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. 2017 Nov 13;73(6):1182–1195. doi: 10.1111/all.13337

Economic evidence for nonpharmacological asthma management interventions: A systematic review

C‐J Crossman‐Barnes 1,✉, A Peel 1, R Fong‐Soe‐Khioe 1, T Sach 1, A Wilson 1, G Barton 1
PMCID: PMC6033175  PMID: 29105788

Abstract

Asthma management, education and environmental interventions have been reported as cost‐effective in a previous review (Pharm Pract (Granada), 2014;12:493), but methods used to estimate costs and outcomes were not discussed in detail. This review updates the previous review by providing economic evidence on the cost‐effectiveness of studies identified after 2012, and a detailed assessment of the methods used in all identified studies. Twelve databases were searched from 1990 to January 2016, and studies included economic evaluations, asthma subjects and nonpharmacological interventions written in English. Sixty‐four studies were included. Of these, 15 were found in addition to the earlier review; 53% were rated fair in quality and 47% high. Education and self‐management interventions were the most cost‐effective, in line with the earlier review. Self‐reporting was the most common method used to gather resource‐use data, accompanied by bottom‐up approaches to estimate costs. Main outcome measures were asthma‐related hospitalizations (69%), quality of life (41%) and utility (38%), with AQLQ and the EQ‐5D being the most common questionnaires measured prospectively at fixed time points. More rigorous costing methods are needed with a more common quality of life tool to aid greater replicability and comparability amongst asthma studies.

Keywords: asthma, cost‐effective, methodology, review

1. INTRODUCTION

Asthma is a chronic lung disease, which affects over 300 million people worldwide.1 Monitoring asthma through personalized asthma action plans (PAAPS), taking medication as prescribed, having self‐awareness of potential triggers and attending regular asthma reviews are some of the ways to manage asthma.2

Much work has explored asthma pharmacological interventions, and fewer works have considered nonpharmacological.3 It has been recognized that there needs to be clearer reporting of methods, outcome measures and all appropriate costs to improve generalizability and validity.3, 4 Previous reviews have been heavily focused on clinical interventions and their level of cost‐effectiveness.4, 5, 6, 7 In order to ensure appropriate healthcare decisions are made, it is essential to understand what methodologies underpin these results.

Due to an earlier comprehensive review discussing enhanced asthma management interventions,3 the objective of this review was to update and extend this work to include a more critical review about the methodologies used to estimate costs and outcomes. The update compares the cost‐effectiveness of interventions from post‐2012 until January 2016, and the extension identifies, describes and assesses the array of methods used in estimating and evaluating both costs and outcomes for economic analyses from 1990 to January 2016. The protocol for this review was registered with PROSPERO International Prospective Register of Systematic Reviews with registration number: CRD42016032963.

2. METHODS

2.1. Eligibility criteria

2.1.1. Study design

Original research articles were considered for inclusion. These were defined as an economic evaluation: cost‐effectiveness analysis (CEA), cost utility analysis (CUA), cost benefit analysis (CBA) or a cost consequences analysis (CCA). Other types of economic studies were excluded, alongside letters, editorials, magazines, conference abstracts and reviews.

2.1.2. Population

Participants with different severities of asthma of any age and from any country were included.

2.1.3. Intervention and comparators

Nonpharmacological asthma interventions were included, such as educational, environmental or self‐management interventions. Comparators of pharmacological, nonpharmacological or usual care alternatives were permitted.

2.1.4. Outcomes

The primary outcomes were to identify the incremental cost‐effectiveness ratios (ICERs) and net benefit results to compare the cost‐effectiveness results in all studies found from the updated search. The secondary outcomes were to identify the effectiveness and monetary outcomes (eg, willingness to pay) to explore how they were evaluated across all included studies.

2.2. Search strategy

A comprehensive database search was conducted (search terms; Appendix S1), including databases searched from Yong and Shafie3 and additional databases to ensure all relevant databases were searched. The included databases searched are as follows: ScienceDirect, Wiley Online Library, EbscoHost, Embase (via OvidSP), Medline (via OvidSP) and Scopus, and additional databases: CINAHL (via EbscoHost), Cochrane (CENTRAL), NHS Economic Evaluation Database (NHS EED), http://ClinicalTrials.gov, ProQuest and Open Grey. The latter 3 databases were included to identify any unpublished literature. Truncation and phrase searching were used for an inclusive search and to retrieve papers that included the specific quoted phrases. All databases were restricted to the English language only with searches from 1990 until January 2016.

2.3. Study selection

All studies retrieved from the database search were transferred into EndNote software manager, with duplicates removed. All titles and abstracts were independently screened for eligibility by 1 reviewer (CJCB) and then second reviewers (AP, RFSK). Full texts of included articles were assessed for eligibility, and if any uncertainties arose, then discussions between 2 reviewers occurred (CJCB, AP or CJCB, RFSK) with a third reviewer required if there were any discrepancies (RFSK, AP).

2.4. Data extraction

Data were extracted from included studies into a predesigned table (Appendix S2) by 1 independent reviewer (CJCB) with second reviewers (AP, RFSK) confirming accuracy and discussing any discrepancies.

2.5. Quality assessment

Two quality assessment checklists were used in this review: Quality of Health Economic Studies (QHES) (Appendix S3) adapted by Yong and Shafie,3 but originally designed by Chiou et al,8 and the Philips et al's9 criteria for model‐based studies. Quality assessment occurred independently by 1 reviewer (CJCB), with second reviewers (AP, RFSK) checking for accuracy and resolving any discrepancies through discussion.

3. RESULTS

The extensive search retrieved 2118 studies. After duplicates were removed (287), a further 1715 studies were excluded from the title and abstract screening. After reviewing the full texts of the remaining studies, 64 studies were included for analysis (Figure 1). Of the 64, 15 studies were found in addition to Yong and Shafie.3

Figure 1.

Figure 1

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PRISMA flow diagram

3.1. Characteristics of the 15 additional papers

Table 1 describes the characteristics of the included studies found in addition to Yong and Shafie.3

Table 1.

