Asthma-specific quality of life and a history of acute episodes can be used together to identify risks of subsequent acute exacerbations.
Michael Schatz, MD; Robert S. Zeiger, MD, PhD; David Mosen, PhD; and William M. Vollmer, PhD
Asthma is a common medical problem that causes substantial morbidity, including hospitalizations and unscheduled physician and emergency department visits.1,2
Moreover, chronic asthma is associated with very large direct and indirect costs, with a large portion of the direct costs attributable to emergency hospital care.3
Several studies have shown that asthma-specific quality of life is associated with the subsequent risk of emergency hospital care.4-7
For this information to be clinically useful, though, a cut-point score on the quality-of-life measure needs to be defined, so that patients can be classified meaningfully according to higher and lower risk for subsequent exacerbations. None of the prior studies have attempted to establish the optimal quality-of-life cut-point score that maximizes both sensitivity and sensitivity in predicting subsequent emergency hospital care.
In addition, to use quality of life clinically to predict subsequent emergency hospital care, its relationship to other clinically defined risk factors should be clarified. Prior acute episodes have been shown to be the strongest predictor of subsequent acute episodes.8-11
Three studies have shown that asthma quality of life is independent of prior acute episodes in predicting subsequent emergency hospital care,4,6,7
but these studies have not provided a clinically applicable algorithm that incorporates both prior utilization and asthma-specific quality of life. Moreover, 2 of the prior studies defined prior utilization based on computerized data, which may not be available in all clinical settings.4,7
The purpose of this study was to use quality-of-life survey data as well as other information obtained from the patient to develop a practical algorithm for identifying patients at increased risk of subsequent emergency hospital care. This involved identifying a quality-of-life cutpoint score that optimally predicts subsequent emergency hospital care in patients with and without a history of unscheduled asthma visits in the past year and determining the additional risk conferred by a prior history of acute episodes.
Patients in this study have been previously described.7
Surveys were sent by the Kaiser Permanente Care Management Institute in August 2000 to a random sample of Kaiser Permanente Medical Care Program adult members aged 18-56 years from the Northern California (n = 3072) and Northwest (n = 543) regions who were diagnosed as having persistent asthma in 1999 based on Healthcare Effectiveness Data and Information Set (HEDIS) criteria.12
The HEDIS criteria comprise 1 or more of the following administrative database observations in a 12-month period: (1) 4 or more asthma medication dispensings, (2) 1 or more emergency department visits or hospitalizations with a primary diagnosis of asthma, or (3) 4 or more asthma outpatient visits with 2 or more asthma medications dispensings.
Completed surveys were returned from 2219 members (61%), of whom 1998 (90%) confirmed a diagnosis of physician- diagnosed asthma. The current study was restricted to the 1100 respondents who met the HEDIS criteria for persistent asthma in 2000 (as well as 1999) and thus had electronic utilization information for 2001 available. Of these patients, 1006 subjects had complete quality-of-life data (see Survey Information section) and are the subjects of this report. The study was approved by the Northern California Region and the Nortwest Region Kaiser Permanente Institutional Review Boards. Survey Information The survey included information regarding age, sex, race or ethnicity, educational attainment, household income, and smoking history. The survey also included the mini-Asthma Quality of Life Questionnaire (mini-AQLQ),13
which includes 15 questions in 4 domains (symptoms, activity, emotions, and environment). Scores range from 1-7, with higher scores indicating better quality of life.
Prior utilization was assessed by the following questions:
1. “In the past 12 months, how many times did you get treatment for an acute asthma attack at a doctor’s office, urgent care facility or emergency department (ED)?” Responses range from “None” to “7 or more.”
2. “When was your most recent overnight hospitalization for asthma?” Responses included “I have never been hospitalized overnight for asthma,” “Within the last week,” “Within the last month,” “Within the last 6 months,” “Within the past year,” and “More than one year ago.”
