Childhood obesity in the United States is a critical public health issue. Although multiple child and parental factors are associated with childhood obesity, few models evaluate how socioeconomic ...status influences these risk factors. We aimed to create a model to examine how socioeconomic status modifies risk factors for child obesity.
We conducted a secondary data analysis of the Early Childhood Longitudinal Birth Cohort. Using logistic regression, we modeled childhood obesity status from known parental and child risk factors for childhood obesity and tested interactions with socioeconomic status.
Compared with healthy-weight children, socioeconomic status, race, birth weight, parental smoking, and not eating dinner as a family were associated with kindergarten-aged children being overweight or obese. Parental smoking increased the odds of a child being overweight or obese by 40%, and eating dinner as a family reduced the odds of a child being overweight or obese by 4%. In addition, black or Hispanic children had a 60% increased odds of being overweight or obese when compared with their white counterparts. Native American children had almost double the odds of being overweight or obese compared with white children. Socioeconomic status did not modify any of these associations.
Parental smoking, birth weight, and not eating dinner as a family were two modifiable factors associated with overweight and obesity in kindergarten-age children, regardless of socioeconomic status. Changing these life-style factors could reduce the child's risk for obesity.
Abstract Purpose Peer support intervention trials have shown varying effects on glycemic control. We aimed to estimate the effect of peer support interventions delivered by people affected by ...diabetes (those with the disease or a caregiver) on hemoglobin A1c (HbA1c ) levels in adults. Methods We searched multiple databases from 1960 to November 2015, including Ovid MEDLINE, the Cochrane Central Register of Controlled Trials, CINAHL, and Scopus. We included randomized controlled trials (RCTs) of adults with diabetes receiving peer support interventions compared with otherwise similar care. Seventeen of 205 retrieved studies were eligible for inclusion. Quality was assessed with the Cochrane risk of bias tool. We calculated the standardized mean difference (SMD) of change in HbA1c level from baseline between groups using a random effects model. Subgroup analyses were predefined. Results Seventeen studies (3 cluster RCTs, 14 RCTs) with 4,715 participants showed an improvement in pooled HbA1c level with an SMD of 0.121 (95% CI, 0.026–0.217; P = .01; I2 = 60.66%) in the peer support intervention group compared with the control group; this difference translated to an improvement in HbA1c level of 0.24% (95% CI, 0.05%-0.43%). Peer support interventions showed an HbA1 c improvement of 0.48% (95% CI, 0.25%-0.70%; P <.001; I2 = 17.12%) in the subset of studies with predominantly Hispanic participants and 0.53% (95% CI, 0.32%-0.73%; P <.001; I2 = 9.24%) in the subset of studies with predominantly minority participants; both were clinically relevant. In sensitivity analysis excluding cluster RCTs, the overall effect size changed little. Conclusions Peer support interventions for diabetes overall achieved a statistically significant but minor improvement in HbA1c levels. These interventions may, however, be particularly effective in improving glycemic control for people from minority groups, especially those of Hispanic ethnicity.
Peer support by persons affected with diabetes improves peer supporter's diabetes self-management skills. Peer support interventions by individuals who have diabetes or are affected by diabetes have ...been shown to improve glycemic control; however, its effects on other cardiovascular disease risk factors in adults with diabetes are unknown. We aimed to estimate the effect of peer support interventions on cardiovascular disease risk factors other than glycemic control in adults with diabetes.
We conducted a systematic review and meta-analysis of randomized controlled trials comparing peer support interventions to a control condition in adults affected by diabetes that measured any cardiovascular disease risk factors Body Mass Index, smoking, diet, physical activity, cholesterol level, glucose control and blood pressure. Quality was assessed by Cochrane's risk of bias tool. We calculated standardized mean difference effect sizes using random effects models.
We retrieved 438 citations from multiple databases including OVID MEDLINE, Cochrane database and Scopus, and author searches. Of 233 abstracts reviewed, 16 articles met inclusion criteria. A random effects model in a total of 3243 participants showed a positive effect of peer support interventions on systolic BP with a pooled effect size of 2.07 mmHg (CI 0.35 mmHg to 3.79 mmHg, p = 0.02); baseline pooled systolic blood pressure was 137 mmHg. There was a non-significant effect of peer support interventions on diastolic blood pressure, cholesterol, body mass index, diet and physical activity. Cardiovascular disease risk factors other than glycemic control outcomes were secondary outcomes in most studies and baseline values were normal or mildly elevated. Only one study reported smoking outcomes.
We found a small (2 mmHg) positive effect of peer support interventions on systolic blood pressure in adults with diabetes whose baseline blood pressure was on average minimally elevated. Additional studies need to be conducted to further understand the effect of peer support interventions on high-risk cardiovascular disease risk factors in adults with diabetes.
Although researchers have identified factors associated with research capacity in academic medicine departments, less is known about how a department builds research capacity over time. The ...Association of Departments of Family Medicine's Research Capacity Scale (RCS) can be used by departments to self-categorize into five capacity levels. Our current study aimed to describe the distribution of infrastructure features and to evaluate how the addition of infrastructure features influences movement of a department along the RCS.
An online survey was sent to US family medicine department chairs in August 2021. Survey questions asked chairs to categorize their department's research capacity in 2018 and 2021 and also about the presence of infrastructure resources and changes in these features across 6 years.
