 To determine whether step-up care recommended by national asthma guidelines improves asthma control in a large managed care organization.

 A cohort with uncontrolled asthma, defined as impairment or risk in a 1-year consecutive period, was identified using electronic medical records among continuously enrolled patients with asthma aged 12 to 56 years. Guideline-based step level of care was determined 3 months before and 3 months after the index event of uncontrolled asthma according to an algorithm of asthma medication dispensing using electronic pharmacy data. Impairment based on short-acting b-agonist canisters dispensed and risk based on asthma emergency or hospital care were compared during the following year in patients with vs without step-up care, adjusting for demographics, prior utilizations, asthma risk, and comorbidities.

 Uncontrolled asthma was identified in 7694 eligible patients (mean [SD] age, 35.7 [14.4] years; 54.0% female). Step-up care during the 3-month period after the uncontrolled asthma event was seen in 2160 of 7177 patients (30.1%) with classifiable step care. Step-up care was associated with significant reductions in impairment, with adjusted relative risks of 0.78 (95% confidence interval [CI], 0.73-0.85) during the first 6 months and 0.84 (95% CI, 0.78-0.90) during the full 12-month follow-up period. Emergency or hospital care was unaffected by step-up care. Subgroups with uncontrolled asthma defined by impairment only and risk only showed outcomes generally similar to those of the entire cohort.

Guideline-based step-up care in uncontrolled asthma was determined by administrative data and was shown to be associated with significant and clinically meaningful improvements in asthma impairment but not risk. 

Determination of national asthma guideline-based step-up care in uncontrolled asthma by administrative data may be useful for improving quality of care in managed care organizations.

Step-up care after determination of uncontrolled asthma is documented in a minority of patients. 

Greater improvement in the impairment domain (short-acting b-agonist canisters dispensed) of asthma control is seen in patients with uncontrolled asthma receiving step-up asthma care compared with those not receiving step-up asthma care. 

Real-time determination of uncontrolled asthma by administrative data is recommended to identify patients in whom step-up asthma care is needed to improve asthma control.

Poor asthma control impairs health-related quality of life, increases resource utilization and cost, and persists as a major public health issue affecting more than 23 million individuals in the United States.

 In 2007, direct and indirect costs for asthma totaled $19.7 billion, with the cost of prescription drugs accounting for most of the direct medical expenses.

 The National Asthma Education and Prevention Program

 (http://www.ginasthma.com) developed guidelines to improve asthma control and to reduce burden. These guidelines emphasize 2 major domains of asthma control: impairment and risk. Impairment refers to rescue medication use, symptoms, nocturnal awakenings, school and work absences, exercise problems, and pulmonary function. Risk addresses frequency and severity of exacerbations, loss of lung function, and adverse effects of medication. In addition, the guidelines established 6 step levels of treatment to implement based on a patient’s asthma severity determined before treatment or level of control determined after therapy is instituted. Additional evidence is needed to determine whether appropriate step-up care in patients with uncontrolled asthma improves asthma  control in large managed care organizations.

 This study used administrative data to identify patients with uncontrolled asthma and their step level of care to determine whether step-up care is associated with improvements in subsequent asthma control. We hypothesized that step-up care instituted after a defined uncontrolled asthma event is associated with improvements in asthma control.

 This institutional review board—approved retrospective cohort study was conducted using administrative pharmacy and utilization databases of health plan members of the Kaiser Permanente Southern California Region. The study design is shown in 

 Patients were identified as having asthma if they met at least 1 of the following criteria

 in both 2005 and 2006: (1) any discharge diagnosis of asthma in the health plan and contracting hospital databases (

International Classification of Diseases, Ninth Revision,

] code 493.xx);(2) emergency department or outpatient asthma-related diagnosis; or (3) at least 2 asthmarelated drug dispensings (excluding oral corticosteroids) in the pharmacy database, including β-agonists (excluding oral terbutaline sulfate) and all asthma controller drugs.

Determination of the Cohort With Uncontrolled Asthma.

 Uncontrolled asthma was defined as impairment or risk in a 1-year consecutive period within the first 18 months (January 1, 2005, to June 30, 2006) of the entire 36-month study period (Figure 1).

 Impairment was defined as at least 7 short-acting β-agonist (SABA) canisters dispensed in 1 year. In a clinical setting, asthma impairment is defined based on rescue therapy, symptoms, functional limitations, and pulmonary function

; however, only rescue therapy use can be obtained in administrative data. We validated the number of SABA canisters dispensed in 1 year as a long-term measure of asthma control because it correlates with patient-reported measures of asthma impairment.

 The SABA cut point of at least 7 canisters dispensed per year defined impairment because at least 70% more asthma control problems

 occurred in patients receiving at least 7 vs 6 or fewer canisters dispensed per year.

 Risk was captured by at least 2 unique exacerbations within a year. These included asthma-related emergency department visits or hospitalizations (emergency or hospital care was defined as a primary diagnosis of asthma [

 code 493.xx] or as a secondary diagnosis of asthma when the primary diagnosis was related to a respiratory disease) or oral corticosteroid courses with a provider visit for asthma within 2 days of dispensing.

 The “index date” of uncontrolled asthma for impairment was the date of the seventh SABA canister dispensing, and the index date for risk was the date of the second exacerbation event during a consecutive 1-year interval within the first 18 months of the study. For patients with both impairment and risk events within the 1-year interval, the date of the last event was used as the index date to determine asthma step care (Figure 1).

 Eligible study patients were health plan members aged 12 to 56 years who met the study definition of having uncontrolled asthma and from 2005 to 2007 were continuously enrolled and had health plan drug benefit. The eligible cohort is shown in 

 Asthma drug dispensing was determined using the health plan pharmacy information management system,

 in which the prescription directions for use, specific drug class and name, and quantities dispensed are available. Daily dosage of inhaled corticosteroid was calculated as the following: ([No. of Canisters] × [No. of Puffs per Canister] × [Strength in Micrograms per Puff]) / No. of Days’ Supply).

 Inhaled corticosteroids were categorized as low dose, medium dose, or high dose based on the calculated daily dosage and on their individual potency using the estimated comparative daily dosages recommended by National Heart, Lung, and Blood Institute guidelines

 for persons 12 years or older. Fluticasone propionate plus salmeterol (Advair) was the only combination inhaled corticosteroid and long-acting β-agonist therapy dispensed during step care determination. Strengths of Advair Diskus 100/50, 250/50, and 500/50 were categorized as low-dose, medium-dose, and high-dose inhaled corticosteroid, respectively.

