Attributing inpatient care to diabetes: The case of Medicare for the elderly in Texas, 1995

Specific aims. This study estimated the accuracy of alternative numerator methods for attributing health care utilization and associated costs to diabetes by comparing findings from those methods with findings from a benchmark denominator method. ^ Methods. Using Medicare's 1995 inpatient and enrollment databases for the elderly in Texas, the researcher developed alternative estimates of costs attributable to diabetes. Among alternative numerator methods were selection of all records having diabetes as a principal or secondary diagnosis, and a complex ICD-9-CM sorting routine as previously developed for study of diabetes costs in Texas. Findings from numerator methods were compared with those from a benchmark denominator method based on attributable risk and adapted from a study of national diabetes costs by the American Diabetes Association. This study applied age, gender and ethnicity specific estimates of diabetes prevalence taken from the 1987–94 National Health Interview Surveys to person-months of Medicare Part A, non-HMO enrollment for Texas in 1995. Outcome measures were number of persons identified as having diabetes using alternative definitions of the disease; and number of hospital stays, patient days, and costs using alternative methods for attributing care and costs to diabetes. Cost estimates were based on Medicare payments plus deductibles, co-pays and third party payments. ^ Findings. Numerator methods for attributing costs to diabetes produced findings quite different than those from the benchmark denominator method. When attribution was based on diabetes as principal or secondary diagnosis, the resulting estimates were significantly higher than those obtained from the denominator method. The more complex sorting routine produced estimates near the lower boundary for the confidence interval associated with estimates from the benchmark method. ^ Conclusions. Numerator methods employed by previous researchers poorly estimate the costs of diabetes. While crude mathematical adjustment can be made to the respective numerator approaches, a more useful strategy would be to refine the complex sorting routine to include more hospitalizations. This report recommends approaches to improving methods previously employed in study of diabetes costs. ^

Children with acute leukemia: A comparison of outcomes and cost-effectiveness from allogeneic blood stem cell and bone marrow transplantation

The relative merits of PBSCT versus BMT for children with standard and high risk hematologic malignancies remain unclear. In a retrospective single center study, we compared allogeneic peripheral blood stem cell transplantation (PBSCT) (n=30) with bone marrow transplantation (BMT) (n=110) in children with acute leukemia. We studied recipients of HLA matched sibling stem cells, and of stem cells from alternative donors (HLA mismatched and/or unrelated) and determined whether sourcing the stem cells from PB or marrow affected engraftment, incidence of acute and chronic GvHD, and disease-free survival at 1 year. Our results show a modest reduction in time to engraftment from PB stem cells and no greater risk of GvHD, but illustrate that the severity of the underlying disease is by far the greatest determinant of 1 year survival. Patients in the BMT group had a higher treatment success rate and lower costs than the recipients of the PBSCT within the standard but not the high risk disease group, where the treatment success rate and the cumulative costs were lower in the PBSCT group compared to the BMT group. Our current incremental cost-effectiveness ratio and analysis of uncertainty suggest that allogeneic transplantation of bone marrow grafts was a more cost-effective treatment option compared to peripheral blood stem cells in patients with standard risk childhood acute leukemia disease. For high risk disease our data are less prescriptive, since the differences were more limited and the range of costs much larger. Neither option demonstrated a clear advantage from a cost-effectiveness standpoint.^

A QUANTITATIVE INVESTIGATION OF SOURCE AND ELEMENTAL COMPOSITION OF INDOOR AND OUTDOOR FINE PARTICULATE AIR POLLUTION IN HOUSTON (TEXAS)

An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^

Cost-benefit analysis: The ``gold standard'' re-examined

The dissertation reviews the recommendations of the Panel on Cost Effectiveness in Health and Medicine (Panel) convened by the US Public Health Service in 1993 in four areas: aggregation of costs and benefits, methods of estimating resources used, definition of population impacted and perspective used in cost benefit analysis. Financial data from a clinical trial was used to test whether different approaches in each of the above four areas would change the net benefit resulting from a cost benefit analysis. Differences in aggregation of cost and benefit resulted in the same net benefit, but not the same cost/benefit ratios. Differences in resource use estimation methods, population subgroups definitions and perspectives all produced different net benefits. Difference in perspective resulted in different and often opposing decisions as to whether the proposed intervention from the clinical trial should be implemented. ^

