in their effect on HF symptoms (17, 22, 24, 26, 46) (Table 1), a prespecified substudy of the Atrial Fibrillation and Congestive Heart Failure study showed that a higher proportion of time spent in sinus rhythm was associated with a greater improvement in New York Heart Association class (29). Table 1. Summary of SOE and Effect Estimates for Rate- Versus Rhythm-Control Strategies Three studies compared a rhythm-control strategy involving catheter ablation with a rate-control strategy involving rate-controlling medications (32) or AVN ablation combined with implantation of a pacemaker (30) or rate-controlling medications (31). One study showed that catheter ablation was better than pharmacologic rate control at improving symptoms, neurohormonal status, and objective physiologic exercise capacity (32). Another study showed that PVI isolation was superior to AVN ablation and pacemaker implantation in improving quality of life, 6-minute walk distance, and ejection fraction (30). Another study showed that PVI resulted in long-term restoration o

The Cholesterol, Hypertension, And Glucose Education (CHANGE) study: results from a randomized controlled trial in African Americans with diabetes.

After its approval by the U.S. Food and Drug Administration (FDA) in 1994, metformin became the recommended initial treatment for type 2 diabetes mellitus in the United States (1). Beyond its glycemic benefits, metformin typically does not cause weight gain or hypoglycemia and may be associated with lower mortality (2, 3). Because of concerns regarding lactic acidosis with use of phenformin, a related biguanide withdrawn from the market in 1977, the FDA applied a boxed warning to metformin concurrent with its approval (4). This warning cautioned against using metformin in the setting of chronic kidney disease (CKD), which may impair excretion of the drug, and recommended caution in patients with conditions that may promote lactate accumulation (such as congestive heart failure [CHF] and chronic liver disease [CLD]) (5). Despite this warning, recent estimates suggest that 20% to 30% of persons receiving metformin have historical contraindications or precautions regarding its use (6, 7). These findings reflect that many prescribers believe the FDA boxed warning is too restrictive (8, 9). Literature reviews indicate no clear association between metformin use and lactic acidosis (10) and suggest that the drug is safe for patients with moderate CKD or CHF (11, 12). In 2006, the FDA removed CHF as a contraindication to metformin use, although acute or unstable CHF remains a precaution (13, 14). In April 2016, the FDA revised its warning regarding metformin use in patients with CKD, switching from a serum creatininebased definition of renal impairment to more-inclusive criteria based on estimated glomerular filtration rate (eGFR) (15). With this change, an estimated 1 million additional patients with moderate CKD (eGFR, 30 to <60 mL/min/1.73 m2) became eligible to receive metformin, although severe CKD (eGFR, <30 mL/min/1.73 m2) remains a contraindication (16). In the wake of these changes, metformin use will continue to increase in populations with historical contraindications and precautions. Prescribers therefore must fully understand the consequences of metformin use in these groups. To promote informed prescribing, we systematically reviewed the literature regarding the benefits and harms of metformin use (beyond lactic acidosis) among patients with common chronic diseases historically identified by the FDAs boxed warning as contraindications or precautions: moderate to severe CKD, CHF, and CLD with impaired hepatic function. Methods Study Design This work was part of a Veterans Health Administration (VHA)-funded report. Additional details are available online (www.hsrd.research.va.gov/publications/esp). The present analysis focuses on the following question: For patients with type 2 diabetes and a historical contraindication or precaution regarding metformin use, what are the benefits and harms (beyond lactic acidosis) of metformin treatment? This review followed a published protocol (PROSPERO: CRD42016027708), and each step was pilot-tested to train and calibrate investigators. Data Sources and Study Selection In consultation with an expert medical librarian, we searched PubMed, the Cochrane Central Register of Controlled Trials, EMBASE, and the International Pharmaceutical Abstracts in November 2015; we subsequently updated our PubMed search through September 2016. We also searched ClinicalTrials.gov for relevant completed and ongoing studies. Appendix Table 1 presents our search strategies. We also screened reference lists of published reviews and queried Bristol-Myers Squibb, the manufacturer of the branded metformin formulation, for other relevant studies. Appendix Table 1. Search Strategies for Online Databases, With Date of Search and Specific Terms Our prespecified inclusion and exclusion criteria are listed in Appendix Table 2. We included English-language clinical trials and observational cohort studies that examined adults with type 2 diabetes and a metformin contraindication or precaution of interest (moderate to severe CKD [eGFR, <60 mL/min/1.73 m2], CHF, or CLD with hepatic impairment); compared antihyperglycemic regimens that included metformin with those that did not; and reported all-cause mortality, major adverse cardiovascular events (MACEs), glycemic control, lipid control, hypoglycemia, weight gain, or vitamin B12 deficiency. Our VHA stakeholders and technical expert panel provided