 Step level of care was determined using drug dispensing 3 months before and 3 months after the uncontrolled asthma index date based on guidelines for patients 12 years or older as follows

: (step 1) no drugs or only SABA dispensed; (step 2) monotherapy low-dose inhaled corticosteroid, leukotriene modifier, mast cell stabilizer, or theophylline; (step 3) (a) combination low-dose inhaled corticosteroid with longacting β-agonist, leukotriene modifier, mast cell stabilizer, or theophylline or (b) monotherapy medium-dose inhaled  corticosteroid; (step 4) (a) combination medium-dose inhaled corticosteroid with long-acting β-agonist, leukotriene modifier, mast cell stabilizer, or theophylline or (b) monotherapy high-dose inhaled corticosteroid; (step 5) high-dose inhaled corticosteroid plus long-acting β-agonist with or without omalizumab; and (step 6) high-dose inhaled corticosteroid plus long-acting β-agonist plus oral corticosteroid with or without omalizumab. Electronic medical records of patients in step 6 were reviewed to determine that the oral corticosteroid  dispensed was for maintenance therapy and not for acute use only. Patients were then divided into categories of step-up care or no step-up care based on whether the post—step care was at least 1 step level higher than the pre–step care level. Patients were considered unclassifiable and were excluded from the final analyses when pharmacy data did not allow step classification because of incomplete or missing information. Immunotherapy could not be captured accurately by our electronic databases during the time of the study. Only 4 patients were taking omalizumab during the study and therefore were of inadequate sample size to allow separate analysis.

 Patient characteristics were captured by administrative data (

). Census block group levels of family household income and educational attainment estimates in 2006 were supplied by Nielsen Claritas (http://www.claritas.com) and were obtained for more than 95% of members through geocoding, a technique that links members’ addresses to census geographic areas.

 Databases did not capture smoking history or race/ethnicity during the study period.

Outcomes (Comparisons Between Step-Up Care vs No Step-Up Care).

 Impairment was defined as at least 7 SABA canisters dispensed in the full year

 or as at least 4 SABA canisters dispensed in months 0 through 6 after the 3-month post—step care period. Risk was defined as a severe asthma exacerbation requiring asthma emergency or hospital care during the first 6 months and entire year after the 3-month post–step care period. Asthma emergency or hospital care was selected as the risk outcome because it is more specific for asthma risk and represents more severe exacerbations than oral corticosteroid dispensing; furthermore, the latter is affected by its frequent prophylactic dispensing during routine visits to be used for future worsening asthma.

 Descriptive analyses for individual resource use items entered as a dichotomous variable (eg, ≥7 SABA canisters dispensed [yes or no]) or as a count variable (eg, the number of SABA canisters dispensed) were conducted to illustrate their association with step care. Counts and proportions were obtained for categorical variables, and the mean (SD) and median (range) were used for continuous variables. Bivariate associations were assessed as appropriate by t test, analysis of variance, χ2 test, or nonparametric methods (eg, Wilcoxon rank sum test and Kruskal-Wallis analysis of variance). Significance was set at 2-tailed 

 Univariate and multivariate Poisson regression analyses with a robust error variance (SAS/GENMOD) were constructed to calculate the unadjusted and adjusted relative risk (RR) and the 95% confidence interval [CI] for the outcome variables, as this type of regression model provides better estimates in health investigations involving common binary outcomes (prevalence rate >10%) than logistic regression.

 All point estimates and 95% CIs were generated using SAS software (version 9.1 for Windows; SAS Institute, Cary, North Carolina).

 The following covariates were available for selection for the multivariate models: (1) baseline variables, including age at the time of the uncontrolled asthma index event, sex, and geocoded educational and income attainment; (2) prior-year variables, including number of SABA canisters dispensed, asthma exacerbations (any asthma emergency or hospital care or any asthma oral corticosteroid dispensing determined

), total nonasthma emergency department visits and outpatient visits,

 and comorbidities (gastroesophageal reflux disease, sinusitis, and nasal polyposis); and (3) the pre—index date step level of care. Covariates were selected according to Akaike  information criterion by means of stepAIC function in R statistical software version 2.9.0 (http://www.r-project.org).

 A total of 7694 patients aged 12 to 56 years with uncontrolled asthma were eligible for the study based on asthma impairment or risk definitions (Figure 2). Of these patients with uncontrolled asthma, 5529 (71.9%) were identified as having asthma impairment only, 1355 (17.6%) as having asthma risk only, and 810 (10.5%) as having both asthma impairment and risk.

The mean patient age was 35.7 years of age, 54.0% were female, and patients were health plan members on average for more than a decade (Table 1). About three-quarters had more than a high school education, and the cohort was middle class by mean income. Compared with the impairment-only subgroup, the risk-only and risk and impairment subgroups had significantly more women, less education and income, and more subsidized insurance.

 Among the cohort, half of the patients met criteria for medium-to-high risk stratification asthma categories,

 and slightly less were in step 2 or higher care. During the year before the uncontrolled asthma index date, frequencies were 13.6% for asthma emergency or hospital care, 38.6% for oral corticosteroid courses, and 12.5% for 15 or more SABA canisters dispensed9 (Table 1). Compared with the impairment-only subgroup, the risk-only and risk and impairment subgroups had statistically more asthma burden.

 Respiratory and allergy comorbidities were common, with frequencies of 20.5% for allergic rhinitis, 15.4% for sinusitis, and 8.2% for gastroesophageal reflux disease (

). Most respiratory comorbidities occurred significantly less frequently in the impairment-only subgroup than in the risk-only and risk and impairment subgroups.

Articles

CLINICAL

Significant clinically meaningful improvements in asthma impairment are documented by administrative data for 1 year after initiation of step-up care in patients with uncontrolled asthma.

Step-Up Care Improves Impairment in Uncontrolled Asthma: An Administrative Data Study

To determine in a large claims database the healthcare utilization and costs associated with treatment of alcohol dependence with medications vs no medication and across 4 US Food and Drug Administration (FDA)-approved medications.

Eligible adults with alcohol dependence claims (n = 27,135) were identified in a commercial database (MarketScan; Thomson Reuters Inc, Chicago, Illinois). Following propensity score-based matching and inverse probability weighting on demographic, clinical, and healthcare utilization variables, patients who had used an FDA-approved medication for alcohol dependence (n = 2977) were compared with patients who had not (n =2977). Patients treated with oral naltrexone hydrochloride (n = 2064), oral disulfiram (n = 2076), oral acamprosate calcium (n = 5068), or extended-release injectable naltrexone (naltrexone XR) (n = 295) were also compared for 6-month utilization rates of alcoholism medication, inpatient detoxification days, alcoholism-related inpatient days, and outpatient services, as well as inpatient charges. 

