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Background: There have been few studies on costs of burn treatment. Furthermore, quantifying the actual cost of care at the patient level is hindered by anomalies of our insurance system. This article presents a practical method for determining the cost of caring for pediatric burn patients, using a cohort of patients from the Multi-Center Benchmarking Study at the Shriners Hospitals for Children-Boston and allows an estimate of resource use that may be linked to need or to best practices, without the confounding variable of inconsistent billing practices., Methods: We estimated the cost of hospitalization for a cohort of 230 pediatric patients who sustained burn injuries. In a simulation of billing patterns of all US hospitals between 2001 and 2009, we applied Shriners Hospitals for Children use data to two external sources of cost information. For the hospital component of costs, we used the Healthcare Cost and Utilization Project Kid's Inpatient Database, and for the physician component of costs, we used the Medicare fee schedule., Results: Patients had a mean of 1.9 hospitalizations over 3 to 4 years. The mean total cost of hospitalization was $83,535 per patient, and the median total cost was $16,331 in 2006 dollars., Conclusion: This is the first effort to estimate the early hospital costs of caring for children and young adults with burns in specialty hospitals and to establish a referent for quantifying the cost of caring for patients with acute burns. It lays the groundwork for studies relating costs of specific interventions to their effects on patient-centered outcomes.

Oral conditions can have serious, disabling effects. The purposes of this study are 2-fold: first to estimate the prevalence and severity of self-reported oral problems in male veterans who use Department of Veterans Affairs (VA) outpatient medical (but not dental) care and, second, we examine to what extent the impact of oral conditions is associated with measures of general health and well-being. Male veteran users of outpatient VA medical care from the Veterans Health Study (N = 2425) were surveyed using questionnaires, which included sociodemographic information, the SF-36, the Geriatric Oral Health Assessment Index (GOHAI), and the Oral Health and Quality of Life (OHQOL) measure. Only 28% of these users of VA outpatient care rated their oral health as excellent or very good, 32% as good, and nearly 40% as fair or poor. Furthermore, only one half of respondents could always eat without discomfort, were pleased with the looks of their teeth, and had no worries about their teeth. Factor analysis of the SF-36, GOHAI, and OHQOL items confirmed that both the GOHAI and the OHQOL are separate and independent of the 8 scales of the SF-36. Regression analyses showed that the GOHAI but not the OHQOL is significantly associated with the mental and physical component summary scales of the SF-36 when both sociodemographics and disease burden are controlled for in the models. Oral problems, as measured by the GOHAI and the OHQOL, are significant burdens on the health and function of veterans who use VA outpatient care. Oral health, as measured by the GOHAI, contributes in an important way to the functional well-being of users of VA healthcare.

Alcohol-related disorders are common in primary care settings; many primary care physicians are ill-equipped to manage patients with alcohol-related disorders. The objective of this prospective cohort study was to develop and validate a patient-based measure, the Primary Care Alcohol Severity Measure, to determine which primary care patients with alcohol-related disorders would benefit from referral to alcohol treatment services. Four Boston-area Department of Veterans Affairs ambulatory care clinics were chosen as study sites. Two hundred seventy-eight male patients, mean age 55.5 years, 89.9% Caucasian, 42.5% married, all with CAGE Questionnaire scores greater than or equal to 2 and drinking within past year, participated in the study. We developed a multidimensional, 30-item measure that contained 2 subscales that assessed 2 symptom clusters of alcohol-related disorders: Physical and Behavioral. Each subscale's score was higher (more severe) for patients with a current Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised diagnosis of alcohol dependence or abuse: P < .01 for the physical subscale and P < .0001 for the behavioral subscale. Patients with more physical symptoms had poorer physical and mental health status, whereas patients with more behavioral symptoms had poorer mental health status. Scores on the 2 subscales, along with age and history of prior treatment, predicted the use of alcohol treatment services in the following year: c = 0.90 in logistic regression. The Primary Care Alcohol Severity Measure is a valid measure of alcohol severity in primary care patients and predicts the use of alcohol treatment services. It is relatively brief and easy to use, requiring only standard medical history items and patient reports of behavioral symptoms. It may be a useful tool to improve the quality of care for primary care patients with alcohol-related disorders.

This study aims to develop a patient-based measure of the complications of type 2 diabetes that can be used in examining its relationship with health-related quality of life (HRQOL) and utilization of health services. Using questions analogous to those typically employed by clinicians, we developed a 17-item questionnaire to identify prior diagnoses and current symptoms of 6 common complications of type 2 diabetes. We administered it to 419 patients with type 2 diabetes who were part of the Veterans Health Study, a larger prospective investigation of veterans receiving ambulatory care. From the responses, we calculated a simple sum of the 6 complications. We examined the correlation of this Diabetes Complications Index (DCI) with use of diabetes-related medical resources, outpatient doctor visits, HRQOL, duration of diabetes, and the degree to which patients perceived their health to be diminished by diabetes. The DCI was significantly correlated with the degree to which patients perceived their health to be diminished by diabetes (r = 0.35, P = .0001), utilization of diabetes-related resources (model R = 0.15, P = .0001), outpatient doctor visits (model R = .08, P = .001), and duration of diabetes (r = 0.11, P = .04). It had a good correlation with aspects of HRQOL that reflect physical function when controlling for age and comorbid conditions (model R = 0.23, P = .0001). The DCI shows promise as an efficient method for assessing the effects of type 2 diabetes on HRQOL and predicting utilization of medical resources.