Characteristics of the 15 additional studies

First author, year, country of population Study design (type of economic evaluation) Patient population group Description of intervention & comparator(s) Intervention participants (No., mean age, gender [%], ethnicity [%]) Comparator participants (No., mean age, gender [%], ethnicity [%]) Study cost perspective, time horizon, discount rate Currency & price year Statistical analysis, sensitivity analysis ICER or Net benefit/Net present value
Atherly et al, 2009, United States10 Prospective quasiexperimental (CEA) 524 asthma adolescents from middle and high schools Int: power breathing education programme
Com: no education programme 		No. 225
Mean age: 13.90
Male: 54.4%
Female: 46.6%
Ethnicity: not stated 		No. 233
Mean age: 13.40
Male: 49.3%
Female: 50.7%
Ethnicity: not stated 		Societal
3 months
Not Applicable 		US ($)
2003‐2004 		Mean comparisons; ordinary least‐squares regression analysis; t test.
Not stated 		$3.90 per symptom‐free day gained
Bhaumik et al, 2013, United States16 Prospective cohort (CBA) 661 people hospitalized or had asthma‐related emergency department (ED) visits from 4 low‐income urban zip codes in Boston Int: received services provided by the community asthma initiative (CAI).
Com: did not receive services provided by CAI 		No. 102
Mean age: 7.90
Male: 53.9%
Female: 46.1%
White: 6.9%
African American: 41.2%
Hispanic/Latino: 46.1%
Asian/Pacific Islander/Native American: 5.9% 		No. 559
Mean age: 7.1
Male: 59.8%
Female: 40.2%
White: 4.1%
African American: 59.2%
Hispanic/
Latino: 34.6%
Asian/Pacific Islander/
Native American: 2% 		Societal
3 years
10% 		US ($)
2006 		χ2 test;
Paired & unpaired t tests; Multivariate regression analysis.
Not stated 		Net present value:
Adjusted cost savings for year 1 = $111 588,
year 2 = $16 365,
year 3 = $83 863
Castro et al, 2003, United States21 Prospective RCT (CCA) 96 asthma hospital patients Int: daily “asthma care” flow sheet, asthma education, self‐management plan and consultations.
Com: normal care 		No. 50
Mean age: 35.00
Male: 20%
Female: 80%
African American: 86%
Non‐African American: 24% 		No. 46
Mean age: 38
Male: 15%
Female: 85%
African American: 78%, none African American: 22% 		Not stated
6 months
Not applicable 		US ($)
1999 		T tests and χ2 tests
Wilcoxon's test;
logistic regression;
log‐rank test
Not stated 		Not applicable
Mean cost: Int = $5726; Con = $12 188
Mean change in AQLQ: Int = 1.4, Con = 1.2
Fabian et al, 2014, United States17 Prospective Model (CBA) 1 million children living in low‐income multifamily housing 7 interventions: fix/operate kitchen and bathroom exhaust fans; replace gas stoves with electric ovens; eliminate the use of stove for heating by fixing the heating system; smoke‐free housing policy; use of HEPA filters; integrated pest management; weatherization. Not stated Not stated Government
10 years
Not stated 		US ($)
2009 		Probabilistic model. Not stated
Flores et al, 2009, United States11 Prospective RCT (CEA) 220 African American and Latino asthmatic children enrolled from 4 hospitals Int: parent mentors provided education, meals and social interaction monthly sessions
Com: traditional asthma care 		No. 112
Mean age: 7.10
Male: 59.8%
Female: 40.2%
Ethnicity: not stated 		No. 108
Mean age: 7.3
Male: 52.8%
Female: 47.2%
Ethnicity: not stated 		Not stated
12 months
Not applicable 		US ($)
Not stated 		Wilcoxon's tests; Fisher's exact test; logarithmic regression.
Not stated. 		Dominant
Higgins et al, 1998, United States20 Prospective before & after (CCA) 61 paediatric asthma patients without a primary care provider identified during an acute asthma exacerbation Int: patients assigned a primary care provider and parents of patients had five 1‐h asthma education sessions. No. 61
Mean age: 8.40
Male: 67.2%
Female: 32.8%
Caucasian: 50.9%
African American: 38.6%
Asian: 4.0%
Hispanic: 2.0% (4 patients did not state their race) 		Not applicable Not stated
12 months
Not applicable 		US ($)
1997 		Paired t test.
Not stated. 		Not applicable
Intervention savings on resource use = $4845.29
Mean monthly hospital admissions: before = 0.149, after = 0.007
Karnick et al, 2007, United States18 Prospective RCT (CBA) 212 children recruited from ED, inpatient units, and from referrals to paediatric pulmonologist for consultation Three interventions.
1) 20‐ to 30‐min asthma education group sessions with referrals to GP if needed.
2) Reinforced education group: same as group 1 plus further education through phone calls (minimum monthly calls)
3) Case management and reinforced education group 		1) No. 74
Mean age: 5.54
Male: 55%
Female: 45%
Non‐Hispanic Black: 70%
Hispanic: 30%
2) No. 68
Mean age: 5.13
Male: 66%
Female: 34%
Non‐Hispanic Black: 65%
Hispanic: 35%
3) No. 70
Mean age: 5.71
Male: 59%
Female: 41%
Non‐Hispanic Black: 64%
Hispanic: 34%
Other: 1% 		Not Applicable Payer
1 year retrospectively & 9 months prospectively
Not stated 		US ($)
1998 		χ2 or Fisher's test; ANOVA; paired t test.
Not stated. 		Not stated
Lara et al, 2013, Caribbean12 Prospective before & after (CEA) 145 children with moderate to severe asthma from local healthcare clinics Int: La red—combined clinic and home‐based intervention adapted from Yes We Can program and Inner‐City Asthma Study No. 145
Mean age: 5.00
Male: 61.4%
Female: 38.6%
Hispanic/Puerto Rican: 100% 		Not applicable Not stated
12 months
Not applicable 		US ($)
2009 		Monte Carlo simulation. Dominant
McCowan et al, 1997, United Kingdom22 Prospective RCT (CCA) 2557 children with diagnosed asthma Int: individuals identified by GP practice had clinical review and has guidelines for diagnosis & management of asthma in records.
Com: standard medical care 		No. 1288
Mean age: 7.67
Male: 55.4%
Female: 44.6%
Ethnicity: not stated 		No. 1269
Mean age: 7.8
Male: 59.6%
Female: 40.4%
Ethnicity: not stated 		Not stated
4 years
Not stated 		GBP (£)
1991 		Not stated.
Not stated. 		Not applicable
Year 1: Int = £68 500 Con = £57 780. Year 2: Int = £62 300 Con = £53 910. Year 3: Int = £45 700 Con = £45 280. Year 4: Int = £43 550 Con = £44 960
No. of children with hospital admissions: Year 1: Int = 33 Con = 18. Year 2: Int = 24, Con = 25. Year 3: Int = 11, Con = 12. Year 4: Int = 9 Con = 14
Mogasale et al, 2013, Australia13 Prospective Model (CEA) Asthma patients Int: asthma clinical approach.
Com: current practice of asthma management 		Not stated Not stated Health care
1 year
3% 		AUS ($)
2003 		Three Monte Carlo simulation scenarios: (1) assumed intervention only; (2) assumed interventions reduced ED visits and days off work; (3) assumed intervention reduced ED visits, unscheduled GP visits, hospitalization and days off work Without time and travel costs: Scenario 2 = $24 000 and Scenario 3 = $17 000.
With time and travel costs: Scenario 2 = $30 000 and Scenario 3 = $20 000
Ryan et al, 2012, United Kingdom14 Prospective RCT (CEA) 288 adolescents and adults with poorly controlled asthma from 32 practices. Prior to randomization, 30‐min educational training was given. Int: mobile phone‐based monitoring using an asthma application.
Com: standard paper‐based monitoring 		No. 145
Mean age: 46.60
Male: 34%
Female: 66%
White: 97%
Non‐White: 3% 		No. 143
Mean age: 51.50
Male: 41%
Female: 59%
White: 99%
Non‐White: 1% 		National Health Service
6 months
Not applicable 		GBP (£)
Not stated 		T test; Mann‐Whitney test; ANOVA.
Per‐protocol sensitivity analysis including patients who completed all questionnaires at all time points. 		Not stated
Smith et al, 2012, United Kingdom24 Prospective RCT (CCA) 911 at‐risk asthma patients with severe exacerbations recruited from 29 primary care practices Int: electronic alerts on computerized records at GP practices to flag at‐risk asthma patients with training provided to staff.
Com: usual care 		No. 14 practices, 457 patients
Mean age: 46.40
Male: 37.2%
Female: 62.8%
Ethnicity: not stated 		No. 15 practices, 454 patients
Mean age: 44.60
Male: 40.2%
Female: 59.8%
Ethnicity: not stated 		National Health Service
1 year
Not applicable 		GBP (£)
2007‐2008 		Odds ratios; Mann‐Whitney test; ICCs; random‐effects negative‐binomial models producing rate ratios.
Not stated 		Not applicable
Mean change in annual level of resource use: Int = £60.23 and Con = £149.14
Moderate‐severe asthma exacerbation: Int = 53.6% and Con = 46.5%
Tai et al, 2011, United States19 Prospective cohort (CBA) School children with asthma Int: school‐based health clinics nationwide including disease management and self‐care monitoring skills
Com: Traditional medical services 		Not stated Not stated Societal
Not stated
3% 		US ($)
2006 		Not stated.
Not stated. 		Not stated
Turcotte et al, 2014, United States23 Prospective before & after (CCA) 170 children recruited in Massachusetts with a diagnosis of asthma. Int: environmental assessor walked through homes to assess the presence of triggers with visits ranging from 4 to 9 times during the year. No. 170
Mean age: 6.08
Male: 59%
Female: 41%
Black: 5%, White: 12%. Asian: 15%, Hispanic: 53%, Other: 15% 		Not applicable Not stated
1 year
Not applicable 		US ($)
Not stated 		Wilcoxon's rank‐sum test.
Not stated 		Not applicable
Net savings from intervention: 4 week = $38 522; 6 months = $394 332 and 12 months = $821 304
Decrease in occurrence: hospitalization = 8, emergency department = 29, doctor visit = 76
Willems et al, 2007, Netherlands15 Prospective RCT (CUA) Asthma outpatients with severity stages I to III from the GINA guidelines. Int: nurse‐led telemonitoring—portable asthma monitor at home for spirometry
Com: regular outpatient care: stable asthma—3‐6 monthly check‐ups; exacerbations—additional GP or outpatient care. 		No. adults (26) Children (29)
Mean age: adults (45.65), children (10.57)
Male: adults (42.3%), children (72.4%)
Female: adults (57.7%), children (27.6%)
Ethnicity: not stated 		No. adults, (27) children (27)
Mean age: adults (45.90), children (10.85)
Male: adults (33.3%), children (55.6%)
Female: adults (66.7%), children (44.4%)
Ethnicity: not stated 		Health care & societal
1 year
Not applicable 		Euro (€)
2002 		Bootstrap simulation; ANCOVA.
One‐way sensitivity analysis testing 2 cost components. 		Healthcare perspective = €15 366/QALY gained. Societal perspective = €31 035/QALY gained.
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ANCOVA, analysis of covariance; ANOVA, analysis of variance; AQLQ, Asthma Quality of Life Questionnaire; AUS, Australian; CBA, cost benefit analysis; CCA, cost consequences analysis; CEA, cost‐effectiveness analysis; Com., comparator; CUA, cost utility analysis; ED, emergency department; GBP, Great British Pound; GINA, Global Initiative for Asthma; GP, general practitioner; HEPA, high‐efficiency particulate air; ICCs, intracluster correlation coefficient; ICER, incremental cost‐effectiveness ratio; Int., intervention; No., number; QALY, quality‐adjusted life year; RCT, randomized control trial; US, United States.