Patients who received alcoholism medications had fewer inpatient detoxification days (706 vs 1163 days per 1000 patients, 

 <.001), alcoholism-related inpatient days (650 vs 1086 days, 

 <.001), and alcoholism-related emergency department visits (127 vs 171, 

 = .005). Among 4 medications, the use of naltrexone XR was associated with fewer inpatient detoxification days (224 days per 1000 patients) than the use of oral naltrexone (552 days, 

 <.001). The group receiving naltrexone XR also had fewer alcoholism-related inpatient days than the groups receiving disulfiram or acamprosate. More patients in the naltrexone XR group had an outpatient substance abuse visit compared with patients in the oral alcoholism medication groups.

 Patients who received an alcoholism medication had lower healthcare utilization than patients who did not. Naltrexone XR showed an advantage over oral medications in healthcare utilization and costs.

Retrospective comparisons among similar patients taking any alcoholism medication vs no alcoholism medication and among similar patients taking 1 of 4 alcoholism medications found the following:

Filling a prescription for alcoholism medication was associated with fewer inpatient detoxification days, alcoholism-related inpatient days, and alcoholism-related emergency department visits. 

Using extended-release naltrexone hydrochloride was associated with fewer inpatient detoxification days and fewer alcoholism-related inpatient days compared with using oral naltrexone, disulfiram, or acamprosate calcium.

Alcohol use disorders (AUDs), including alcohol abuse and dependence, occur commonly in the general population, with an estimated 12-month prevalence of 8.46%.

 Alcohol abuse and dependence are associated with a range of adverse medical, psychiatric, family, legal, and work-related problems. Although alcoholism is a leading cause of preventable death in the United States,

 evidence-based treatment of AUDs is not commonly used.

 Since 2005, the National Institute on Alcohol Abuse and Alcoholism

 has recommended that medication should be considered for every patient with alcohol dependence. In practice, few patients with alcohol dependence are prescribed medications approved by the US Food and Drug Administration (FDA) to treat the disorder.

 Moreover, among patients who are prescribed such medication, adherence is low, which significantly reduces efficacy.

 In part, the reluctance of physicians to prescribe alcoholism medications and of patients to take the medications stems from  skepticism about their efficacy.

 Comparative effectiveness investigations, particularly comparing alcoholism medication treatment with standard care, are needed to address this information gap. Efficacy studies

 using randomized controlled trial (RCT) designs have found that pharmacotherapy is superior to psychosocial treatment alone. However, there are inconsistencies in results across studies, with large multisite RCTs failing to meet their specified end points for disulfiram,

 Furthermore, where efficacy trials have shown positive findings, results have demonstrated only modest effects.

 Information is also needed to compare the relative efficacy of existing alcoholism medications, particularly their ability to address the problem of poor adherence. There are 4 FDA-approved medications for the treatment of alcohol dependence. Disulfiram, an aversive agent, acts as a deterrent to drinking.

 Naltrexone is an opioid antagonist and is thought to reduce the rewarding effects of alcohol.

 Acamprosate is believed to reduce the risk of relapse by stabilizing glutamatergic pathways in individuals during the postwithdrawal phase.

 First approved as an oral treatment, naltrexone was subsequently approved also as an extended-release injectable suspension (naltrexone XR). In contrast to oral naltrexone, disulfiram, and acamprosate, which require daily dosing, naltrexone XR is administered as a monthly injection. Because naltrexone XR was designed to enhance patient adherence, comparison of the effect of that formulation vs oral medications on treatment outcomes is of considerable interest.

 Although RCTs are an important source of information on comparative effectiveness, they pose obstacles to external validity that limit their applicability to clinical practice. These include enrollment that favors highly motivated patients, compliance-inducing pill accounting procedures, unblinding because of adverse events, and assessment reactivity in research subjects.

 In contrast to data from RCTs, observational studies can reflect the experiences of a broad sample of patients with alcoholism who receive care in naturalistic settings. In particular, retrospective analysis of large data sets (such as those composed of insurance claims) does not impose artificially constrained treatment frequencies, fixed duration of treatment, visits with nonprovider research assistants, or incentives for participation. In addition, providers of services detailed in these data sets represent the full spectrum of disciplines and settings that exist in the real world. These features favor generalizability. The main drawback of observational data is the potential for selection bias, which may be addressed with statistical controls.

 This study evaluated approved treatments for alcohol dependence in a naturalistic population using a 2-stage approach. First, we compared the use of any of the FDA-approved medications vs no medication treatment. Second, we compared 4 alcoholism medications with one another relative to treatment persistence and healthcare utilization and cost outcomes.

 Data were obtained from the Thomson Reuters 

 Commercial Claims and Encounter database that comprises enrollment information and medical and prescription medication claims from approximately 150 large self-insured employers and regional health plans located throughout the United States (yielding approximately 25 million individuals per year). The contributors to the database provide insurance coverage under various fee-for-service and capitated health plans, including  preferred provider organizations, indemnity plans, and health maintenance organizations.

 For comparison of patient groups receiving any vs no alcoholism medication, the index date was defined as the earliest date of utilization of 1 of 4 alcoholism medications or as the alcohol dependence diagnosis date for the group receiving no alcoholism medication. Patients in the latter group had no prescription fills for an alcoholism medication, while patients in the group receiving any alcoholism medication had at least 1 fill for any of 4 alcoholism medications. Patients were required to be 18 years or older and to have at least 6 months of continuous enrollment before the index date and 6 months after the index date. Patients were required to have at least 1 claim for alcohol dependence 

(Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition

] code 303.xx) during the pre—index date or post–index date periods and to have a diagnosis of alcohol dependence or abuse (

 code 303.xx or 305.xx) before the index date. The study required an alcohol dependence diagnosis to be consistent with the labeled indication for the medications. A preperiod alcohol dependence or abuse diagnosis was required for the analysis of any vs no alcoholism medication use, as otherwise it would be likely that the group receiving no alcoholism medication would be earlier in their treatment course than the group receiving any alcoholism medication. These inclusion and exclusion criteria led to final samples of 4047 patients in the group receiving any alcoholism medication and 4730 patients in the group receiving no alcoholism medication. 

) gives sample sizes after applying each inclusion or exclusion criterion.

