Efficiency of the hospitals affects the price of health services. Health care payments have equity implications. Evidence on hospital performance can support to design the policy; however, the recent literature on hospital efficiency produced conflicting results. Consequently, policy decisions are uncertain. