Dataset Information

Theory-based approach to developing an implementation plan to support the adoption of a patient decision aid for Down syndrome prenatal screening.

ABSTRACT:

Background

Our team has developed a decision aid to help pregnant women and their partners make informed decisions about Down syndrome prenatal screening. However, the decision aid is not yet widely available in Quebec's prenatal care pathways.

Objective

We sought to identify knowledge translation strategies and develop an implementation plan to promote the use of the decision aid in prenatal care services in Quebec, Canada.

Methods

Guided by the Knowledge-to-Action Framework and the Theoretical Domains Framework, we performed a synthesis of our research (11 publications) on prenatal screening in Quebec and on the decision aid. Two authors independently reviewed the 11 articles, extracted information, and mapped it onto the Knowledge-to-Action framework. Using participatory action research methods, we then recruited pregnant women, health professionals, managers of three prenatal care services, and researchers to (a) identify the different clinical pathways followed by pregnant women and (b) select knowledge translation strategies for a clinical implementation plan. Then, based on all the information gathered, the authors established a consensus on strategies to include in the plan.

Results

Our knowledge synthesis showed that pregnant women and their partners are not sufficiently involved in the decision-making process about prenatal screening and that there are numerous barriers and facilitators of the use of the decision aid in clinical practice (e.g., low intention to use it among health providers). Using a participatory action approach, we met with five pregnant women, three managers, and six health professionals. They informed us about three of Quebec's prenatal care pathways and helped us identify 20 knowledge translation strategies (e.g., nurse discusses decision aid with women before they meet the doctor) to include in a clinical implementation plan. The research team reached a consensus about the clinical plan and also about broader organizational strategies, such as training healthcare providers in the use of the decision aid, monitoring its impact (e.g., measure decisional conflict) and sustaining its use (e.g., engage key stakeholders in the implementation process).

Conclusion

Next steps are to pilot our implementation plan while further identifying global strategies that target institutional, policy, and systemic supports for implementation.

SUBMITTER: Agbadje TT

PROVIDER: S-EPMC8152135 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundElectronic health record (EHR)-based clinical decision support tools can improve the use of evidence-based clinical guidelines for preeclampsia management that can reduce maternal mortality and morbidity. No study has investigated the organizational capabilities that enable hospitals to use EHR-based decision support tools to manage preeclampsia.ObjectiveTo examine the association of organizational capabilities and hospital adoption of EHR-based decision support tools for preeclampsia management.MethodsCross-sectional analyses of hospitals providing obstetric care in 2017. In total, 739 hospitals responded to the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS) and were linked to the 2017 American Hospital Association (AHA) Annual Survey Database and the Area Health Resources File (AHRF). A total of 425 hospitals providing obstetric care across 49 states were included in the analysis. The main outcome was whether a hospital adopted EHR-based clinical decision support tools for preeclampsia management. Hospital organizational capabilities assessed as predictors include EHR functions, adoption of evidence-based clinical treatments, use of quality improvement methods, and dissemination processes to share best patient care practices. Logistic regression estimated the association of hospital organizational capabilities and hospital adoption of EHR-based decision support tools to manage preeclampsia, controlling for hospital structural and patient sociodemographic characteristics.ResultsTwo-thirds of the hospitals (68%) adopted EHR-based decision support tools for preeclampsia, and slightly more than half (56%) of hospitals had a single EHR system. Multivariable regression results indicate that hospitals with a single EHR system were more likely to adopt EHR-based decision support tools for preeclampsia (17.4 percentage points; 95% CI, 1.9 to 33.0; P < .05) than hospitals with a mixture of EHR and paper-based systems. Compared with hospitals having multiple EHRs, on average, hospitals having a single EHR were also more likely to adopt the tools by 9.3 percentage points, but the difference was not statistically significant (95% CI, -1.3 to 19.9). Hospitals with more processes to aid dissemination of best patient care practices were also more likely to adopt EHR-based decision-support tools for preeclampsia (0.4 percentage points; 95% CI, 0.1 to 0.6, for every 1-unit increase in dissemination processes; P < .01).ConclusionStandardized EHRs and policies to disseminate evidence are foundational hospital capabilities that can help advance the use of EHR-based decision support tools for preeclampsia management in the approximately one-third of US hospitals that still do not use them.