Quantifying uncertainty in cost effectiveness analyses

This study compared four alternative approaches (Taylor, Fieller, percentile bootstrap, and bias-corrected bootstrap methods) to estimating confidence intervals (CIs) around cost-effectiveness (CE) ratio. The study consisted of two components: (1) Monte Carlo simulation was conducted to identify characteristics of hypothetical cost-effectiveness data sets which might lead one CI estimation technique to outperform another. These results were matched to the characteristics of an (2) extant data set derived from the National AIDS Demonstration Research (NADR) project. The methods were used to calculate (CIs) for data set. These results were then compared. The main performance criterion in the simulation study was the percentage of times the estimated (CIs) contained the “true” CE. A secondary criterion was the average width of the confidence intervals. For the bootstrap methods, bias was estimated. ^ Simulation results for Taylor and Fieller methods indicated that the CIs estimated using the Taylor series method contained the true CE more often than did those obtained using the Fieller method, but the opposite was true when the correlation was positive and the CV of effectiveness was high for each value of CV of costs. Similarly, the CIs obtained by applying the Taylor series method to the NADR data set were wider than those obtained using the Fieller method for positive correlation values and for values for which the CV of effectiveness were not equal to 30% for each value of the CV of costs. ^ The general trend for the bootstrap methods was that the percentage of times the true CE ratio was contained in CIs was higher for the percentile method for higher values of the CV of effectiveness, given the correlation between average costs and effects and the CV of effectiveness. The results for the data set indicated that the bias corrected CIs were wider than the percentile method CIs. This result was in accordance with the prediction derived from the simulation experiment. ^ Generally, the bootstrap methods are more favorable for parameter specifications investigated in this study. However, the Taylor method is preferred for low CV of effect, and the percentile method is more favorable for higher CV of effect. ^

Comparison of medical care costs, utilization, and satisfaction of AIDS patients with and without home care

A sample of 157 AIDS patients 17 years of age or over were followed for six months from the date of hospital discharge to derive average total cost of medical care, utilization and satisfaction with care. Those referred for home care follow-up after discharge from the hospital were compared with those who did not receive home care.^ The average total cost of medical care for all patients was $34,984. Home care patient costs averaged \$29,614 while patients with no home care averaged $37,091. Private hospital patients had average costs of \$50,650 compared with $25,494 for public hospital patients. Hospital days for the six months period averaged 23.9 per patient for the no home care group and 18.5 days for home care group. Patient satisfaction with care was higher in the home care group than no home care group, with a mean score of 68.2 compared with 61.1.^ Other health services information indicated that 98% of the private hospital patients had insurance while only 2% of public hospital patients had coverage. The time between the initial date of diagnosis with AIDS and admission to the study was longer for private hospital patients, survival time over the study period was shorter, and the number of hospitalizations prior to entering the study was higher for private hospital patients. These results suggest that patients treated in the private hospital were sicker than public hospital patients, which may explain their higher average total cost. Statistical analyses showed that cost and utilization have no significant relationship with home care or no home care when controlling for indicators of the severity of illness and treatment in public or private hospital.^ In future studies, selecting a matched group of patients from the same hospital and following them for nine months to one year would be helpful in making a more realistic comparison of the cost effectiveness of home care. ^

COSTS AND EFFECTS OF ARKANSAS' LONG-TERM CARE DEMONSTRATION PROJECT (MEDICAID, CHANELLING, COMMUNITY ASSESSMENT)

