An intensive nurse-led, multi-interventional clinic is more successful in achieving vascular risk reduction targets than standard diabetes care

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

BACKGROUND

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.

OBJECTIVES

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.

SEARCH METHODS

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.

SELECTION CRITERIA

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.

DATA COLLECTION AND ANALYSIS

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.

MAIN RESULTS

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).

AUTHORS' CONCLUSIONS

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.

Leveraging Registered Dietitian Nutritionists and Registered Nurses in Medication Management to Reduce Therapeutic Inertia

Objective

To conduct a systematic review of studies that used registered dietitian nutritionists (RDNs) or registered nurses (RNs) to deliver pharmacological therapy using protocols for diabetes, dyslipidemia, or hypertension.

Research Design and Methods

A database search of PubMed, the Cochrane Central Register of Controlled Trials, Ovid, and the Cumulative Index to Nursing and Allied Health Literature was conducted of literature published from 1 January 2000 to 31 December 2019.

Results

Twenty studies met the inclusion criteria, representing randomized controlled trials (12), retrospective (1) and prospective cohort design studies (6), and time series (1). In all, the studies include 7,280 participants with a median study duration of 12 months (range 6-25 months). Fifteen studies were led by RNs alone, two by RDNs, and three by a combination of RDNs and RNs. All demonstrated improvements in A1C, blood pressure, or lipids. Thirteen studies provided a lifestyle behavior change component in addition to medication protocols.

Conclusion

This systematic review provides evidence that RDN- and RN-led medication management using physician-approved protocols or treatment algorithms can lead to clinically significant improvements in diabetes, dyslipidemia, and hypertension management and is as good or better than usual care.

Impacts of nurse-led clinic and nurse-led prescription on hemoglobin A1c control in type 2 diabetes: A meta-analysis

BACKGROUND

To evaluate the impacts of nurse-led clinic and nurse-led prescription on hemoglobin A1c (HbA1c) control in type 2 diabetes.

METHODS

We searched relevant publications in English and Chinese database and conducted meta-analysis by Stata 12.0. We divided the case groups of included studies into 2 categories according to the role of nurse: nurse-led clinic and nurse-led prescription. Nurse-led clinic was implemented on the basis of standard diabetes care provided by doctor, and control group also receive the standard diabetes care but without nurse-led clinic. The doctor mentioned above might work alone or in a health care team. Nurse-led prescription was prescribed by nurse independently and compared with that of doctor.

RESULTS

The meta-analysis shown that, compared with the standard diabetes care, nurse-led clinic significantly decreases HbA1c level (standard mean difference [SMD] = -0.767; 95% confidence interval [CI]: -1.062, -0.471; P < .001). In subgroup analysis, nurse-led clinic also had positive impacts on controlling HbA1c level, no matter in developed countries (SMD = -0.353; 95% CI: -0.6, -0.106; P = .005) or developing countries (SMD = -1.114; 95% CI: -1.498, -0.73; P < .001). Additionally, there was no significant difference between nurse-led prescription and doctor prescription in controlling HbA1c levels (SMD = -0.203; 95% CI: -0.434, 0.029; P = .086).

CONCLUSION

The nurse-led clinic had positive significance for HbA1c control. Meanwhile, the impact of nurse-led prescription on controlling HbA1c is comparable to that of doctor. It is valuable to provide nurse-led clinic on the basis of standard diabetes care provided by doctor to better control HbA1c, and nurse-led prescription should be provided when doctor-led service is limited.

Non-medical prescribing versus medical prescribing for acute and chronic disease management in primary and secondary care

BACKGROUND

A range of health workforce strategies are needed to address health service demands in low-, middle- and high-income countries. Non-medical prescribing involves nurses, pharmacists, allied health professionals, and physician assistants substituting for doctors in a prescribing role, and this is one approach to improve access to medicines.

OBJECTIVES

To assess clinical, patient-reported, and resource use outcomes of non-medical prescribing for managing acute and chronic health conditions in primary and secondary care settings compared with medical prescribing (usual care).

