Predictors for waiting time for coronary angioplasty in a high risk population.
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Objective--To describe the clinical and non-clinical factors which influence the waiting time from initial angiography to angioplasty. Design--Follow up of a random sample of 106 patients undergoing their first coronary angiography for whom a decision to revascularise by percutaneous transluminal angioplasty was made in 1991. The period between the date of angiography and the date of angioplasty and various clinical characteristics of patients were retrieved from medical notes in mid 1993. Patients were sampled from those investigated in the two Northern Ireland catheterisation laboratories in Belfast, which provide services for the whole of the province (population 1.5 million). Main measures--The dependent variable was the period between initial angiography and angioplasty, and the independent variables included age, sex, distance from cardiac catheterisation centre, referral source, characteristics of the clinical history, severity of angina, and anatomical extent of disease. Cox's proportional hazards analysis was used to derive a relative hazard, expressing the relative chances of revascularisation occurring at any time during follow up. Results--Of the 106 patients studied, 93 had had percutaneous transluminal angioplasty at follow up. The most important predictors of waiting time were the presence of severe angina (relative hazards 3.1(95 % confidence interval (95% CI) 1.4-6.8) and 2.7(1.2-6.2) for Canadian Cardiovascular grades III and IV v angina grade I angina), a recent history of myocardial infarction (relative hazard, 2.5(1.3-4.8), and whether or not the patient was economically active (relative hazard 0.6(0.4-1.0) for economically inactive v active patients). Although there was also an association with the relative deprivation of the area of residence of the patient it had no clear linear trend. Conclusions--Although waiting time for percutaneous transluminal angioplasty was predictably related to the patient's clinical presentation, demographic factors may also be important in determining access to intervention. These factors clearly merit further study; ultimately, the evaluation of equity in a waiting time distribution may more properly be a societal rather than a clinical judgment. (+info)
Use of PRISM scores in triage of pediatric patients with diabetic ketoacidosis.
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Triage guidelines are needed to help in the decision process of intensive care unit (ICU) versus non-ICU admission for patients with diabetic ketoacidosis (DKA). Pediatric risk of mortality (PRISM) scores have long been used to assess mortality risk. This study assess the usefulness of the traditional PRISM score and adaptation of that score (PRISM-ED, which uses presentation data only) in predicting hospital stay in pediatric patients with DKA. PRISM and PRISM-ED were tested for correlation with length of stay and length of ICU stay. A medical record review was conducted for patients admitted to The Children's Hospital of Alabama with DKA during an 18-month period (n = 79). Two scores were calculated for each study entrant: PRISM using the worst recorded values over the first 24 hours and PRISM-ED using arrival values. Median scores, median test, and Spearman rank correlations were determined for both tests. Median PRISM scores were PRISM = 11 and PRISM-ED = 12; Median PRISM and PRISM-ED scores for patients admitted to the ICU were less than median scores among floor-admitted patients: [table: see text] Spearman rank correlations were significant for both scores versus total stay: PRISM, rs = 0.29; P = 0.009; PRISM-ED, rs = 0.60, P < 0.001. Also, correlations were significant for both scores versus ICU stay: PRISM rs = 0.22, P = 0.05; PRISM-ED, rs = 0.41, P < 0.001. Triage guidelines for ICU versus floor admission for DKA patients could have significant economic impact (mean ICU charge = $11,417; mean charge for floor admission = $4,447). PRISM scores may be an important variable to include in a multiple regression model used to predict the need for ICU monitoring. (+info)
The diagnosis, classification, and management of asthma according to severity.
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This activity is designed for primary care and specialist physicians. GOAL: To provide prompt and appropriate treatment for asthma of all levels of severity resulting in improved level of activity and decreased need for urgent care and hospitalization with a possible reduction in the annual decline of lung function, degree of permanent airway damage, and mortality. OBJECTIVES: 1. To provide a framework on the basis of history, physical findings, and laboratory results for the diagnosis of asthma. 2. To improve the ability to classify asthma by degree of severity. 3. To describe an incremental therapeutic approach to asthma by degree of severity. 4. To provide a systematic approach with regard to periodic reevaluation of asthma severity and modification of the treatment plan. (+info)
Clinical improvement with bottom-line impact: custom care planning for patients with acute and chronic illnesses in a managed care setting.
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A fully capitated, integrated healthcare delivery system endeavored to improve the care of its sickest members. A computer algorithm severity index that encompassed a 1-year history of hospitalization and adjusted for inclusion of a variety of chronic conditions was calculated on the basis of clinical and administrative claims databases for the entire membership of the healthcare system. Monthly updated lists were produced to find patients with acute and chronic illnesses. These patients accounted for one-fourth of hospital admissions and almost half of inpatient days, but they numbered less than 1% of system membership. Each listed person, regardless of age or diagnosis, had a custom care plan formulated by nurses in consultation with the primary care physician and involved specialists. Plan development featured in-home assessments in most instances and incorporated a variety of ancillary services, telephone and home-care follow-up, and strategies to increase continuity and access to care. Patient-reported functional status was obtained at establishment of the care plan and periodically thereafter in expectation of raising the cross-sectional mean values of the population. Three months after initiation of the program, the expected winter hospitalization peak did not occur, and utilization tended to be lower in subsequent months. Inpatient admissions among members with acute and chronic illnesses decreased 20%, and inpatient days decreased 28% from baseline levels. Among the subset of seniors in the population, inpatient days decreased 37%. Net financial impact was a medical expenditure decrease of more than 5% from 1995 levels. On a population basis, functional status was raised, and the acuity of patients' conditions and need for inpatient hospital care were reduced. (+info)
Health-based payment and computerized patient record systems.
