Dataset Information

Electronic Health Risk Behavior Screening With Integrated Feedback Among Adolescents in Primary Care: Randomized Controlled Trial.

ABSTRACT:

Background

Health risk behaviors are the most common sources of morbidity among adolescents. Adolescent health guidelines (Guidelines for Preventive Services by the AMA and Bright Futures by the Maternal Child Health Bureau) recommend screening and counseling, but the implementation is inconsistent.

Objective

This study aims to test the efficacy of electronic risk behavior screening with integrated patient-facing feedback on the delivery of adolescent-reported clinician counseling and risk behaviors over time.

Methods

This was a randomized controlled trial comparing an electronic tool to usual care in five pediatric clinics in the Pacific Northwest. A total of 300 participants aged 13-18 years who attended a well-care visit between September 30, 2016, and January 12, 2018, were included. Adolescents were randomized after consent by employing a 1:1 balanced age, sex, and clinic stratified schema with 150 adolescents in the intervention group and 150 in the control group. Intervention adolescents received electronic screening with integrated feedback, and the clinicians received a summary report of the results. Control adolescents received usual care. Outcomes, assessed via online survey methods, included adolescent-reported receipt of counseling during the visit (measured a day after the visit) and health risk behavior change (measured at 3 and 6 months after the visit).

Results

Of the original 300 participants, 94% (n=282), 94.3% (n=283), and 94.6% (n=284) completed follow-up surveys at 1 day, 3 months, and 6 months, respectively, with similar levels of attrition across study arms. The mean risk behavior score at baseline was 2.86 (SD 2.33) for intervention adolescents and 3.10 (SD 2.52) for control adolescents (score potential range 0-21). After adjusting for age, gender, and random effect of the clinic, intervention adolescents were 36% more likely to report having received counseling for endorsed risk behaviors than control adolescents (adjusted rate ratio 1.36, 95% CI 1.04 to 1.78) 1 day after the well-care visit. Both the intervention and control groups reported decreased risk behaviors at the 3- and 6-month follow-up assessments, with no significant group differences in risk behavior scores at either time point (3-month group difference: β=-.15, 95% CI -0.57 to -0.01, P=.05; 6-month group difference: β=-.12, 95% CI -0.29 to 0.52, P=.57).

Conclusions

Although electronic health screening with integrated feedback improves the delivery of counseling by clinicians, the impact on risk behaviors is modest and, in this study, not significantly different from usual care. More research is needed to identify effective strategies to reduce risk in the context of well-care.

Trial registration

ClinicalTrials.gov NCT02882919; https://clinicaltrials.gov/ct2/show/NCT02882919.

SUBMITTER: Richardson L

PROVIDER: S-EPMC7998326 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Electronic health screening tools for primary care present an opportunity to go beyond data collection to provide education and feedback to adolescents in order to motivate behavior change. However, there is limited research to guide feedback message development.The aim of this study was to explore youth perceptions of and preferences for receiving personalized feedback for multiple health risk behaviors and reinforcement for health promoting behaviors from an electronic health screening tool for primary care settings, using qualitative methodology.In total, 31 adolescents aged 13-18 years completed the screening tool, received the electronic feedback, and subsequently participated in individual, semistructured, qualitative interviews lasting approximately 60 min. Participants were queried about their overall impressions of the tool, perceptions regarding various types of feedback messages, and additional features that would help motivate health behavior change. Using thematic analysis, interview transcripts were coded to identify common themes expressed across participants.Overall, the tool was well-received by participants who perceived it as a way to enhance-but not replace-their interactions with providers. They appreciated receiving nonjudgmental feedback from the tool and responded positively to information regarding the consequences of behaviors, comparisons with peer norms and health guidelines, tips for behavior change, and reinforcement of healthy choices. A small but noteworthy minority of participants dismissed the peer norms as not real or relevant and national guidelines as not valid or reasonable. When prompted for possible adaptations to the tool, adolescents expressed interest in receiving follow-up information, setting health-related goals, tracking their behaviors over time, and communicating with providers electronically between appointments.Adolescents in this qualitative study desired feedback that validates their healthy behavior choices and supports them as independent decision makers by neutrally presenting health information, facilitating goal setting, and offering ongoing technological supports.

