Nurse versus physician led care for the management of asthma
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
We aim to review the effectiveness of care provided by a specialized asthma nurse, nurse practitioner or physician assistant, working relatively independently from a physician, compared to traditional care provided by a physician. Our scope includes all outpatient care for asthma, both in primary care and hospital settings.
Background
Why it is important to do this review
Health economics are increasingly important and intelligent use of human resources is an important issue with regard to effective healthcare. Nurse led outpatient management may be provided at a lower cost than medical care by a physician.
Objectives
We aim to review the effectiveness of care provided by a specialized asthma nurse, nurse practitioner or physician assistant, working relatively independently from a physician, compared to traditional care provided by a physician. Our scope includes all outpatient care for asthma, both in primary care and hospital settings.
Methods
Criteria for considering studies for this review
Types of studies
All RCTs restricted to patients with asthma, comparing care led by other health professionals (specialized asthma nurse, nurse practitioner or physician assistant) with care provided by physicians.
Types of participants
Adults and children with the clinical diagnosis asthma, as defined by the authors of the study, reviewed on a regular basis in primary or in hospital care.
Types of interventions
Intervention
Any aspect of asthma management led by an allied health professional (specialized asthma nurse, nurse practitioner or physician assistant), supervised by a physician.
Control
The same aspect of asthma management provided by physicians.
Types of outcome measures
Effects of interventions will be assessed using three categories of outcomes where available: patient‐related, health economic and objective measures of lung function, airway reactivity and inflammation.
Primary outcomes
- Frequency of exacerbations (A)
- Asthma severity and symptoms: measured by validated asthma control questionnaires [such as ACQ (Juniper 1999; Juniper 2006) or Asthma Control Test (Schatz 2006)] (A)
- Healthcare costs; direct and indirect (B)
Secondary outcomes
A. Patient related variables
- Quality of life: measured by validated questionnaires (e.g. Asthma Quality of Life Questionnaire Juniper 1993)
- Symptom free days (as measured in symptom diaries)
- Patient satisfaction with care
- Quality of care: including
- patient knowledge of asthma and understanding of disease
- use of an action plan
- prescription of inhaled corticosteroids
- check of appropriate inhalation technique
- Compliance with medication
- Use of rescue medication
B. Health‐economics
- Absence from school/work due to asthma
- Hospital admissions
- Referrals from primary to hospital care
- Duration of consultation
- Evidence of stepping down therapy
C. Objective tests: lung function, airway reactivity, airway inflammation
- Airway hyperreactivity (including PD/PC20 methacholine/histamine)
- Forced expiratory volume in 1 second (FEV1)
- Peak expiratory flow rate (PEF)
Search methods for identification of studies
Electronic searches
We will identify trials from the Cochrane Airways Group Specialised Register of trials (CAGR), which is derived from systematic searches of bibliographic databases including the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL, AMED, and PsycINFO, and handsearching of respiratory journals and meeting abstracts (please see Appendix 1 for further details). All records in the CAGR coded as ‘asthma’ will be searched using the following terms:
nurse* or nursing* or allied*
We will also conduct additional searches of MEDLINE, EMBASE, CINAHL, CENTRAL, AMED and prospective trial registers (the WHO trial register and other registers listed in The Cochrane Handbook for Systematic Reviews of Intervetnions (section 6.2.3.1 Higgins 2011)) using the keywords: nurse or nursing or allied combined with Mesh terms and free text words for asthma, combined with the sensitive Cochrane RCT filter.
We will also conduct a search of ClinicalTrials.gov. We will search all databases from their inception to the present and there will be no restriction on language of publication.
Searching other resources
We will check reference lists of all primary studies and review articles for additional references.
Data collection and analysis
Selection of studies
Two of us (WvA, MCK) will independently assess all the potential studies we identify as a result of the search strategy on title and abstract for eligibility. Once agreement is obtained on studies to be considered for inclusion, we will retrieve full text articles. Two of us (WvA, MCK) will assess each study for inclusion, based on the pre‐defined criteria for study selection. Any disagreement will be resolved through discussion, if required, we will consult a third reviewer (AVV) to make a final decision.
Data extraction and management
We will develop and test a data extraction form before we independently extract data from included studies. MK will enter these in RevMan 5.1. In case of missing data, we will attempt to contact authors to confirm data for accuracy and completeness. We will extract the following characteristics of included studies:
Study design
- Randomisation method
- Follow up procedures and withdrawals
- Sample size
- Inclusion criteria
- Exclusion criteria
Demographic
- Age
- Gender
Clinical
- Asthma diagnosis
- Asthma severity
- Other medical diagnosis
Intervention
- Specialized asthma nurse led care
- Nurse practitioner led care
- Physician assistant led care
Control
- Physician led care
Outcomes
- Data on all outcomes as listed in the section Types of outcome measures
Assessment of risk of bias in included studies
Two of us (WvA, MCK) will independently assess the risk of bias for each study using the criteria outlined below and judge the risk of bias as high, low or unclear for the criteria listed below according to recommendations in The Handbook (Higgins 2011). Any disagreement will be resolved by discussion or by consulting a third assessor (AVV). Since it is not possible to blind nurses, physicians and participating patients in these studies these criteria will not be assessed but the potential impact of non‐blinding will be reflected in the discussion of the results.
