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

Overview of attention for article published in Cochrane database of systematic reviews, November 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
3 news outlets
blogs
3 blogs
twitter
475 tweeters
facebook
12 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
93 Dimensions

Readers on

mendeley
609 Mendeley
citeulike
1 CiteULike
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Title
Non-medical prescribing versus medical prescribing for acute and chronic disease management in primary and secondary care
Published in
Cochrane database of systematic reviews, November 2016
DOI 10.1002/14651858.cd011227.pub2
Pubmed ID
Authors

Greg Weeks, Johnson George, Katie Maclure, Derek Stewart

Abstract

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. 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). 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. 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. 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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 475 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 609 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Spain 1 <1%
Unknown 606 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 127 21%
Student > Ph. D. Student 78 13%
Student > Bachelor 71 12%
Researcher 65 11%
Student > Postgraduate 40 7%
Other 128 21%
Unknown 100 16%
Readers by discipline Count As %
Medicine and Dentistry 159 26%
Nursing and Health Professions 139 23%
Pharmacology, Toxicology and Pharmaceutical Science 45 7%
Social Sciences 41 7%
Psychology 26 4%
Other 71 12%
Unknown 128 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 378. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 April 2020.
All research outputs
#39,542
of 16,056,369 outputs
Outputs from Cochrane database of systematic reviews
#76
of 11,375 outputs
Outputs of similar age
#1,883
of 391,304 outputs
Outputs of similar age from Cochrane database of systematic reviews
#2
of 158 outputs
Altmetric has tracked 16,056,369 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,375 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.8. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 391,304 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.