 Patients in the comparison of 4 alcoholism medications were required to have 6 months of continuous enrollment before the index date and after the index date and to be 18 years or older. Patients treated with oral naltrexone, disulfiram, or acamprosate were identified using outpatient drug claims based on national drug codes. The index date was defined as the earliest utilization date of 1 of 4 medications. Patients treated with naltrexone XR were identified on the basis of an outpatient drug claim with a national drug code for naltrexone XR or a medical claim with a Healthcare Common Procedure Coding System code for naltrexone XR. The earliest such claim was set as the index date. The following numbers of patients from the database met the study criteria: 295 for naltrexone XR, 2064 for oral naltrexone, 2076 for disulfiram, and 5068 for acamprosate.

 Drug utilization patterns and other outcomes were measured during the first 6 months following the index date. Naltrexone XR utilization amounts were calculated by determining the number of unique service dates (ie, injections) for naltrexone XR and multiplying those unique days by 30.5 days (the mean number of days per month in a year) to derive the total days a patient was receiving naltrexone XR. The total number of days of receiving naltrexone XR was then divided by 180 days to determine the percentage of time over 6 months that the patient was receiving naltrexone XR. For the oral agents, the percentage of days with medication fills was determined by adding the days supplied indicated on each prescription drug claim and dividing by 180 days.

 The following inpatient utilization outcomes were examined: detoxification admissions (admissions with an 

International Classification of Diseases, Ninth Revision, Clinical Modification 

procedure code for detoxification), alcoholismrelated admissions (admissions with a principal diagnosis of alcohol dependence), and nonalcoholism-related admissions. Utilization was measured as the percentage of patients with admissions and the total inpatient days. Emergency department (ED) utilization was captured as the percentage of patients visiting an ED and the number of alcoholism-related ED visits. Outpatient behavioral health services utilization was captured as the percentage of patients having visits with a primary diagnosis of substance abuse or a combined substance abuse and mental health diagnosis. We also measured the occurrence of diagnoses of schizophrenia, bipolar disorder, depression, and anxiety disorder. Finally, we measured costs for inpatient detoxification days and alcoholism-related admissions by multiplying charges per day by the number of inpatient detoxification days or alcoholism-related inpatient days.

 Charges for inpatient treatment were determined using the Healthcare Cost and Utilization Project National Inpatient Sample (NIS) data set (http://hcupnet.ahrq.gov/). The NIS is the largest all-payer inpatient care database in the United States. The sampling frame for the 2008 NIS is a hospital sample that comprises approximately 90% of all hospital discharges in the United States. Charge information is provided on all patients, regardless of payer, including persons covered by Medicare, Medicaid, and private insurance, as well as the uninsured. For this study, charges were used for patients with private insurance having a principal diagnosis of alcohol dependence.

 We used propensity score—based matching and inverse probability weighting to reduce the potential for cohort selection bias. We developed propensity scores using a logit model to compare the groups receiving any vs no alcoholism medication.  Explanatory variables were selected based on their hypothesized confounding relationship with the outcome variables and included the following: (1) sex, (2) percentage of college graduates in the patient’s zip code, (3) log of the median household income in the patient’s zip code, (4) geographic region, (5) relationship to employee (employee, spouse, or child or dependent), (6) preperiod comorbidity burden measured using the Charlson Comorbidity Index,

The following preperiod measures were also included: (8) comorbid psychiatric diagnosis, (9) AUD diagnosis, (10) drug abuse or dependence diagnosis, (11) detoxification admission, (12) alcoholism-related admission, and (13) nonalcoholism-related admission. Propensity scores were calculated as the predicted probability of being in the group receiving any alcoholism  medication given the demographic, geographic region, and clinical factors listed. A nearest neighbor matching with a 1:1 matching ratio was used to match the 2 groups based on their scores. The balancing of variables was examined using  standardized difference (threshold of 10), paired t test (for continuous variables), or McNemar test (for dichotomous variables). The matched sample comprised 2977 patients each in the group receiving any alcoholism medication and the group receiving no alcoholism medication.

 Inverse probability of treatment weighting (IPTW) was used to adjust for differences in the characteristics of the 4 alcoholism medication groups being compared. To estimate the IPTW, a multinomial logit model was used in which the dependent variable was the treatment group. The independent variables were the demographic, geographic region, and clinical factors already listed. The IPTW was calculated as the inverse of the predicted conditional probability of being in the particular treatment group. The IPTW was normalized by its mean and was applied to the data to generate a reweighted pseudopopulation. Adjusted Wald test was performed to test for the difference in weighted continuous characteristics across the treatment cohorts. Rao-Scott χ2 test was conducted to test for the difference in the distribution of discrete outcomes across groups. STATA 9.2 MP (StataCorp LP, College Station, Texas) was used in the analyses.

Comparison of Groups Receiving Any vs No Alcoholism Medication

 A total of 27,135 eligible adults were identified in the commercial database. 

 gives characteristics of 2977 matched patients in the group receiving any alcoholism medication and the group receiving no alcoholism medication. Approximately 60 percent of patients were male, with a mean age of 45 years. During the preperiod, 19% had a drug abuse or dependence diagnosis, 8% to 9% had a bipolar disorder diagnosis, 37% to 38% had a depression diagnosis, and 12% to 13% had an anxiety disorder diagnosis. Preperiod alcoholism-related healthcare utilization was high, with 22% to 24% of patients having a detoxification admission, 19% having a hospital admission with a principal diagnosis of alcohol dependence, and 21% having an alcoholism-related ED visit in the 6 months before medication initiation.

 Among the prematched sample, patients receiving any alcoholism medication were slightly older, more likely to be female, and more likely to live in areas with more college graduates, a higher median household income, and less poverty (

). Patients prescribed any alcoholism medication were more likely to have a preperiod diagnosis of depression, anxiety disorder, or bipolar disorder. In the preperiod, the group receiving any alcoholism medication had higher percentages of patients with a detoxification admission, an alcoholism-related admission, or an alcoholism-related ED visit.

 gives utilization outcomes and postperiod psychiatric comorbidities in the 2 groups after propensity score matching. The group receiving no alcoholism medication had a higher percentage of patients with a detoxification admission after the index date (13% vs 9%, 

 <.001) and more inpatient detoxification days per 1000 patients (1163 vs 706, 

 <.001) than the group receiving any alcoholism medication. Inpatient detoxification days translated to costs of $1,890,822 per 1000 patients treated  with any alcoholism medication and $3,113,389 per 1000 patients treated with no alcoholism medication.