3.1.1. Study design

There were 5 CEA,10, 11, 12, 13, 14 1 CUA,15 4 CBA16, 17, 18, 19 and 5 CCA20, 21, 22, 23, 24 studies included. Of these, 7 were randomized control trials,11, 14, 15, 18, 21, 22, 24 3 before and after studies,12, 20, 23 2 model‐based studies,13, 17 2 cohort studies16, 19 and 1 quasiexperimental study.10

3.1.2. Population

Population groups chosen were mostly children‐focused10, 11, 12, 16, 17, 18, 19, 20, 22, 23 with 1 adult‐only study,21 and combination of the 2.13, 14, 15, 24 Only 7 studies12, 14, 16, 18, 20, 21, 23 stated the ethnic background of the populations chosen, with 5 of those representing a mixed ethnic population.16, 18, 20, 21, 23

3.1.3. Interventions

Interventions compared were mainly educational based provided by school, health professionals or environmental assessors;10, 11, 12, 15, 16, 18, 20, 21, 23 asthma management based using applications and/or at‐risk registers;13, 14, 19, 22, 24 and environmental based.17

3.1.4. Perspective and time horizon

Study cost perspectives included societal,10, 15, 16, 19 governmental,17 health care13, 14, 15, 24 and individual payer18 with the remaining studies not stating their perspective.11, 12, 20, 21, 22, 23 Time horizons varied with 1 study having 3 months,10 2 studies having 6 months,14, 21 7 studies having 1 year,11, 12, 13, 15, 20, 23, 24 3 studies ranging between 2 and 4 years16, 18, 22 and 1 study having 10 years.17

3.2. Cost‐effectiveness of 15 additional papers

Two studies were dominant (the intervention was less costly and more effective) compared to the comparator,11, 12 and both had time horizons of 1 year. Two of 5 of the CEA studies were cost‐effective (the ICER was lower than the stated willingness to pay threshold)10, 13 and had varied time horizons (3 months and 1 year, respectively), perspectives (societal and health care, respectively) and thresholds. The stated threshold for Atherly et al10 was AUS $50 000/DALY, whereas Mogasale and Vos13 did not state the willingness to pay threshold. One of the CEA studies was not cost‐effective.14 The only CUA study15 presented with a cost‐effective ICER and had a time horizon of 1 year based on a societal and healthcare perspective separately. Only 1 CBA study16 of 4 CBA studies produced positive net present values for the adjusted cost savings for years 1, 2 and 3, meaning that the benefits outweighed the costs and the intervention should be implemented. The remaining CCA studies20, 21, 22, 23, 24 did not present with an ICER value and therefore were not compared for cost‐effectiveness; however where available, the cost and outcome results are detailed in Table 1.

