Key messages
- Quality improvement programmes can improve diabetes care, especially when multiple strategies are used in combination.
- Strategies used in these programmes that lead to the largest improvements in key outcomes in people with diabetes are: case management, team changes, patient education and promotion of self-management.
Why is improving diabetes care important?
Diabetes, a disorder of how sugar is managed by the body, can lead to complications such as heart disease and blindness. If people with diabetes get the best possible treatment, their risk for these and other diabetes-related complications will be lowered. Unfortunately, many people with diabetes do not get the best possible treatment.
What are quality improvement strategies?
Quality improvement programmes using different strategies help healthcare professionals improve care. We examined 12 common types of quality improvement strategies.
- Four strategies were directed at healthcare professionals: audit and feedback, clinician education, clinician reminders and financial incentives.
- Three strategies were directed at people living with diabetes: patient education, patient reminders and promotion of self-management.
- Five strategies involved healthcare organisations: case management, team changes, electronic patient registry, facilitated relay of clinical information and continuous quality improvement.
What did we want to find out?
We wanted to find out which strategies worked best to improve:
- blood sugar control (measured using a test called glycated haemoglobin or HbA1c);
- blood pressure;
- low-density lipoprotein cholesterol (LDL-C).
Lower levels on these tests are associated with lower rates of complications such as heart attacks.
We also assessed whether quality improvement strategies improved rates of screening for eye damage (also known as retinopathy) and loss of sensation in the foot (also known as neuropathy). Routine screening for these issues in people living with diabetes is recommended to prevent blindness or amputation, respectively.
What did we do?
We searched for randomised trials including adults living with diabetes managed in outpatient settings, which evaluated at least one quality improvement strategy. Although we were interested in strategies directed at people living with diabetes, patient strategies needed to be tested in combination with strategies directed at healthcare organisations or professionals for the study to be included. We summarised the results of the studies and rated our confidence in the evidence, based on factors such as study methods, size and other considerations.
What did we find?
We found 553 studies that involved 412,161 people with diabetes up to the year 2019. Studies took place in countries around the world with most being conducted in the USA (231) and in medical settings.
Most studies (367) involved people with type 2 diabetes. Half of the study participants were female. The average age of participants was 57 years. Most studies lasted 12 months.
Studies usually used multiple quality improvement strategies together. Most commonly, studies featured three quality improvement strategies.
Main results
Overall, case management, team changes, patient education and promotion of self-management appeared to be the most effective quality improvement strategies for diabetes care.
When considering three-strategy combinations (the median number of quality improvement strategies in multicomponent interventions), the combination of clinician education, promotion of self-management and patient reminders may lead to the most improvement in blood sugar control in people who begin with lower HbA1c. Whereas the combination of case management, patient education and electronic patient registries may lead to the largest improvement in blood sugar control for people who begin with higher HbA1c.
For blood pressure, people who have lower systolic blood pressure may see the most improvement with the combination of patient education, team changes and promotion of self-management. People who have higher systolic blood pressure may improve the most with the combination of case management, team changes and promotion of self-management.
For cholesterol, we found that team changes, patient education and case management may lead to the most improvement in people who already have lower low-density lipoprotein levels. For those who have higher levels of low-density lipoprotein, team changes, case management and clinician reminders may lead to the largest improvement.
Patient education, patient reminders and team changes may lead to an increase in retinopathy screening rates. Patient education, team changes and audit and feedback, financial incentives and continuous quality improvement strategies combined may lead to an increase in foot screening rates.
What does this mean?
Clinics can improve their diabetes care by engaging in quality improvement programmes (especially those including case management, team changes, patient education and patient self-management).
What are the limitations of the evidence?
Many studies did not provide information on everything we were interested in. Most focused on blood sugar control and few studies reported screening rates. We included studies in this review that had important flaws in the way they were conducted, which limits how confident we can be in our findings.
How up-to-date is this evidence?
The evidence for this review is up-to-date to June 2019, and we have further searched for and screened studies up to September 2021. We are currently working on a living systematic review that will be updated with new evidence at least once a year.
There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.
There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations.
To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care.
We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section.
We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy.
- System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI).
- Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI).
- Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy.
We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.
Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available.
We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.
Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.
Combinations of the three most effective QI strategies were estimated to lead to the below effects:
- PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%;
- CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;
- PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg;
- CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;
- TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL;
- TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL.
Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other).