Pdf using collaborative learning to improve diabetes care and outcomes

Posted on Wednesday, May 12, 2021 12:19:13 AM Posted by Ibi C. - 12.05.2021 and pdf, manual pdf 4 Comments

pdf using collaborative learning to improve diabetes care and outcomes

File Name: using collaborative learning to improve diabetes care and outcomes.zip

Size: 1416Kb

Published: 12.05.2021

No overall standardized mean difference SMD was calculated because of the differences between the baseline HbA 1c groups. Characteristics of the Studies Not Included in the Meta-analysis.

Short- and long-term effects of a quality improvement collaborative on diabetes management

No overall standardized mean difference SMD was calculated because of the differences between the baseline HbA 1c groups. Characteristics of the Studies Not Included in the Meta-analysis. Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response. Not all submitted comments are published. Please see our commenting policy for details. Primary care ICP was associated with reductions in HbA 1c regardless of baseline levels, but the greatest reductions were found with HbA 1c levels of 9 or higher. However, limited evidence exists regarding its association with patient outcomes.

A dual review was performed for screening and selection. Two dual review teams conducted independent data extraction with consensus.

Data were pooled using a random-effects model for meta-analyses and forest plots constructed to report standardized mean differences SMDs. For high heterogeneity I 2 , data were stratified by baseline level and by study design. Varied ICP features were reported.

However, the greatest reductions were found with HbA 1c levels of 9 or higher. The implementation of ICP in primary care may be associated with improvements in patient outcomes in diabetes and hypertension. Diabetes and hypertension are substantial causes of heart disease and stroke, which are leading causes of death in the US.

Although ICP is recognized as a central component of providing optimal primary care, to our knowledge, there is limited evidence of its role in patient-oriented health outcomes. Two systematic reviews reported conflicting results for ICP in patients with diabetes.

A previous scoping review examined the breadth of information on ICP in primary care and reported broad consequences associated with patient outcomes.

Conversely, 6 additional studies reported no differences in HbA 1c , and 3 reported no differences in BP. Non-English records, reviews, meta-analyses, drug trials, case studies, editorials, and news articles were excluded. To be included in the meta-analysis, the reported comparative data had to be sufficient to calculate a standardized mean difference SMD. For the present study, an ICP team was defined as a collaboration among individuals from at least 3 different health professions.

At least 1 member of the team needed to serve as the primary care professional bearing the authority to diagnose and initiate treatments. Results were limited to English and initially to publication years from January to ; this start year was selected to build on the previous scoping review A dual review process, having 2 teams of 2 reviewers, was used for study inclusion and data extraction using previously tested standardized forms to minimize variability.

Each reviewer independently screened articles and extracted data, then met to reconcile the differences by consensus. The SMD outcome measure that indicated the difference in effect between ICP and comparison was calculated for each study. Subsequently, the SMDs were pooled using a random-effects model, and a forest plot was constructed.

The I 2 , which measures the percent of variation owing to factors other than random variation, was used to determine whether excessive nonrandom variation was present. The studies were stratified by design RCT, prospective cohort, retrospective cohort, and pre-post studies , and the analysis was repeated to determine whether the SMD was associated with study design.

For HbA 1c , stratification by baseline HbA 1c was performed to identify associations of ICP with patient cohorts having varied diabetes control status. The meta-analysis process and data are shown in eMethods 2 in the Supplement. Because we included diverse study designs, the tools based on the framework of the Cochrane Collaboration recommendations for Effective Practice and Organization of Care were used. Each item was ranked low risk of bias, unclear, or high risk of bias.

A dual review was performed with consensus generation. We identified articles from the searches and articles from other sources. After removing duplicates, the review teams screened titles or abstracts then reviewed abstracts or full-texts to assess 63 articles for eligibility, including the 12 relevant articles from the previous scoping review 12 and 5 from the abbreviated search update to March Of these, 13 records were excluded for having 3 or fewer health professions or no usable outcome measures, leaving 50 articles retained in the systematic review.

A final 39 studies were included in the meta-analysis 24 - 62 after 11 studies were excluded because of inadequate data eTable in the Supplement. Characteristics of the 50 studies included in the systematic review are listed in Table 1. Of the 39 studies included in the meta-analyses, 15 were RCTs, 24 - 38 7 were prospective cohort trials, 39 - 45 1 was a retrospective cohort, 46 and 16 were pre-post studies.

