PROJECTION OF HEALTH DEMAND IN TERMS OF HOSPITAL ADMISSIONS FOR SELECTED DIAGNOSES IN HEALTH SYSTEMS AGENCY SERVICE AREAS

The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^

Factors associated with hospital admission of elder cardiovascular patients in an emergency center

Context. Healthcare utilization of elder cardiovascular patients in United States will increase in near future, due to an aging population. This trend could burden urban emergency centers, which have become a source of primary care. ^ Objective. The objective of this study was to determine the association of age, gender, ethnicity, insurance and other presenting variables on hospital admission in an emergency center for elder cardiovascular patients. ^ Design, setting and participants. An anonymous retrospective review of emergency center patient login records of an urban emergency center in the years 2004 and 2005 was conducted. Elder patients (age ≥ 65 years) with cardiovascular disease (ICD91 390-459) were included. Multivariate logistic regression analysis was used to identify independent factors for hospital admission. Four major cardiovascular reasons for hospitalisation – ischemic heart disease, heart failure, hypertensive disorders and stroke were analysed separately. ^ Results. The number of elder patients in the emergency center is increasing, the most common reason for their visit was hypertension. Majority (59%) of the 12,306 elder patients were female. Forty five percent were uninsured and 1,973 patients had cardiovascular disease. Older age (OR 1.10; CI 1.02-1.19) was associated with a marginal increase in hospital admission in elder stroke patients. Elder females compared to elder males were more likely to be hospitalised for ischemic heart disease (OR 2.71; CI 1.22-6.00) and heart failure (OR 1.58; CI 1.001-2.52). Furthermore, insured elder heart failure patients (OR 0.54; CI 0.31-0.93) and elder African American heart failure patients (OR 0.32; CI 0.13-0.75) were less likely to be hospitalised. Ambulance use was associated with greater hospital admissions in elder cardiovascular patients studied, except for stroke. ^ Conclusion. Appropriate health care distribution policies are needed for elder patients, particularly elder females, uninsured, and racial/ethnic minorities. These findings could help triage nurse evaluations in emergency centers to identify patients who were more likely to be hospitalised to offer urgent care and schedule appointments in primary care clinics. In addition, health care plans could be formulated to improve elder primary care, decrease overcrowding in emergency centers, and decrease elder healthcare costs in the future. ^

Modern approaches to pediatric brain injury therapy.

Each year, pediatric traumatic brain injury (TBI) accounts for 435,000 emergency department visits, 37,000 hospital admissions, and approximately 2,500 deaths in the United States. TBI results in immediate injury from direct mechanical force and shear. Secondary injury results from the release of biochemical or inflammatory factors that alter the loco-regional milieu in the acute, subacute, and delayed intervals after a mechanical insult. Preliminary preclinical and clinical research is underway to evaluate the benefit from progenitor cell therapeutics, hypertonic saline infusion, and controlled hypothermia. However, all phase III clinical trials investigating pharmacologic monotherapy for TBI have shown no benefit. A recent National Institutes of Health consensus statement recommends research into multimodality treatments for TBI. This article will review the complex pathophysiology of TBI as well as the possible therapeutic mechanisms of progenitor cell transplantation, hypertonic saline infusion, and controlled hypothermia for possible utilization in multimodality clinical trials.

Persistently elevated troponin I in heart failure patients - a suitable prognosticator and a possible boon to public health?