Prior acute episodes were defined as an answer of one or more on question 1 above, an overnight hospitalization in the past year on question 2, or both.Utilization Information
Survey records were matched to year 2001 administrative data by using a unique record number. These electronic data included asthma hospitalizations and ED visits. For the purpose of these analyses, the outcomes of hospitalizations and ED visits were combined into a single variable to increase power—presence of 1 or more asthma hospitalizations or ED visits (emergency hospital care) versus nonutilization.Data Analyses
Demographic and utilization characteristics of the population were evaluated by means of descriptive analyses. The optimal cut-point of the mini-AQLQ for predicting year 2001 emergency hospital care was determined by means of stepwise logistic regression analyses with emergency hospital care as the outcome and various mini-AQLQ cut-point levels as the predictors. Mini-AQLQ cut-points between 3.0 and 6.0 at 0.1 increments were offered as potential predictors. The analyses were done separately in patients with and without a history of acute episodes in the prior year.
Hypothesis testing for univariate analyses was by means of Wilcoxon (continuous variables) or chi-square (categorical variables) tests. Multivariable analyses were performed using logistic regression methodology in which the outcome was year 2001 emergency hospital care and the predictors were (1) mini-AQLQ score (optimal cut-point) and (2) prior acute episodes (as defined above, in the Survey Information section). To determine the clinical significance of the findings, predictive properties were evaluated. Sensitivity was defined as the proportion of subjects with subsequent utilization who were in the high-risk group. Specificity was defined as the proportion of participants without subsequent utilization who were not in the high-risk group. Positive predictive value was defined as the proportion of patients in the high-risk group with subsequent utilization. Negative predictive value was defined as the proportion of participants not in the high-risk group who did not experience subsequent utilization. Finally, a risk ratio was calculated as the risk of the outcome in patients with the risk factor or factors divided by the risk in patients without the risk factor or factors.
Nominal 2-tailed statistical significance for all analyses was set at P
<.05. All analyses were performed using SAS statistical software (SAS version 8.2 for Windows, SAS Institute Inc, Cary, North Carolina).
The majority of the patients were white, female, well educated (at least some college), not poor (annual income >$35,000), and nonsmokers.7
In 2001, 82.2% of patients received inhaled corticosteroids, and 11.3% of the study patients had emergency hospital care for asthma.Relationships of Risk Factors to Subsequent Emergency Hospital Care
A mini-AQLQ cut-point score of 4.7 was chosen in the stepwise logistic regression model for patients without prior acute episodes (odds ratio [OR] = 3.1; 95% confidence interval [CI] = 1.4, 6.9). An mini-AQLQ cut-point score of 4.3 was chosen in the stepwise logistic regression model for patients with prior acute episodes (OR = 3.5; 95% CI = 2.1, 5.9). In the total cohort, a low mini-AQLQ score (either cut-point) or a history of acute episodes in the prior year was associated with an approximate 20% risk of subsequent emergency hospital care compared with a 5% to 6% risk in patients without the predictor (Table 1
Although a cut-point of 4.3 was more significantly related to subsequent exacerbations in the logistic regression model than a cut-point of 4.7 in patients with prior episodes, the difference would appear to be clinically unimportant because the 2 cut-points produced equal ORs for subsequent exacerbations in these patients (Table 1). Because a cut-point of 4.7 was associated with higher ORs in the total cohort and in patients without prior acute episodes, this mini-AQLQ cut-point was chosen to define higher risk in subsequent analyses.
Prior acute episodes (OR = 3.8; 95% CI = 2.4, 6.1) and a mini-AQLQ score ≤4.7 (OR = 3.4; 95% CI = 2.1, 5.4) were independently related to emergency hospital care the following year in the multivariable logistic regression analysis. The C statistic for the area under the receiver operating characteristic curve was 0.69 for prior acute episodes alone, 0.68 for a mini-AQLQ score ≤4.7 alone, and 0.75 when both were included in the model.
PDF is available on the last page.