Clinician Agreement, Self-efficacy, and Adherence with the Guidelines for the Diagnosis and Management of Asthma

Abstract

Background

The 2007 Guidelines for the Diagnosis and Management of Asthma provide evidence-based recommendations to improve asthma care. Limited national-level data are available about clinician agreement and adherence to these guidelines.

Objective

To assess clinician-reported adherence with specific guideline recommendations, as well as agreement with and self-efficacy to implement guidelines

Methods

We analyzed 2012 National Asthma Survey of Physicians data for 1412 primary care clinicians and 233 asthma specialists about four cornerstone guideline domains: asthma control, patient education, environmental control, and pharmacologic treatment. Agreement and self-efficacy were measured using Likert scales; two overall indices of agreement and self-efficacy were compiled. Adherence was compared between primary care clinicians and asthma specialists. Logistic regression models assessed the association of agreement and self-efficacy indices with adherence.

Results

Asthma specialists expressed stronger agreement, higher self-efficacy, and greater adherence with guideline recommendations than primary care clinicians. Adherence was low among both groups for specific core recommendations, including written asthma action plan (30.6% and 16.4%, respectively P<.001); home peak flow monitoring, (12.8% and 11.2%, P=.34); spirometry testing, (44.7% and 10.8%, P<.001); and repeated assessment of inhaler technique, (39.7% and 16.8%, P<.001). Among primary care clinicians, greater self-efficacy was associated with greater adherence. For specialists, self-efficacy was associated only with increased odds of spirometry testing. Guideline agreement was generally not associated with adherence.

Conclusions

Agreement with and adherence to asthma guidelines was higher for specialists than primary care clinicians, but was low in both groups for several key recommendations. Self-efficacy was a good predictor of guideline adherence among primary care clinicians but not among specialists.

Introduction

Clinical guidelines aid in disease diagnosis and management, and exist for multiple conditions including asthma.(1) Previous reports on primary care clinicians and specialists demonstrate that adherence to guidelines in general is low (2–6) and that adherence to the 2007 National Asthma Education and Prevention Program’s (NAEPP) Expert Panel Report 3 (EPR-3) asthma guidelines(1) is no exception.(7–10) The National Ambulatory Medical Care Survey (NAMCS), an ongoing nationally representative survey, covers visits to office-based physicians and clinicians in Community Health Centers (CHC).(11) In 2012, the National Asthma Survey of Physicians (NAS) was fielded as a one-time provider questionnaire supplement to NAMCS.(12) The supplement was conceived of and sponsored by the National Asthma Education and Prevention Program Coordinating Committee (NAEPP-CC). The questionnaire design group was co-lead by the National Center for Environmental Health, CDC and the National Heart, Lung and Blood Institute with staff and NAEPP-CC members participating (see supplemental material in Online Repository). It queried primary care clinicians’ and specialists’ opinions, self-efficacy, and self-reported adherence regarding asthma care and key recommendations in the EPR-3 report. The goal of this manuscript is to characterize and compare agreement with the national asthma guidelines by primary care and asthma specialty clinicians, their confidence in implementing the guidelines, and assess their self-reported adherence to the four core components of the guidelines. This information could inform new guidelines and future studies.

Methods

Data Source and Study Population

NAMCS is conducted annually by the National Center for Health Statistics (NCHS) to collect information about patient, clinician, and office visit characteristics. Data from the 2012 NAS supplement(12) to NAMCS were released in 2017. Clinician eligibility for NAMCS was determined by responses to the Physician Induction Interview (PII).(11, 13) Participating clinicians who responded affirmatively to the PII asthma screener question (“Do you treat patients with asthma?”), regardless of specialty, were included in the NAS. Since 2006, NAMCS has included visits to office-based physicians and a panel of CHCs with up to three physicians and/or midlevel clinicians sampled per CHC. Sample selection is designed to produce nationally representative estimates for both NAMCS and CHC visits. Starting in 2012, the office-based component of NAMCS was split from the CHC component to produce separate data files for visits to private physician offices and CHCs to increase flexibility in use of patient visit data.(11) However, patient visit data from either component could not be linked to physician responses to the NAS supplement. This analysis utilized the 2012 NAS file released by NCHS that included NAMCS office-based physicians, CHC physicians and CHC mid-level clinicians. The 2012 NAS file included specific physician/clinician survey weights provided by NCHS. The NAMCS physician sampling frame included non-federally employed physicians who were classified as being engaged primarily in office-based patient care by the American Medical Association or the American Osteopathic Association and included general/family practitioners, internists, pediatricians and obstetricians. Specialty physicians in anesthesiology, radiology, and pathology, and those over age 85 years were excluded. Allergists and pulmonologists were oversampled to provide a sufficient sample size of asthma specialists for the NAS supplement. The CHC sampling frame included physicians and mid-level practitioners (i.e., physician assistants, nurse practitioners, and nurse midwives) from sampled CHC delivery sites. No asthma specialists were sampled in the CHC-based portion of the NAS. The NCHS Institutional Review Board approved NAS and informed consent was obtained from participating clinicians.