Among the studies that reported patient age and sex, the mean age ranged from 51 to 70 years, and the percentage of male participants ranged from 0 to The team makeup varied widely from the number of professionals involved to types of professions included Similarly, interprofessional team function and intervention features reported by the included studies varied.

For group 1 mean baseline HbA 1c , 7. Given the substantial differences among these groups, no overall SMD was calculated. Heterogeneity was not associated with the number of professions involved in ICP; the correlation between the number of professions and decrease in HbA 1c was not significant.

The correlation of study duration and HbA 1c effects was also nonsignificant. However, the research design was confounded by baseline HbA 1c levels. The mean baseline HbA 1c level for the prospective cohort studies was 7. However, the SMD varied by study design. Nonetheless, when excluding the retrospective cohort study, there was no difference in the SMD between RCTs, pre-post studies, and prospective cohort studies.

The funnel plot eFigure 3 in the Supplement showed missing studies to the right of the mean. The fail-safe N was studies. The bias assessment for studies included in the meta-analyses are presented in Table 2. For SBP and DBP, important clinical measures of hypertension and cardiovascular status for diabetes, and negative studies, respectively, are needed to refute the effects of ICP. While previous research has assessed the association between team care and diabetes and hypertension outcomes, the latest search, to our knowledge, ended in in an RCT-only meta-analysis.

Yet, the findings from RCTs may lack real-life scenarios and patient behaviors in response to clinical interventions that more closely reflect everyday experience. Moreover, previous research included teams of at least 2 professionals in various settings, whereas we included ICPs of at least 3 health professions in primary care.

Among the 35 studies in the meta-analysis, 6 only 2 studies overlapped with the 39 studies included in our meta-analysis, 27 , 37 indicating differences in research scope. To strengthen the confidence to detect the directly aligned effects of ICP, we strictly adhered to the prespecified inclusion criteria and required the use of explicitly stated data from each study.

Therefore, in study selection, we excluded studies that did not clearly report involvement of at least 3 professions in primary care. For HbA 1c , baseline HbA 1c likely contributed to the heterogeneity, but significant heterogeneity remained within the HbA 1c groups. Study design may have been a factor in the heterogeneity, but it was difficult to assess for HbA 1c given the confounding by baseline HbA 1c levels.

Such differences may stem from studies with more control having the intervention group receive all aspects of the intervention, whereas less controlled studies may have missing intervention aspects or contaminated comparison groups. The number of professions included in the ICP teams did not seem to contribute to the heterogeneity.

The study duration also varied months , yet the association of study duration and HbA 1c was not significant. Hence, heterogeneity may be associated with factors that were not assessed in this meta-analysis, such as intervention dose-effect. Sources of variation were also likely due to differences in sample size and population, setting, and possible publication bias.

Sample size may have similar effects as the study design; for example, smaller studies may be easier to control than very large studies. Simultaneously, studies with a small sample size may have been underpowered to detect the intervention effect, and biased selection may have taken place.

There was a varying degree of diabetes control among the participants indicated by baseline HbA 1c levels, which may mean that the source populations were varied. Although the mean age ranged from 51 to 70 years, only 2 studies reported a mean age greater than 65 years.

While all ICP teams delivered primary care 18 in the US and 21 elsewhere , study settings varied from ambulatory care clinics to community health centers, public health centers, Veterans Affairs health systems. Publication bias, which can also be a factor in variation among included studies, was found to be likely for HbA 1c and SBP. Similar to previous findings, 21 , 75 , 76 we uncovered inconsistencies among the number and types of professionals involved in ICP, how the team functioned, and types of interventions delivered.

The number of professions ranged from 3 to 10, which suggests differing interventions delivered by diverse expertise.

The focus of our study, however, was to assess ICP and not the addition of specific health care professionals. The secondary analysis showed no association between the number of professions in ICP and HbA 1c reduction. With such diversity, identifying an ideal team feature and function for effectiveness and efficiency, perhaps tailored to patient risk, may be an appropriate future research area. This study has limitations. No determination of differences in the source population was evaluated, such as educational level that may be a factor in medication adherence, lifestyle modifications that can affect outcomes, or insurance information that may reveal socioeconomic status.

Neither the degree of integration among team members in primary care nor the intervention intensity was clearly specified in most studies. Study funding sources were also not considered.