The purpose of this study was to assess the impact of the Arkansas Long-Term Care Demonstration Project upon Arkansas' Medicaid expenditures and upon the clients it serves. A Retrospective Medicaid expenditure study component used analyses of variance techniques to test for the Project's effects upon aggregated expenditures for 28 demonstration and control counties representing 25 percent of the State's population over four years, 1979-1982.^ A second approach to the study question utilized a 1982 prospective sample of 458 demonstration and control clients from the same 28 counties. The disability level or need for care of each patient was established a priori. The extent to which an individual's variation in Medicaid utilization and costs was explained by patient need, presence or absence of the channeling project's placement decision or some other patient characteristic was examined by multiple regression analysis. Long-term and acute care Medicaid, Medicare, third party, self-pay and the grand total of all Medicaid claims were analyzed for project effects and explanatory relationships.^ The main project effect was to increase personal care costs without reducing nursing home or acute care costs (Prospective Study). Expansion of clients appeared to occur in personal care (Prospective Study) and minimum care nursing home (Retrospective Study) for the project areas. Cost-shifting between Medicaid and Medicare in the project areas and two different patterns of utilization in the North and South projects tended to offset each other such that no differences in total costs between the project areas and demonstration areas occurred. The project was significant ((beta) = .22, p < .001) only for personal care costs. The explanatory power of this personal care regression model (R('2) = .36) was comparable to other reported health services utilization models. Other variables (Medicare buy-in, level of disability, Social Security Supplemental Income (SSI), net monthly income, North/South areas and age) explained more variation in the other twelve cost regression models. ^

Costs and quality of medication reconciliation practice in primary care clinics

Medication reconciliation, with the aim to resolve medication discrepancy, is one of the Joint Commission patient safety goals. Medication errors and adverse drug events that could result from medication discrepancy affect a large population. At least 1.5 million adverse drug events and $3.5 billion of financial burden yearly associated with medication errors could be prevented by interventions such as medication reconciliation. This research was conducted to answer the following research questions: (1a) What are the frequency range and type of measures used to report outpatient medication discrepancy? (1b) Which effective and efficient strategies for medication reconciliation in the outpatient setting have been reported? (2) What are the costs associated with medication reconciliation practice in primary care clinics? (3) What is the quality of medication reconciliation practice in primary care clinics? (4) Is medication reconciliation practice in primary care clinics cost-effective from the clinic perspective? Study designs used to answer these questions included a systematic review, cost analysis, quality assessments, and cost-effectiveness analysis. Data sources were published articles in the medical literature and data from a prospective workflow study, which included 150 patients and 1,238 medications. The systematic review confirmed that the prevalence of medication discrepancy was high in ambulatory care and higher in primary care settings. Effective strategies for medication reconciliation included the use of pharmacists, letters, a standardized practice approach, and partnership between providers and patients. Our cost analysis showed that costs associated with medication reconciliation practice were not substantially different between primary care clinics using or not using electronic medical records (EMR) ($0.95 per patient per medication in EMR clinics vs. $0.96 per patient per medication in non-EMR clinics, p=0.78). Even though medication reconciliation was frequently practiced (97-98%), the quality of such practice was poor (0-33% of process completeness measured by concordance of medication numbers and 29-33% of accuracy measured by concordance of medication names) and negatively (though not significantly) associated with medication regimen complexity. The incremental cost-effectiveness ratios for concordance of medication number per patient per medication and concordance of medication names per patient per medication were both 0.08, favoring EMR. Future studies including potential cost-savings from medication features of the EMR and potential benefits to minimize severity of harm to patients from medication discrepancy are warranted. ^

Relationship of hospital volume to patient mortality, length of stay and total costs in patients receiving brain surgery for cancer: A nationwide analysis

Better morbidity and mortality outcomes associated with increased hospital procedural volume have been demonstrated across a number of different medical procedures. Existence of such a volume-outcome relationship is posited to lead to increased specialization of care, such that patients requiring specific procedures are funneled to physicians and hospitals that achieve a minimum volume of such procedures each year. In this study, the 2009 Nationwide Inpatient Sample is used to examine the relationship between hospital volume and patient outcome among patients undergoing procedures related to malignant brain cancer. Multiple regression models were used to examine the impact of hospital volume on length of inpatient stay and cost of inpatient stay; logistic regression was used to examine the impact of hospital volume on morbidity. Hospital volume was found to be a significant predictor of both length of stay and cost of stay. Hospital volume was associated with a lower length of stay, but was also associated with increased costs. Hospital volume was not found to be a statistically significant predictor of morbidity, though less than three percent of this sample died while in the hospital. Volume is indeed a significant predictor of outcome for procedures related to brain malignancies, though further research regarding the cost of such procedures is recommended.^

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. ^