guidance on outcome selection. Appendix Table 2. Inclusion and Exclusion Criteria for Citations Data Extraction and Quality Assessment of Individual Studies Two investigators screened all citations for eligibility, and citations considered relevant by either individual advanced to full-text review. Two investigators reviewed all full-text articles and resolved disagreements through discussion or adjudication by a third investigator. Before excluding any potentially eligible study whose primary analysis did not explicitly address a population with a metformin contraindication or precaution, we examined the full text for relevant subgroup analyses. Two investigators independently assessed study quality, and disagreements were resolved by consensus or through arbitration by a third investigator. Using published quality criteria, we developed a customized risk-of-bias (ROB) assessment tool designed to address selection, performance, attrition, detection, and reporting biases (Appendix Figure 1) (17). We assigned each study an ROB score (low, moderate, or high). Appendix Figure 1. Quality assessment for observational studies. BNP = brain natriuretic peptide; CHF = congestive heart failure; CKD = chronic kidney disease; CT = computed tomography; CV = cardiovascular; DM = diabetes mellitus; DM2 = type 2 diabetes mellitus; eGFR = estimated glomerular filtration rate; FBS = fasting blood sugar; f/u = follow-up; HbA1c = hemoglobin A1c; HTN = hypertension; ICD = International Classification of Diseases; MACEs = major adverse cardiovascular events; MI = myocardial infarction; NA = not applicable; NR = not reported; PE = physical examination. Appendix Figure 1. Continued Data Abstraction For each included study, an investigator abstracted data by using a customized DistillerSR database (Evidence Partners); a second investigator independently reviewed these data for accuracy. Relevant data included demographics, study setting, contraindication or precaution definitions, metformin dosage, other antihyperglycemic agents, comparators, and outcomes. We treated multiple publications from a single study as a single data point, prioritizing the longest-term and most complete results. If critical data were missing or unclear in a published report, we contacted the manuscript authors. Data Synthesis We developed summary tables to characterize all included studies for each metformin contraindication or precaution of interest. Of note, 2 studies (18, 19) separately compared distinct groups of metformin usersthose receiving metformin monotherapy and those receiving metforminsulfonylurea combination therapywith patients receiving sulfonylurea monotherapy. In each case, we derived a pooled, weighted hazard ratio (HR) for all metformin users, incorporating an approximation of the correlation resulting from the shared sulfonylurea monotherapy reference group (Appendix). For another study (20), we estimated the HR and variance from the reported frequencies and the odds ratio (OR) by using an established approach (21, 22) (Appendix). If 3 or more studies were conceptually similar in terms of design, population, intervention, and outcomes, we performed quantitative synthesis by using a random-effects model to generate summary HRs. For analyses with fewer than 20 studies, we used the KnappHartung approach to adjust the SEs of the estimated coefficients (23, 24). If appropriate, we conducted sensitivity analyses by omitting subgroups with more severe contraindications or precautions (such as an eGFR <30 mL/min/1.73 m2), studies with shorter follow-up (<2 years), and studies not using propensity-score adjustment. We evaluated statistical heterogeneity by using Cochran Q and I 2 statistics; for analyses including 10 or more studies, we assessed publication bias by using funnel plots and Begg and Egger tests (25, 26). For cases with too few studies to warrant meta-analysis, we performed qualitative synthesis. We conducted all quantitative analyses by using R (version 3.1.2) (The R Foundation), including the metafor package (version 1.9-7), for meta-analysis. Strength of Evidence We used the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to evaluate the overall strength of evidence (SOE) for outcomes with sufficient data. Using the domains of ROB, directness, and consistency or precision of treatment effects, an investigator (J.W.W.) rated the SOE as high, moderate, low, or insufficient. We considered the effect of residual confounders, magnitude of effect, and publication bias (27, 28). Role of the Funding Source This review was funded by the U.S. Department of Veterans Affairs. The funding source had no role in the study design, data collection, analysis, preparation of the manuscript, or decision to submit the manuscript for publication. Results From 4910 screened citations, we reviewed 532 full-text articles and identified 17 eligible studies (Figure 1). All were observational and addressed populations with moderate to severe CKD (n= 5), CHF (n= 11), or CLD with hepatic impairment (n= 3); 3 studies addressed both CKD and CHF. Appendix Table 3 provides details on the included studies. Of note, we identified no ongoing studies in ClinicalTrials.gov that met our inclusion criteria. Figure 1. Flow of articles through the literature search and screening process. CHF = congestive heart failure; CKD = chronic kidney disease; CLD = chronic liver disease; OECD = Organization for Economic Cooperation and Development. * Search results are from EMBASE (n = 2512), PubMed (n = 2381), and Cochrane (n = 17). Three references

