To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules.
The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013.
Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution.
Primary and secondary outcome measures
The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules.
Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores.
Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty.
INTERNAL MEDICINE; HEALTH SERVICES ADMINISTRATION & MANAGEMENT; MEDICAL EDUCATION & TRAINING
Statins reduce the risk of coronary heart disease (CHD) in individuals with a history of CHD or risk equivalents. A 10-year CHD risk >20% is considered a risk equivalent but is frequently not detected. Statin use and low density lipoprotein cholesterol (LDL-C) control were examined among participants with CHD or risk equivalents in the nationwide Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (n=8,812).
Participants were categorized into 4 mutually exclusive groups: (1) history of CHD (n=4,025), (2) no history of CHD but with a history of stroke and/or abdominal aortic aneurysm (AAA) (n=946), (3) no history of CHD or stroke/AAA but with diabetes mellitus (n=3,134), or (4) no history of the conditions in (1) through (3) but with 10-year Framingham CHD risk score (FRS) >20% calculated using the ATP-III point scoring system (n=707).
Statins were used by 58.4% of those in the CHD group and 41.7%, 40.4%, and 20.1% of those in the stroke/AAA, diabetes, and FRS>20% groups, respectively. Among those taking statins, 65.1% had LDL-C <100mg/dL, with no difference between the CHD, stroke/AAA, or diabetes groups. However, compared to those in the CHD group, LDL-C <100mg/dL was less common among participants in the FRS>20% group (multivariable adjusted prevalence ratio: 0.72; 95% CI: 0.62 – 0.85). Results were similar using the 2013 ACC/AHA cholesterol treatment guideline.
These data suggest many people with high CHD risk, especially those with a FRS>20%, do not receive guideline-concordant lipid-lowering therapy and do not achieve an LDL-C <100mg/dL.
cardiovascular disease; risk assessment; prevention; population health; epidemiology
The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS—providers—are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations.
The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR).
We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define “context sensitive triggers” as being workflow events (i.e., context) that result in a CDS intervention.
Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT).
Results and Conclusion:
iCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT. The level of leadership support and clinical guidance for iCPR was key in establishing a culture of acceptance for both the tool and its recommendations contributing to adoption and acceptance. The dedicated training and support lead to the majority of the residents reporting a high level of comfort with both iCPR tools strep pharyngitis (64.4 percent) and pneumonia (62.7 percent) as well as a high likelihood of using the tools in the future. A surprising framework addition resulted from usability testing: context sensitive triggers.
Health Information Technology; Human Computer Interaction (HCI)
This study assessed the baseline knowledge, perceptions, attitudes and behaviors of prediabetes patients in order to tailor a new technology-enhanced primary care-based lifestyle modification intervention.
Patients with a diagnosis of prediabetes were enrolled in a randomized, controlled pilot study, Avoiding Diabetes Thru Action Plan Targeting (ADAPT), a technology-based intervention to promote action plan discussions around patient-selected behavior change goals.
A total of 54 adults (82% female) were enrolled in the pilot study. Most (89%) had comorbid conditions and mean BMI was 36. Participants exhibited high risk of diabetes knowledge (knowledge score 20 on a 32 point scale) and high levels of willingness to make changes to decrease diabetes risk. Number of daily steps was inversely correlated with perceived physical activity (r=−0.35082, p<0.001). Poorer scores on diet quality were inversely correlated with BMI.
Participants in this sample demonstrated requisite levels of knowledge, self-efficacy, motivation and risk perception for effective behavior change. These data suggest that primary care-based prediabetes interventions can move beyond educational goals and focus on enhancing patients’ ability to select, plan and enact action plans.
Type II Diabetes Mellitus; Prediabetes; Behavior Modification; Self-Efficacy; Risk-Perception
Evidence-based solutions for changing health behaviors exist but problems with feasibility, sustainability, and dissemination limit their impact on population-based behavior change and maintenance.
Our goal was to overcome the limitations of an established behavior change program by using the inherent capabilities of smartphones and wireless sensors to develop a next generation mobile health (mHealth) intervention that has the potential to be more feasible.