3.3. Quality assessment for the 15 additional papers

The QHES checklist score varied across the 15 additional studies found (Table 2). Eight studies scored within the range of fair quality (50%‐74%).10, 12, 17, 19, 20, 21, 22, 23 The remaining 7 studies11, 13, 14, 15, 16, 18, 24 scored within the range of high quality (>74%). Two studies were model based, and Fabian et al17 provided a sound quality for the majority of the assessment categories in the Phillips criteria; however, a reference to cycle length, internal consistency or methodological, structural and heterogeneity uncertainty was not mentioned. Mogasale and Vos13 also provided a good quality assessment overall, but were lacking in areas considering cycle length and uncertainties.

Table 2.

Quality assessment scores using QHES checklist for the 15 additional studies

QHES criteria no.a Atherly et al (2009)10 Bhaumik et al (2013)16 Castro et al (2003)21 Fabian et al (2014)17 Flores et al (2009)11 Higgins et al (1998)20 Karnick et al (2007)18 Lara et al (2013)12 McCowan et al (1997)22 Mogasale et al (2013)13 Ryan et al (2012)14 Smith et al (2012)24 Tai et al (2011)19 Turcotte et al (2014)23 Willems et al (2007)15
1 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7
2 2 4 0 4 0 0 4 0 0 2 2 2 2 0 2
3 8 6 8 4 8 6 8 6 8 8 8 8 6 6 8
4 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1
5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 0 9 9 4.5 0 4.5 9
6 6 6 0 0 6 0 0 0 0 6 0 6 0 0 6
7 5 5 5 0 5 5 5 5 0 5 5 5 5 5 5
8 7 7 0 5 7 7 7 7 0 0 7 7 0 7 7
9 6 6 2 6 8 8 8 6 8 8 6 6 8 8 8
10 6 6 4 0 6 4 4 6 4 0 4 6 0 4 4
11 0 7 7 0 7 7 7 7 7 7 0 7 0 7 7
12 4 8 8 4.5 4 8 8 5 2 8 8 8 2 4 8
13 3.5 7 3.5 7 3.5 3.5 3.5 3.5 3.5 7 7 7 7 7 3.5
14 0 6 6 0 0 6 6 3 0 0 3 0 6 0 6
15 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
16 0 3 3 3 3 0 3 3 3 3 3 3 0 3 0
Total 67 90.5 66 54 77 74 84 71 50.5 78 77 84.5 51 70.5 89.5
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a

Full table of criteria and scoring system can be found in Appendix S3.

3.4. Methods used to estimate and value costs across all 64 papers

Multiple methods were used to gather resource‐use data across the included studies; however, not all studies reported the associated unit cost for the resource use (Appendix S4). The most commonly reported items of resource use were asthma‐related hospitalizations (72%) and emergency department visits (70%), with physician visits (58%), other healthcare professional visits (28%), lost productivity (38%) and medication use (44%) also collected.

Data were mostly gathered from medical or computerized records (19%) for hospital‐related costs,14, 21, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 wage rates by employers or case managers for productivity loss (22%)11, 13, 15, 16, 19, 26, 29, 30, 33, 36, 37, 38, 39, 40 and by patient or parent self‐reported data (80%) for productivity loss and quality of life.11, 15, 21, 26, 29, 30, 32, 33, 41, 42, 43, 44, 45 Claims, billing or reimbursement data (25%) were often used for those countries who operate on healthcare insurance systems to also capture hospital‐related costs.15, 17, 35, 36, 37, 44, 46, 47, 48, 49, 50 Costing manuals for health care were mostly used to gather the unit costs of resources amongst the papers, such as the Dutch Drug Compendium, 2000, and the Dutch Manual for Costing in Economic Evaluations51 and the Pharmacy price listing.20

The methods used to estimate the intervention components’ resource use were not always clearly stated, with all of the necessary individual components needed to form the successful running of the intervention and the costing behind this, not often reported. Staff costs, programme materials and training were the most commonly reported intervention component costs; however, only some studies stated the unit costs of the components11, 15, 29, 30, 38, 39, 43, 44, 49, 50, 52, 53, 54, 55, 56 (Appendix S4). Only a select few papers took into account any associated travel costs involved in the intervention,29, 30, 37, 38, 50, 55 and some studies reimbursed participants for taking part in their research.10, 11, 23, 35, 55 Likewise, with estimating the wider health resource use, some papers were more detailed with the microcosting of the intervention component (of which was summed) than others (Appendix S6 and Appendix S7). The bottom‐up approach (individual's healthcare service use aggregated) (78%) was generally a more popular method used to estimate and value the resource‐use costs including most of the intervention component costs, as opposed to the top‐down approach (total healthcare service costs divided by activity days).18, 19, 20, 25, 31, 32, 36, 41, 57, 58, 59, 60, 61 Methods used to estimate productivity loss also varied between the human capital approach (each hour lost at work per patient),30, 40, 43 the friction cost method (each hour lost at work until the employer replaces the patient who is unable to work)15, 33 or using the caregivers income multiplied by the mid‐point of the family's income.11

3.5. Methods used to estimate and value outcomes (1990 to January 2012)

The outcomes measured varied widely, across all included studies, with multiple data collection methods often used within each study (Appendix S5). The hospital visits and emergency department visits were the most frequently stated resource use, and they were also the most common type of outcomes measured. Over two‐thirds identified the emergency department visits or hospitalizations (46 papers or 45 papers, respectively), followed by approximately one‐third investigating quality of life and physician (GP) visits (26 papers and 29 papers, respectively). Other papers reported a wide range of other outcomes, including intensive care admissions,23, 28, 32, 58 frequency of exacerbations and symptoms,11, 14, 22, 62, 63 asthma knowledge,10, 39, 48, 60 peak expiratory flow (PEF),30, 38, 42, 48, 54, 58, 63, 64, 65, 66, 67 forced expiratory volume,15, 26, 30, 31, 37, 42, 43, 54, 58, 64, 65, 66 forced vital capacity (FVC)15, 30, 31, 37, 42, 54, 58, 64, 65, 66 and medications.18, 30, 39, 47, 50, 58, 68, 69 A PEF meter was used to estimate the PEF, a spirometry was used to estimate the forced expiratory volume in one second and FVC, and histamine was used to estimate airway responsiveness.

A wide selection of health questionnaires were used to collect data in the studies (Figure 2), mostly by patient self‐report, but often in conjunction with face‐to‐face visits12, 14, 37, 39, 40, 51, 58, 64, 65, 66, 70 or telephone interview sessions.11, 13, 18, 25, 36, 44, 50, 53, 57, 60, 62, 69, 70, 71 Other options of completing questionnaire data were by proxy, that is, parent‐reported questionnaires,12, 42, 55, 70 caregivers’ questionnaires40 or case managers’ self‐reported questionnaires.16, 56

Figure 2.

Figure 2

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Different health questionnaires used in studies

The disease‐specific questionnaires—Asthma Quality of Life Questionnaire (AQLQ)15, 21, 34, 43, 48, 58 and the St. George's Respiratory Questionnaire (SGRQ)31, 37, 64, 65, 66—and the generic questionnaires—EuroQol‐5 Dimensions (EQ‐5D)15, 29, 33, 42 and 15 Dimensions (15D)64, 65, 66, 67—were the most commonly used. The studies that used the EQ‐5D and Short Form‐6 Dimension (SF‐6D)15 converted the scores into utility values and used these to estimate quality‐adjusted life years (QALYs). Other studies that did not estimate QALYs used total and/or overall mean scores from the health questionnaires in their analysis.