SEARCH METHODS

We searched databases including CENTRAL, MEDLINE, Embase, and five other databases on 19 July 2016. We also searched the grey literature and handsearched bibliographies of relevant papers and publications.

SELECTION CRITERIA

Randomised controlled trials (RCTs), cluster-RCTs, controlled before-and-after (CBA) studies (with at least two intervention and two control sites) and interrupted time series analysis (with at least three observations before and after the intervention) comparing: 1. non-medical prescribing versus medical prescribing in acute care; 2. non-medical prescribing versus medical prescribing in chronic care; 3. non-medical prescribing versus medical prescribing in secondary care; 4 non-medical prescribing versus medical prescribing in primary care; 5. comparisons between different non-medical prescriber groups; and 6. non-medical healthcare providers with formal prescribing training versus those without formal prescribing training.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. Two review authors independently reviewed studies for inclusion, extracted data, and assessed study quality with discrepancies resolved by discussion. Two review authors independently assessed risk of bias for the included studies according to EPOC criteria. We undertook meta-analyses using the fixed-effect model where studies were examining the same treatment effect and to account for small sample sizes. We compared outcomes to a random-effects model where clinical or statistical heterogeneity existed.

MAIN RESULTS

We included 46 studies (37,337 participants); non-medical prescribing was undertaken by nurses in 26 studies and pharmacists in 20 studies. In 45 studies non-medical prescribing as a component of care was compared with usual care medical prescribing. A further study compared nurse prescribing supported by guidelines with usual nurse prescribing care. No studies were found with non-medical prescribing being undertaken by other health professionals. The education requirement for non-medical prescribing varied with country and location.A meta-analysis of surrogate markers of chronic disease (systolic blood pressure, glycated haemoglobin, and low-density lipoprotein) showed positive intervention group effects. There was a moderate-certainty of evidence for studies of blood pressure at 12 months (mean difference (MD) -5.31 mmHg, 95% confidence interval (CI) -6.46 to -4.16; 12 studies, 4229 participants) and low-density lipoprotein (MD -0.21, 95% CI -0.29 to -0.14; 7 studies, 1469 participants); we downgraded the certainty of evidence from high due to considerations of serious inconsistency (considerable heterogeneity), multifaceted interventions, and variable prescribing autonomy. A high-certainty of evidence existed for comparative studies of glycated haemoglobin management at 12 months (MD -0.62, 95% CI -0.85 to -0.38; 6 studies, 775 participants). While there appeared little difference in medication adherence across studies, a meta-analysis of continuous outcome data from four studies showed an effect favouring patient adherence in the non-medical prescribing group (MD 0.15, 95% CI 0.00 to 0.30; 4 studies, 700 participants). We downgraded the certainty of evidence for adherence to moderate due to the serious risk of performance bias. While little difference was seen in patient-related adverse events between treatment groups, we downgraded the certainty of evidence to low due to indirectness, as the range of adverse events may not be related to the intervention and selective reporting failed to adequately report adverse events in many studies.Patients were generally satisfied with non-medical prescriber care (14 studies, 7514 participants). We downgraded the certainty of evidence from high to moderate due to indirectness, in that satisfaction with the prescribing component of care was only addressed in one study, and there was variability of satisfaction measures with little use of validated tools. A meta-analysis of health-related quality of life scores (SF-12 and SF-36) found a difference favouring usual care for the physical component score (MD 1.17, 95% CI 0.16 to 2.17), but not the mental component score (MD 0.58, 95% CI -0.40 to 1.55). However, the quality of life measurement may more appropriately reflect composite care rather than the prescribing component of care, and for this reason we downgraded the certainty of evidence to moderate due to indirectness of the measure of effect. A wide variety of resource use measures were reported across studies with little difference between groups for hospitalisations, emergency department visits, and outpatient visits. In the majority of studies reporting medication use, non-medical prescribers prescribed more drugs, intensified drug doses, and used a greater variety of drugs compared to usual care medical prescribers.The risk of bias across studies was generally low for selection bias (random sequence generation), detection bias (blinding of outcome assessment), attrition bias (incomplete outcome data), and reporting bias (selective reporting). There was an unclear risk of selection bias (allocation concealment) and for other biases. A high risk of performance bias (blinding of participants and personnel) existed.