In response to the clinical need and the growing capabilities of smartphones, our study team decided to develop a behavioral hypertension reduction mHealth system inspired by Dietary Approaches to Stop Hypertension (DASH), a lifestyle modification program. We outline the key design and development decisions that molded the project including decisions about behavior change best practices, coaching features, platform, multimedia content, wireless devices, data security, integration of systems, rapid prototyping, usability, funding mechanisms, and how all of these issues intersect with clinical research and behavioral trials.
Over the 12 months, our study team faced many challenges to developing our prototype intervention. We describe 10 lessons learned that will ultimately stimulate more effective and sustainable approaches.
The experiences presented in this case study can be used as a reference for others developing mHealth behavioral intervention development projects by highlighting the benefits and challenges facing mHealth research.
mHealth; chronic disease; behavior change
Although higher visit-to-visit variability (VVV) of blood pressure (BP) is associated with increased cardiovascular disease risk, the physiological basis for VVV of BP is incompletely understood.
We examined the associations of aortic distensibility (assessed by magnetic resonance imaging) and artery elasticity indices (determined by radial artery pulse contour analysis) with VVV of BP in 2,640 and 4,560 participants, respectively, from the Multi-Ethnic Study of Atherosclerosis. Arterial measures were obtained at exam 1. BP readings were taken at exam 1 and at 3 follow-up visits at 18-month intervals (exams 2, 3, and 4). VVV was defined as the SD about each participant’s mean systolic BP (SBP) across visits.
The mean SDs of SBP were inversely associated with aortic distensibility: 7.7, 9.9, 10.9, and 13.2mm Hg for quartiles 4, 3, 2, and 1 of aortic distensibility, respectively (P trend < 0.001). This association remained significant after adjustment for demographics, cardiovascular risk factors, mean SBP, and antihypertensive medication use (P trend < 0.01). In a fully adjusted model, lower quartiles of large artery and small artery elasticity (LAE and SAE) indices were also associated with higher mean SD of SBP (P trend = 0.02 for LAE; P trend < 0.001 for SAE).
In this multiethnic cohort, functional alterations of central and peripheral arteries were associated with greater long-term VVV of SBP.
arteries; blood pressure; epidemiology; hypertension; vasculature.
Many studies of diabetes have examined risk factors at the time of diabetes diagnosis instead of considering the lifetime burden of adverse risk factor levels. We examined the 30-year cardiovascular disease (CVD) risk factor burden that participants have up to the time of diabetes diagnosis.
RESEARCH DESIGN AND METHODS
Among participants free of CVD, incident diabetes cases (fasting plasma glucose ≥126 mg/dL or treatment) occurring at examinations 2 through 8 (1979–2008) of the Framingham Heart Study Offspring cohort were age- and sex-matched 1:2 to controls. CVD risk factors (hypertension, high LDL cholesterol, low HDL cholesterol, high triglycerides, obesity) were measured at the time of diabetes diagnosis and at time points 10, 20, and 30 years prior. Conditional logistic regression was used to compare risk factor levels at each time point between diabetes cases and controls.
We identified 525 participants with new-onset diabetes who were matched to 1,049 controls (mean age, 60 years; 40% women). Compared with those without diabetes, individuals who eventually developed diabetes had higher levels of hypertension (odds ratio [OR], 2.2; P = 0.003), high LDL (OR, 1.5; P = 0.04), low HDL (OR, 2.1; P = 0.0001), high triglycerides (OR, 1.7; P = 0.04), and obesity (OR, 3.3; P < 0.0001) at time points 30 years before diabetes diagnosis. After further adjustment for BMI, the ORs for hypertension (OR, 1.9; P = 0.02) and low HDL (OR, 1.7; P = 0.01) remained statistically significant.
CVD risk factors are increased up to 30 years before diagnosis of diabetes. These findings highlight the importance of a life course approach to CVD risk factor identification among individuals at risk for diabetes.