The unweighted and weighted response rates for the overall combined NAS sample were 38% and 28%, respectively, similar or higher than other national physician surveys.(14) The weighted response rate was higher for CHC providers (73%) than for NAMCS physicians (26%). Of the 1726 respondents, 49 were specialists unlikely to directly manage asthma, leaving 1677 eligible participants. Seventeen records were missing demographic data and were excluded from the sample. Clinician race/ethnicity was not included in the NAMCS questionnaire used in CHCs. Non-clinical respondents were also excluded (n=15). The final sample of 1645 included 1412 primary care clinicians (primary care physicians from the office-based and CHC samples and CHC mid-level practitioners from the CHC sample) and 233 asthma specialists (allergists and pulmonologists from the office-based sample). Available information on demographic characteristics included specialty, age, sex, and Census practice region, level of practice urbanization, practice ownership, and age of patient population.

Outcomes

Outcome variables were categorized into the four EPR-3 cornerstones of care: assessment and monitoring, patient education, environmental control, and pharmacologic treatment (Table E1). Clinician agreement with and adherence to specific EPR-3 recommendations and self-efficacy defined as clinician confidence in their ability to competently implement specific EPR-3 recommendations were determined by self-report (Table E2). Missing responses were low (0.01%-2.0%) and were excluded for individual outcomes.(15)

Indices for Agreement and Self-efficacy

The association between adherence and overall agreement and overall self-efficacy with providing guideline-based care were assessed using two index variables. An agreement index variable was defined dichotomously as a response of “strongly agree” versus all other responses to all 5 questions about agreement (Table E2). Similarly, a self-efficacy index variable was defined as a response of “very confident” versus all other responses for all 5 questions about self-efficacy (Table E2).

Statistical Analysis

Descriptive statistics were used to summarize clinician characteristics and outcome measures using provided sample weights to calculate nationally representative estimates. Differences between primary care clinicians and asthma specialists in distributions across response categories for guideline adherence outcomes were assessed using chi-square tests, with P<.05 (2-sided) considered statistically significant. Thus, P values in the text and tables reflect differences across the range of Likert scale response categories (e.g., “never (0% of the time)” to “almost always (75% to 100% of the time)” in Table II) rather than differences for one particular response category. Separate logistic regression models assessed the impact of agreement and self-efficacy on guideline adherence for each outcome that could be dichotomized to “almost always” versus all other responses. For some covariate categories, there were zero cells for asthma specialists. Therefore, the simplest models with the control indices for agreement and self-efficacy as the only independent variables are reported. Multivariate results that include additional covariates but that omit covariates with zero counts for any category are shown in the supplement. National estimates were calculated using NAS sample weights that accounted for the probability of clinician selection and non-response. Estimation of standard errors (SE) and statistical inference took the complex survey design into account. Analyses were conducted using SAS 9.4 (SAS Institute Inc., Cary, NC) and SUDAAN 11.0 (RTI, Research Triangle Park, NC). Estimates with a relative standard error >30% (SE/estimate) are flagged to indicate that these estimates have lower precision.

Table II.

Assessment and Monitoring of Asthma Severity and Control: Clinician - Reported Adherence to EPR - 3 Asthma Guideline Component 1

		Primary Care Clinicians			Asthma Specialists
	n	Almost always	Often	Sometimes /Never	Almost always	Often	Sometimes /Never	P Value
Assessment of impairment frequency, weighted % (SE)
Document asthma control	1550	32.0 (2.2)	44.6 (2.4)	23.4 (2.0)	76.8 (3.8)	20.5 (3.7)	2.7* (1.2)	<.001
Ask about ability to engage in normal activities	1625	48.4 (2.4)	38.7 (2.3)	12.9 (1.5)	84.5 (3.3)	14.9 (3.2)	0.6* (0.6)	<.001
Ask about frequency of daytime symptoms	1632	56.0 (2.3)	35.9 (2.3)	8.1 (1.3)	91.1 (2.5)	8.5 (2.5)	0.4* (0.4)	<.001
Ask about frequency of nighttime awakening	1630	53.4 (2.4)	31.8 (2.2)	14.8 (1.8)	81.7 (3.6)	14.9 (3.3)	3.4* (1.9)	<.001
Ask about perception of control	1629	50.7 (2.4)	33.1 (2.1)	16.2 (1.8)	70.7 (4.2)	26.0 (4.0)	3.3* (1.9)	<.001
Use control assessment tool	1629	13.2 (1.5)	17.2 (1.9)	69.7 (2.2)	28.6 (3.5)	20.4 (3.4)	51.0 (4.2)	<.001
Ask about frequency rescue inhaler	1632	72.3 (2.1)	23.1 (1.9)	4.6 (1.1)	90.6 (2.8)	6.5* (2.2)	2.9* (1.7)	<.001
Assessment of risk frequency, weighted % (SE)
Ask about oral steroid frequency	1629	52.9 (2.4)	34.0 (2.2)	13.1 (1.6)	86.8 (3.1)	11.6 (3.1)	1.6* (0.8)	<.001
Ask about ED visit frequency	1631	56.2 (2.3)	29.2 (2.0)	14.6 (1.8)	81.9 (3.4)	12.6 (3.2)	5.6* (2.2)	<.001
Objective assessment and monitoring, weighted % (SE)
Ask about peak flow results	1628	11.2 (1.5)	22.9 (2.0)	65.9 (2.2)	12.8 (2.5)	27.9 (3.7)	59.3 (4.1)	.34
Perform spirometry	1611	10.8 (1.6)	25.1 (2.0)	61.6 (2.2)	44.7 (4.1)	35.0 (4.0)	20.3 (4.0)	<.001
Ongoing monitoring frequency, weighted % (SE)
Assess daily controller use for persistent asthma	1625	59.5 (2.3)	31.6 (2.1)	8.9 (1.4)	91.7 (2.4)	8.2 (2.4)	0.2* (0.1)	<.001
Repeated assessment of inhaler technique	1627	16.8 (1.7)	38.7 (2.4)	44.6 (2.3)	39.7 (4.0)	44.9 (4.3)	15.5 (3.0)	<.001

