Publications

2006

Garey, Kevin W, Milind Rege, Manjunath P Pai, Dana E Mingo, Katie J Suda, Robin S Turpin, and David T Bearden. (2006) 2006. “Time to Initiation of Fluconazole Therapy Impacts Mortality in Patients With Candidemia: A Multi-Institutional Study.”. Clinical Infectious Diseases : An Official Publication of the Infectious Diseases Society of America 43 (1): 25-31.

BACKGROUND: Inadequate antimicrobial treatment is an independent determinant of hospital mortality, and fungal bloodstream infections are among the types of infection with the highest rates of inappropriate initial treatment. Because of significant potential for reducing high mortality rates, we sought to assess the impact of delayed treatment across multiple study sites. The goals our analyses were to establish the frequency and duration of delayed antifungal treatment and to evaluate the relationship between treatment delay and mortality.

METHODS: We conducted a retrospective cohort study of patients with candidemia from 4 medical centers who were prescribed fluconazole. Time to initiation of fluconazole therapy was calculated by subtracting the date on which fluconazole therapy was initiated from the culture date of the first blood sample positive for yeast.

RESULTS: A total of 230 patients (51% male; mean age +/- standard deviation, 56 +/- 17 years) were identified; 192 of these had not been given prior treatment with fluconazole. Patients most commonly had nonsurgical hospital admission (162 patients [70%]) with a central line catheter (193 [84%]), diabetes (68 [30%]), or cancer (54 [24%]). Candida species causing infection included Candida albicans (129 patients [56%]), Candida glabrata (38 [16%]), Candida parapsilosis (25 [11%]), or Candida tropicalis (15 [7%]). The number of days to the initiation of antifungal treatment was 0 (92 patients [40%]), 1 (38 [17%]), 2 (33 [14%]) or > or = 3 (29 [12%]). Mortality rates were lowest for patients who began therapy on day 0 (14 patients [15%]) followed by patients who began on day 1 (9 [24%]), day 2 (12 [37%]), or day > or = 3 (12 [41%]) (P = .0009 for trend). Multivariate logistic regression was used to calculate independent predictors of mortality, which include increased time until fluconazole initiation (odds ratio, 1.42; P < .05) and Acute Physiology and Chronic Health Evaluation II score (1-point increments; odds ratio, 1.13; P < .05).

CONCLUSION: A delay in the initiation of fluconazole therapy in hospitalized patients with candidemia significantly impacted mortality. New methods to avoid delays in appropriate antifungal therapy, such as rapid diagnostic tests or identification of unique risk factors, are needed.

Motl, Susannah E, Katie J Suda, John C Kuth, and Thomas J Gladney. (2006) 2006. “Racial Comparison of Outcomes and Costs for Inpatient Neutropenic Patients: A Multicenter Evaluation.”. Journal of Oncology Practice 2 (2): 53-6.

PURPOSE: Racial disparities have been reported in the care and outcome of cancer patients. We evaluated whether race would influence the cost and outcomes of inpatient neutropenic cancer patients in a multicenter study from a large health care system in the southern United States.

METHODS: Data was collected on all cancer inpatients with a diagnosis code for neutropenia in a 16-hospital system between October 1, 2002, and September 30, 2003. Demographics, treatment outcomes, and costs were compared between white and minority patients. A P value less than .05 was considered statistically significant.

RESULTS: Two hundred seventy-nine cancer patients (0.29% of all admits) had a diagnosis of neutropenia. Demographics were similar between white and minority patients. However, minorities were more likely to be younger than whites (P = .002). With regards to outcomes, length of stay (LOS), LOS in the intensive care unit, and discharge status were not statistically different. Total hospital, medication, laboratory, radiation, surgery, and respiratory costs were also similar (P > .05), although minorities were less likely to receive myeloid colony-stimulating factors (P = .032) and more likely to have higher nursing care costs (P = .048).

CONCLUSION: In light of the escalating reports of racial disparities in cancer care, these minimal differences are encouraging.

Gellad, Walid F, Haiden A Huskamp, Kathryn A Phillips, and Jennifer S Haas. (2006) 2006. “How the New Medicare Drug Benefit Could Affect Vulnerable Populations.”. Health Affairs (Project Hope) 25 (1): 248-55.

This study estimates how out-of-pocket drug costs could change for vulnerable populations (racial and ethnic minorities, the near-poor, and seniors with a greater burden of chronic conditions) who qualify for the standard Medicare drug benefit. Although the new benefit might be associated with modest-to-moderate declines in out-of-pocket spending for seniors who do not qualify for subsidies, the savings might not be shared equitably and therefore might not reduce financial barriers to medication use for these populations.

2005

Sales, Mariscelle M, Francesca E Cunningham, Peter A Glassman, Michael A Valentino, and Chester B Good. (2005) 2005. “Pharmacy Benefits Management in the Veterans Health Administration: 1995 to 2003.”. The American Journal of Managed Care 11 (2): 104-12.

The Department of Veterans Affairs (VA) Pharmacy Benefits Management Strategic Healthcare Group (VA PBM) oversees the formulary for the entire VA system, which serves more than 4 million veterans and provides more than 108 million prescriptions per year. Since its establishment in 1995, the VA PBM has managed pharmaceuticals and pharmaceutical-related policies, including drug safety and efficacy evaluations, pharmacologic management algorithms, and criteria for drug use. These evidence-based practices promote, optimize, and assist VA providers with the safe and appropriate use of pharmaceuticals while allowing for formulary decisions that can result in substantial cost savings. The VA PBM also has utilized various contracting techniques to standardize generic agents as well as specific drugs and drug classes (eg, antihistamines, angiotensin-converting enzyme inhibitors, alpha-blockers, and 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors [statins]). These methods have enabled the VA to save approximately dollar 1.5 billion since 1996 even as drug expenditures continued to rise from roughly dollar 1 billion in fiscal year (FY) 1996 to more than dollar 3 billion in FY 2003. Furthermore, the VA PBM has established an outcomes research section to undertake quality-improvement and safety initiatives that ultimately monitor and determine the clinical impact of formulary decisions on the VA system nationwide. The experiences of this pharmacy benefits program, including clinical and contracting processes/procedures and their impact on the VA healthcare system, are described.

Zahid, Maliha, Ali F Sonel, Samir Saba, and Chester B Good. (2005) 2005. “Perioperative Risk of Noncardiac Surgery Associated With Aortic Stenosis.”. The American Journal of Cardiology 96 (3): 436-8.

The perioperative risk of noncardiac surgery in patients with aortic stenosis (AS) remains ill-defined, and the few studies published have reported conflicting results. A sample of patients from the National Hospital Discharge Survey database diagnosed with AS who underwent any noncardiac surgical procedure was searched. Patients who underwent any cardiac surgery were excluded. Patients with AS were matched by decile of age and surgical risk for twice as many controls. A discharge diagnosis of acute myocardial infarction (AMI) and death was used as the end points for analysis. From 1996 to 2002, 5,149 patients with a diagnosis of AS had undergone noncardiac surgery and were matched with 10,284 controls. The incidence of AMI was greater in patients with AS than in controls (3.86% vs 2.03%, p <0.001). After correcting for gender and the presence of coronary artery disease, hypertension, and diabetes mellitus in a multivariate logistic regression model, the presence of AS was associated with an increased likelihood of AMI (odds ratio 1.55, 95% confidence interval 1.27 to 1.90, p <0.001). There was no significantly increased risk for death in patients with AS versus controls. In the era of more intense perioperative medical management of patients who undergo noncardiac surgery, the presence of AS increases the risk for perioperative AMI but not overall mortality. The impact of the actual severity of AS on outcomes with noncardiac surgery needs further study.

Aspinall, Sherrie L, Chester B Good, Peter A Glassman, and Michael A Valentino. (2005) 2005. “The Evolving Use of Cost-Effectiveness Analysis in Formulary Management Within the Department of Veterans Affairs.”. Medical Care 43 (7 Suppl): 20-6.

The Veterans Health Administration (VHA) runs the largest integrated healthcare system in the nation. Formulary management within VHA primarily involves 3 national groups: the Medical Advisory Panel, the Veterans Integrated Service Network Formulary Leaders, and the Pharmacy Benefits Management Strategic Healthcare Group. Together, these groups manage the VHA national drug formulary with a goal of providing a comprehensive, safe, and cost-effective pharmacy benefit for veterans. Traditionally, VHA has relied on cost-minimization analyses in formulary decisions. More recently, VHA has emphasized the use of cost-effectiveness data, especially for newer, costly drugs. In addition to including this data in drug monographs, the VHA has begun requiring formal cost-effectiveness analysis from manufacturers of selected pharmaceuticals. VHA has also requested that clinically relevant information such as quality of life plus mortality benefit be made available from industry so that internal cost analyses can be performed. It is hoped that by setting the expectation that cost-effectiveness will be formally considered in all VHA formulary decisions, the pharmaceutical industry and others will be stimulated to collect and report data that enables these analyses. We believe that if other organizations also place an emphasis on economic evaluations, industry and the public will be more accepting of decisions that incorporate cost considerations.

Zahid, Maliha, Ali F Sonel, Mary E Kelley, Lauren Wall, Jeff Whittle, Michael J Fine, and Chester B Good. (2005) 2005. “Effect of Both Elevated Troponin-I and Peripheral White Blood Cell Count on Prognosis in Patients With Suspected Myocardial Injury.”. The American Journal of Cardiology 95 (8): 970-2.

We found a high white blood cell count (>11,000/mul) to be of additive prognostic value to high troponin-I levels in predicting risk of recurrent nonfatal myocardial infarctions and all-cause mortality in patients who present with acute coronary syndromes and non-ST-elevation myocardial infarctions. A high troponin-I level or white blood cell count increased the odds ratio of an event to 2.2 (95% confidence interval 1.0 to 4.73, p = 0.05), but high values for the 2 markers increased the odds ratio to 4.5 (95% confidence interval 1.42 to 14.21, p = 0.01).

Kilbourne, Amy M, Charles F Reynolds, Chester B Good, Susan M Sereika, Amy C Justice, and Michael J Fine. (2005) 2005. “How Does Depression Influence Diabetes Medication Adherence in Older Patients?”. The American Journal of Geriatric Psychiatry : Official Journal of the American Association for Geriatric Psychiatry 13 (3): 202-10.

OBJECTIVE: Using various measures (electronic monitoring, patient/provider report, pharmacy data), the authors assessed the association between depression and diabetes medication adherence among older patients with Type 2 diabetes.

METHODS: Patients completed a baseline survey on depression (Patient Health Questionnaire) and were given electronic monitoring caps (EMCs) to use with their oral hypoglycemic medication. At the time of the patient baseline survey, providers completed a survey on their patients' overall medication adherence. Upon returning the caps after 30 days, patients completed a survey on their overall medication adherence. EMC adherence was defined as percent of days out of 30 with correct number of doses. Using pharmacy refill data from the patient baseline through 1 year later, they defined adherence as the percentage of days with adequate medication, based on days' supply across refill periods.

RESULTS: Of 203 patients (mean age: 67 years), 10% (N=19) were depressed. Depressed patients were less likely to self-report good adherence and had a lower median percentage of days with adequate medication coverage (on the basis of pharmacy refill data). After adjustment for alcohol use, cognitive impairment, age, and other medication use, depression was still negatively associated with adequate adherence, according to patient report and pharmacy data. Depression showed no associated with adherence on the basis of provider or EMC data.

CONCLUSIONS: Depression was independently associated with inadequate medication adherence on the basis of patient self-report and pharmacy data.

Kilbourne, Amy M, Mark S Bauer, Xiaoyan Han, Gretchen L Haas, Patrick Elder, Chester B Good, Mujeeb Shad, Joseph Conigliaro, and Harold Pincus. (2005) 2005. “Racial Differences in the Treatment of Veterans With Bipolar Disorder.”. Psychiatric Services (Washington, D.C.) 56 (12): 1549-55.

OBJECTIVES: The authors examined whether African Americans, compared with whites, received guideline-concordant care for bipolar I disorder.

METHODS: A retrospective analysis was conducted of data for patients who received a diagnosis of bipolar I disorder in fiscal year 2001 and received care in facilities in the Department of Veterans Affairs (VA) mid-Atlantic region. Indicators of guideline-concordant care were based on prescription data and data on utilization of inpatient and outpatient services from VA databases.

RESULTS: A total of 2,316 patients with a diagnosis of bipolar I disorder were identified. Their mean age was 52 years; 9.4 percent (N=218) were women, and 13.1 percent (N=303) were African American. Overall, mood stabilizers were prescribed for 74.6 percent (N=1,728) of the patients; 67.1 percent (N=1,554) had an outpatient mental health visit within 90 days after the index diagnosis, and 54.3 percent (N=1,258) had an outpatient visit within 30 days after discharge from a psychiatric hospitalization. Multivariate logistic regression analyses with adjustment for sociodemographic and facility factors revealed that African Americans were less likely than whites to have an outpatient follow-up visit within 90 days after the index diagnosis. Race was not associated with receipt of mood stabilizers or use of outpatient services after a hospital discharge.

CONCLUSIONS: Although a majority of patients received guideline-concordant care for bipolar disorder, potential gaps in continuity of outpatient care may exist for African-American patients.