Non-adherence to cardiovascular medications such as statins is a common, important problem. Clinicians currently rely on intuition to identify medication non-adherence. The visit-to-visit variability (VVV) of LDL-C may represent an opportunity to identify statin non-adherence with greater accuracy. We examined the clinical and pharmacy data from 782 members of the Boston Medical Center (BMC) Health Plan, seen at either BMC or its affiliated Community Health Centers, who were taking statins and had at least 3 LDL-C measurements between 2008 and 2011. The LDL-C VVV (defined by the within-patient standard deviation) was categorized into quintiles. Multivariable logistic regression models were generated with statin non-adherence (defined by the standard 80% pharmacy refill based medication possession ratio threshold) as the dependent variable. The proportion of statin non-adherence increased across quintiles of LDL-C VVV (64.3%, 71.2%, 89.2%, 92.3%, 91.7%). Higher quintiles of LDL-C VVV had a strong positive association with statin non-adherence with an adjusted odds ratio of 3.4 (CI: 1.7–7.1) in the highest versus lowest quintile of LDL-C VVV. The age and gender adjusted model had poor discrimination [C-statistic 0.62 (CI: 0.57, 0.67)] while the final adjusted (age, gender, race, mean LDL-C) model demonstrated good discrimination [C-statistic 0.75 (CI: 0.71, 0.79)] between adherent and non-adherent patients. In conclusion, the VVV of LDL-C demonstrated a strong association with statin non-adherence in a clinic setting. Further, a VVV- of LDL-C based model has good discrimination characteristics for statin non-adherence. Research is needed to validate and generalize these findings to other populations and biomarkers.
Visit-to-visit variability; statins; medication adherence
Given the results of the JUPITER trial, statin initiation may be considered for individuals with elevated high sensitivity C-reactive protein (CRP). However, if followed prospectively, many individuals with elevated CRP may become statin-eligible, limiting the impact of elevated CRP as a treatment indication. This analysis estimates the proportion of people with elevated CRP that become statin eligible over time.
We followed 2,153 Multi-Ethnic Study of Atherosclerosis (MESA) participants free of cardiovascular disease (CVD) and diabetes with LDL-cholesterol (LDL-C) <130 mg/dL at baseline to determine the proportion who become eligible for statins over 4.5 years. The proportion eligible for statin therapy, defined by the National Cholesterol Education Program (NCEP) 2004 updated guidelines, was calculated at baseline and during follow-up stratified by baseline CRP level (≥2 mg/L).
At baseline, 47% of the 2,153 participants had elevated CRP. Among participants with elevated CRP, 29% met NCEP criteria for statins, compared to 28% without elevated CRP at baseline. By 1.5 years later, 26% and 22% (p=0.09) of those with and without elevated CRP at baseline reached NCEP LDL-C criteria and/or had started statins, respectively. These increased to 42% and 39% (p=0.24) at 3 years and 59% and 52% (p=0.01) at 4.5 years following baseline.
A substantial proportion of those with elevated CRP did not achieve NCEP based statin eligibility over 4.5 years of follow-up. These findings suggest that many patients with elevated CRP may not receive the benefits of statins if CRP is not incorporated into the NCEP screening strategy.
It has been hypothesized that high visit-to-visit variability (VVV) of systolic blood pressure (SBP) may be the result of poor antihypertensive medication adherence. We studied this association using data from 1,391 individuals taking antihypertensive medication selected from a large managed care organization. The 8-item Morisky Medication Adherence Scale, administered during three annual surveys, captured self-report adherence with scores <6, 6 to <8 and 8 representing low, medium and high adherence, respectively. The mean (standard deviation [SD]) for SD of SBP across study visits was 12.9 (4.4), 13.5 (4.8), and 14.1 (4.5) mmHg in participants with high, medium and low self-reported adherence, respectively. After multivariable adjustment and compared to those with high self-report adherence, SD of SBP was 0.60 (95% CI: 0.13–1.07) and 1.08 (95% CI: 0.29–1.87) mmHg higher among participants with medium and low self-report adherence, respectively. Results were consistent when pharmacy fill was used to define adherence. These data suggest low antihypertensive medication adherence explains only a small proportion of VVV of SBP.