 The group receiving no alcoholism medication also had a higher percentage of patients with an inpatient admission for a  principal diagnosis of alcohol dependence (11% vs 7%, 

 <.001) and more alcoholism-related inpatient days (1086 vs 650, 

 <.001) (Table 2). Total charges for alcoholism-related inpatient days were estimated at $1,818,292 per 1000 patients treated with any alcoholism medication and $3,037,374 per 1000 patients treated with no alcoholism medication. There was no difference in the non-AUD inpatient admission rates. Finally, compared with groups receiving any alcoholism medication, the group receiving no alcoholism medication had a higher percentage of patients with alcoholism-related ED visits (10% vs 8%, 

 = .007) and had more alcoholism-related ED visits per 1000 patients (171 vs 127, 

 The pattern of greater healthcare utilization among the group receiving no alcoholism medication was also true for outpatient visits. Compared with the group receiving any alcoholism medication, the group receiving no alcoholism medication was more likely to have an outpatient visit with a substance abuse diagnosis (95% vs 63%, 

 <.001) and had more substance abuse visits (7.7 vs 5.4, 

 <.001) (Table 2). The percentages of patients with schizophrenia, bipolar disorder, or anxiety disorder during the  postperiod did not differ between the 2 study groups. The group receiving any alcoholism medication had a higher percentage of patients with a depression diagnosis than the group receiving no alcoholism medication (37% vs 33%, 

Comparisons Among 4 Alcoholism Medication Groups

 gives the characteristics of the 4 alcoholism medication groups after propensity score weighting. The characteristics were balanced across the groups. Differences among the 4 groups before weighting are given in 

 gives differences in outcomes after propensity score weighting across the 4 alcoholism medication groups. Patients receiving naltrexone XR had more time with filled prescriptions than patients receiving acamprosate (41% vs 34% of days covered in a 6-month period, 

 Differences in percentages with detoxification admissions among the 4 alcoholism medication groups did not reach statistical significance at conventional levels. On average, the naltrexone XR group also had fewer inpatient detoxification days than the oral naltrexone group (

 <.001) (Table 4). Fewer inpatient days translated to significantly lower inpatient costs per 1000 patients treated. Differences in percentages of patients with an alcoholism-related hospital admission did not reach statistical significance at conventional levels. On average, the naltrexone XR group had fewer alcoholism-related inpatient days than the disulfiram (

 < .001) groups, which translated into lower inpatient costs per 1000 patients ($382,460 for naltrexone XR, $1,040,749 for disulfiram, and $1,214,881 for acamprosate).

 A significantly higher percentage of patients receiving naltrexone XR (69%) had an outpatient visit for substance abuse treatment than patients receiving oral agents (38% for oralnaltrexone, 40% for disulfiram, and 40% for acamprosate; 

 <.001) (Table 4). Similar results were found for the category of combined substance abuse and mental health visits. The difference in the mean number of outpatient substance abuse or mental health visits did not reach statistical significance.

 There were no statistically significant differences among the 4 alcoholism medication groups in the percentages of patients diagnosed as having anxiety disorder, schizophrenia, bipolar disorder, depression, or any psychiatric diagnosis. Similarly, there were no significant differences in the numbers of psychiatric diagnoses.

 In this retrospective claims analysis of matched commercially insured individuals, patients who received any alcoholism medication had fewer detoxification admissions, alcoholism-related inpatient care, alcoholism-related ED visits, and substance abuse outpatient visits in the 6 months following medication initiation than patients who received no alcoholism medication. Among the 4 groups of alcoholism medication users, naltrexone XR users were found to utilize more medication than acamprosate users. Furthermore, naltrexone XR use was associated with fewer inpatient detoxification days than oral naltrexone or acamprosate use and was associated with fewer inpatient days for a principal diagnosis of alcohol dependence than disulfiram or acamprosate use.

 The data also reveal an inverse utilization pattern among 4 groups of alcoholism medication users relative to inpatient vs outpatient services. The naltrexone XR group had significantly less inpatient utilization, but significantly more patients in the naltrexone XR group had at least 1 outpatient substance abuse visit compared with patients receiving oral alcoholism agents. Higher outpatient services utilization may be an indication of better engagement, which may have contributed to lower inpatient services utilization. Notably, patients who used no alcoholism medication had greater outpatient services utilization than patients who used any alcoholism medication; however, there was no corresponding decline in inpatient services utilization. This finding suggests that engagement in outpatient treatment should be associated with better utilization outcomes, but perhaps only if that treatment is comprehensive in addressing both psychosocial and biologic aspects of alcohol dependence. Indeed, this conclusion is consistent with guidelines published by the National Institute on Alcohol Abuse and Alcoholism  stating that psychosocial approaches and medication use are complementary and “share the same goals while addressing different aspects of alcohol dependence: neurobiological, psychological, and social.”

 This study must be understood in light of its limitations. First, the observed associations may not be causal. Without randomization, there may be unmeasured confounding factors such as differential motivation and illness severity that underlie the observed differences in utilization. This risk may have been mitigated by baseline propensity score matching and weighting for relevant demographic, baseline clinical, and utilization variables. Furthermore, the results derive from a range of practices, settings, and provider types in community settings, which enhances external validity. Second, the study examined only commercial claims; therefore, the results may not generalize to other populations such as Medicaid beneficiaries. However, in parallel analyses among a limited number of Medicaid patients, results were consistent with the findings presented herein,  providing further support for their external validity. Third, study outcomes were utilization measures that, while important, did not include alcohol consumption patterns. However, intensive healthcare services utilization (eg, the number of subsequent inpatient detoxification days) may be a reasonable proxy for drinking behavior. Fourth, because of the recent introduction of naltrexone XR, the sample of 295 users of naltrexone XR was small, which may have limited the statistical power, and should be expanded in future analyses. Fifth, the inclusion criteria required continuous enrollment for 1 year, and individuals with continuous enrollment may have differed from those without continuous enrollment (eg, because of job loss) in severity, adherence, and outcomes. Sixth, comparisons across products did not attempt to control for the extent to which patients filled an “adequate” course of the medication, as the study intent was to focus on the effect of outcomes of the “usual” treatment patterns; however, this would be a useful follow-up study. Seventh, adherence was measured according to filled paid claims,  and while naltrexone XR is administered by a health professional and persists over 1 month, patients receiving oral agents may not have taken them as prescribed.

 These findings are clinically significant and address the significant gap in information on the effects of alcoholism medications in clinical practice. Despite general research that has shown benefits of these medications in the treatment of alcohol dependence and the recommendation by the National Institute on Alcohol Abuse and Alcoholism

 that providers should consider the use of approved medications for the treatment of all patients with alcohol dependence, it is estimated that more than 90% of patients diagnosed as having alcohol dependence do not receive such pharmacotherapy.