^*The relative standard error is >30%.

ED: emergency department; EPR-3: Expert Panel Report 3; SE: standard error Data Source: NCHS, National Asthma Survey of Physicians, 2012.

Results

Compared to primary care clinicians, asthma specialists were more likely to be older, male, work in private practice settings, and practice in the South, and in large metropolitan areas (Table I). Asthma specialists were less likely to exclusively treat pediatric populations.

Table I.

National Asthma Survey clinician characteristics, 2012

	Total (n=1645)		Primary care cliniciansa (n=1,412)	Asthma specialistsb (n=233)
	n	weighted % (SE)	weighted % (SE)	weighted % (SE)	P Valuec
Clinician age (years)
<40	372	15.6 (1.4)	16.0 (1.5)	9.5 (2.3)	.004
40 - 59	907	60.3 (2.1)	60.6 (2.2)	54.0 (4.1)
60+	366	24.1 (1.9)	23.4 (2.0)	36.5 (4.0)
Clinician sex
Female	772	40.0 (2.0)	41.4 (2.1)	15.7 (2.7)	<.001
Male	873	60.0 (2.0)	58.6 (2.1)	84.3 (2.7)
Ownership of practice
Private	653	61.7 (1.8)	60.3 (2.0)	84.4 (2.8)	<.001
CHC	688	16.0 (0.8)	17.0 (0.8)	0.0* (0.0)
HMO, Academic Center, Other hospital/health care corporation	194	16.1 (1.6)	16.4 (1.7)	12.0 (2.5)
missing	110	6.2 (1.1)	6.3 (1.2)	3.6* (1.4)
Census region
Northeast	255	20.7 (0.9)	20.6 (0.9)	21.1 (2.0)	.007
Midwest	400	19.5 (0.6)	19.6 (0.7)	17.8 (1.5)
South	553	30.2 (0.8)	29.7 (0.9)	38.0 (2.7)
West	437	29.7 (0.8)	30.1 (0.9)	23.2 (1.8)
Level of urbanization
Large Metro	737	56.8 (1.9)	56.3 (2.0)	66.5 (3.8)	.002
Medium/Small Metro	532	28.8 (1.9)	28.9 (2.0)	27.2 (3.7)
Non - metro	376	14.3 (1.1)	14.8 (1.2)	6.3* (2.2)
Patient population
Pediatric only	333	22.6 (1.7)	23.4 (1.8)	8.2* (2.8)	<.001
Adult or all ages	1312	77.4 (1.7)	76.6 (1.8)	91.9 (2.8)

^aPrimary care clinicians include general/family practitioners, internists, pediatricians, obstetricians and CHC mid-level providers.

^bAsthma specialist include allergists and pulmonologists.

^cChi-square test for difference between primary care clinicians and asthma specialists.

^*The relative standard error is >30%. Source: NCHS, National Ambulatory Medical Care Survey, 2012.

EPR-3 Component 1: Assessment and Monitoring of Asthma Severity and Control

EPR-3 recommends that clinicians assess asthma impairment (symptom frequency and asthma control) and risk for adverse outcomes (hospitalizations, ED visits, and courses of systemic corticosteroids) during clinic visits. A higher percentage of asthma specialists almost always assessed all measures of asthma impairment than primary care clinicians, including a patient’s ability to engage in normal daily activities (84.5% versus 48.4%), frequency of daytime symptoms (91.1% versus 56.0%) and nighttime awakenings (81.7% versus 53.4%), and patient’s perception of control (70.7% versus 50.7%) (P<0.001 for distributional comparison across the Likert scale for all comparisons) (Table II). Most primary care clinicians (72.3%) asked about frequency of rescue inhaler use, albeit less frequently than asthma specialists (90.6%; P<.001). In contrast, use of a control assessment tool (e.g., Asthma Control Test, Asthma Control Questionnaire, Asthma Therapy Assessment Questionnaire, or similar tool) was low in both groups. More than half of the specialists (51.0%) and 69.7% of the primary care clinicians reported that they either sometimes or never used such tools. Indeed, 39.7% of primary care clinicians and 28.9% of specialists reported that they never used control assessment tools (data not shown).