Project description:ImportanceHealth risk behaviors are a leading cause of morbidity during adolescence. Screening and counseling for health risk behaviors are recommended but infrequently performed.ObjectiveTo test the effect of an electronic screening and feedback tool on clinician counseling and adolescent-reported health risk behaviors.Design, setting, and participantsA randomized clinical trial compared electronic screening and feedback on an intention-to-treat basis with usual care among 300 youths 13 to 18 years of age at 5 pediatric clinics in the Pacific Northwest. Outcomes were assessed via electronic survey at 1 day and 3 months after the initial visit. Study data collection occurred from March 13, 2015, to November 29, 2016, and statistical analysis was conducted between February 6, 2017, and June 20, 2018.InterventionsYouths in the intervention group (n = 147) received electronic screening and personalized feedback with clinician clinical decision support. Youths in the control group (n = 153) received standard screening and counseling as provided by their clinic.Main outcomes and measuresYouths' report of receipt of counseling during the visit and risk behaviors at 3 months.ResultsIn the final study sample of 300 youths (intervention group, 75 girls and 72 boys; mean [SD] age, 14.5 [1.4 years]; and control group, 80 girls and 73 boys; mean [SD] age, 14.5 [1.4] years), 234 (78.0%) were aged 13 to 15 years. After adjusting for age, sex, and random effect of clinic, youths in the intervention group were more likely to receive counseling for each of their reported risk behaviors than were youths in the control group (adjusted rate ratio, 1.32; 95% CI, 1.07-1.63). Youths in the intervention group had a significantly greater reduction (β = -0.48; 95% CI, -0.89 to -0.02; P = .02) in their risk behavior scores at 3 months when compared with youths in the control group.Conclusions and relevanceElectronic screening of health risk behavior with clinical decision support and motivational feedback to teens can improve care delivery and outcomes.Trial registrationClinicalTrials.gov identifier: NCT02360410.

Project description:BackgroundMost smokers with chronic obstructive pulmonary disease (COPD) have not yet been diagnosed, a statistic that has remained unchanged for over two decades. A dual-focused telehealth intervention that promotes smoking cessation, while also facilitating COPD screening, could help address national priorities to improve the diagnosis, prevention, treatment, and management of COPD. The purpose of this study was to preliminarily evaluate an integrated asynchronous smoking cessation and COPD screening e-visit (electronic visit) that could be delivered proactively to adult smokers at risk for COPD, who are treated within primary care.ObjectiveThe aims of this study were (1) to examine e-visit feasibility and acceptability, particularly as compared to in-lab diagnostic pulmonary function testing (PFT), and (2) to examine the efficacy of smoking cessation e-visits relative to treatment as usual (TAU), all within primary care.MethodsIn a randomized clinical trial, 125 primary care patients who smoke were randomized 2:1 to receive either proactive e-visits or TAU. Participants randomized to the e-visit condition were screened for COPD symptoms via the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE). Those with scores ≥2 were invited to complete both home spirometry and in-lab PFTs, in addition to two smoking cessation e-visits. Smoking cessation e-visits assessed smoking history and motivation to quit and included completion of an algorithm to determine the best Food and Drug Administration-approved cessation medication to prescribe. Primary outcomes included measures related to (1) e-visit acceptability, feasibility, and treatment metrics; (2) smoking cessation outcomes (cessation medication use, 24-hour quit attempts, smoking reduction ≥50%, self-reported abstinence, and biochemically confirmed abstinence); and (3) COPD screening outcomes.ResultsOf 85 participants assigned to the e-visits, 64 (75.3%) were invited to complete home spirometry and in-lab PFTs based on CAPTURE. Among those eligible for spirometry, 76.6% (49/64) completed home spirometry, and 35.9% (23/64) completed in-lab PFTs. At 1 month, all cessation outcomes favored the e-visit, with a significant effect for cessation medication use (odds ratio [OR]=3.22). At 3 months, all cessation outcomes except for 24-hour quit attempts favored the e-visit, with significant effects for cessation medication use (OR=3.96) and smoking reduction (OR=3.09).ConclusionsA proactive, asynchronous e-visit for smoking cessation and COPD screening may offer a feasible, efficacious approach for broad interventions within primary care.Trial registrationClinicalTrials.gov NCT04155073; https://clinicaltrials.gov/ct2/show/NCT04155073.