Medication adherence; blood pressure variability; hypertension
Low medication adherence may explain part of the high prevalence of apparent treatment resistant hypertension (aTRH). We assessed medication adherence and aTRH among 4,026 participants taking ≥ 3 classes of antihypertensive medication in the population-based REGARDS Study using the 4-item Morisky Medication Adherence Scale (MMAS). Low adherence was defined as a MMAS score ≥ 2. Overall, 66% of participants taking ≥ 3 classes of antihypertensive medication had aTRH. Perfect adherence on the MMAS was reported by 67.8% and 70.9% of participants with and without aTRH, respectively. Low adherence was present among 8.1% of participants with aTRH and 5.0% of those without aTRH (p<0.001). Among those with aTRH, female gender, residence outside the US stroke belt or stroke buckle, physical inactivity, elevated depressive symptoms, and a history of coronary heart disease were associated with low adherence. In the current study, a small percentage of participants with aTRH had low adherence.
Hypertension; Treatment Resistant Hypertension; Medication adherence; Risk Factors
Diabetes incidence is increasing worldwide and providers often do not feel they can effectively counsel about preventive lifestyle changes. The goal of this paper is to describe the development and initial feasibility testing of the Avoiding Diabetes Thru Action Plan Targeting (ADAPT) program to enhance counseling about behavior change for patients with pre-diabetes.
Primary care providers and patients were interviewed about their perspectives on lifestyle changes to prevent diabetes. A multidisciplinary design team incorporated this data to translate elements from behavior change theories to create the ADAPT program. The ADAPT program was pilot tested to evaluate feasibility.
Leveraging elements from health behavior theories and persuasion literature, the ADAPT program comprises a shared goal-setting module, implementation intentions exercise, and tailored reminders to encourage behavior change. Feasibility data demonstrate that patients were able to use the program to achieve their behavior change goals.
Initial findings show that the ADAPT program is feasible for helping improve primary care providers’ counseling for behavior change in patients with pre-diabetes.
If successful, the ADAPT program may represent an adaptable and scalable behavior change tool for providers to encourage lifestyle changes to prevent diabetes.
Major depressive disorder (MDD) is prevalent in clinical weight loss settings and predicts poor weight loss outcomes. It is unknown whether the severity of depressive symptoms among those with MDD is associated with diet quality or physical activity levels. This knowledge is important for improving weight loss treatment for these patients. It was hypothesized that more severe depression is associated with poorer diet quality and lower physical activity levels among individuals with obesity and MDD. Participants were 161 women with current MDD and obesity enrolled in the baseline phase of a weight loss trial between 2007 and 2010. Depression severity was measured with the Beck Depression Inventory II. The Alternate Healthy Eating Index (AHEI) was applied to data from three 24-hour diet recalls to capture overall diet quality. Daily metabolic equivalents expended per day (MET-hrs/d) were calculated from three 24-hour physical activity recalls. Greater depression severity was associated with poorer overall diet quality (estimate=−.26, SE=.11, p=.02), but not with physical activity (estimate=.07, SE=.05, p=.18), in linear regression models controlling for income, education, depression-related appetite change, binge eating disorder, and other potential confounds. Associations with diet quality were primarily driven by greater intake of sugar (r=.20, p<.01), saturated fat (r=.21, p<.01), and sodium (r=.22, p<.01). More severe depression was associated with poorer overall diet quality, but not physical activity, among treatment-seeking women with MDD and obesity. Future studies should identify mechanisms linking depression to diet quality, and determine whether diet quality improves with depression treatment.