AUTHORS' CONCLUSIONS

The findings suggest that non-medical prescribers, practising with varying but high levels of prescribing autonomy, in a range of settings, were as effective as usual care medical prescribers. Non-medical prescribers can deliver comparable outcomes for systolic blood pressure, glycated haemoglobin, low-density lipoprotein, medication adherence, patient satisfaction, and health-related quality of life. It was difficult to determine the impact of non-medical prescribing compared to medical prescribing for adverse events and resource use outcomes due to the inconsistency and variability in reporting across studies. Future efforts should be directed towards more rigorous studies that can clearly identify the clinical, patient-reported, resource use, and economic outcomes of non-medical prescribing, in both high-income and low-income countries.

Nurses' Role in Cardiovascular Risk Assessment and Management in People with Inflammatory Arthritis: A European Perspective

INTRODUCTION

Cardiovascular risk (CVR) assessment and management in patients with inflammatory arthritis (IA) is recommended but European nurses' involvement in this role has not been well studied.

AIM

The aim of the present study was to explore European nurses' role in assessing and managing CVR, in order to suggest topics for practice development and research in this area regarding persons with IA.

METHODS

We searched Embase, Cinahl, Cochrane, PsycInfo and PubMed databases and included European articles from the past ten years if they described how nurses assess and/or manage CVR. In addition to the systematic review, we provided case studies from five different countries to illustrate national guidelines and nurses' role regarding CVR assessment and management in patients with IA.

RESULTS

Thirty-three articles were included. We found that trained nurses were undertaking CVR assessment and management in different settings and groups of patients. The assessments include blood pressure, body mass index, waist circumference, glucose and lipid-profile, adherence to medication and behavioural risk factors (unhealthy diet, physical inactivity, alcohol and smoking). Different tools were used to calculate patients' risk. Risk management differed from brief advice to long-term follow-up. Nurses tended to take a holistic and individually tailored approach. Clinical examples of inclusion of rheumatology nurses in these tasks were scarce.

CONCLUSION

Nurses undertake CVR assessment, communication and management in different types of patients. This is considered to be a highly relevant task for rheumatology nursing, especially in patients with IA. Further studies are needed to assess patients' perspective, effectiveness and cost-effectiveness of nurse-led CVR. Copyright © 2015 John Wiley & Sons, Ltd.

WITHDRAWN: Targeting intensive glycaemic control versus targeting conventional glycaemic control for type 2 diabetes mellitus

The Cochrane Metabolic and Endocrine Disorders Group withdrew this review as of Issue 7, 2015 because the involvement of two authors (C Hemmingsen and SS Lund) being employed in pharmaceutical companies. The authors of the review and the Cochrane Metabolic and Endocrine Disorders Group did not find that this was a breach of the rules of the Cochrane Collaboration at the time when it was published. However, after the publication of the review, the Cochrane Collaboration requested withdrawal of the review due to the employment of the two authors. A new protocol for a review to cover this topic will be published. This will have a new title and a markedly improved protocol fulfilling new and important developments and standards within the Cochrane Collaboration as well as an improved inclusion and search strategy making it necessary to embark on a completely new review project.

The editorial group responsible for this previously published document have withdrawn it from publication.

Targeting intensive glycaemic control versus targeting conventional glycaemic control for type 2 diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2D) have an increased risk of cardiovascular disease and mortality compared to the background population. Observational studies report an association between reduced blood glucose and reduced risk of both micro- and macrovascular complications in patients with T2D. Our previous systematic review of intensive glycaemic control versus conventional glycaemic control was based on 20 randomised clinical trials that randomised 29 ,986 participants with T2D. We now report our updated review.

OBJECTIVES

To assess the effects of targeted intensive glycaemic control compared with conventional glycaemic control in patients with T2D.

SEARCH METHODS

Trials were obtained from searches of The Cochrane Library, MEDLINE, EMBASE, Science Citation Index Expanded, LILACS, and CINAHL (all until December 2012).