Treatment intensification in a hypertension telemanagement trial: clinical inertia or good clinical judgment?

BACKGROUND Cardiovascular disease (CVD) and diabetes account for one-third of the mortality difference between African American and white patients. We evaluated the effect of a CVD risk reduction intervention in African Americans with diabetes. METHODS We randomized 359 African Americans with type 2 diabetes to receive usual care or a nurse telephone intervention. The 12-month intervention provided monthly self-management support and quarterly medication management facilitation. Coprimary outcomes were changes in systolic blood pressure (SBP), hemoglobin A1c (HbA1c), and low-density lipoprotein cholesterol (LDL-C) over 12 months. We estimated between-intervention group differences over time using linear mixed-effects models. The secondary outcome was self-reported medication adherence. RESULTS The sample was 72% female; 49% had low health literacy, and 37% had annual income <

Factors associated with persistent poorly controlled diabetes mellitus: Clues to improving management in patients with resistant poor control

10,000. Model-based estimates for mean baseline SBP, HbA1c, and LDL-C were 136.8 mm Hg (95% CI 135.0-138.6), 8.0% (95% CI 7.8-8.2), and 99.1 mg/dL (95% CI 94.7-103.5), respectively. Intervention patients received 9.9 (SD 3.0) intervention calls on average. Primary providers replied to 76% of nurse medication management facilitation contacts, 18% of these resulted in medication changes. There were no between-group differences over time for SBP (P = .11), HbA1c (P = .66), or LDL-C (P = .79). Intervention patients were more likely than those receiving usual care to report improved medication adherence (odds ratio 4.4, 95% CI 1.8-10.6, P = .0008), but adherent patients did not exhibit relative improvement in primary outcomes. CONCLUSIONS This intervention improved self-reported medication adherence but not CVD risk factor control among African Americans with diabetes. Further research is needed to determine how to maximally impact CVD risk factors in African American patients.

Factors Associated with Non-Adherence to Three Hypertension Self-Management Behaviors: Preliminary Data for a New Instrument

Clinical inertia represents a barrier to hypertension management. As part of a hypertension telemanagement trial designed to overcome clinical inertia, we evaluated study physician reactions to elevated home blood pressures. We studied 296 patients from the Hypertension Intervention Nurse Telemedicine Study who received telemonitoring and study physician medication management. When a patients 2-week mean home blood pressure was elevated, an “intervention alert” prompted study physicians to consider treatment intensification. We examined treatment intensification rates and subsequent blood pressure control. Patients generated 1216 intervention alerts during the 18-month intervention. Of 922 eligible intervention alerts, study physicians intensified treatment in 374 (40.6%). Study physician perception that home blood pressure was acceptable was the most common rationale for nonintensification (53.7%). When “blood pressure acceptable” was the reason for not intensifying treatment, the mean blood pressure was lower than for intervention alerts where treatment intensification occurred (135.3/76.7 versus 143.2/80.6 mm Hg; P<0.0001). Blood pressure acceptable intervention alerts were associated with the lowest incidence of repeat alerts (hazard ratio: 0.69 [95% CI: 0.58 to 0.83]), meaning that the patient home blood pressure was less likely to subsequently rise above goal, despite apparent clinical inertia. This telemedicine intervention targeting clinical inertia did not guarantee treatment intensification in response to elevated home blood pressures. However, when physicians did not intensify treatment, it was because blood pressure was closer to an acceptable threshold, and repeat blood pressure elevations occurred less frequently. Failure to intensify treatment when home blood pressure is elevated may, at times, represent good clinical judgment, not clinical inertia.