Diet quality; Depression; Obesity; AHEI; Physical activity
Few data are available on factors associated with low adherence or early clopidogrel discontinuation following percutaneous coronary intervention (PCI). Patients (n=284) were evaluated prior to hospital discharge following PCI to identify factors associated with low adherence to clopidogrel 30 days later. Pre-PCI adherence to daily medications was assessed using the 8-item Morisky Medication Adherence Scale (MMAS-8) and categorized as low, medium, or high (scores <6, 6 to <8 and 8, respectively). Low adherence to clopidogrel was defined as a MMAS-8 score < 6 (n=21) or having discontinued clopidogrel (n=11), both ascertained during a 30-day post-PCI interview. At 30 days post-PCI, 11% of patients had low adherence to clopidogrel. The odds ratios (95% confidence interval) for low adherence to clopidogrel was 3.78 (1.09 – 13.1), 3.06 (1.36 – 6.87), 2.46 (0.97 – 6.27) and 3.36 (0.99 – 11.4) for patients who reported, prior to PCI, taking smaller doses of medication due to cost, had difficulty filling prescriptions, had difficulty reaching their primary physician and were not comfortable asking their doctor for instructions, respectively. The odds ratios (95% CI) for low clopidogrel adherence following PCI among patients with medium and low, versus high adherence, to daily medications prior to PCI was 6.13 (1.34 – 28.2) and 10.9 (2.46 – 48.7), respectively. The c-statistic associated with pre-PCI MMAS-8 scores for discriminating low clopidogrel adherence at 30 days post-PCI was 0.733 (95% CI: 0.650 – 0.852). Pre-PCI adherence to daily medications may be a useful indicator for identifying patients who will have low clopidogrel adherence following PCI.
Clopidgrel; medication adherence; percutaneous coronary intervention
The prevalence of albuminuria in the general population is high, but awareness of it is low. Therefore, we sought to develop and validate a self-assessment tool that allows individuals to estimate their probability of having albuminuria.
Setting & Participants
The population-based REasons for Geographic And Racial Differences in Stroke (REGARDS) study for model development and the National Health and Nutrition Examination Survey 1999-2004 (NHANES 1999-2004) for model validation. US adults ≥ 45 years of age in the REGARDS study (n=19,697) and NHANES 1999-2004 (n=7,168)
Candidate items for the self-assessment tool were collected using a combination of interviewer- and self-administered questionnaires.
Albuminuria was defined as a urinary albumin to urinary creatinine ratio ≥ 30 mg/g in spot samples.
Eight items were included in the self-assessment tool (age, race, gender, current smoking, self-rated health, and self-reported history of diabetes, hypertension, and stroke). These items provided a c-statistic of 0.709 (95% CI, 0.699 – 0.720) and a good model fit (Hosmer-Lemeshow chi-square p-value = 0.49). In the external validation data set, the c-statistic for discriminating individuals with and without albuminuria using the self-assessment tool was 0.714. Using a threshold of ≥ 10% probability of albuminuria from the self-assessment tool, 36% of US adults ≥ 45 years of age in NHANES 1999-2004 would test positive and be recommended screening. The sensitivity, specificity, and positive and negative predictive values for albuminuria associated with a probability ≥ 10% were 66%, 68%, 23% and 93%, respectively.
Repeat urine samples were not available to assess the persistency of albuminuria.
Eight self-report items provide good discrimination for the probability of having albuminuria. This tool may encourage individuals with a high probability to request albuminuria screening.
Background. East Harlem is an epicenter of the intertwining epidemics of obesity and diabetes in New York. Physical activity is thought to prevent and control a number of chronic illnesses, including diabetes, both independently and through weight control. Using data from a survey collected on adult (age 18+) residents of East Harlem, this study evaluated whether perceptions of safety and community-identified barriers were associated with lower levels of physical activity in a diverse sample. Methods. We surveyed 300 adults in a 2-census tract area of East Harlem and took measurements of height and weight. Physical activity was measured in two ways: respondents were classified as having met the weekly recommended target of 2.5 hours of moderate physical activity (walking) per week (or not) and reporting having engaged in at least one recreational physical activity (or not). Perceived barriers were assessed through five items developed by a community advisory board and perceptions of neighborhood safety were measured through an adapted 7-item scale. Two multivariate logistic regression models with perceived barriers and concerns about neighborhood safety were modeled separately as predictors of engaging in recommended levels of exercise and recreational physical activity, controlling for respondent weight and sociodemographic characteristics. Results. The most commonly reported perceived barriers to physical activity identified by nearly half of the sample were being too tired or having little energy followed by pain with exertion and lack of time. Multivariate regression found that individuals who endorsed a greater number of perceived barriers were less likely to report having met their weekly recommended levels of physical activity and less likely to engage in recreational physical activity controlling for covariates. Concerns about neighborhood safety, though prevalent, were not associated with physical activity levels. Conclusions. Although safety concerns were prevalent in this low-income, minority community, it was individual barriers that correlated with lower physical activity levels.