The response rate was 54.2%. Departments identified substantial variation in research capacity. Most departments classified into the middle three levels. Departments in higher levels were more likely than those at lower levels to have any of the infrastructure resources in 2021. Department size, as measured by full time faculty, was highly associated with department level. From 2018 and 2021, 43% of responding departments climbed at least one level. Of these, more than half added three or more infrastructure features. Adding a PhD researcher was the feature most associated with increasing research capacity (P<.001).
Most departments that increased their research capacity added multiple additional infrastructure features. For chairs of departments without a PhD researcher, this additional resource may be the most impactful investment to increase research capacity.
Abstract
Objective
Most electronic health records display historical medication information only in a data table or clinician notes. We designed a medication timeline visualization intended to ...improve ease of use, speed, and accuracy in the ambulatory care of chronic disease.
Materials and Methods
We identified information needs for understanding a patient medication history, then applied human factors and interaction design principles to support that process. After research and analysis of existing medication lists and timelines to guide initial requirements, we hosted design workshops with multidisciplinary stakeholders to expand on our initial concepts. Subsequent core team meetings used an iterative user-centered design approach to refine our prototype. Finally, a small pilot evaluation of the design was conducted with practicing physicians.
Results
We propose an open-source online prototype that incorporates user feedback from initial design workshops, and broad multidisciplinary audience feedback. We describe the applicable design principles associated with each of the prototype’s key features. A pilot evaluation of the design showed improved physician performance in 5 common medication-related tasks, compared to tabular presentation of the same information.
Discussion
There is industry interest in developing medication timelines based on the example prototype concepts. An open, standards-based technology platform could enable developers to create a medication timeline that could be deployable across any compatible health IT application.
Conclusion
The design goal was to improve physician understanding of a patient’s complex medication history, using a medication timeline visualization. Such a design could reduce temporal and cognitive load on physicians for improved and safer care.
PURPOSE Evidence shows the value of home blood pressure (BP) monitoring in hypertension management. Questions exist about how to effectively incorporate these readings into BP follow-up visits. We ...developed and implemented a tool that combines clinical and home BP readings into an electronic health record (EHR)-integrated visualization tool. We examined how this tool was used during primary care visits and its effect on physician-patient communication and decision making about hypertension management, comparing it with home BP readings on paper. METHODS We video recorded the hypertension follow-up visits of 73 patients with 15 primary care physicians between July 2018 and April 2019. During visits, physicians reviewed home BP readings with patients, either directly from paper or as entered into the EHR visualization tool. We used conversation analysis to analyze the recordings. RESULTS Home BP readings were viewed on paper for 26 patients and in the visualization tool for 47 patients. Access to home BP readings during hypertension management visits, regardless of viewing mode, positioned the physician and patient to assess BP management and make decisions about treatment modification, if needed. Length of BP discussion with the visualization tool was similar to or shorter than that with paper. Advantages of the visualization tool included ease of use, and enhanced and faster sense making and decision making. Successful use of the tool required patients' ability to obtain their BP readings and enter them into the EHR via a portal, and an examination room configuration that allowed for screen sharing. CONCLUSIONS Reviewing home BP readings using a visualization tool is feasible and enhances sense making and patient engagement in decision making. Practices and their patients need appropriate infrastructure to realize these benefits. Key words: patient-generated health data; home blood pressure monitoring; hypertension control; clinical decision support; EHR; health information technology; ergonomics; data visualization; shared decision making
Abstract
Objectives
To identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning ...electronic health records (EHR) to address these needs.
Materials and Methods
In this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users’ information needs, which were then used to produce EHR design principles.
Results
Analyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information.
Conclusion
Developing EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.
Abstract Objective To systematically examine current evidence pertaining to information needs of informal caregivers of older adults with chronic health conditions. Methods Structured search of ...MEDLINE, MEDLINE IN-PROCESS, CINAHL, and PsycINFO databases to identify studies of caregiver information needs, followed by data extraction and syntheses. Results The 62 articles that met the stated inclusion criteria highlighted extensive needs among informal caregivers for practical, accessible, timely information. Conclusion The identified information needs of informal caregivers can inform organizations and agencies that seek to provide disease and illness-related information. Practice implications Existing evidence supports the implementation of a health information delivery system designed to meet the needs of informal caregivers of older adults with chronic health conditions.
Abstract Purpose We compared use of a new diabetes dashboard screen with use of a conventional approach of viewing multiple electronic health record (EHR) screens to find data needed for ambulatory ...diabetes care. Methods We performed a usability study, including a quantitative time study and qualitative analysis of information-seeking behaviors. While being recorded with Morae Recorder software and “think-aloud” interview methods, 10 primary care physicians first searched their EHR for 10 diabetes data elements using a conventional approach for a simulated patient, and then using a new diabetes dashboard for another. We measured time, number of mouse clicks, and accuracy. Two coders analyzed think-aloud and interview data using grounded theory methodology. Results The mean time needed to find all data elements was 5.5 minutes using the conventional approach vs 1.3 minutes using the diabetes dashboard ( P < .001). Physicians correctly identified 94% of the data requested using the conventional method, vs 100% with the dashboard ( P < .01). The mean number of mouse clicks was 60 for conventional searching vs 3 clicks with the diabetes dashboard ( P < .001). A common theme was that in everyday practice, if physicians had to spend too much time searching for data, they would either continue without it or order a test again. Conclusions Using a patient-specific diabetes dashboard improves both the efficiency and accuracy of acquiring data needed for high-quality diabetes care. Usability analysis tools can provide important insights into the value of optimizing physician use of health information technologies.
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