Despite these limitations, we assessed an ample number of studies that used the equivalent outcome measures. Worldwide, health care is transforming rapidly, with team-based care suggested for diverse patients.

Concurrently, aging populations with chronic conditions may overwhelm primary care systems. ICP appears to be a plausible option for areas with limited access to care and in patients with poorer diabetes control. Using our findings, primary care practices may wish to consider providing ICP involving at least 3 professions to improve diabetes and hypertension outcomes.

The results of this systematic review and meta-analysis suggest that there is a positive association of ICP in primary care with HbA 1c , SBP, and DBP levels in adult patients with diabetes or hypertension. Published: February 12, Corresponding Author: Jeannie K. Author Contributions: Drs Lee and Slack had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Critical revision of the manuscript for important intellectual content: Lee, McCutcheon, Cooley, Slack. No other disclosures were reported. Our website uses cookies to enhance your experience.

Download PDF Comment.

Association of a Multisite Interprofessional Education Initiative With Quality of Primary Care

Sensitivity analysis 2 was conducted at 3 sites that divided their resident clinicians into 2 groups, some who participated in the CoEPCE initiative and some who did not. Measures of high-risk medication use and hemoglobin A 1c HbA 1c control have been reversed so that the direction that favors intervention vs comparison is consistent across all measures. ACSC indicates ambulatory care—sensitive condition. Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued. If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Primary healthcare PHC quality improvement QI initiatives are designed to improve patient care and health outcomes. This manuscript highlights the impact of QIIP on diabetes outcomes and associated vascular risk factors. A cluster matched-control, retrospective prechart and postchart audit was conducted. Eligible charts were reviewed for prespecified type 2 diabetes mellitus clinical process and outcome data at baseline, during intervention range: 15— Primary outcome measures were the A1c of patients above study target and proportion of patients with an annual foot exam.

CARIDIAB—Guiding and supporting national quality improvement initiatives for diabetes in less well-served parts of the world: a proof-of-concept project in the Caribbean. Lucia, Suriname, and Trinidad and Tobago. Project Objective: Achieve real and sustained improvement in the quality of diabetes care and outcomes in 10 Caribbean countries. While acknowledging the scarcity of resources for diabetes care in less developed parts of the world, there are interventions for the prevention of diabetes-related complications that are both highly cost-effective and feasible in such settings, including moderate blood glucose and blood pressure control and foot care. There is much evidence to show, however, that such interventions are at best poorly implemented.


Using collaborative learning to improve diabetes care and outcomes: The measure. Results: The proportion of people with good glycemic control (A1c<7%) among those in as a patient manual entitled “How to Treat My Diabetes” [12].


Short- and long-term effects of a quality improvement collaborative on diabetes management

The annual Learning Days conference brings together more than health care providers, public health professionals and community partners to exchange information, advance health transformation, and build relationships. Close to people braved the weather for a day of networking and collaborative learning at Learning Days on April at the University of Minnesota Continuing Education and Conference Center in St. Check out the links below for meeting illustrations, photos, information on the Health Care Homes Innovation Awards, and downloadable copies of the Learning Days presentations. Conference Program PDF. Resource navigators are proficient in the languages and cultures of their patients and families, which helps to establish open communication and trust.

CARIDIAB: Caribbean Diabetes Project

This study examined the short- and long-term effects of a quality improvement collaborative on patient outcomes, professional performance, and structural aspects of chronic care management of type 2 diabetes in an integrated care setting. Controlled pre- and post-intervention study assessing patient outcomes hemoglobin A1c, cholesterol, blood pressure, weight, blood lipid levels, and smoking status , professional performance guideline adherence , and structural aspects of chronic care management from baseline up to 24 months. Analyses were based on 1, patients with diabetes in six intervention and nine control regions representing 37 general practices and 13 outpatient clinics.

COMMENT 4

  • Results were adjusted for the clustering of patients within practices and baseline measure. Results: The proportion of people with good glycemic. Tempeste P. - 15.05.2021 at 19:02
  • Thank you for visiting nature. Laurence C. - 16.05.2021 at 02:25
  • Cooper, K. Avenall J. - 20.05.2021 at 02:05
  • Using collaborative learning to improve diabetes care and outcomes: The VIDA project as well as a patient manual entitled “How to Treat My Diabetes” [12]. Herodes T. - 20.05.2021 at 18:14

LEAVE A COMMENT