Project description:BACKGROUND:Cancer Care Ontario's Screening Activity Report (SAR) is an online audit and feedback tool designed to help primary care physicians in Ontario, Canada, identify patients who are overdue for cancer screening or have abnormal results requiring follow-up. Use of the SAR is associated with increased screening rates. To encourage SAR use, Cancer Care Ontario sends monthly emails to registered primary care physicians announcing that updated data are available. However, analytics reveal that 50% of email recipients do not open the email and less than 7% click the embedded link to log in to their report. OBJECTIVE:The goal of the study is to determine whether rewritten emails result in increased log-ins. This manuscript describes how different user- and theory-informed messages intended to improve the impact of the monthly emails will be experimentally tested and how a process evaluation will explore why and how any effects observed were (or were not) achieved. METHODS:A user-centered approach was used to rewrite the content of the monthly email, including messages operationalizing 3 behavior change techniques: anticipated regret, material incentive (behavior), and problem solving. A pragmatic, 2x2x2 factorial experiment within a multiphase optimization strategy will test the redesigned emails with an embedded qualitative process evaluation to understand how and why the emails may or may not have worked. Trial outcomes will be ascertained using routinely collected administrative data. Physicians will be recruited for semistructured interviews using convenience and snowball sampling. RESULTS:As of April 2017, 5576 primary care physicians across the province of Ontario, Canada, had voluntarily registered for the SAR, and in so doing, signed up to receive the monthly email updates. From May to August 2017 participants received the redesigned monthly emails with content specific to their allocated experimental condition prompting use of the SAR. We have not yet begun analyses. CONCLUSIONS:This study will inform how to communicate effectively with primary care providers by email and identify which behavior change techniques tested are most effective at encouraging engagement with an audit and feedback report. TRIAL REGISTRATION:ClinicalTrials.gov NCT03124316; https://clinicaltrials.gov/ct2/show/NCT03124316 (Archived by WebCite at http://www.webcitation.org/6w2MqDWGu).

Project description:IntroductionThe extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring.ObjectiveThe aim of the study was to investigate the feasibility of linked primary and secondary care electronic health record data for surveillance of medication safety, examining not only prescribing but also monitoring, and associations with patient- and general practice-level characteristics.MethodsA cross-sectional study was conducted using linked records of patients served by one hospital and over 50 general practices in Salford, UK. Statistical analysis consisted of mixed-effects logistic models, relating prescribing safety indicators to potential determinants.ResultsThe overall prevalence (proportion of patients with at least one medication safety hazard) was 5.45 % for prescribing indicators and 7.65 % for monitoring indicators. Older patients and those on multiple medications were at higher risk of prescribing hazards, but at lower risk of missed monitoring. The odds of missed monitoring among all patients were 25 % less for males, 50 % less for patients in practices that provide general practitioner training, and threefold higher in practices serving the most deprived compared with the least deprived areas. Practices with more prescribing hazards did not tend to show more monitoring issues.ConclusionsSystematic collection, collation, and analysis of linked primary and secondary care records produce plausible and useful information about medication safety for a health system. Medication safety surveillance systems should pay close attention to patient age and polypharmacy with respect to both prescribing and monitoring failures; treat prescribing and monitoring as different statistical processes, rather than a combined measure of prescribing safety; and audit the socio-economic equity of missed monitoring.

Project description:BACKGROUND:An estimated 8.2 million adults in the United States live with co-occurring mental health and substance use disorders. Although the benefits of integrated treatment services for persons with co-occurring disorders has been well-established, gaps in access to integrated care persist. Implementation research can address this gap. We evaluated if the Network for the Improvement of Addiction Treatment (NIATx) implementation strategy was effective in increasing integrated services capacity among organizations treating persons with co-occurring disorders. METHODS:This study employed a cluster randomized waitlist control group design. Forty-nine addiction treatment organizations from the State of Washington were randomized into one of two study arms: (1) NIATx strategy (active implementation strategy), or (2) waitlist (control). The primary outcome was a standardized organizational measure of integrated service capability: the Dual Diagnosis in Addiction Treatment (DDCAT) Index. Intent-to-treat analyses and per-protocol analyses were conducted to address the following questions: (1) Is NIATx effective in increasing integrated service capacity? and (2) Are there differences in organizations that actually use NIATx per-protocol versus those that do not? RESULTS:From baseline to one-year post active implementation, both the NIATx strategy and waitlist arms demonstrated improvements over time in DDCAT Index total and DDCAT dimension scores. In intent-to-treat analyses, a moderate but statistically significant difference in improvement between study arms was seen only in the Program Milieu dimension (p =?0.020, Cohen's d?=?0.54). In per-protocol analyses, moderate-to-large effects in Program Milieu (p =?0.002, Cohen's d?=?0.91) and Continuity of Care (p =?0.026, Cohen's d?=?0.63) dimensions, and in total DDCAT Index (p =?0.046, Cohen's d?=?0.51) were found. CONCLUSIONS:Overall, organizations in both study arms improved DDCAT Index scores over time. Organizations in the NIATx strategy arm with full adherence to the NIATx protocol had significantly greater improvements in the primary outcome measure of integrated service capacity for persons with co-occurring disorders. TRAIL REGISTRATION:ClinicalTrials.gov, NCT03007940 . Retrospectively registered January 2017.

Project description: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.