 In this study, we found a consistent pattern of better outcomes associated with pharmacotherapy than with no pharmacotherapy. Similarly, naltrexone XR use was associated with better outcomes than the use of oral alcoholism medications in many comparisons. Differences are clinically and economically meaningful. For example, when inpatient detoxification days are converted to hospital charges using the mean daily charges reported by US insurers (based on Healthcare Cost and Utilization Project National Inpatient Sample data for 2007 from the US Agency for Healthcare Research and Quality [http:// hcupnet.ahrq.gov/]), naltrexone XR use was associated with significantly lower detoxification costs ($0.60 million per 1000 patients over 6 months) than oral naltrexone use ($1.48 million, 

 of oral naltrexone have shown that most patients do not persist through a clinically relevant course of treatment, and nonpersistence has been associated with significantly more intensive healthcare services utilization.

 In the present study, the group receiving naltrexone XR had greater medication utilization and lower inpatient services utilization and costs than the groups receiving oral alcoholism medications. These findings may be attributable to the administration of naltrexone XR formulation on a monthly basis rather than a daily basis. The findings from this study have important implications for alcohol dependence pharmacotherapy and provide support for the use of FDA-approved medications, particularly naltrexone XR, in clinical settings. Additional comparative research on alcohol dependence pharmacotherapy using larger samples and longer durations of treatment is needed to enhance the care of this undertreated patient population.

 From Thomson Reuters Inc (TLM), Washington, DC; Thomson Reuters Inc (LM), Cambridge, MA; University of Connecticut School of Medicine (HRK), Farmington, CT; Treatment Research Institute, Inc (MC), Philadelphia, PA; and Alkermes Inc (DRG), Waltham, MA.

This study was funded through a contract from Alkermes Inc to Thompson Reuters Inc. Dr Kranzler's involvement was supported by grant K24 AA013736 from the National Institute on Alcohol Abuse and Alcoholism.

Treatment of alcohol dependence with medications offered advantages in reduced healthcare utilization and costs compared with usual treatment without medications.

Comparison of Healthcare Utilization Among Patients Treated With Alcoholism Medications

To present pilot data from an ongoing electronic health record (EHR) quality improvement study to improve medication management using patient previsit review of the EHR medication list and a plain-language new medication information sheet to provide with every new EHR prescription.

 Postvisit survey of 191 patients at an academic general internal medicine clinic.

 Patients were asked about discrepancies and problems, concerns, and questions (PCQs) in their EHR summary for up to 10 current medications and about knowledge of new prescriptions. Findings describe the extent of medication discrepancies, perceived PCQs about current medications, and patient knowledge about new medications.

 Overall, 78.0% of patients had at least 1 discrepancy, more than half had a drug listed that they were not taking or dose or frequency discrepancies, and 8.9% reported an omission; 41.9% indicated at least 1 PCQ about their current medications. Among patients who received a new prescription, most knew what the new medication was for and how to take it. However, 66.0% indicated uncertainty about potential adverse effects that they should telephone the physician about.

Discrepancies can be efficiently categorized by previsit review of EHR medication lists. Prereview offers physicians the opportunity to better address important medication PCQs. Testing the value of EHR-generated plain-language medication information sheets requires follow-up interviews after medications are filled. Patients may not understand the actual benefits of new medications.

Medication discrepancies, patients' perceived problems with current medications, and understanding of new prescriptions were evaluated in a postvisit survey of 191 patients from an academic general internal medicine clinic.

Seventy-eight percent of patients had at least 1 discrepancy. 

Almost half of the patients had problems, concerns, and questions about their current medications. 

Two-thirds of patients were uncertain about potential adverse effects of newly prescribed medications. 

These results suggest the need for patient previsit review of the electronic health record (EHR) medication list and for use of EHR plain-language information about new prescriptions, including a description of medication benefits.

More than a decade of experience with our general internal medicine clinic electronic health record (EHR) (EPIC, Madison, Wisconsin) has shown that the EHR provides clinicians with increased efficiency in documentation, more rapid and timely access to tests and procedure findings, and useful preventive services alerts for patients.

 However, we have also found that the attention required to enter and access EHR information in the examination room can potentially detract from the quality of interpersonal communication with patients.

 Physicians may avoid spending the time required to clean up and update EHR medication screens during a particular visit, old prescriptions are left on lists, drugs that were prescribed by other medical specialists or alternative providers are not entered, and newly ordered prescriptions may be hastily discussed with patients.

 The advent of the EHR offers the potential for primary care practices to adopt new approaches to eliminating medication discrepancies, while also providing patients with easy-to-understand instructions about new prescriptions that will enhance medication safety and adherence. The Northwestern University general internal medicine clinic in downtown Chicago, Illinois, was recently awarded a grant from the Agency for Healthcare Research and Quality to design an EHR-based physician-randomized trial to simultaneously improve medication reconciliation and communication about new medications.

 Because the EHR is in use during each patient visit, it is possible to easily review current medication lists. To aid in this process, our intervention includes a new step in the rooming process that enlists patients’ help in flagging potential discrepancies. Patients receive an EHR medication list of their current medications at check-in, allowing them to review any discrepancies before their physician visit. In addition, to improve patient understanding of their new medications, we created plain-language medication information sheets that have been populated in the EHR to be printed out for patients when they are prescribed a new medication.

 To help shape this intervention, we conducted postvisit in-person patient interviews to evaluate (1) the extent of medication discrepancies; (2) perceived problems, concerns, and questions (PCQs) about current medications; and (3) patient knowledge about new prescriptions, including what the newly prescribed medication is for, how and when to take it, and potential adverse effects. The results of this baseline study are being used to guide our planned EHR-based intervention.

 For our baseline feasibility study, we decided to enroll a convenience sample of approximately 200 patients who were 21 years or older and fluent in English. On completion of the interview, participants were given $10. The Northwestern University Institutional Review Board approved the study.

Interview Protocol About Current Medications

 Each month, physicians were sent a list of scheduled patients and were asked to give permission for patients to receive a mailing regarding the study interview. Immediately after a scheduled patient visit checkout, patients were approached by a trained study research assistant (JRW) to assess interest and to obtain consent. Participants were asked if the physician had reviewed their current medications with them during that day’s visit. Participants were then asked to go over their postvisit summary report, which is routinely printed directly from the EHR and given to them at checkout. The postvisit summary contains a list of their current medications and any new medications prescribed at that visit and includes all prescriptions from our large multispecialty practice. The research assistant then went through up to 10 previously existing prescriptions on the medication list summary. The research assistant asked participants if they were taking any medications that were not on the postvisit summary list. For this study, we only describe discrepancies with prescription medications.