4. DISCUSSION

This systematic review updated and extended a previous study that evaluated the cost‐effectiveness of nonpharmacological asthma interventions with databases searched from 1990 until 2012.3 The extension included extending this database search until January 2016, and the update included an assessment of the methods used to estimate both costs and outcomes in all studies found from 1990 until 2016.

4.1. Main findings

In line with the findings from Yong and Shafie,3 the additional education and self‐management study‐based interventions found in this review were deemed most cost‐effective or dominant. The quality of studies has since improved with the additional studies presenting with fair (50%‐74%) to high (>74%) quality. Multiple methods were often used to gather resource‐use data with self‐report being the most common, the bottom‐up approach being the most common estimation method of resource use gathered, and health‐related questionnaires being a common outcome measure with AQLQ and EQ‐5D being the most common HRQOL questionnaires.

4.2. Comparison with other studies

Earlier systematic reviews of asthma interventions also highlighted the importance of the quality assessment in studies.5, 6, 72, 73 One study, in particular, believed their peak flow monitoring intervention was cost‐effective, but could not conclude this due to the study qualities being so low.72 This review shows that the quality of studies has much improved since then, with nearly 50% of the studies found post‐2012 presenting with high quality.

Although improvement has been noticed in the quality of the studies, some still have an inadequate follow‐up, which can reduce validity and generalizability.74 It was previously acknowledged that a short time horizon was inadequate for chronic conditions,6 with a time horizon of 3 months or less considered to be unacceptable.4 The additional studies found in this review presented with 1 study having a time horizon of 3 months,10 and others longer at between 6 months and 10 years.

As different cost perspectives are used amongst the included studies in this review, it becomes difficult to compare the total costs associated with each intervention. An earlier review noted that the author's definitions of direct medical costs, direct nonmedical costs and indirect costs sometimes varied, where costs assigned to direct nonmedical costs should have been assigned to indirect costs.72 Previous literature discusses that a societal perspective is important to synthesize the evidence and gain a proper understanding on peak flow monitoring interventions.72, 75, 76 However, perspectives chosen can differ from country to country and the definitions of a societal perspective can also vary.

It was surprising that only about a quarter of papers included lost productivity as an outcome measure. Due to asthma being a chronic condition, it is thought that more papers would have discussed lost productivity, and the possible implications that this may have on presenteeism and/or absenteeism. With patients who have asthma exacerbations often not well enough to continue at work or with their usual activities, it is important to include nonmedical resource use and productivity costs in studies.77

In all of the included studies in this review, the intervention details were often reported, but the details surrounding the costs of conducting the interventions with the associated unit costs were limited. Three studies provided comprehensive details about how they estimated the intervention, including the breakdown of the intervention components, their associated unit costs and the methods chosen to estimate such costs.15, 29, 55 The common approach between all 3 was a microcosting approach. Difficulties can sometimes occur with this approach when prices for certain resources are not always available from various data sources, leaving room for customization.78

From the 26 studies that also incorporated quality of life as an outcome measure, there were over 20 different questionnaires that were used to measure this. Many of the questionnaires used to analyse quality of life were more specific to asthma, but there did not appear to be a preferred measure that was used across the studies. The EQ‐5D‐3L questionnaire (5 dimensions with 3 levels: no problems, moderate problems and extreme problems) was used across a number of studies, but often used alone and not in conjunction with another quality of life questionnaire. As discussed by Yong and Shafie,3 EQ‐5D‐3L might not be the best tool to use for quality of life in asthma, as it is not seen as sensitive enough to detect differences in HRQOL particularly in people with mild asthma. However, there have been recent developments of a new EQ‐5D‐5L questionnaire, which includes the same 5 dimensions but with 5 levels: no problems, slight problems, moderate problems, severe problems or extreme problems.79 The newly developed EQ‐5D‐5L tool may be more suitable as it was designed to be more sensitive and reduce the high ceiling effects. This has been confirmed in several studies that have shown increased reliabilities, sensitivities and validities.79, 80

4.3. Recommendations for future

In the light of the above, there are many areas for which focus is required when conducting an asthma study. The main recommendations are to use time horizons greater than 3 months to ensure adequate follow‐up, to include all relevant costs and benefits that have been accounted for as asthma is a chronic condition (particularly the high cost drivers77), and to conduct a microcosting approach where possible. For economic evaluations where QALYs are estimated, the EQ‐5D‐5L can be used as a generic measure. However, even though this has been proven in earlier studies to show positive results in terms of increased sensitivities and validities compared to the EQ‐5D‐3L, due to it being a relatively new questionnaire, it may be advisable to use this in conjunction with a more established disease‐specific questionnaire. Due to the difficulties that arise in economic evaluations and to ensure the comparability across different countries and decision‐makers,81 it may be useful to adhere to an international reference case, which is a useful guide from the planning stages of research through to reporting findings and completion. Future research should also ensure that the appropriate guidelines and checklists are adhered to, such as the TiDieR checklist,82 the CHEERS statement,83 CONSORT statement84 and the COMET initiative85 for ease of replicability of both the intervention and control groups by clinicians or researchers looking to implement or expand research ideas, respectively. This will in turn aid the comparability of studies.

4.4. Strengths and limitations

The strength of this review is that it provides a comprehensive synthesis of studies from an extensive database search with studies analysed from 12 databases. The included studies help to understand how asthma interventions and methodologies chosen have evolved over the years, with discussions leading to recommendations for future practice. Bias has been reduced during this review by including 2 independent reviewers during the systematic review process. However, a limitation of this review is that only English language studies were included, with restrictions of this placed during the database search. Therefore, we are unable to acknowledge how many non‐English studies have been excluded from this review, but it is apparent that due to this selection bias, additional studies may have been relevant for inclusion in this review.

5. CONCLUSIONS

The additional 15 studies identified were of fair to high quality. Most of the additional studies found had dominant or cost‐effective interventions that were educational or management based, which mirrored the previous review. The methods used to estimate costs and outcomes varied, with the bottom‐up approach being the most common approach; however, the reporting of unit costs was lacking amongst some studies, with only a few studies providing detailed microcosting methodologies for the intervention components. For future studies, a thorough description of methods used in all components of the study is needed, including reporting of unit costs and a common quality of life measure to provide more comparability.

AUTHOR CONTRIBUTIONS

CJCB, TS, AW and GB were involved in the design of the study from conception. CJCB, AP and RFSK participated in the systematic process of screening the titles, abstracts and full texts of articles based on the eligibility criteria. CJCB, AP and RFSK also contributed to the data extraction and quality assessment stages. CJCB drafted the manuscript, with all authors providing critical revisions and final approvals.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

Supporting information

 

Click here for additional data file. (405.8KB, docx)

ACKNOWLEDGMENTS

The authors would like to thank the funders of this research, the National Institute for Health Research Collaborations for leadership in Applied Health Research and Care East of England.