The criteria assessed will be:
- Adequate sequence generation?
- Adequate allocation concealment?
- Adequate blinding of assessors?
- Incomplete outcome data adequately assessed?
- Free of suggestion of selective outcome reporting?
- Free of other bias?
Measures of treatment effect
We will calculate mean difference (MD) with 95% confidence intervals (CI) for continuous variables measured on identical metrics. In studies with a “non inferiority design” we will use MD and 95% CI. If parameters are non‐normally distributed, log transformation will be applied.
We will use Standardised Mean Difference (SMD) for the same continuous variables measured with different metrics.
For dichotomous outcomes, we will calculate the Risk Ratio (RR) and 95% CI.
When incorporating results from cluster randomised studies for continuous and dichotomous variables we will extract direct estimates of effect measures from an analysis that properly accounts for the cluster design and combined results from studies using the generic inverse variance (GIV) method in RevMan 5.1.
Dealing with missing data
We will contact investigators or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible.
Assessment of heterogeneity
We will asses heterogeneity by comparing clinical characteristics of the included studies such as type of patients, intervention, comparison and outcome measures. We will explore clinical homogeneity in the review. Based on this discussion we will decide whether pooling of results is sensible. We will initially assess statistical heterogeneity by visual inspection of the forest plots. We will apply the Chi‐squared test for homogeneity and calculate the I2 statistic. To increase the power of the test for homogeneity we will use a P value less than 0.1 for rejecting the null‐hypothesis of homogeneity. Interpretation of statistical heterogeneity is according to the recommendation of The Handbook (Higgins 2011), as follows:
- 0%‐40%: might not be important;
- 30% to 60%: may represent moderate heterogeneity;
- 50% to 90%: may represent substantial heterogeneity;
- 75% to 100%: considerable heterogeneity.
When interpreting the results of the test for heterogeneity and the I2 statistic, we will take into account the size of the studies that are included in the meta‐analysis.
Assessment of reporting biases
Where we suspect reporting bias, we will attempt to contact study authors asking them to provide missing outcome data. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results using a sensitivity analysis.
We will explore publication bias using visual inspection of a funnel plot, if 10 or more studies are incorporated into a meta‐analysis.
Data synthesis
If distinctive studies are sufficiently comparable in relation to subjects, interventions and outcome variables, we will combine data in a meta‐analysis. For continuous outcome variables we will calculate a mean difference (MD) or a weighted standardised mean difference (SMD) with 95% CI using the generic inverse variance method. For dichotomous outcomes, we will estimate a pooled RR using the Mantel‐Hensel method. We hypothesise that the individual studies that evaluated the effect of asthma management provided by an allied health professional may contain different real values per study for the effect and therefore we will combine the results using a random‐effects model. If statistical heterogeneity is observed (Chi‐squared: p‐value < 0.1 and I‐squared > 30%), we will explore factors, other than the predefined subgroups, that can explain heterogeneity such as clinical or methodological characteristics of studies.
Subgroup analysis and investigation of heterogeneity
We plan to carry out the following subgroup analyses
- Adults versus children
- Disease severity (using hospital admissions as a surrogate marker for disease severity)
- Doctor‐led clinics versus nurse‐led clinics versus nurse/doctor shared clinics
- Duration of intervention
Sensitivity analysis
We plan sensitivity analyses to test the robustness of the results based on the results of the risk of bias assessment. We will exclude studies according to the following categories: high risk of bias for allocation concealment, high risk of bias for assessor blinding or high risk of bias for incomplete follow‐up.
Summary of findings table
We will evaluate the quality of the body of evidence according to recommendations in The Handbook (Section 8.5 and Chapter 12, Higgins 2011), using GRADEpro software (Grade Working Group 2004) to generate a summary of findings table. We will use the most relevant outcomes (Asthma Control Status, Symptom Free Days, Number of Exacerbations, Quality of Life, Hospital admissions).
Results of RCTs are considered initially as ‘High Level’ evidence. The level of evidence may decrease (be downgraded) based on potential risk of bias of the included studies, indirectness of evidence, unexplained heterogeneity or inconsistency in results, imprecision of results or high probability of publication bias (Higgins 2011). The necessity to apply down grading will be evaluated according to table 12.2.d (Grade Working Group 2004; Higgins 2011)
- How Long Does Marijuana Stay in Your System. The Ultimate Guide
- Detox Drinks For Weed: What To Drink To Get Weed Out Of Your System
- How to use activated charcoal for THC detox
- How to get THC out of the system with exercise. Instructions
- 14 Safe And Natural Home Remedies for Weed Detox + BONUS
- Detox Shampoos That Work: Your Hair Drug Test Secret Weapon
- Do THC detox drinks really work?
- THC Detox Calculator: Discover how long THC and Delta-8 THC remain detectable in drug tests.
- THC Detox Guide. How To Get Weed Out Of Your System