Observational studies suggest there are differences in adherence to antihypertensive medications in different classes. Our objective was to quantify the association between antihypertensive drug class and adherence in clinical settings.
Methods and Results
Studies were identified through a systematic search of English-language articles published from inception of computerized databases till February 1, 2009. Studies were included if they measured adherence to antihypertensives using medication refill data and contained sufficient data to calculate a measure of relative risk of adherence and its variance. An inverse-variance weighted random-effects model was used to pool results. Hazard ratios (HR) and odds ratios (OR) were pooled separately, and HRs were selected as the primary outcome. Seventeen studies met inclusion criteria. The pooled mean adherence by drug class ranged from 28% for beta-blockers to 65% for angiotensin II-receptor blockers (ARBs).There was better adherence to ARBs compared to angiotensin-converting enzyme inhibitors (ACEIs) (HR 1.33, 95%CI 1.13–1.57), calcium channel blockers (HR 1.57, 95% CI 1.38–1.79), diuretics (HR 1.95, 95%CI 1.73–2.20), and beta-blockers (HR 2.09, 95%CI 1.14–3.85). Conversely, there was lower adherence to diuretics compared to the other drug classes. The same pattern was present when pooling studies that used ORs. When accounting for publication bias, there were no longer significant differences in adherence between ARBs and ACEIs or between diuretics and beta-blockers.
In clinical settings, there are important differences in adherence to antihypertensives in separate classes with lowest adherence to diuretics and beta-blockers and highest to ARBs and ACEIs. Yet, adherence was suboptimal regardless of drug class.
hypertension; medication adherence; meta-analysis
Increased left ventricular (LV) mass and changes in LV geometry may precede hypertension onset. The authors examined the associations of LV mass and geometry, assessed by cardiac magnetic resonance imaging, with hypertension incidence in 2,567 normotensive participants enrolled in 2000–2002 in the Multi-Ethnic Study of Atherosclerosis, an ethnically diverse, population-based, US study. Over a median follow-up of 4.8 years, 745 (29%) participants developed hypertension. In a fully adjusted model including baseline blood pressure, the relative risks of incident hypertension from the lowest to highest LV mass quartile were 1.00 (referent), 1.13 (95% confidence interval (CI): 0.89, 1.43), 1.28 (95% CI: 1.00, 1.63), and 1.78 (95% CI: 1.38, 2.30) (P < 0.001 for linear trend). Higher levels of LV concentric geometry, defined by higher LV mass to end-diastolic volume quartiles, were associated with higher risk of incident hypertension in a fully adjusted model (P = 0.044 for linear trend). In a final model containing both quartiles of LV mass and LV mass/volume along with all covariates including baseline blood pressure, higher LV mass quartiles were associated with incident hypertension (P < 0.001 for linear trend), whereas higher LV mass/volume quartiles were not (P = 0.643 for linear trend). In this multiethnic cohort, alterations in LV mass preceded hypertension onset among normotensive individuals.
hypertension; hypertrophy, left ventricular; magnetic resonance imaging; risk factors
Polypills which include multiple medications for reducing cardiovascular disease (CVD) risk in a single pill have been proposed for population-wide use. The number of US adults eligible for polypills and potential benefits are unknown.