Crossman‐Barnes C‐J, Peel A, Fong‐Soe‐Khioe R, Sach T, Wilson A, Barton G. Economic evidence for nonpharmacological asthma management interventions: A systematic review. Allergy. 2018;73:1182–1195. https://doi.org/10.1111/all.13337

REFERENCES

  • 1. Global Asthma Network . The Global Asthma Report 2014. Auckland, New Zealand: Global Asthma Network; 2014. [Google Scholar]
  • 2. British Thoracic Society , Scottish Intercollegiate Guidelines Network . British guideline on the management of asthma: A national clinical guideline 2016.
  • 3. Yong YV, Shafie AA. Economic evaluation of enhanced asthma management: a systematic review. Pharm Pract (Granada). 2014;12:493. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Feenstra TL, Rutten‐Van Molken MP, Jager JC, Van Essen‐Zandvliet LE. Cost effectiveness of guideline advice for children with asthma: a literature review. Pediatr Pulmonol. 2002;34:442‐454. [DOI] [PubMed] [Google Scholar]
  • 5. Persson U, Ghatnekar O. Cost‐effectiveness analysis of inhaled corticosteroids in asthma: a review of the analytical standards. Respir Med. 2003;97:1‐11. [DOI] [PubMed] [Google Scholar]
  • 6. Campbell JD, Spackman DE, Sullivan SD. Health economics of asthma: assessing the value of asthma interventions. Allergy. 2008;63:1581‐1592. [DOI] [PubMed] [Google Scholar]
  • 7. Norman G, Faria R, Paton F, et al. Omalizumab for the treatment of severe persistent allergic asthma: a systematic review and economic evaluation. Health Technol Assess. 2013;17:1‐342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Chiou CF, Hay JW, Wallace JF, et al. Development and validation of a grading system for the quality of cost‐effectiveness studies. Med Care. 2003;41:32‐44. [DOI] [PubMed] [Google Scholar]
  • 9. Philips Z, Ginnelly L, Sculpher M, et al. Review of guidelines for good practice in decision‐analytic modelling in health technology assessment. Health Technol Assess. 2004;8:iii‐iv, ix‐xi, 1‐158. [DOI] [PubMed] [Google Scholar]
  • 10. Atherly A, Nurmagambetov T, Williams S, Griffith M. An economic evaluation of the school‐based “power breathing” asthma program. J Asthma. 2009;46:596‐599. [DOI] [PubMed] [Google Scholar]
  • 11. Flores G, Bridon C, Torres S, et al. Improving asthma outcomes in minority children: a randomized, controlled trial of parent mentors. Pediatrics. 2009;124:1522‐1532. [DOI] [PubMed] [Google Scholar]
  • 12. Lara M, Ramos‐Valencia G, Gonzalez‐Gavillan JA, et al. Reducing quality‐of‐care disparities in childhood asthma: La Red de Asma Infantil intervention in San Juan, Puerto Rico. Pediatrics. 2013;131(Suppl 1):S26‐S37. [DOI] [PubMed] [Google Scholar]
  • 13. Mogasale V, Vos T. Cost‐effectiveness of asthma clinic approach in the management of chronic asthma in Australia. Aust N Z J Public Health. 2013;37:205‐210. [DOI] [PubMed] [Google Scholar]
  • 14. Ryan D, Price D, Musgrave SD, et al. Clinical and cost effectiveness of mobile phone supported self monitoring of asthma: multicentre randomised controlled trial. BMJ. 2012;344:e1756. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Willems DC, Joore MA, Hendriks JJ, Wouters EF, Severens JL. Cost‐effectiveness of a nurse‐led telemonitoring intervention based on peak expiratory flow measurements in asthmatics: results of a randomised controlled trial. Cost Eff Resour Alloc. 2007;5:10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Bhaumik U, Norris K, Charron G, et al. A cost analysis for a community‐based case management intervention program for pediatric asthma. J Asthma. 2013;50:310‐317. [DOI] [PubMed] [Google Scholar]
  • 17. Fabian MP, Adamkiewicz G, Stout NK, Sandel M, Levy JI. A simulation model of building intervention impacts on indoor environmental quality, pediatric asthma, and costs. J Allergy Clin Immunol. 2014;133:77‐84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Karnick P, Margellos‐Anast H, Seals G, Whitman S, Aljadeff G, Johnson D. The pediatric asthma intervention: a comprehensive cost‐effective approach to asthma management in a disadvantaged inner‐city community. J Asthma. 2007;44:39‐44. [DOI] [PubMed] [Google Scholar]
  • 19. Tai T, Bame SI. Cost‐benefit analysis of childhood asthma management through school‐based clinic programs. J Community Health. 2011;36:253‐260. [DOI] [PubMed] [Google Scholar]
  • 20. Higgins JC, Kiser WR, McClenathan S, Tynan NL. Influence of an interventional program on resource use and cost in pediatric asthma. Am J Manag Care. 1998;4:1465‐1469. [PubMed] [Google Scholar]
  • 21. Castro M, Zimmermann NA, Crocker S, Bradley J, Leven C, Schechtman KB. Asthma intervention program prevents readmissions in high healthcare users. Am J Respir Crit Care Med. 2003;168:1095‐1099. [DOI] [PubMed] [Google Scholar]
  • 22. McCowan C, Neville RG, Crombie IK, Clark RA, Warner FC. The facilitator effect: results from a four‐year follow‐up of children with asthma. Br J Gen Pract. 1997;47:156‐160. [PMC free article] [PubMed] [Google Scholar]
  • 23. Turcotte DA, Alker H, Chaves E, Gore R, Woskie S. Healthy homes: in‐home environmental asthma intervention in a diverse urban community. Am J Public Health. 2014;104:665‐671. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Smith JR, Noble MJ, Musgrave S, et al. The at‐risk registers in severe asthma (ARRISA) study: a cluster‐randomised controlled trial examining effectiveness and costs in primary care. Thorax. 2012;67:1052‐1060. [DOI] [PubMed] [Google Scholar]
  • 25. Bratton DL, Price M, Gavin L, et al. Impact of a multidisciplinary day program on disease and healthcare costs in children and adolescents with severe asthma: a two‐year follow‐up study. Pediatr Pulmonol. 2001;31:177‐189. [DOI] [PubMed] [Google Scholar]
  • 26. Bunting BA, Cranor CW. The Asheville Project: long‐term clinical, humanistic, and economic outcomes of a community‐based medication therapy management program for asthma. J Am Pharm Assoc (2003). 2006;46:133‐147. [DOI] [PubMed] [Google Scholar]
  • 27. Doan T, Grammer LC, Yarnold PR, Greenberger PA, Patterson R. An intervention program to reduce the hospitalization cost of asthmatic patients requiring intubation. Ann Allergy Asthma Immunol. 1996;76:513‐518. [DOI] [PubMed] [Google Scholar]