The assessment of risk also differed between the two groups (Table II). While 86.8% and 81.9% of asthma specialists reported almost always asking patients about oral steroid use and emergency department (ED)/urgent care visits, fewer primary care clinicians (52.9% and 56.2%, respectively; P<.001 for comparison between clinician groups) almost always assessed these risk factors for adverse outcomes.

Both groups reported low frequencies of objective asthma assessment and monitoring. Only 11.2% of primary care clinicians and 12.8% of specialists almost always asked about home peak flow results (P=.34). Specialists were more likely to report almost always performing spirometry than primary care clinicians (e.g., 44.7% versus 10.8%; P<.001). The 64.1% of primary care clinicians who reported that they sometimes or never performed spirometry was made up of 36.3% who sometimes and 27.8% who never performed spirometry.

Asthma specialists were more likely to report assessing daily controller use for persistent asthma than primary care clinicians (91.7% versus 59.5% respectively, P<.001). Repeated assessment of inhaler technique was less frequently reported by both groups: 39.7% of asthma specialists reported almost always assessing technique versus 16.8% of primary care clinicians (P<.001).

EPR-3 Component 2: Patient Education

Guideline-recommended patient education items covered in the survey included the frequency of providing asthma action plans (Likert scale), and whether or not the clinician provided trigger and risk education, inhaler use observation and advised changing home and work environment (Table III). Although written asthma action plans can improve asthma-related outcomes,(1, 16, 17) only 30.6% (SE 3.6) of specialists and 16.4% (SE 1.6) of primary care clinicians used them almost always (P <.001), and 6.1% (SE 2.3, RSE>30%) and 17.6% (SE 1.8) never used them, respectively (P <.001) (Table III, Panel A). Almost all specialists reported providing patient education regarding asthma symptom recognition, avoiding risk factors, inhaler technique and changing the home/work environment. Primary care providers also reported providing patient education in these areas with a high frequency but with a lower frequency than specialists, especially for inhaler use observation (Table III, Panel B).

Table III.

Patient education: Clinician-Reported Adherence to EPR-3 Asthma Guideline Component 2

		Primary Care Clinicians				Asthma Specialists
Panel A: Frequency of asthma action plan provision, Likert scale (weighted %, SE)
	n	Almost always	Often	Sometimes	Never	Almost always	Often	Sometimes	Never	p-value
Provide asthma action plan with medication, triggers, etc	1625	16.4 (1.6)	30.7 (2.2)	35.4 (2.2)	17.6 (1.8)	30.6 (3.6)	32.7 (4.1)	30.6 (4.3)	6.1* (2.3)	<0.001
Panel B: Provision of patient education, yes versus no (weighted %, SE)
	n	Yes		No		Yes		No
Educate patient to recognize symptoms	1645	95.2 (1.0)		4.8 (1.0)		99.9 (0.1)		0.1* (0.1)		<0.001
Educate patient to avoid risk factors	1645	96.1 (0.8)		3.9 (0.8)		99.9 (0.1)		0.1* (0.1)		<0.001
Observe inhaler use	1621	73.1 (2.1)		26.9 (2.1)		99.5 (0.3)		0.5* (0.3)		<0.001
Advise patient to change home/work environment	1645	89.5 (1.6)		10.5 (1.6)		95.5 (1.6)		4.5* (1.6)		0.009

^*The relative standard error is >30%.

Both groups reported patient concerns and misunderstandings about asthma pharmacologic therapies (Figure 1). Both groups reported patients sometimes or often misunderstood medication risks, were concerned about the side effects of inhaled corticosteroid (ICS) therapy, and were confused between rescue and controller medications. Specialists, however, more often than primary care clinicians reported that patients were almost always concerned about long-term ICS effects (8.6% versus 5.1%; P=.002) while primary care clinicians more often reported that patients were almost always confused rescue and controller medications, although the estimate for asthma specialists had an RSE>30% (11.7% versus 4.0%; P=.004).

Figure 1.

Clinician reported frequency of patient misunderstanding and concerns about asthma medications

Note: Results for all four medication questions differ statistically significantly between primary care clinicians and allergy specialists (chi square P value<.05).

* Relative standard error > 30%.

Source: NCHS, National Ambulatory Medical Care Survey, 2012.

EPR-3 Component 3: Control of Environmental Factors

Control of environmental factors can reduce asthma morbidity.(18) Asthma specialists were more likely to assess environmental triggers at home, school and/or workplace than primary care clinicians (Table IV). Specialists more often (67.3%) reported performing allergy testing “almost always” or “often” versus 24.8% of primary care clinicians (P<.001). Nearly a third (30.4%, SE 2.2) of primary care clinicians reported never performing these tests versus 5.3% (SE 2.1) of specialists (P<.001) (data not shown).