Baseline elevation of troponin I (TnI) has been associated with worse outcomes in heart failure (HF). However, the prevalence of persistent TnI elevation and its association with clinical outcomes has not been well described. HF is a major public health issue due to its wide prevalence and prognosticators of this condition will have a significant impact on public health. Methods: A retrospective study was performed in 510 patients with an initial HF admission between 2002 to 2004, and all subsequent hospital admissions up to May 2009 were recorded in a de-identified database. Persistent TnI elevation was defined as a level ≥0.05 ng/ml on ≥3 HF admissions. Baseline characteristics, hospital readmissions and all cause mortality were compared between patients with persistent TnI elevation (Persistent), patients with no persistence of TnI (Nonpersistent) and patients who had less than three hospital admissions (admission <3) groups. Also the same data was analyzed using the mean method in which the mean value of all recorded troponin values of each patient was used to define persistence i.e. patients who had a mean troponin level ≥0.05 ng/ml were classified as persistent. Results: Mean age of our cohort was 68.4 years out of which 99.6% subjects were male, 62.4% had ischemic HF. 78.2% had NYHA class III to IV HF, mean LVEF was 25.9%. Persistent elevation of TnI was seen in 26% of the cohort and in 66% of patients with more than 3 hospital admissions. Mean TnI level was 0.67 ± 0.15 ng/ml in the 'Persistent' group. Mean TnI using the mean method was 1.11 ± 7.25 ng/ml. LVEF was significantly lower in persistent group. Hypertension, diabetes, chronic renal insufficiency and mean age did not differ between the two groups. 'Persistent' patients had higher mortality (HR = 1.26, 95% CI = 0.89–1.78, p = 0.199 when unadjusted and HR = 1.29, 95% CI = 0.89–1.86, p = 0.176 when adjusted for race, LVEF and ischemic etiology) HR for mortality in persistent patients was 1.99 (95% CI = 1.06–3.73, p = 0.03) using the mean method. The following results were found in those with ischemic cardiomyopathy (HR = 1.44034, 95% CI = 0.92–2.26, p = 0.113) and (HR = 1.89, 95% CI = 1.01–3.55, p = 0.046) by using the mean method. 2 out of three patients with HF who were readmitted three or more times had persistent elevation of troponin I levels. Patients with chronic persistence of troponin I elevation showed a trend towards lesser survival as compared to patients who did not have chronic persistence, however this did not reach statistical significance. This trend was seen more among ischemic patients than non ischemic patients, but did not reach statistical significance. With the mean method, patients with chronic persistence of troponin I elevation had significantly lesser survival than those without it. Also ischemic patients had significantly lesser survival than non ischemic patients. ^

Effects of air pollution on asthma hospitalization rates in different age groups in metropolitan cities of Korea

Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

Exposure to nonsteroidal anti-inflammatory drugs and weight loss and hospitalization in non-small cell lung cancer patients

Background. Cancer cachexia is a common syndrome complex in cancer, occurring in nearly 80% of patients with advanced cancer and responsible for at least 20% of all cancer deaths. Cachexia is due to increased resting energy expenditure, increased production of inflammatory mediators, and changes in lipid and protein metabolism. Non-steroidal anti-inflammatory drugs (NSAIDs), by virtue of their anti-inflammatory properties, are possibly protective against cancer-related cachexia. Since cachexia is also associated with increased hospitalizations, this outcome may also show improvement with NSAID exposure. ^ Design. In this retrospective study, computerized records from 700 non-small cell lung cancer patients (NSCLC) were reviewed, and 487 (69.57%) were included in the final analyses. Exclusion criteria were severe chronic obstructive pulmonary disease, significant peripheral edema, class III or IV congestive heart failure, liver failure, other reasons for weight loss, or use of research or anabolic medications. Information on medication history, body weight and hospitalizations was collected from one year pre-diagnosis until three years post-diagnosis. Exposure to NSAIDs was defined if a patient had a history of being treated with NSAIDs for at least 50% of any given year in the observation period. We used t-test and chi-square tests for statistical analyses. ^ Results. Neither the proportion of patients with cachexia (p=0.27) nor the number of hospitalizations (p=0.74) differed among those with a history of NSAID use (n=92) and those without (n=395). ^ Conclusions. In this study, NSAID exposure was not significantly associated with weight loss or hospital admissions in patients with NSCLC. Further studies may be needed to confirm these observations.^

The determinants of improvements in health outcomes and of cost reduction in hospital inpatient care

This study aims to address two research questions. First, ‘Can we identify factors that are determinants both of improved health outcomes and of reduced costs for hospitalized patients with one of six common diagnoses?’ Second, ‘Can we identify other factors that are determinants of improved health outcomes for such hospitalized patients but which are not associated with costs?’ The Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) database from 2003 to 2006 was employed in this study. The total study sample consisted of hospitals which had at least 30 patients each year for the given diagnosis: 954 hospitals for acute myocardial infarction (AMI), 1552 hospitals for congestive heart failure (CHF), 1120 hospitals for stroke (STR), 1283 hospitals for gastrointestinal hemorrhage (GIH), 979 hospitals for hip fracture (HIP), and 1716 hospitals for pneumonia (PNE). This study used simultaneous equations models to investigate the determinants of improvement in health outcomes and of cost reduction in hospital inpatient care for these six common diagnoses. In addition, the study used instrumental variables and two-stage least squares random effect model for unbalanced panel data estimation. The study concluded that a few factors were determinants of high quality and low cost. Specifically, high specialty was the determinant of high quality and low costs for CHF patients; small hospital size was the determinant of high quality and low costs for AMI patients. Furthermore, CHF patients who were treated in Midwest, South, and West region hospitals had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. Gastrointestinal hemorrhage and pneumonia patients who were treated in South region hospitals also had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. This study found that six non-cost factors were related to health outcomes for a few diagnoses: hospital volume, percentage emergency room admissions for a given diagnosis, hospital competition, specialty, bed size, and hospital region.^

