5 resultados para Information Costs
em DigitalCommons@The Texas Medical Center
Resumo:
The aim of this study was to examine the association between determinants of access to healthcare and preventable hospitalizations, based on Davidson et al.'s framework for evaluating the effects of individual and community determinants on access to healthcare. The study population consisted of the low income, non-elderly, hospitalized adults residing in Harris County, Texas in 2004. The objectives of this study were to examine the proportion of the variance in preventable hospitalizations at the ZIP-code level, to analyze the association between the proximity to the nearest safety net clinic and preventable hospitalizations, to examine how the safety net capacity relates to preventable hospitalizations, to compare the relative strength of the associations of health insurance and the proximity to the nearest safety net clinic with preventable hospitalizations, and to estimate and compare the costs of preventable hospitalizations in Harris County with the average cost in the literature. The data were collected from Texas Health Care Information Collection (2004), Census 2000, and Project Safety Net (2004). A total of 61,841 eligible individuals were included in the final data analysis. A random-intercept multi-level model was constructed with two different levels of data: the individual level and the ZIP-code level. The results of this study suggest that ZIP-code characteristics explain about two percent of the variance in preventable hospitalizations and safety net capacity was marginally significantly associated with preventable hospitalizations (p= 0.062). Proximity to the nearest safety net clinic was not related to preventable hospitalizations; however, health insurance was significantly associated with a decreased risk of preventable hospitalization. The average direct cost was $6,466 per preventable hospitalization, which is significantly different from reports in the literature. ^
Resumo:
The federal government is currently developing the Nationwide Health Information Network (NHIN). Described as a “network of networks,” the NHIN seeks to provide a nationwide, interoperable health information infrastructure that will securely connect consumers with those involved in health care. As part of the national health information technology (HIT) agenda, the NHIN aims to improve individual and population health by enabling health information to follow the consumer, be available for clinical decision-making, and support important public health measures such as biosurveillance. While the NHIN promises to improve clinical care to individuals and to reduce U.S. health care system costs overall, this electronic environment presents novel challenges for protecting individually identifiable health information. A major barrier to achieving public trust in the NHIN is the development of, and adherence to, a consistent and coordinated approach to privacy and security of health information. This paper will analyze the policy framework for electronic health information exchange with the NHIN. This exercise will demonstrate that the current policy is an effective framework for achieving effective biosurveillance with the NHIN. ^
Resumo:
Background. Childhood immunization programs have dramatically reduced the morbidity and mortality associated with vaccine-preventable diseases. Proper documentation of immunizations that have been administered is essential to prevent duplicate immunization of children. To help improve documentation, immunization information systems (IISs) have been developed. IISs are comprehensive repositories of immunization information for children residing within a geographic region. The two models for participation in an IIS are voluntary inclusion, or "opt-in," and voluntary exclusion, or "opt-out." In an opt-in system, consent must be obtained for each participant, conversely, in an opt-out IIS, all children are included unless procedures to exclude the child are completed. Consent requirements for participation vary by state; the Texas IIS, ImmTrac, is an opt-in system.^ Objectives. The specific objectives are to: (1) Evaluate the variance among the time and costs associated with collecting ImmTrac consent at public and private birthing hospitals in the Greater Houston area; (2) Estimate the total costs associated with collecting ImmTrac consent at selected public and private birthing hospitals in the Greater Houston area; (3) Describe the alternative opt-out process for collecting ImmTrac consent at birth and discuss the associated cost savings relative to an opt-in system.^ Methods. Existing time-motion studies (n=281) conducted between October, 2006 and August, 2007 at 8 birthing hospitals in the Greater Houston area were used to assess the time and costs associated with obtaining ImmTrac consent at birth. All data analyzed are deidentified and contain no personal information. Variations in time and costs at each location were assessed and total costs per child and costs per year were estimated. The cost of an alternative opt-out system was also calculated.^ Results. The median time required by birth registrars to complete consent procedures varied from 72-285 seconds per child. The annual costs associated with obtaining consent for 388,285 newborns in ImmTrac's opt-in consent process were estimated at $702,000. The corresponding costs of the proposed opt-out system were estimated to total $194,000 per year. ^ Conclusions. Substantial variation in the time and costs associated with completion of ImmTrac consent procedures were observed. Changing to an opt-out system for participation could represent significant cost savings. ^
Resumo:
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. ^
Resumo:
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. ^