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Bravata DM, Sundaram V, Lewis R, et al. Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 5: Asthma Care). Rockville (MD): Agency for Healthcare Research and Quality (US); 2007 Jan. (Technical Reviews, No. 9.5.)

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Closing the Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol. 5: Asthma Care).

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2Methods

We sought articles describing evaluations of quality improvement strategies designed to improve the care of patients with asthma. In the sections that follow, we describe the types of QI strategies and study designs that we considered eligible for inclusion in this review.

Types of Quality Improvement Strategies

We defined QI strategies as interventions aimed at reducing the quality gap (the difference between health care processes or outcomes observed in practice and those potentially obtainable on the basis of current professional knowledge) for a group of patients representative of those encountered in routine practice.19 By modifying several well-established classification systems,2023 we developed a taxonomy of nine QI strategies,19 including patient education, provider education, organizational change, audit and feedback, provider reminders, patient reminders, facilitated relay of clinical data to providers, financial or legislative incentives, and the promotion of self-monitoring or self-management. Table 1 presents the QI strategy definitions used for this report. We direct interested readers to a complete description of the taxonomy of QI strategies and the methods used to develop it.19

Table 1. Definitions of the nine quality improvement strategies used in the Closing the Quality Gap series.

Table 1

Definitions of the nine quality improvement strategies used in the Closing the Quality Gap series.

Inclusion and Exclusion Criteria

We sought English language studies of interventions that included one or more of these nine QI strategies for the outpatient management of children and adults with asthma. We adopted the NHLBI definition of asthma.8 Included articles had to evaluate QI interventions in the outpatient setting. We defined outpatient programs broadly (e.g., including school-based programs, self-monitoring or self-management programs, and clinician-based interventions).

Because most health care is delivered in settings where continuous QI efforts are occurring, evaluations of QI strategies that are not randomized or controlled may be subject to confounding from other QI programs ongoing in the facility or region. Thus, included trials had to have one of three types of study designs: randomized controlled trials (RCTs) (including quasi-RCTs which typically allocated patients according to non-random means such as “every other patient” was assigned to the intervention or control group), controlled before-after trials, or interrupted time series trials. Given the seasonal nature of asthma in many patients, we required that controlled before-after trials included contemporaneous observation periods for control and intervention groups. We required that articles reporting interrupted time series trials provided data at three or more time points both before and after intervention to facilitate time trend analysis.

Included studies had to report at least one of the four following primary outcomes: measures of clinical status (monitoring of medications, symptoms or symptom-free days, peak flow or spirometric measures, number of asthma attacks); measures of functional status (days lost from work or school, 6-minute walk times, school grades); measures of health services utilization (hospital admissions, ED visits, unscheduled MD visits); or measures of adherence to guidelines (e.g., number of patients given prescriptions for inhaled corticosteroids).

Search Strategy

We searched four literature sources: MEDLINE® (1966 to April 2006), the Cochrane Effective Practice and Organisation of Care (EPOC) Group databases (1966 to April 2006), the Cochrane Consumers and Communication Group database (1966 to May 2006), and bibliographies of retrieved articles.

The EPOC databases contain the results of extensive periodic searches of MEDLINE® (from 1966-present), CINAHL® (1982-present), and EMBASE® (1980-present), and hand searches of journals and article bibliographies.24 These EPOC searches are aimed at identifying studies that attempt to “improve professional practice and the delivery of effective health care services,” regardless of clinical topic. The EPOC strategy for identification of studies meeting this definition has a sensitivity of 92.4%.24 The articles identified by initial EPOC searches are triaged into different registries depending on EPOC's inclusion/exclusion criteria. The main EPOC registry primarily includes studies of provider and system-targeted interventions. To maximize our yield of articles, an EPOC research librarian searched the main registry, other EPOC registries, as well as the larger database of initially identified articles.

Because the EPOC databases are restricted to studies targeting provider and system-based interventions, we also performed separate searches of the Cochrane Consumers and Communication Group database and MEDLINE® to identify articles involving patient education or self-monitoring or self-management. The Cochrane Consumers and Communication Group database includes studies that focus on “consumers' interactions with health care professionals, services and researchers.”25 Our detailed search strategies are presented in Appendix A *.

Data Abstraction and Evaluation

Two independent investigators reviewed the title and abstract of each article found in our search to determine if the article met inclusion criteria (Appendix B *). All disagreements were resolved by repeated review and discussion. Articles requiring full text review were abstracted by a single investigator and then all abstracted data were verified by a second abstracter. Throughout the abstraction process, the investigators engaged in an active dialog about specific articles and reviewed questions regarding data abstraction to maintain a consensus approach among abstractors.

