Effects of overweight and obesity on economic outcomes among U.S. adults with kidney disease

Background. Kidney disease is a growing public health phenomenon in the U.S. and in the world. Downstream interventions, dialysis and renal transplants covered by Medicare's renal disease entitlement policy in those who are 65 years and over have been expensive treatments that have been not foolproof. The shortage of kidney donors in the U.S. has grown in the last two decades. Therefore study of upstream events in kidney disease development and progression is justified to prevent the rising prevalence of kidney disease. Previous studies have documented the biological route by which obesity can progress and accelerate kidney disease, but health services literature on quantifying the effects of overweight and obesity on economic outcomes in the context of renal disease were lacking. Objectives . The specific aims of this study were (1) to determine the likelihood of overweight and obesity in renal disease and in three specific adult renal disease sub-populations, hypertensive, diabetic and both hypertensive and diabetic (2) to determine the incremental health service use and spending in overweight and obese renal disease populations and (3) to determine who financed the cost of healthcare for renal disease in overweight and obese adult populations less than 65 years of age. Methods. This study was a retrospective cross-sectional study of renal disease cases pooled for years 2002 to 2009 from the Medical Expenditure Panel Survey. The likelihood of overweight and obesity was estimated using chi-square test. Negative binomial regression and generalized gamma model with log link were used to estimate healthcare utilization and healthcare expenditures for six health event categories. Payments by self/family, public and private insurance were described for overweight and obese kidney disease sub-populations. Results. The likelihood of overweight and obesity was 0.29 and 0.46 among renal disease and obesity was common in hypertensive and diabetic renal disease population. Among obese renal disease population, negative binomial regression estimates of healthcare utilization per person per year as compared to normal weight renal disease persons were significant for office-based provider visits and agency home health visits respectively (p=0.001; p=0.005). Among overweight kidney disease population health service use was significant for inpatient hospital discharges (p=0.027). Over years 2002 to 2009, overweight and obese renal disease sub-populations had 53% and 63% higher inpatient facility and doctor expenditures as compared to normal weight renal disease population and these result were statistically significant (p=0.007; p=0.026). Overweigh renal disease population had significant total expenses per person per year for office-based and outpatient associated care. Overweight and obese renal disease persons paid less from out-of-pocket overall compared to normal weight renal disease population. Medicare and Medicaid had the highest mean annual payments for obese renal disease persons, while mean annual payments per year were highest for private insurance among normal weight renal disease population. Conclusion. Overweight and obesity were common in those with acute and chronic kidney disease and resulted in higher healthcare spending and increased utilization of office-based providers, hospital inpatient department and agency home healthcare. Healthcare for overweight and obese renal disease persons younger than 65 years of age was financed more by private and public insurance and less by out of pocket payments. With the increasing epidemic of obesity in the U.S. and the aging of the baby boomer population, the findings of the present study have implications for public health and for greater dissemination of healthcare resources to prevent, manage and delay the onset of overweight and obesity that can progress and accelerate the course of the kidney disease.^

State rate -setting in conjunction with Medicare prospective payment: The effects of the Maine program

Maine implemented a hospital rate-setting program in 1984 at approximately the same time as Medicare started the Prospective Payment System (PPS). This study examines the effectiveness of the program in controlling cost over the period 1984-1989. Hospital costs in Maine are compared to costs in 36 non rate-setting states and 11 other rate-setting states. Changes in cost per equivalent admission, adjusted patient day, per capita, admissions, and length of stay are described and analyzed using multivariate techniques. A number of supply and demand variables which were expected to influence costs independently of rate-setting were controlled for in the study. Results indicate the program was effective in containing costs measured in terms of cost per adjusted patient day. However, this was not true for the other two cost variables. The average length of stay increased during the period in Maine hospitals indicating an association with rate-setting. Several supply variables, especially the number of beds per 1,000 population were strongly associated with the cost and use of hospitals. ^

Hospital district viability and Medicaid /market changes

Hospital districts (HD) that serve the uninsured and the needy face new challenges with the implementation of Medicaid managed. The potential loss of Medicaid patients and revenues may affect the ability to cost-shift and subsequently decrease the ability of the HD to meet its legal obligation of providing care for the uninsured. ^ To investigate HD viability in the current market, the aims of this study were to: (1) describe HD's environment, (2) document the HDs strategic response, (3) document changes in the HD's performance (patient volume) and financial status, and (4) determine whether relationships or trends exist between HD strategy, performance and financial status. ^ To achieve these aims, three Texas HDs (Fort Worth, Lubbock, and San Antonio) were selected to be evaluated. For each HD four types of strategic responses were documented and evaluated for change. In addition, the ability of each HD to sustain operations was evaluated by documenting performance and financial status changes (patient volume and financial ratios). A pre-post case study design method was used in which the Medicaid managed care “rollout'” date, at each site, was the central date. First, a descriptive analysis was performed which documented the environment, strategy, financial status, and patient volume of each hospital district. Second, to compare hospital districts, each hospital district was: (i) classified by a risk index, (ii) classified by its strategic response profile, and (iii) given a performance score based upon pre-post changes in patient volume and financial indicators. ^ Results indicated that all three HDs operate in a high risk environment compared to the rest of the nation. Two HDs chose the “Status Quo” response whereas one HD chose the “Competitive Proactive” response. Medicaid patient volume decreased in two of three HDs whereas indigent patient volume increased in two of the three (an indication of increasing financial risk). Total patient revenues for all HDs increased over the study period; however, the rate of increase slowed for all three after the Medicaid rollout date. All HDs experienced a decline in financial status between pre-post periods with the greatest decline observed in the HD that saw the greatest increase in indigent patient volume. ^ The pre-post case study format used and the lack of control study sites do not allow for assignment of causality. However, the results suggest possible adverse effects of Medicaid managed care and the need for a larger study, based on a stronger evaluation research design. ^

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. ^