Improving diabetes medication adherence: successful, scalable interventions.

Objectives Patients with persistent poorly controlled diabetes mellitus (PPDM), defined as an uninterrupted hemoglobin A1c >8.0% for ≥1 year despite standard care, are at high risk for complications. Additional research to define patient factors associated with PPDM could suggest barriers to improvement in this group and inform the development of targeted strategies to address these patients’ resistant diabetes. Methods We analyzed patients with type 2 diabetes from a multi-site randomized trial. We characterized patients with PPDM relative to other patients using detailed survey data and multivariable modeling. Results Of 963 patients, 118 (12%) had PPDM, 265 (28%) were intermittently poorly controlled, and 580 (60%) were well-controlled. Patients with PPDM had younger age, earlier diabetes diagnosis, insulin use, higher antihypertensive burden, higher low-density lipoprotein cholesterol, and lower statin use relative to well-controlled patients. Among patients with objective adherence data (Veterans Affairs patients), a larger oral diabetes medication refill gap was associated with PPDM. Discussion Strategies are needed to target-specific barriers to improvement among patients whose diabetes is resistant to standard diabetes care. Our data suggest that strategies for targeting PPDM should accommodate younger patients’ lifestyles, include medication management for insulin titration and comorbid disease conditions, and address barriers to self-management adherence.

Association Between Perceived Life Chaos and Medication Adherence in a Postmyocardial Infarction Population

ABSTRACTBACKGROUNDClinicians have difficulty in identifying patients that are unlikely to adhere to hypertension self-management. Identifying non-adherence is essential to addressing suboptimal blood pressure control and high costs.OBJECTIVES1) To identify risk factors associated with non-adherence to three key self-management behaviors in patients with hypertension: proper medication use, diet, and exercise; 2) To evaluate the extent to which an instrument designed to identify the number of risk factors present for non-adherence to each of the three hypertension self-management behaviors would be associated with self-management non-adherence and blood pressure.DESIGNCross-sectional analysis of randomized trial data.PATIENTSSix hundred and thirty-six primary care patients with hypertension.MEASUREMENTS1) Demographic, socioeconomic, psychosocial, and health belief-related factors; 2) measures of self-reported adherence to recommended medication use, diet recommendations, and exercise recommendations, all collected at baseline assessment; 3) systolic blood pressure (SBP) and diastolic blood pressure (DBP).RESULTSWe identified patient factors associated with measures of non-adherence to medications, diet, and exercise in hypertension. We then combined risk factors associated with ≥1 adherence measure into an instrument that generated three composite variables (medication, diet, and exercise composites), reflecting the number of risk factors present for non-adherence to the corresponding self-management behavior. These composite variables identified subgroups with higher likelihood of medication non-adherence, difficulty following diet recommendations, and difficulty following exercise recommendations. Composite variable levels representing the highest number of self-management non-adherence risk factors were associated with higher SBP and DBP.CONCLUSIONSWe identified factors associated with measures of non-adherence to recommended medication use, diet, and exercise in hypertension. We then developed an instrument that was associated with non-adherence to these self-management behaviors, as well as with blood pressure. With further study, this instrument has potential to improve identification of non-adherent patients with hypertension.

Prioritization of patient-centered comparative effectiveness research for osteoarthritis.

Effective medications are a cornerstone of prevention and disease treatment, yet only about half of patients take their medications as prescribed, resulting in a common and costly public health challenge for the US health care system. Since poor medication adherence is a complex problem with many contributing causes, there is no one universal solution. This paper describes interventions that were not only effective in improving medication adherence among patients with diabetes, but were also potentially scalable (ie, easy to implement to a large population). We identify key characteristics that make these interventions effective and scalable. This information is intended to inform health care systems seeking proven, low resource, cost-effective solutions to improve medication adherence.