Table IV.

Control of Environmental Factors: Clinician-Reported Adherence to EPR-3 Asthma Guideline Component 3

		Primary Care Clinicians			Asthma Specialists
	n	Almost always	Often	Sometimes /Never	Almost always	Often	Sometimes /Never	P Value
Assessment of triggers, weighted % (SE)
Assess home triggers	1628	40.1 (2.3)	42.0 (2.3)	17.9 (1.8)	58.7 (4.2)	35.2 (4.2)	6.1* (2.2)	<.001
Assess school or workplace triggers	1619	35.4 (2.3)	38.4 (2.2)	26.2 (2.0)	71.3 (3.9)	24.2 (3.6)	4.5* (2.0)	<.001
Test for allergic sensitivity	1617	7.2 (1.4)	17.6 (1.8)	75.3 (2.1)	35.0 (3.6)	32.3 (4.1)	32.8 (4.0)	<.001
Recommendations, weighted % (SE)	n	Most patients	Patients with sensitivity	Sometimes/never recommend	Most patients	Patients with sensitivity	Sometimes/never recommend	P Value
Recommend d ust mite control measures	1609	40.8 (2.3)	46.8 (2.4)	12.4 (1.5)	36.5 (3.8)	56.8 (3.9)	6.8* (2.3)	.039
Recomme nd control of mold and pests	1608	44.1 (2.4)	42.6 (2.3)	13.3 (1.7)	46.9 (4.4)	47.1 (4.3)	6.0* (2.3)	.025
Recommend pet removal	1609	28.6 (2.1)	59.8 (2.3)	11.6 (1.4)	29.3 (3.9)	58.8 (4.1)	11.9 (2.4)	.97
Recommend avoiding pollen	1611	43.3 (2.3)	47.7 (2.3)	9.1 (1.6)	37.3 (4.4)	55.4 (4.3)	7.3 (1.9)	.28
Recommend avoiding air pollution	1604	44.8 (2.3)	33.6 (2.2)	21.6 (2.1)	63.2 (4.2)	30.0 (4.1)	6.8 (1.9)	<.001
Recommend cooking appliance change	1610	16.2 (1.8)	30.7 (2.2)	53.1 (2.4)	21.7 (3.5)	33.6 (4.0)	44.7 (4.3)	.18
Recommend avoiding ETS	1611	83.5 (1.8)	12.2 (1.5)	4.3 (1.1)	85.4 (3.3)	12.7 (3.2)	1.9* (0.8)	.24

^*The relative standard error is >30%.

EPR-3: Expert Panel Report 3; ETS: environmental tobacco smoke; SE: standard error Data Source: NCHS, National Asthma Survey of Physicians, 2012.

Recommendations for control of environmental factors differed between specialists and primary care clinicians. Primary care clinicians were less likely to recommend dust mite, mold and pest control measures than specialists but almost 60% of all clinicians recommended removing pets from homes with pet-sensitive patients. While both clinician groups provided recommendations on pollen avoidance, recommendations regarding cooking appliances were infrequent (i.e., 44.7%-53.1% of clinicians sometimes or never gave recommendations). The majority of specialists and primary care clinicians (>83%) recommended environmental tobacco smoke (ETS) avoidance, whereas air pollution avoidance was more frequently recommended by specialists. The biggest differences between primary care clinicians and specialists were observed for recommendations regarding air pollution avoidance. Specialists more often recommended air pollution avoidance for most patients than primary care clinicians (63.2 % vs 44.8%; P<.001). In addition, more primary care clinicians sometimes/never recommended air pollution avoidance as compared to specialists (21.6% vs 6.8%; P<.001).

EPR-3 Component 4: Pharmacologic Treatment

Self-reported medication prescription for both groups was consistent with EPR-3 recommendations (e.g., short-acting beta agonists for symptom relief, and ICS for difficult to control asthma, add-on daily control and long-term control) (Figure 2). Asthma specialists reported greater use of other asthma medications than primary care clinicians (e.g., the percentage reporting never using specific medications was 16.6% of specialists versus 42.2% of primary care providers for long-course oral steroids, 14.1% versus 83.3% for Omalizumab, 45.9% versus 75.3% for methylxanthines, and 13.7% versus 30.6% for anticholinergics). Both groups prescribed short courses of oral steroids for asthma exacerbations, but specialists were less likely to prescribe short course oral steroids for symptom relief (43.2% versus 56.9%), and more likely to prescribe this medication for difficult-to-control asthma (60.7% versus 45.1%) and as add-on daily therapy (12.1% versus 5.3%) (P<0.05 for all comparisons).

Figure 2.

Clinician-Reported Use of Asthma Medications, by Specialty

† P Value <.05 for pairwise difference between asthma specialists and primary care.

* Relative standard error > 30%.