 For each current medication that was actually being taken, the research assistant then asked the participant: (1) Are you still taking it? (2) Are you taking it the way listed here? (3) Do you have any problems, concerns, or questions about the medication? If so, the research assistant asked what those PCQs were. Participants were asked if they wanted their physician or nurse to contact them about any reported PCQs. We describe the proportions of patients with commission discrepancies (not taking a listed medication), omission discrepancies (taking an unlisted medication), and dose or frequency discrepancies (not taking a listed medication as prescribed), as well as an overall proportion of patients with any discrepancy.

 Interview Questions About New Medications

 Patients who were prescribed a new medication during the visit were asked to rate their degree of uncertainty about each new prescription. Patients were asked (1) Do you know what your physician prescribed the medication for? (2) Do you know how to use or take it? (3) Do you know if there are any adverse effects that you should call your physician about? Patients were also asked if they had any PCQs about the new prescription that they were unable to discuss with their physician. The research assistant did not judge whether  patient answers were correct but only whether the patient was confident that he or she understood the prescription. Patients were also asked how long they were supposed to take the new medication. However, because duration of use for as-needed or trial prescriptions is often uncertain, this variable was not included in calculating the proportion of patients who indicated that they fully understood their new prescriptions.

 A total of 116 patients refused participation before we reached our goal of interviewing 191 patients with current prescriptions. Among 191 patients, 38.7% had at least 10 prescription medicines listed on their postvisit summary report, 77.0% had at least 5, and 23.0% had 1 to 4. Only 5.2% of patients reported that they had not discussed their medications with their physician during the visit.

 Current Medication Discrepancies and PCQs

gives the proportion of patients with any medication discrepancies between their postvisit self-report and their EHR postvisit summary printout, summed across up to 10 current prescriptions. We present each discrepancy category by patient sociodemographic characteristics. Commission and dose or frequency discrepancies were reported by 55.5% of all patients. (Indeed, about one-quarter of all patients had more than 1 medication discrepancy in these categories [data not shown].) About 9% of patients reported omission discrepancies. Combining these categories across all prescriptions resulted in a remarkable 78.0% of patients who had at least 1 (any) discrepancy. There were no  significant differences in discrepancies by patient characteristics.

 When asked whether they had PCQs about any medication they were taking, 41.9% of patients had at least 1. While patients reported various PCQs, the most frequent concerns were about whether medications were working, if certain symptoms were potential adverse effects, when to stop taking a drug, and what were the correct dosages. Three percent of patients indicated that they wanted to contact their physician about a particular PCQ.

 Forty-eight study patients (25.1%) received at least 1 new prescription at their study visit. Only 1 patient indicated that he or she did not know what the new medication was for. Only 5 patients expressed uncertainty about how to take their new medication. However, 35 patients indicated uncertainty about potential adverse effects that they should call the physician about. Only 3 patients had PCQs that they were unable to discuss with the physician.

 Approximately 4 of 5 interviewed patients had some type of discrepancy on their EHR summary, almost half of the patients reported a PCQ about at least 1 existing medication, and two thirds of patients receiving a new medication reported inadequate information, mainly about potentially harmful adverse effects that would merit calling their physician. Many discrepancies were the result of specialty medications that had not been entered in or removed from medication lists. While patient PCQs were common, it was unclear to what extent these issues reflected poor communication with the primary care physician as opposed to inevitable concerns and ambiguity about medication safety and efficacy. Finally, patients’ failure to clearly understand the most important adverse effects of new medications may have largely been a function of overly detailed warnings such as those found on package inserts, as well as lack of physician time to fully address adverse effects and other issues at the time of a new prescription.

 Our EHR-Based Medication Communication Quality Improvement Effort

 For physicians randomized to the intervention, an EHR medication list is automatically printed when a patient checks in for the physician visit, with instructions for the patient to cross out any duplicate medications or medications that he or she is no longer taking. On the same printout, patients are asked to indicate any concerns that they have by marking checkboxes labeled for adverse effects, cost, refill requirements, or other needs. There is also space for patients to add any medications they are taking that are not on the list, including any over-the-counter medications, vitamins, or supplements. These sheets are collected when patients are roomed and are made available for review by their physician. Anecdotally, physicians have reported that the sheets are of great value in “cleaning up” discrepancies. Our initial tracking of visit durations finds no additional time for experimental vs usual-care physicians, although it is unknown whether additional discussion of medications may be displacing time that would have been used for other patient concerns.

 Improving Patient Knowledge About New Medications

 Medication information sheets used in our study were created for the top 250 prescribed medications by the joint efforts of a communication specialist (GM) and a health literacy  specialist (MSW), as well as pharmacists, physicians, and patients interviewed in focus groups. Each sheet is formatted under the following 8 headings: purpose, benefit, length of treatment, instructions, safe use, adverse effects and warnings, discussion points, and follow-up. These medication information sheets are automatically printed for patients along with each new prescription at checkout following visits to physicians randomized to our quality improvement intervention.

 Other Lessons for Evaluating Medication Communication Quality Improvement

 Investigations have found that when prescribing a new medication physicians most frequently mentioned product name and instructions for use; other topics such as risks and benefits were mentioned far less frequently.

Herein, while patients knew what a medication was prescribed for, they had much less certainty of what to expect about the actual health benefits of their prescription. With the creation of new medication information sheets, we stress the importance and understanding of medication benefits, in part to balance fears about the potential adverse effects listed. We also emphasize the most common adverse effects and warnings that patients should call their physician about if they experience them, rather than relying on package insert warnings that often include a long laundry list of every reported adverse effect regardless of its rarity.

 To obtain a more objective rating of patient knowledge about their new medications, we now use postvisit interviews and telephone follow-up interviews, which take place after the patient has filled (or not filled) his or her prescription. Only by waiting until patients have filled their prescriptions can we assess their understanding as correct or incorrect and obtain a better idea of how patients are actually taking their medications.

 In conclusion, these pilot data were used to develop a better strategy to improve medication reconciliation and patient knowledge about medication regimens. Using real-time  review and access to educational materials afforded by the EHR, we expect to create a higher standard of care for primary care physicians that will require no significant additional time or effort over the long run. We are evaluating these changes to our process of care in a physician-randomized trial. If proved successful, our approach has the potential for rapid adaptation and dissemination by any practice that uses the EHR.

From the Division of General Internal Medicine (JRW, JF, CLW, DPD, DWB, MSW), Department of Medicine, Northwestern University, Chicago, IL; and Saint Francis Hospital and Medical Center (GM), Hartford, CT.

TRENDS FROM THE FIELD

Patients' problems in understanding of new and existing medications were evaluated to design a primary care electronic health record quality improvement study.

Can Electronic Health Records Help Improve Patients' Understanding of Medications?

