Estimates of hospital and physician costs of epilepsy in the United States for 1995 comparing the provider -based survey method and a patient -based medical charts and billing method

This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^

Correlation between dental care utilization and oral cavity cancer in a large sample of community-based United States residents

Cancer of the oral cavity and pharynx remains one of the ten leading causes of cancer death in the United States (US). Besides smoking and alcohol consumption, there are no well established risk factors. While poor dental care had been implicated, it is unknown if the lack of dental care, implying poor dental hygiene predisposes to oral cavity cancer. This study aimed to assess the relationship between dental care utilization during the past twelve months and the prevalence of oral cavity cancer. A cross-sectional design of the National Health Interview Survey of adult, non-institutionalized US residents (n=30,475) was used to assess the association between dental care utilization and self reported diagnosis of oral cavity cancer. Chi square statistic was used to examine the crude association between the predictor variable, dental care utilization and other covariates, while unconditional logistic regression was used to assess the relationship between oral cavity cancer and dental care utilization. There were statistically significant differences between those who utilized dental care during the past twelve months and those who did not with respect to education, income, age, marital status, and gender (p < 0.05), but not health insurance coverage (p = 0.53). Also, those who utilized dental care relative to those who did not were 65% less likely to present with oral cavity cancer, prevalence odds ratio (POR), 0.35, 95% Confidence Interval (CI), 0.12–0.98. Further, higher income advanced age, people of African heritage, and unmarried status were statistically significantly associated with oral cavity cancer, (p < 0.05), but health insurance coverage, alcohol use and smoking were not, p > 0.05. However, after simultaneously controlling for the relevant covariates, the association between dental care and oral cavity cancer did not attenuate nor persist. Thus, compared with those who did not use dental care, those who did wee 62% less likely to present with oral cavity cancer adjusted POR, 0.38, 95% CI, 0.13-1.10. Among US adults residing in community settings, use of dental care during the past twelve months did not significantly reduce the predisposition to oral cavity cancer. However, due to the nature of the data used in this study, which restricts temporal sequence, a large sample prospective study that may identify modifiable factors associated with oral cancer development namely poor dental care, is needed. ^