Source: NCHS, National Ambulatory Medical Care Survey, 2012.

Agreement and Self-Efficacy with EPR-3 Guideline Recommendations

More asthma specialists than primary care clinicians agreed strongly with the EPR-3 recommendations regarding spirometry for asthma diagnosis (77.6% versus 35.5%), the effectiveness of inhaled corticosteroids (ICS) for persistent asthma (76.0% versus 48.3%), twice yearly follow-up visits for persistent asthma (68.8% versus 48.9%) and assessment of asthma severity for initial treatment (79.3% versus 50.3%) (P<0.001 for all comparisons) (Table V, Panel A). In contrast, less than half of specialists and primary care clinicians strongly agreed that asthma action plans are effective, but strong agreement was still higher among specialists (41.0% versus 30.6%, P=.026). Strong agreement with all five guideline recommendations included in the survey was higher among specialists than primary care clinicians (27.9% versus 12.1%, P<.001).

Table V.

Clinician-Reported Agreement and Self-efficacy with EPR-3 Asthma Guidelines

		Primary Care Clinicians	Asthma Specialists
Panel A: Agreement, weighted % (SE)	n	Strongly agree	Strongly agree	P Valuea
Spirometry is essential for diagnosis	1638	35.5 (2.3)	77.6 (3.8)	<.001
ICS are effective for persistent asthma	1633	48.3 (2.3)	76.0 (3.4)	<.001
Asthma Action Plans are effective	1639	30.6 (2.1)	41.0 (4.1)	.0258
Follow up visits for persistent asthma every 6 months	1639	48.9 (2.3)	68.8 (3.5)	<.001
Assessing severity is necessary for initial therapy	1632	50.3 (2.4)	79.3 (3.3)	<.001
Overall agreement index	1642	12.1 (1.4)	27.9 (3.9)	<.001
Panel B: Asthma Self - efficacy, weighted % (SE)	n	Very confident	Very confident
Confidence using spirometry	1636	37.0 (2.3)	92.8 (2.1)	<.001
Confidence assessing severity	1635	49.4 (2.4)	81.3 (3.5)	<.001
Confidence prescribing ICS	1642	65.2 (2.2)	91.1 (2.2)	<.001
Confidence step ping up therapy	1641	64.5 (2.3)	89.5 (2.4)	<.001
Confidence step ping down therapy	1639	49.8 (2.4)	87.0 (2.6)	<.001
Overall self - efficacy index	1642	21.5 (2.1)	72.3 (3.9)	<.001

	Primary Care Clinicians			Asthma Specialists
Panel C: Association between adherence and strong agreement and high self-efficacy, OR (95% CI)b	n	Strong agreement (vs other)	High self-efficacy (vs. other)	n	Strong agreement (vs. other)	High self-efficacy (vs other)
Provide Asthma Action Plan	1391	2.0 (1.1, 3.6)*	2.4 (1.3, 4.3)*	233	1.6 (0.7, 3.3)	1.1 (0.5, 2.5)
Document asthma control	1321	1.4 (0.8, 2.5)	1.8 (1.0, 3.0)*	226	0.8 (0.3, 2.1)	1.5 (0.6, 3.5)
Ask about ability to engage in normal activities	1392	1.7 (0.9, 3.2)	2.1 (1.2, 3.5)*	232	1.3 (0.4, 4.4)	1.5 (0.6, 4.3)
Ask about frequency of daytime symptoms	1398	1.5 (0.8, 2.9)	2.3 (1.3, 4.1)*	233	1.6 (0.4, 7.5)	3.9 (1.0, 16.0)
Ask about frequency of nighttime awakenings	1396	1.4 (0.8, 2.5)	1.7 (1.0, 2.9)	233	0.7 (0.2, 2.0)	2.7 (0.9, 7.8)
Ask about patient perception of control	1395	0.9 (0.5, 1.5)	1.9 (1.1, 3.3)*	233	1.6 (0.6, 4.3)	1.2 (0.4, 3.0)
Use a control assessment tool	1395	1.5 (0.8, 2.9)	1.7 (0.9, 3.0)	233	1.0 (0.5, 2.1)	1.3 (0.6, 2.9)
Ask about frequency of rescue inhaler use	1398	2.9 (1.6, 5.5)*	2.7 (1.5, 4.7)*	233	0.4 (0.1, 2.2)	3.0 (0.6, 14.4)
Ask about ED visit frequency	1398	1.3 (0.7, 2.3)	3.0 (1.8, 4.8)*	232	0.8 (0.3, 2.8)	2.9 (1.0, 8.4)
Ask about oral steroid frequency	1396	1.1 (0.6, 2.1)	4.3 (2.6, 7.1)*	232	0.7 (0.2, 2.8)	1.4 (0.4, 5.1)
Ask about home peak flow results	1396	2.0 (1.0, 4.0)	3.1 (1.6, 6.1)*	231	1.8 (0.7, 5.0)	2.4 (0.8, 7.6)
Perform spirometry	1378	2.1 (0.9, 4.7)	6.3 (3.0, 13.4)*	232	1.1 (0.5, 2.2)	4.3 (2.0, 9.0)*
Assess daily controller use for persistent asthma	1392	1.9 (1.1, 3.2)*	2.4 (1.4, 4.4)*	232	0.7 (0.2, 2.7)	2.0 (0.6, 6.6)
Repeated assessment of inhaler technique	1393	1.5 (0.7, 2.9)	2.8 (1.6, 5.0)*	233	1.5 (0.8, 3.1)	0.8 (0.4, 1.9)
Assess home triggers	1394	1.5 (0.9, 2.5)	3.3 (1.9, 5.5)*	233	0.8 (0.4, 1.7)	1.9 (0.9, 4.2)
Assess school or workplace triggers	1408	1.4 (0.8, 2.4)	4.1 (2.5, 6.9)*	233	0.8 (0.3, 1.7)	1.5 (0.7, 3.6)
Test for allergic sensitivity	1383	1.3 (0.5, 3.7)	6.0 (2.5, 14.4)*	233	1.1 (0.5, 2.4)	1.8 (0.9, 3.8)