To evaluate the effects of switching from multiple daily injection (MDI) therapy to insulin pump therapy, also called continuous subcutaneous insulin infusion (CSII), on antidiabetic drug and healthcare resource utilization.

This study was a retrospective analysis of administrative claims data from a large geographically diverse health plan in the United States from January 1, 2005, through April 30, 2008.

 Changes in antidiabetic drug use, antidiabetic drug switching and augmentation, and healthcare utilization during the baseline period and after CSII initiation were assessed using paired t test.

 There were 3649 possible subjects, of whom 943 met the criteria for analysis. The mean number of antidiabetic drugs used decreased by 46% after CSII initiation, and the mean reduction in antidiabetic drug utilization was 0.67; both were statistically significant. More than one-third of subjects who were taking antidiabetic drugs before CSII initiation discontinued oral therapy after CSII initiation. The number of subjects using multiple antidiabetic drugs significantly decreased after CSII initiation by 58%, and rates of switching or augmenting significantly decreased from 42% at baseline to 25% after CSII initiation.The rates of emergency department visits and inpatient admissions significantly decreased, and the rate of ambulatory visits significantly increased.

 CSII was associated with significant decreases in antidiabetic drug and healthcare resource utilization, contributing to stability of care. The evidence from this study indicates that CSII should be considered as an option for patients with type 2 diabetes mellitus who are using MDI and are experiencing a high degree of antidiabetic drug and healthcare resource utilization.

A retrospective analysis of a large sample of managed care enrollees with type 2 diabetes mellitus was performed to examine the effect on antidiabetic drug and healthcare resource utilization of switching from multiple daily injections to insulin pump therapy, also called continuous subcutaneous insulin infusion.

After initiation of continuous subcutaneous insulin infusion, antidiabetic drug utilization was reduced by 0.67 drug (a change of 46%), and more than one-third of subjects discontinued antidiabetic drugs altogether. 

Inpatient admissions and emergency department visits decreased significantly. Ambulatory visits increased significantly. 

Continuous subcutaneous insulin infusion should be considered an alternative to continued use of multiple daily injections after the latter therapy has failed.

	A major challenge of managing type 2 diabetes mellitus (T2D) is the escalation of therapies in the response to treatment regimen failure. Indeed, this treatment escalation is now the standard of care for this disease. Antidiabetic drugs are added to therapy regimens if hyperglycemia and elevated glycosylated hemoglobin (A1C) values persist after the first stage of lifestyle and pharmacologic interventions.1 Intensive insulin therapy is often not added until multiple antidiabetic drugs fail to maintain euglycemia. However, even with the addition of insulin, many patients continue using multiple antidiabetic drugs. Moreover, as the disease progresses, patients with T2D have increased healthcare resource utilization, including emergency department (ED) visits and inpatient admissions for diabetesrelated complications and comorbidities.

 Insulin pump therapy, also called continuous subcutaneous insulin infusion (CSII), is not usually initiated in most T2D treatment regimens until multiple daily injection (MDI) therapy has failed. A few studies

 have examined whether switching from antidiabetic drugs or conventional insulin therapy to CSII offers a clinical benefit over switching to MDI. Such studies have focused on change in A1C level  and have had mixed results. These studies did not examine whether CSII reduces utilization of antidiabetic drugs or other healthcare resources.

	A plausible area for investigation drawn from the sparse literature about CSII in T2D is whether switching to this therapy after MDI has failed can reduce the number of antidiabetic drugs used and the amount of healthcare resource utilization needed to manage the disease. The present study investigates antidiabetic drug and healthcare resource utilization among a large real-world population of patients with T2D who switched from MDI to CSII.

	This study was a claims analysis using medical, pharmacy, enrollment, and laboratory data to assess the effects of switching from MDI to CSII. Subjects were enrollees in a large geographically diverse US managed care health plan with documentation of T2D. No identifiable protected health information was extracted or accessed during the course of the study. Pursuant to the Health Insurance Portability and Accountability Act of 1996,

 the use of deidenti-fied data does not require institutional review board approval or waiver of authorization. Clinical outcomes (change in A1C levels and A1C targets) of this population are published separately.

	Medical claims or encounter data were collected from all available points of service such as inpatient and outpatient hospital records, ED visits, physician’s office encounters, and surgery center data, including specialty, preventive, and office-based treatments. Medical claims and coding conformed to insurance industry standards. Included in the database were pharmacy claims representing all prescriptions filled at outpatient pharmacies and submitted to the insurance plan for reimbursement. A 12-month period before CSII initiation was used to examine baseline demographic and clinical characteristics. The follow-up period was a minimum of 6 months and a maximum of 40 months. Baseline and follow-up periods were measured from the date of CSII initiation. Data from January 1, 1998, through April 30, 2008, were included in the study.

	Patients were included if they initiated CSII during the subject identification period (January 1, 2005, through October 31, 2007) and had evidence of T2D. Evidence of T2D was determined by the presence of 

International Classification of Diseases, Ninth Revision, Clinical Modification

) codes for T2D (a fifth digit of 0 or 2) in the medical record or by the use of any oral antidiabetic drug or exenatide in the claims history. Exclusion criteria included age younger than 18 years, missing information on sex, evidence of CSII use during the baseline period, lack of continuous enrollment in the health plan for a 12-month baseline period or less than a 6-month follow-up period, and type 1 diabetes mellitus—related 

codes without evidence of oral antidiabetic drug or exenatide use.

	Claims were analyzed at the baseline period and after CSII initiation for changes in antidiabetic drug (defined as any oral antidiabetic drug or exenatide) and healthcare resource  utilization. Change in antidiabetic drug utilization was calculated as the number of antidiabetic drugs used after CSII initiation minus the number of antidiabetic drugs used during the baseline period. Healthcare resource utilization was calculated as the rate of ED visits, inpatient admissions, and ambulatory visits per subject per month (PSPM) during the baseline period and after CSII initiation. The number of ambulatory visits represented all visits for outpatient services that generated costs for care and not just physician office visits for the care and management of diabetes.

	All study variables were analyzed descriptively. Numbers and percentages were provided for dichotomous and polychotomous variables. Means, medians, standard deviations,and percentiles were calculated for continuous variables. Univariate analysis using paired t test was performed on the changes in antidiabetic drug and healthcare resource utilization. 

 <.05 was considered statistically significant.

	Of 3649 enrollees identified as having T2D and using CSII, 943 met criteria for inclusion in the study (

A retrospective claims analysis of managed care enrollees with type 2 diabetes mellitus showed that insulin pump therapy reduced antidiabetic drug and healthcare resource use.

December 2010

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Resource Utilization With Insulin Pump Therapy for Type 2 Diabetes Mellitus

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