SELECTION CRITERIA

We included randomised clinical trials that prespecified targets of intensive glycaemic control versus conventional glycaemic control targets in adults with T2D.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed the risk of bias and extracted data. Dichotomous outcomes were assessed by risk ratios (RR) and 95% confidence intervals (CI). Health-related quality of life and costs of intervention were assessed with standardized mean differences (SMD) and 95% Cl.

MAIN RESULTS

Twenty-eight trials with 34,912 T2D participants randomised 18,717 participants to intensive glycaemic control versus 16,195 participants to conventional glycaemic control. Only two trials had low risk of bias on all risk of bias domains assessed. The duration of the intervention ranged from three days to 12.5 years. The number of participants in the included trials ranged from 20 to 11,140. There were no statistically significant differences between targeting intensive versus conventional glycaemic control for all-cause mortality (RR 1.00, 95% CI 0.92 to 1.08; 34,325 participants, 24 trials) or cardiovascular mortality (RR 1.06, 95% CI 0.94 to 1.21; 34,177 participants, 22 trials). Trial sequential analysis showed that a 10% relative risk reduction could be refuted for all-cause mortality. Targeting intensive glycaemic control did not show a statistically significant effect on the risks of macrovascular complications as a composite outcome in the random-effects model, but decreased the risks in the fixed-effect model (random RR 0.91, 95% CI 0.82 to 1.02; and fixed RR 0.93, 95% CI 0.87 to 0.99; P = 0.02; 32,846 participants, 14 trials). Targeting intensive versus conventional glycaemic control seemed to reduce the risks of non-fatal myocardial infarction (RR 0.87, 95% CI 0.77 to 0.98; P = 0.02; 30,417 participants, 14 trials), amputation of a lower extremity (RR 0.65, 95% CI 0.45 to 0.94; P = 0.02; 11,200 participants, 11 trials), as well as the risk of developing a composite outcome of microvascular diseases (RR 0.88, 95% CI 0.82 to 0.95; P = 0.0008; 25,927 participants, 6 trials), nephropathy (RR 0.75, 95% CI 0.59 to 0.95; P = 0.02; 28,096 participants, 11 trials), retinopathy (RR 0.79, 95% CI 0.68 to 0.92; P = 0.002; 10,300 participants, 9 trials), and the risk of retinal photocoagulation (RR 0.77, 95% CI 0.61 to 0.97; P = 0.03; 11,212 participants, 8 trials). No statistically significant effect of targeting intensive glucose control could be shown on non-fatal stroke, cardiac revascularization, or peripheral revascularization. Trial sequential analyses did not confirm a reduction of the risk of non-fatal myocardial infarction but confirmed a 10% relative risk reduction in favour of intensive glycaemic control on the composite outcome of microvascular diseases. For the remaining microvascular outcomes, trial sequential analyses could not establish firm evidence for a 10% relative risk reduction. Targeting intensive glycaemic control significantly increased the risk of mild hypoglycaemia, but substantial heterogeneity was present; severe hypoglycaemia (RR 2.18, 95% CI 1.53 to 3.11; 28,794 participants, 12 trials); and serious adverse events (RR 1.06, 95% CI 1.02 to 1.10; P = 0.007; 24,280 participants, 11 trials). Trial sequential analysis for a 10% relative risk increase showed firm evidence for mild hypoglycaemia and serious adverse events and a 30% relative risk increase for severe hypoglycaemia when targeting intensive versus conventional glycaemic control. Overall health-related quality of life, as well as the mental and the physical components of health-related quality of life did not show any statistical significant differences.

AUTHORS' CONCLUSIONS

Although we have been able to expand the number of participants by 16% in this update, we still find paucity of data on outcomes and the bias risk of the trials was mostly considered high. Targeting intensive glycaemic control compared with conventional glycaemic control did not show significant differences for all-cause mortality and cardiovascular mortality. Targeting intensive glycaemic control seemed to reduce the risk of microvascular complications, if we disregard the risks of bias, but increases the risk of hypoglycaemia and serious adverse events.