Epidemiological trends of influenza A positive patients hospitalized at St. Luke's Episcopal Hospital, Houston, Texas September, 2009--January, 2010

This study was a descriptive analysis of 437 influenza A positive inpatients and outpatients during the five month period between September, 2009 and January, 2010. The objective of the study was to describe the epidemiological trends of the total influenza A positive population and more specifically the clinical features of patients hospitalized with influenza A at St. Luke's Episcopal Hospital in Houston, Texas from September 2009 through January 2010. Eligible cases were included if they tested positive for influenza A test using the rapid antigen test and/or rRT-PCR. Hospitalized cases were included based on the laboratory confirmation of influenza A as well as hospital admission for at least 24 hours. Data was collected from medical record abstraction and included patient demographics, clinical history and history of chronic disease. Clinical findings in the differential diagnosis that led to laboratory-confirmation of influenza A as well as course of treatment during the hospital admission were summarized. Finally, co-morbid conditions charted during the hospital visit were reviewed and evaluated for associations with influenza A complications. During the study period, forty-eight patients were included in the study of which 27 tested positive for the H1N1 subtype. Females were more likely to be hospitalized than men. The median age of all patients admitted to St. Luke's Episcopal Hospital with influenza A was 42. The distribution for admitted cases was 15 White, 15 Black, and 18 Hispanic. Patients with co-morbid disease constituted 81% of the admissions for Influenza A. The presence of an underlying medical condition remains a risk factor for both seasonal and H1N1 influenza. Although respiratory conditions such as asthma and COPD are commonly associated with complications of seasonal influenza, patients with metabolic disorders such as kidney disease and/or diabetes were admitted more frequently (58%) during the study period. The patients in the study also of a much younger age than the age that is usually associated with complications of influenza infection, i.e. no patients greater than 65 years of age were admitted with a diagnosis of influenza A. Lower infection rates among elderly populations were similarly reported in other studies of influenza during the same time period. Older patient populations may benefit from antibodies to previous H1N1 strains that have circulated during the twentieth century, whereas younger age groups lack these exposures.^

THE DISCHARGED PSYCHIATRIC PATIENT: POST-HOSPITAL ADJUSTMENT AND FACTORS AFFECTING REHOSPITALIZATION

Discharged psychiatric patients were studied six months post-discharge to determine those demographic, social and clinical characteristics affecting positive or negative adjustment and the degree to which the use of mental health services and medication compliance mediated the effects. With the exception of those with primary or secondary diagnoses of OBS, substance abuse or mental retardation, sixty-three psychiatric subjects between the ages of eighteen and sixty-four were chosen from all admissions into the hospital and interviewed six months after discharge using a specially designed questionnaire.^ The subjects' adjustment to community living was found to be marginal. Although not engaged in destructive activities, over half were living with their family members who supported them financially and emotionally. Most were unemployed and had been so for a long time. Others worked sporadically and frequently changed residences. Most did have substantial social ties with extended family and with friends with whom they interacted regularly, but one-fourth were socially isolated. Almost three-quarters continued to obtain regular mental health services after discharge and followed medication instructions under the supervision of their physician. The use of mental health services after discharge and the use of medication did not appear to affect the subjects' community adaption or their rate of rehospitalization.^ Forty percent of those discharged were rehospitalized by the end of the follow-up period. Four levels of risk of rehospitalization emerged. The highest risk was associated with a history of five or more prior hospitalizations, living alone, and social isolation. One third or more of the subjects expressed a need for more counseling, leisure time activities, case-manager assistance, vocational guidance, supervised housing, and placement into a transitional residential treatment program.^ Recommendations were made to enhance the ability to predict recidivism, to develop interorganizational casework management programs linking the patient and family to the community mental health system and to create computerized tracking and monitoring programs that systematically report patient treatment regimen and progress cross-sectionally and longitudinally. ^

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. ^