Measures of case mix are needed to control for patients' clinical status in studies assessing the process and outcomes of care. The Veterans Health Study (VHS) is a longitudinal study of determinants of health outcomes in ambulatory veterans. This study assessed the validity of a case-mix measure developed to quantify severity of illness in ambulatory type 2 diabetic patients. As part of the pilot phase of the VHS, 245 veterans using 4 primary care clinics in Boston were screened for diabetes and 5 other chronic illnesses when they presented for care. Subjects screening positive for diabetes returned to complete severity of illness and outcome measures. The variables for the diabetes case-mix module were chosen based upon the principles of parsimony, duration of follow-up, and clinical validity and credibility. Variables were selected to predict function, as measured by the Medical Outcomes Study Short-Form 36 (SF-36). The diabetic patients in this study had a heavy burden of chronic illness, with an average of 3.9 comorbid conditions and a mean general health perceptions score of 48 on the SF-36 (scored from 0 to 100, with 100 indicating best health). A summary variable called DMSEV was created for "diabetes severity". This included atherosclerotic complications(stroke, transient ischemic attack or myocardial infarction; chest pain frequency; and claudication), plus any history of eye, foot, or neuropathic symptoms. DMSEV correlated with all 8 outcome scales of the SF-36, and in particular was highly associated with physical function (r=0.49, P=.0001). Least squares linear regression analysis controlling for age and comorbidity confirmed the association of DMSEV with all 8 SF-36 scales. The correlation with physical function remained highly significant (P<.0001), with an R of 0.31. This patient-based self-assessment questionnaire and the summary variable DMSEV appear to be valid measures of severity of illness in ambulatory diabetic veterans with multiple comorbidities. After further testing, this case-mix measure may be suitable for controlling for severity of illness in ambulatory-based studies of diabetic patients with multiple chronic illnesses.

Using longitudinal data from the Veterans Health Study (VHS), we extended our earlier published cross-sectional analysis in comparing the generic SF-36 physical functioning (PF) and role limitations (role-physical [RP]) scales with the disease-specific PF and RP scales using disease attributions. The present study included 569 patients with chronic lung disease (CLD) and 352 patients with chronic low back pain (LBP) who received Veterans Affairs (VA) ambulatory care between June 1993 and March 1996. Consistent with our earlier study, we found that changes in the generic PF and RP scales had higher correlations with the other generic SF-36 scales than those in the disease-specific PF and RP scales over 12 months. On the other hand, disease-specific measures of PF and RP had larger R and t statistic values in discriminating the impacts of symptom-based illness severity as well as clinical services on physical and role functioning. These results suggest that the generic and disease-specific measures of PF and RP behave distinctly different from each other over time. The generic measures of PF and RP tend to assess a broad array of health-related quality of life, whereas disease-specific attributions of PF and RP scales tend to evaluate disease progression and clinical management associated with specific disease conditions. Disease-specific attribution is an important alternative to the development of new disease-specific instruments for assessing illness severity and the impact of clinical services.

The objective of the study was to develop a self-reported measure of patients' comorbid illnesses that could be readily administered in ambulatory care settings and that would improve assessment of their health-related quality of life and utilization of health services. Data were analyzed from the Veterans Health Study, an observational study of health outcomes in patients receiving Veterans Administration (VA) ambulatory care. Patients who received ambulatory care services in 4 VA outpatient clinics in the greater Boston area between August 1993 and March 1996 were eligible for inclusion. Among the 4137 patients recruited, 2425 participated in the Veterans Health Study, representing a response rate of 59%. Participants were mailed a health-related quality of life questionnaire, the Medical Outcomes Study Short Form Health Survey (SF-36). They were also scheduled for an in-person interview at which time they completed a medical history questionnaire. We developed a comorbidity index (CI) that included 30 self-reported medical conditions (physical CI) and 6 self-reported mental conditions (mental CI). The physical CI and the mental CI were significantly associated with all SF-36 scales and explained 24% and 36%, respectively, of the variance in the physical component summary and the mental component summary of the SF-36. Both indexes were also significant predictors of future outpatient visits and mortality. The CI is an independent predictor of health status, outpatient visits, and mortality. Its use appears to be a practical approach to case-mix adjustment to account for differences in comorbid illnesses in observational studies of the quality of healthcare. It can be administered to large patient populations at relatively low cost. This method may be particularly valuable for clinicians and researchers interested in population-based studies, case-mix adjustment, and clinical trials.