  • 28. Levenson T, Grammer LC, Yarnold PR, Patterson R. Cost‐effective management of malignant potentially fatal asthma. Allergy Asthma Proc. 1997;18:73‐78. [DOI] [PubMed] [Google Scholar]
  • 29. van der Meer V, van den Hout WB, Bakker MJ, et al. Cost‐effectiveness of Internet‐based self‐management compared with usual care in asthma. PLoS One. 2011;6:e27108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Runge C, Lecheler J, Horn M, Tews JT, Schaefer M. Outcomes of a Web‐based patient education program for asthmatic children and adolescents. Chest. 2006;129:581‐593. [DOI] [PubMed] [Google Scholar]
  • 31. Shelledy DC, Legrand TS, Gardner DD, Peters JI. A randomized, controlled study to evaluate the role of an in‐home asthma disease management program provided by respiratory therapists in improving outcomes and reducing the cost of care. J Asthma. 2009;46:194‐201. [DOI] [PubMed] [Google Scholar]
  • 32. Shelledy DC, McCormick SR, LeGrand TS, Cardenas J, Peters JI. The effect of a pediatric asthma management program provided by respiratory therapists on patient outcomes and cost. Heart Lung. 2005;34:423‐428. [DOI] [PubMed] [Google Scholar]
  • 33. Steuten L, Palmer S, Vrijhoef B, van Merode F, Spreeuwenberg C, Severens H. Cost‐utility of a disease management program for patients with asthma. Int J Technol Assess Health Care. 2007;23:184‐191. [DOI] [PubMed] [Google Scholar]
  • 34. Tschopp JM, Frey JG, Janssens JP, et al. Asthma outpatient education by multiple implementation strategy. Outcome of a programme using a personal notebook. Respir Med. 2005;99:355‐362. [DOI] [PubMed] [Google Scholar]
  • 35. Wood MR, Bolyard D. Making education count: the nurse's role in asthma education using a medical home model of care. J Pediatr Nurs. 2011;26:552‐558. [DOI] [PubMed] [Google Scholar]
  • 36. Bolton MB, Tilley BC, Kuder J, Reeves T, Schultz LR. The cost and effectiveness of an education program for adults who have asthma. J Gen Intern Med. 1991;6:401‐407. [DOI] [PubMed] [Google Scholar]
  • 37. Gallefoss F, Bakke PS. Cost‐effectiveness of self‐management in asthmatics: a 1‐yr follow‐up randomized, controlled trial. Eur Respir J. 2001;17:206‐213. [DOI] [PubMed] [Google Scholar]
  • 38. Ghosh CS, Ravindran P, Joshi M, Stearns SC. Reductions in hospital use from self management training for chronic asthmatics. Soc Sci Med. 1998;46:1087‐1093. [DOI] [PubMed] [Google Scholar]
  • 39. Polisena J, Tam S, Lodha A, Laporte A, Coyte PC, Ungar WJ. An economic evaluation of asthma action plans for children with asthma. J Asthma. 2007;44:501‐508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Sullivan SD, Lee TA, Blough DK, et al. A multisite randomized trial of the effects of physician education and organizational change in chronic asthma care – cost‐effectiveness analysis of the Pediatric Asthma Care Patient Outcomes Research Team II (PAC‐PORT II). Arch Pediatr Adolesc Med. 2005;159:428‐434. [DOI] [PubMed] [Google Scholar]
  • 41. Drummond N, Abdalla M, Buckingham JK, et al. Integrated care for asthma: a clinical, social, and economic evaluation. Grampian Asthma Study of Integrated Care (GRASSIC). BMJ. 1994;308:559‐564. [PMC free article] [PubMed] [Google Scholar]
  • 42. Lindberg M, Ahlner J, Ekstrom T, Jonsson D, Moller M. Asthma nurse practice improves outcomes and reduces costs in primary health care. Scand J Caring Sci. 2002;16:73‐78. [DOI] [PubMed] [Google Scholar]
  • 43. Schermer TR, Thoonen BP, van den Boom G, et al. Randomized controlled economic evaluation of asthma self‐management in primary health care. Am J Respir Crit Care Med. 2002;166:1062‐1072. [DOI] [PubMed] [Google Scholar]
  • 44. Sullivan SD, Weiss KB, Lynn H, et al. The cost‐effectiveness of an inner‐city asthma intervention for children. J Allergy Clin Immunol. 2002;110:576‐581. [DOI] [PubMed] [Google Scholar]
  • 45. Tschopp JM, Frey JG, Pernet R, et al. Bronchial asthma and self‐management education: implementation of Guidelines by an interdisciplinary programme in health network. Swiss Med Wkly. 2002;132:92‐97. [DOI] [PubMed] [Google Scholar]
  • 46. D'Souza AO, Rahnama R, Regan TS, Common B, Burch S. The h‐e‐B value‐based health management program: impact on asthma medication adherence and healthcare cost. Am Health Drug Benefits. 2010;3:394‐402. [PMC free article] [PubMed] [Google Scholar]
  • 47. Tinkelman D, Wilson S. Asthma disease management: regression to the mean or better? Am J Manag Care. 2004;10:948‐954. [PubMed] [Google Scholar]
  • 48. Chan AL, Wang HY. Pharmacoeconomic assessment of clinical pharmacist interventions for patients with moderate to severe asthma in outpatient clinics: experience in Taiwan. Clin Drug Investig. 2004;24:603‐609. [DOI] [PubMed] [Google Scholar]
  • 49. Gordois A, Armour C, Brillant M, et al. Cost‐effectiveness analysis of a pharmacy asthma care program in Australia. Dis Manag Health Outcomes. 2007;15:387‐396. [Google Scholar]
  • 50. Kattan M, Stearns SC, Crain EF, et al. Cost‐effectiveness of a home‐based environmental intervention for inner‐city children with asthma. J Allergy Clin Immunol. 2005;116:1058‐1063. [DOI] [PubMed] [Google Scholar]
  • 51. Kamps AW, Roorda RJ, Kimpen JL, Overgoor‐van de Groes AW, van Helsdingen‐Peek LC, Brand PL. Impact of nurse‐led outpatient management of children with asthma on healthcare resource utilisation and costs. Eur Respir J. 2004;23:304‐309. [DOI] [PubMed] [Google Scholar]
  • 52. de Asis ML, Greene R. A cost‐effectiveness analysis of a peak flow‐based asthma education and self‐management plan in a high‐cost population. J Asthma. 2004;41:559‐565. [PubMed] [Google Scholar]
  • 53. Donald KJ, McBurney H, Teichtahl H, et al. Telephone based asthma management – financial and individual benefits. Aust Fam Physician. 2008;37:272‐275. [PubMed] [Google Scholar]
  • 54. Neri M, Migliori GB, Spanevello A, et al. Economic analysis of two structured treatment and teaching programs on asthma. Allergy. 1996;51:313‐319. [PubMed] [Google Scholar]
  • 55. Rhee H, Pesis‐Katz I, Xing J. Cost benefits of a peer‐led asthma self‐management program for adolescents. J Asthma. 2012;49:606‐613. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Xu C, Jackson M, Scuffham PA, et al. A randomized controlled trial of an interactive voice response telephone system and specialist nurse support for childhood asthma management. J Asthma. 2010;47:768‐773. [DOI] [PubMed] [Google Scholar]