The National Health and Nutrition Examination Survey 2003-2004 and 2007-2008 were analyzed to estimate treatment rates for medications proposed for inclusion in polypills (aspirin, statin, an ACE-inhibitor, and a thiazide-type diuretic for those without, a beta-blocker for those with, a history of myocardial infarction) among US adults. The number of coronary heart disease (CHD) and stroke events potentially prevented through polypill use was projected by published meta-analyses and three large population-based cohort studies. Two polypill eligibility criteria were analyzed (1) US adults ≥ 55 years and (2) US adults with a history of CVD.
There are 67.6 million US adults ≥ 55 years and 15.4 million US adults with a history of CVD and, thus, eligible for polypills using the two outlined criteria. In 2007-2008, 37.3% of US adults ≥ 55 years and 57.0% of those with a history of CVD were taking statins. Use of other polypill medications was also low. Polypill use by US adults age ≥ 55 years is projected to potentially prevent 3.2 million CHD events and 1.7 million strokes over 10 years. Amongst those with a history of CVD, the potential to prevent of 0.9 million CHD events and 0.5 million strokes is projected.
Polypills have the potential to lower CVD incidence substantially among US adults.
Studies have shown that lifestyle behavior changes are most effective to prevent onset of diabetes in high-risk patients. Primary care providers are charged with encouraging behavior change among their patients at risk for diabetes, yet the practice environment and training in primary care often do not support effective provider counseling. The goal of this study is to develop an electronic health record-embedded tool to facilitate shared patient-provider goal setting to promote behavioral change and prevent diabetes.
The ADAPT (Avoiding Diabetes Thru Action Plan Targeting) trial leverages an innovative system that integrates evidence-based interventions for behavioral change with already-existing technology to enhance primary care providers' effectiveness to counsel about lifestyle behavior changes. Using principles of behavior change theory, the multidisciplinary design team utilized in-depth interviews and in vivo usability testing to produce a prototype diabetes prevention counseling system embedded in the electronic health record.
The core element of the tool is a streamlined, shared goal-setting module within the electronic health record system. The team then conducted a series of innovative, "near-live" usability testing simulations to refine the tool and enhance workflow integration. The system also incorporates a pre-encounter survey to elicit patients' behavior-change goals to help tailor patient-provider goal setting during the clinical encounter and to encourage shared decision making. Lastly, the patients interact with a website that collects their longitudinal behavior data and allows them to visualize their progress over time and compare their progress with other study members. The finalized ADAPT system is now being piloted in a small randomized control trial of providers using the system with prediabetes patients over a six-month period.
The ADAPT system combines the influential powers of shared goal setting and feedback, tailoring, modeling, contracting, reminders, and social comparisons to integrate evidence-based behavior-change principles into the electronic health record to maximize provider counseling efficacy during routine primary care clinical encounters. If successful, the ADAPT system may represent an adaptable and scalable technology-enabled behavior-change tool for all primary care providers.
ClinicalTrials.gov Identifier NCT01473654
New clinical practice recommendations include A1C as an alternative to fasting glucose as a diagnostic test for identifying pre-diabetes. The impact of these new recommendations on the diagnosis of pre-diabetes is unknown.
RESEARCH DESIGN AND METHODS
Data from the National Health and Nutrition Examination Survey 1999–2006 (n = 7,029) were analyzed to determine the percentage and number of U.S. adults without diabetes classified as having pre-diabetes by the elevated A1C (5.7–6.4%) and by the impaired fasting glucose (IFG) (fasting glucose 100–125 mg/dl) criterion separately. Test characteristics (sensitivity, specificity, and positive and negative predictive values) using IFG as the reference standard were calculated.
The prevalence of pre-diabetes among U.S. adults was 12.6% by the A1C criterion and 28.2% by the fasting glucose criterion. Only 7.7% of U.S. adults, reflecting 61 and 27% of those with pre-diabetes by A1C and fasting glucose, respectively, had pre-diabetes according to both definitions. A1C used alone would reclassify 37.6 million Americans with IFG to not having pre-diabetes and 8.9 million without IFG to having pre-diabetes (46.5 million reclassified). Using IFG as the reference standard, pre-diabetes by the A1C criterion has 27% sensitivity, 93% specificity, 61% positive predictive value, and 77% negative predictive value.