^*P<.05.

^aChi-square test for difference between primary care clinicians and asthma specialists.

^bLogistic regression models stratified by primary care clinicians and asthma specialists. Independent variables included agreement index (strong agreement versus all other responses) and self-efficacy index (high self-efficacy versus all other responses). See Supplemental Table e4 for logistic regression models with additional covariates.

CI: confidence interval; ED: emergency department; EPR-3: Expert Panel Report 3; ICS: inhaled corticosteroids; SE: standard error

Data Source: NCHS, National Asthma Survey of Physicians, 2012

Asthma specialists reported higher self-efficacy with providing guideline-recommended care than primary care clinicians (Table V, Panel B). Specialists were very confident in using spirometry (92.8%), in assessing severity (81.3%), in prescribing inhaled corticosteroids (91.1%), and in stepping up or down therapy (89.5%, 87.0%), while percentages were lower among primary care clinicians (37.0%, 49.4%, 65.2%, 64.5%, and 49.8%, respectively; P <.001). Accordingly, self-efficacy for all five recommendations was higher among specialists than primary care clinicians (72.3% versus 21.5%, P<.001).

The association between guideline agreement and self-efficacy with self-reported adherence to guideline recommendations was analyzed for outcomes for which responses could be dichotomized as “almost always” performed versus other responses (Table V, Panel C). Strong agreement was not associated with almost always performing any guideline component for either clinician group with three exceptions. In unadjusted models, among primary care clinicians, agreement with guidelines was significantly associated with almost always providing a written asthma action plan (OR 2.0, 95% CI 1.1, 3.6), almost always asking about the frequency of rescue inhaler use (OR 2.9, 95% CI 1.6, 5.5) and assessing daily controller use (OR 1.9, 95% CI 1.1, 3.2), but not among specialists. For primary care clinicians, higher self-efficacy in providing guideline components was associated with higher adherence to most guideline recommendations. For specialists, high self-efficacy was associated with higher odds of performing spirometry (OR 4.3, 95% CI 2.0, 9.0). In models adjusted for clinician age, sex, and region (Table E3), guideline agreement was associated with asking about rescue inhaler use, home peak flow monitoring, and assessing daily controller use for persistent asthma, but not with providing a written asthma action plan for primary care clinicians. Self-efficacy continued to be associated with adherence to most guideline recommendations for primary care clinicians in adjusted models but not for specialists in whom only high self-efficacy regarding spirometry and testing for allergic sensitivity were associated with guideline agreement (Table E3).

Discussion

In this representative sample of U.S. clinicians, most asthma specialists but less than half of primary care clinicians strongly agreed with key EPR-3 guideline recommendations for asthma assessment and treatment including use of spirometry, ICS therapy, follow-up visits for persistent asthma and assessment of asthma severity. Self-reported asthma medication use for both groups was consistent with EPR-3 recommendations and more than 80% of both clinician groups recommended ETS avoidance. Specialist self-efficacy overall was higher than primary care clinician self-efficacy and for most measures, including environmental control assessment and testing, specialist assessment and monitoring were higher. Primary care clinicians with high self-efficacy in using the guidelines more likely reported guideline adherence while guideline agreement was generally not associated with adherence for either group. This suggests that further efforts to increase clinician self-efficacy might increase guideline use and adherence.

While the lack of strong endorsement of guideline recommendations among primary care clinicians is notable, there were several key guideline recommendations that were not strongly endorsed by either group including the provision of a written asthma action plan. This result extends published data from several smaller studies and is in contrast to the evidence (Grade B, small number of randomized control trials) that support use of treatment plans (19–23) although their effectiveness when used by specialists has recently been questioned.(24) In addition, neither of the clinician groups reported frequent use of asthma control assessment tools, and home peak flow assessment rates were especially low. Furthermore, rates of adherence to spirometry testing and repeated inhaler technique assessment were low among both specialists and primary care clinicians.