  • 57. Anderson ME, Freas MR, Wallace AS, Kempe A, Gelfand EW, Liu AH. Successful school‐based intervention for inner‐city children with persistent asthma. J Asthma. 2004;41:445‐453. [DOI] [PubMed] [Google Scholar]
  • 58. Franco R, Santos AC, do Nascimento HF, et al. Cost‐effectiveness analysis of a state funded programme for control of severe asthma. BMC Public Health. 2007;7:82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Johnson AE, Yin M, Berg G. Utilization and financial outcomes of an asthma disease management program delivered to Medicaid members: results of a three‐group comparison study. Dis Manag Health Outcomes. 2003;11:455‐465. [Google Scholar]
  • 60. Lucas DO, Zimmer LO, Paul JE, et al. Two‐year results from the asthma self‐management program: long‐term impact on health care services, costs, functional status, and productivity. J Asthma. 2001;38:321‐330. [DOI] [PubMed] [Google Scholar]
  • 61. Rossiter LF, Whitehurst‐Cook MY, Small RE, et al. The impact of disease management on outcomes and cost of care: a study of low‐income asthma patients. Inquiry. 2000;37:188‐202. [PubMed] [Google Scholar]
  • 62. Ng DK, Chow PY, Lai WP, Chan KC, And BL, So HY. Effect of a structured asthma education program on hospitalized asthmatic children: a randomized controlled study. Pediatr Int. 2006;48:158‐162. [DOI] [PubMed] [Google Scholar]
  • 63. Tagaya E, Tamaoki J, Nagai A, Murasugi H, Igi H. The role of a self‐management program in the control of mild to moderate asthma: a randomized controlled study. Allergol Int. 2005;54:527‐531. [Google Scholar]
  • 64. Kauppinen R, Sintonen H, Tukiainen H. One‐year economic evaluation of intensive vs conventional patient education and supervision for self‐management of new asthmatic patients. Respir Med. 1998;92:300‐307. [DOI] [PubMed] [Google Scholar]
  • 65. Kauppinen R, Sintonen H, Vilkka V, Tukiainen H. Long‐term (3‐year) economic evaluation of intensive patient education for self‐management during the first year in new asthmatics. Respir Med. 1999;93:283‐289. [DOI] [PubMed] [Google Scholar]
  • 66. Kauppinen R, Vilkka V, Sintonen H, Klaukka T, Tukiainen H. Long‐term economic evaluation of intensive patient education during the first treatment year in newly diagnosed adult asthma. Respir Med. 2001;95:56‐63. [DOI] [PubMed] [Google Scholar]
  • 67. McLean W, Gillis J, Waller R. The BC Community Pharmacy Asthma Study: a study of clinical, economic and holistic outcomes influenced by an asthma care protocol provided by specially trained community pharmacists in British Columbia. Can Respir J. 2003;10:195‐202. [DOI] [PubMed] [Google Scholar]
  • 68. Taitel MS, Kotses H, Bernstein IL, Bernstein DI, Creer TL. A self‐management program for adult asthma. Part II: cost‐benefit analysis. J Allergy Clin Immunol. 1995;95:672‐676. [DOI] [PubMed] [Google Scholar]
  • 69. Watanabe T, Ohta M, Murata M, Yamamoto T. Decrease in emergency room or urgent care visits due to management of bronchial asthma inpatients and outpatients with pharmaceutical services. J Clin Pharm Ther. 1998;23:303‐309. [DOI] [PubMed] [Google Scholar]
  • 70. Woods ER, Bhaumik U, Sommer SJ, et al. Community asthma initiative: evaluation of a quality improvement program for comprehensive asthma care. Pediatrics. 2012;129:465‐472. [DOI] [PubMed] [Google Scholar]
  • 71. Greineder DK, Loane KC, Parks P. A randomized controlled trial of a pediatric asthma outreach program. J Allergy Clin Immunol. 1999;103(3 Pt 1):436‐440. [DOI] [PubMed] [Google Scholar]
  • 72. Willems DC, Joore MA, Hendriks JJ, Wouters EF, Severens JL. Cost‐effectiveness of self‐management in asthma: a systematic review of peak flow monitoring interventions. Int J Technol Assess Health Care. 2006;22:436‐442. [DOI] [PubMed] [Google Scholar]
  • 73. Ismaila AS, Sayani AP, Marin M, Su Z. Clinical, economic, and humanistic burden of asthma in Canada: a systematic review. BMC Pulm Med. 2013;13:70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74. Woolard RH, Carty K, Wirtz P, et al. Research fundamentals: follow‐up of subjects in clinical trials: addressing subject attrition. Acad Emerg Med. 2004;11:859‐866. [DOI] [PubMed] [Google Scholar]
  • 75. Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes, 4th edn New York, NY: Oxford University Press; 2015. [Google Scholar]
  • 76. Jonsson B. Ten arguments for a societal perspective in the economic evaluation of medical innovations. Eur J Health Econ. 2009;10:357‐359. [DOI] [PubMed] [Google Scholar]
  • 77. Ramsey SD, Willke RJ, Glick H, et al. Cost‐effectiveness analysis alongside clinical trials II‐An ISPOR Good Research Practices Task Force report. Value Health. 2015;18:161‐172. [DOI] [PubMed] [Google Scholar]
  • 78. Raftery J. Costing in economic evaluation. BMJ. 2000;320:1597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Herdman M, Gudex C, Lloyd A, et al. Development and preliminary testing of the new five‐level version of EQ‐5D (EQ‐5D‐5L). Qual Life Res. 2011;20:1727‐1736. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80. Janssen MF, Pickard AS, Golicki D, et al. Measurement properties of the EQ‐5D‐5L compared to the EQ‐5D‐3L across eight patient groups: a multi‐country study. Qual Life Res. 2013;22:1717‐1727. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81. Wilkinson T, Sculpher MJ, Claxton K, et al. The international decision support initiative reference case for economic evaluation: an aid to thought. Value Health. 2016;19:921‐928. [DOI] [PubMed] [Google Scholar]
  • 82. Hoffmann TC, Glasziou PP, Boutron I, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. [DOI] [PubMed] [Google Scholar]
  • 83. Husereau D, Drummond M, Petrou S, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ. 2013;346:f1049. [DOI] [PubMed] [Google Scholar]
  • 84. Schulz KF, Altman DG, Moher D, CONSORT Group . CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85. COMET Initiative . COMET initiative: core outcome measures in effectiveness trials 2011‐2017. http://www.comet-initiative.org/. Accessed 10/05/2017.

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