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Health care information technology is changing rapidly and dramatically. A small but growing number of clinicians, especially those in staff and group model HMOs and hospital-affiliated practices, are automating their patient medical records in response to pressure to improve quality and reduce costs. Computerized patient record systems in HMOs track risks, diagnoses, patterns of care, and outcomes across large populations. These systems provide access to large amounts of clinical information; as a result, they are very useful for risk-adjusted or health-based payment. The next stage of evolution in health-based payment is to switch from fee-for-service (claims) to HMO technology in calculating risk coefficients. This will occur when HMOs accumulate data sets containing records on provider-defined disease episodes, with every service linked to its appropriate disease episode for millions of patients. Computerized patient record systems support clinically meaningful risk-assessment models and protect patients and medical groups from the effects of adverse selection. They also offer significant potential for improving quality of care. (+info)
Public hospital resource allocations in El Salvador: accounting for the case mix of patients.
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National hospitals in developing countries command a disproportionate share of medical care budgets, justified on the grounds that they have a more difficult patient case mix and higher occupancy rates than decentralized district hospitals or clinics. This paper empirically tests the hypothesis by developing direct measures of the severity of patient illness, hospital case-mix and a resource intensity index for each of El Salvador's public hospitals. Based on an analysis of inpatient care staffing requirements, national hospitals are found to receive funding far in excess of what case-mix and case-load considerations would warrant. The findings suggest that significant system-wide efficiency gains can be realized by allocating hospital budgets on the bases of performance-related criteria which incorporate the case-mix approach developed here. (+info)
Predictors of acute hospital costs for treatment of ischemic stroke in an academic center.
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BACKGROUND AND PURPOSE: We sought to determine predictors of acute hospital costs in patients presenting with acute ischemic stroke to an academic center using a stroke management team to coordinate care. METHODS: Demographic and clinical data were prospectively collected on 191 patients consecutively admitted with acute ischemic stroke. Patients were classified by insurance status, premorbid modified Rankin scale, stroke location, stroke severity (National Institutes of Health Stroke Scale score), and presence of comorbidities. Detailed hospital charge data were converted to cost by application of department-specific cost-to-charge ratios. Physician's fees were not included. A stepwise multiple regression analysis was computed to determine the predictors of total hospital cost. RESULTS: Median length of stay was 6 days (range, 1 to 63 days), and mortality was 3%. Median hospital cost per discharge was $4408 (range, $1199 to $59 799). Fifty percent of costs were for room charges, 19% for stroke evaluation, 21% for medical management, and 7% for acute rehabilitation therapies. Sixteen percent were admitted to an intensive care unit. Length of stay accounted for 43% of the variance in total cost. Other independent predictors of cost included stroke severity, heparin treatment, atrial fibrillation, male sex, ischemic cardiac disease, and premorbid functional status. CONCLUSIONS: We conclude that the major predictors of acute hospital costs of stroke in this environment are length of stay, stroke severity, cardiac disease, male sex, and use of heparin. Room charges accounted for the majority of costs, and attempts to reduce the cost of stroke evaluation would be of marginal value. Efforts to reduce acute costs should be monitored for potential cost shifting or a negative impact on quality of care. (+info)
Prediction of sleep-disordered breathing by unattended overnight oximetry.
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Between January 1994 and July 1997, 793 patients suspected of having sleep-disordered breathing had unattended overnight oximetry in their homes followed by laboratory polysomnography. From the oximetry data we extracted cumulative percentage time at SaO2 < 90% (CT90) and a saturation variability index (delta Index, the sum of the differences between successive readings divided by the number of readings - 1). CT90 was weakly correlated with polysomnographic apnea/hypopnea index (AHI). (Spearman rho = 0.36, P < 0.0001) and with delta Index (rho = 0.71, P < 0.0001). delta Index was more closely correlated with AHI (rho = 0.59, P < 0.0001). In a multivariate model, only delta Index was significantly related to AHI, the relationship being AHI = 18.8 delta Index + 7.7. The 95% CI for the coefficient were 16.2, 21.4, and for the constant were 5.8, 9.7. The sensitivity of a delta Index cut-off of 0.4 for the detection of AHI > or = 15 was 88%, for detection of AHI > or = 20 was 90% and for the detection of AHI > or = 25 was 91%. The specificity of delta Index > or = 0.4 for AHI > or = 15 was 40%. In 113 further patients, oximetry was performed simultaneously with laboratory polysomnography. Under these circumstances delta Index was more closely correlated with AHI (rho = 0.74, P < 0.0001), as was CT90 (rho = 0.58, P < 0.0001). Sensitivity of delta Index > or = 0.4 for detection of AHI > or = 15 was not improved at 88%, but specificity was better at 70%. We concluded that oximetry using a saturation variability index is sensitive but nonspecific for the detection of obstructive sleep apnea, and that few false negative but a significant proportion of false positive results arise from night-to-night variability. (+info)