It is possible that the strength and/or the “age” of the scientific evidence supporting the recommendation influence agreement and adherence. The 2007 EPR-3 guidelines used an evidence-based approach to assess strength of evidence for the first time. The EPR-3 guidelines were also the first to recommend routine spirometry (Grade B and C, observational studies), the assessment of risk in the determination of asthma severity (Grade C and D, expert panel consensus) and use of peak flow testing (Grade B).(1) However, the low uptake of components supported by higher grade evidence such as spirometry, asthma treatment plans, and peak flow testing suggests that adherence may not be directly related to strength of evidence. Of note, the survey did not ask clinicians about perceived usefulness of guideline recommendations, a factor related to adherence in smaller studies.(19) Time constraints, clinical inertia, and workflow barriers are factors in addition to agreement and self-efficacy that affect adherence, and these factors may work differently for primary care clinicians compared to specialists.(3, 8, 10, 25) Further studies to understand barriers may be needed, especially in primary care which provides most of the asthma care in the US.

Results from this study could be used to help guide the NAEPP recommendations that are currently being revised. These revised guidelines should carefully assess the strength of evidence for specific recommendations, identify areas and approaches to implementation that are specific for primary care clinicians and specialists, and focus clinical research on strengthening recommendations that are currently not embraced by clinicians. The guidelines also need to recommend new approaches to meeting patient concerns and to improving adherence by addressing barriers, especially workflow barriers.

Perceptions of patient concerns were more similar than disparate, but primary care clinicians reported greater patient confusion between controller and rescue medications whereas specialists reported more patient concerns regarding long-term corticosteroid therapy. This and other observed differences may reflect differences in disease severity and visit duration. Specialists care for patients with greater asthma severity and may spend more time explaining how to use asthma medications as their patient visits are longer compared to primary care clinicians.(25)

Strengths of the NAS include the national-representativeness of the survey sample, the inclusion of both adult and pediatric generalists and specialists, examination of the 4 cornerstones of the 2007 NAEPP guidelines and the inclusion of guideline agreement and clinician self-efficacy. Two other studies have reported asthma guideline results in primary care clinicians—one (26) reported low utilization of spirometry in the assessment of newly diagnosed patients with asthma, while the other (27) surveyed both clinicians and patients and noted low use of asthma treatment plans and spirometry. In contrast to these studies, this study offers valuable insight into areas of guideline disagreement and where additional evidence may be needed to achieve behavior changes. The differences between primary care clinicians and specialists suggest that the achievement of guideline adherence may require interventions specifically tailored to different groups of clinicians and to different health care systems and settings.

Although new literature/evidence has accumulated since 2007, the results reflect clinical practice after the latest guideline update. Self-reported behaviors are subject to social and recall bias, and actual behavior might differ.(27) Low response rates are known limitations in physician surveys,(28) and declining trends have been reported.(29, 30) The NAS response rate is, however, higher than the 2014 National Physician Survey which surveyed 63,817 physicians and had a response rate of 16%.(14) The characteristics of the NAS asthma specialists were also comparable to the allergists in a 2014 workforce survey.(31) NCHS evaluated whether lower response rates and the changes in the design and implementation (larger sample size, electronic data collection) introduced bias in 2012 NAMCS and found no or minimal bias in physician-level estimates.(29)

In conclusion, overall agreement, confidence and adherence to the EPR-3 guidelines are higher for specialists than primary care clinicians but vary between different elements. Low rates of agreement and adherence are reported for several important core elements of the guidelines including use of a written asthma treatment plan, use of an asthma control assessment tool, home peak flow monitoring, spirometry performance, repeated assessment of inhaler technique, and environmental control assessment and testing. Follow-up studies to examine reasons for low adherence and interventions designed to increase adherence in these areas may improve guideline use and overall asthma care and may reduce asthma morbidity.

Highlights.

What is known about this topic?

Adherence to the 2007 National Asthma Education and Prevention Program’s (NAEPP) Expert Panel Report 3 asthma guidelines have been suboptimal, and a long-standing target of implementation interventions. However, little national data are available on adherence.

What does this article add to our knowledge?

Nationally representative data shows higher adherence among asthma specialists versus primary care clinicians, and highlights overall low clinician adherence with written asthma action plans, home peak flow monitoring, spirometry testing and assessment of inhaler technique.

How does this study impact current management guidelines?

Among primary care physicians who deliver the majority of asthma care, self-efficacy with the recommended measures was a predictor of higher adherence. These data highlight areas for progress in realizing clinical asthma guidelines.

Abbreviations

AAP

Asthma Action Plan

CHC

Community Health Center

EPR-3

Expert Panel Report 3

ETS

Environmental Tobacco Smoke

ICS

Inhaled corticosteroids

LABA

Long acting beta agonist

NAEPP

National Asthma Education and Prevention Program

NAMCS

National Ambulatory Medical Care Survey

NAS

National Asthma Survey of Physicians

RSE

relative standard error