Using A1C as the pre-diabetes criterion would reclassify the pre-diabetes diagnosis of nearly 50 million Americans. It is imperative that clinicians and health systems understand the differences and similarities in using A1C or IFG in diagnosis of pre-diabetes.
Clinical prediction rules (CPRs) represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR) has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR) trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting.
A multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS) tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149) were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated) groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters) and chest x-rays (pneumonia iCPR only) between intervention and control providers.
Using iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative process will lead to higher rates of utilization and EBM guided use of antibiotics and chest x-ray's in primary care.
ClinicalTrials.gov Identifier NCT01386047
A prediction model, developed in the Framingham Heart Study (FHS), has been proposed for use in estimating a given individual’s risk of hypertension. We compared this model with systolic blood pressure (SBP) alone and age-specific diastolic blood pressure (DBP) categories for the prediction of hypertension. Participants in the Multi-Ethnic Study of Atherosclerosis, without hypertension or diabetes (n=3013), were followed for the incidence of hypertension (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg and/or the initiation of antihypertensive medication). The predicted probability of developing hypertension between four adjacent study examinations, with a median of 1.6 years between examinations, was determined. The mean (standard deviation) age of participants was 58.5 (9.7) years and 53% were women. During follow-up, 849 incident cases of hypertension occurred. The c-statistic for the FHS model was 0.788 (95% CI: 0.773, 0.804) compared with 0.768 (95% CI: 0.751, 0.785; p=0.096 compared to the FHS model) for SBP alone and 0.699 (95% CI: 0.681, 0.717; p<0.001 compared to the FHS model) for age-specific DBP categories. The relative integrated discrimination improvement index for the FHS model versus SBP alone was 10.0% (95% CI: −1.7%, 22.7%) and versus age-specific DBP categories was 146% (95% CI: 116%, 181%). Using the FHS model, there were significant differences between observed and predicted hypertension risk (Hosmer-Lemeshow goodness of fit p<0.001); re-calibrated and best-fit models produced a better model fit (p=0.064 and 0.245, respectively). In this multi-ethnic cohort of U.S. adults, the FHS model was not substantially better than SBP alone for predicting hypertension.
hypertension; epidemiology; systolic blood pressure; diastolic blood pressure; risk prediction
Several models for estimating risk of incident diabetes in US adults are available. The authors aimed to determine the discriminative ability and calibration of published diabetes risk prediction models in a contemporary multiethnic cohort. Participants in the Multi-Ethnic Study of Atherosclerosis without diabetes at baseline (2000–2002; n = 5,329) were followed for a median of 4.75 years. The predicted risk of diabetes was calculated using published models from the Framingham Offspring Study, the Atherosclerosis Risk in Communities (ARIC) Study, and the San Antonio Heart Study. The mean age of participants was 61.6 years (standard deviation, 10.2); 29.3% were obese, 53.1% had hypertension, 34.9% had a family history of diabetes, 27.5% had high triglyceride levels, 33.8% had low high density lipoprotein cholesterol levels, and 15.3% had impaired fasting glucose. There were 446 incident cases of diabetes (fasting glucose level ≥126 mg/dL or initiation of antidiabetes medication use) diagnosed during follow-up. C statistics were 0.78, 0.84, and 0.83 for the Framingham, ARIC, and San Antonio risk prediction models, respectively. There were significant differences between observed and predicted diabetes risks (Hosmer-Lemeshow goodness-of-fit chi-squared test for each model: P < 0.001). The recalibrated and best-fit models achieved sufficient goodness of fit (each P > 0.10). The Framingham, ARIC, and San Antonio models maintained high discriminative ability but required recalibration in a modern, multiethnic US cohort.
cohort studies; diabetes mellitus; models, statistical; risk; validation studies as topic