Project description:BackgroundRecent studies have shown substantial deficiencies in the quality or quantity (or both) of communication and decision-making during serious illness. We evaluated the efficacy of a novel decision support intervention, the Plan Well Guide, in increasing completion of a standard medical order form for advance medical care planning and improving decisional outcomes in nonacademic primary care settings.MethodsWe conducted a randomized trial in 3 primary care practices in Lethbridge, Alberta in 2017-2018. We recruited "patients at high risk" referred by the primary care doctor who required establishment or review of their Goals of Care Designation (GCD). Enrolled patients were randomly allocated to receive the Plan Well Guide, delivered by a trained facilitator, or usual care. Eight to 12 weeks after the intervention, a research assistant blinded to intervention assignment contacted the patients in both groups by telephone to do a final outcome assessment. The primary outcome was completion of GCD forms; secondary outcomes included decisional conflict scores and ratings of satisfaction.ResultsA total of 123 patients (59 women [48.0%]; mean age 73.9 yr) were enrolled, 66 in the intervention arm and 57 in the usualcare arm; 119 patients completed the trial. After the intervention, GCD completion rates in the intervention and usual-care groups were 95.3% and 90.9%, respectively (risk difference [RD] 4%, 95% confidence interval [CI] -14% to 22%), and the rate of concordance between medical orders and expressed preferences on follow-up was 78% and 66%, respectively (RD 12%, 95% CI -7% to 30%). Significantly fewer patients in the intervention group than in the usual-care group had written medical orders for intensive care unit care and cardiopulmonary resuscitation (22 [34%] v. 33 [60%], RD -26%, 95% CI -42% to -8%). Patients in the intervention group had lower decisional conflict scores than those in the usual-care group (mean 30.9 v. 43.1, adjusted mean difference -12.0, 95% CI -23.2 to -0.8). Physicians considered patients in the intervention group to have lower decisional conflict than those in the usual-care group, although not significantly so (mean score 10.4 v. 14.9, adjusted mean difference -4.7, 95% CI -9.9 to 0.4) and spent less time with the former (mean 9.7 v. 13.2 min, adjusted mean difference -3.5, 95% CI -5.5 to -1.5 min).InterpretationThe decision-support intervention did not increase GCD completion rates but did seem to improve some aspects of decisional quality while reducing the physician's time to accomplish GCD decisions. Trial registration: ClinicalTrials.gov, no. NCT01297946.

Project description:BackgroundExploring barriers to the uptake of research based recommendations into practice is an important part of the development of implementation programmes. Techniques to identify barriers can include use of theory-informed questionnaires and qualitative interviews. Conceptualising and measuring theory-informed factors, and engaging health professionals' to uncover all potential barriers, can be a difficult task. This paper presents a case study of the process of trying to identify, systematically, the key factors influencing health professionals' referrals for women diagnosed with mild to moderate postnatal depression for psychological treatment. The paper illustrates how the factors were conceptualised and measured and explores the real world challenges experienced, with implications for future implementation studies.MethodsTheory-informed factors were conceptualised and measured using a questionnaire and interviews. The questionnaire was piloted, before being administered to general practitioners, practice nurses and health visitors working in general practices in one area of the UK NHS. The interviews were conducted with a small sample of general practitioners who had not completed the questionnaire, further exploring factors influencing their referral decisions in the local context.ResultsThe response rate to the questionnaire was low (19%), despite selecting the recommendation to target through engagement with local stakeholders and surveying local health professionals, and despite using two reminders, an incentive prize, and phone calls to practice managers to bolster response rates.ConclusionsTwo significant challenges to achieving higher response rates and successfully exploring local context were identified: the difficulties of developing a robust- but feasible- questionnaire to explore theory-informed factors, and targeting recommendations that are important to policy makers, but which health professionals view as unimportant. This case study highlights the "trade-off" between scientifically rigorous collection of data against the pragmatism and flexibility requirements of "real world" implementation. Future implementation studies should explore different ways of identifying factors influencing the adoption of recommendations to bridge this gulf.

Project description:ObjectivesUsing strong structuration theory, we aimed to understand the adoption and implementation of an electronic clinical audit and feedback tool to support medicine optimisation for patients in primary care.DesignThis is a qualitative study informed by strong structuration theory. The analysis was thematic, using a template approach. An a priori set of thematic codes, based on strong structuration theory, was developed from the literature and applied to the transcripts. The coding template was then modified through successive readings of the data.SettingClinical commissioning group in the south of England.ParticipantsFour focus groups and five semi-structured interviews were conducted with 18 participants purposively sampled from a range of stakeholder groups (general practitioners, pharmacists, patients and commissioners).ResultsUsing the system could lead to improved medication safety, but use was determined by broad institutional contexts; by the perceptions, dispositions and skills of users; and by the structures embedded within the technology. These included perceptions of the system as new and requiring technical competence and skill; the adoption of the system for information gathering; and interactions and relationships that involved individual, shared or collective use. The dynamics between these external, internal and technological structures affected the adoption and implementation of the system.ConclusionsSuccessful implementation of information technology interventions for medicine optimisation will depend on a combination of the infrastructure within primary care, social structures embedded in the technology and the conventions, norms and dispositions of those utilising it. Future interventions, using electronic audit and feedback tools to improve medication safety, should consider the complexity of the social and organisational contexts and how internal and external structures can affect the use of the technology in order to support effective implementation.