From each of the included studies we abstracted data about the study design, participants, detailed descriptions of the QI intervention, and the reported outcomes. In addition to the primary outcomes, we also abstracted data about the following secondary outcomes: cost of the QI strategy implementation; patient or provider satisfaction; quality of life (QOL) outcomes (for either patients with asthma or their caregivers); and reduction in environmental allergens (e.g., tobacco, pets/dander, cockroach antigen). The complete full-text abstraction form is provided in Appendix B *.

Multiple articles describing the same population were included only once in our analyses.

Statistical Analysis

Univariate Analyses

We used exploratory univariate analyses to identify the patient, intervention, and study design characteristics associated with the four primary outcomes of interest (clinical status, functional status, health services utilization, and adherence to guidelines). Because we make multiple comparisons, we recommend rejecting the null hypothesis for p values≤0.0125 (0.05 ÷ 4 = 0.0125)—we provide p values and 95% confidence intervals when possible.

We sought evidence of publication bias by evaluating the association between the sample size of a study and the likelihood of that study reporting statistically significant outcomes by visual inspection of funnel plots and calculation of unweighted correlation coefficients between sample size and the likelihood of reporting statistically significant outcomes.

For each type of intervention evaluated in a particular population (e.g., patient education strategies for children) for which 15 or more studies presented data on the same specific outcome (e.g., school absenteeism), we calculated both weighted mean differences and standardized mean differences between intervention and control groups at the end of the trial using a random effects model. We only performed this calculation for outcomes of 15 or more because the purpose of these analyses was to evaluate the predictors of these outcomes and needed to have at least 15 observations to have the statistical power to find such an effect. We performed these calculations using RevMan software version 4.2.8.26 To be included in a weighted mean difference or standardized mean difference calculation, studies must report an estimate of variance—if the included studies did not report an estimate of variance, we used a mean variance from the other studies reporting that outcome.

The weighted mean difference has the same units as the outcome of interest; thus, it is relatively easy to interpret. However, the standardized mean difference, which is unitless and therefore somewhat less readily interpretable, is less subject to bias. We present both effect sizes in the text. However, we used the more stable standardized mean difference as the dependent variable in our regression analyses seeking the association between study and intervention design characteristics and changes in the outcomes of interest (see below, in the section on multivariate analyses, for additional details on those analyses).

To minimize heterogeneity, we only synthesized those studies describing similar interventions in similar populations. We performed formal assessments of heterogeneity for our summary weighted mean differences and present the Chi2 statistic for heterogeneity. Additionally, we calculated the I2 statistic measuring the extent of inconsistency among the studies' results—which is interpreted as the approximate proportion of total variation in study estimates that is due to heterogeneity rather than sampling error.26 I2 statistics in excess of 50% are considered heterogeneous.

Multivariate Analyses

For those types of intervention for which we found 15 or more studies reporting on the same outcome, we performed multivariate analyses to evaluate the association between study design characteristics (e.g., duration of the study, whether the study specified the use of an underlying theoretical or conceptual framework) and intervention characteristics (e.g., the setting of the intervention, whether there were multiple QI strategies utilized) and the four primary outcomes of interest (i.e., clinical status, functional status, health services utilization, and adherence to guidelines). For these analyses, we used the standardized mean difference in the outcome of interest as the dependent variable in a weighted least squares regression (weighted by the study sample size).

For those types of interventions for which no specific outcomes were reported by 15 or more studies, we performed logistic regression to evaluate the association between study design and intervention characteristics and the reporting of statistically significant improvements in each of the four primary outcomes of interest.

Peer Review Process

A draft of this Evidence Report was sent to a panel of 15 experts in quality improvement, patient education, and asthma (Appendix D *). Their comments were incorporated into the final Report.

Footnotes

NHLBI Definition: “Asthma is a chronic inflammatory disorder of the airways in which many cells and cellular elements play a role, in particular, mast cells, eosinophils, T lymphocytes, neutrophils, and epithelial cells. In susceptible individuals, this inflammation causes recurrent episodes of wheezing, breathlessness, chest tightness, and cough, particularly at night and in the early morning. These episodes are usually associated with widespread but variable airflow obstruction that is often reversible either spontaneously or with treatment. The inflammation also causes an associated increase in the existing bronchial hyperresponsiveness to a variety of stimuli.”

*

Appendixes cited in this report are provided electronically at http://www.ahrq.gov/clinic/tp/asthmagaptp.htm

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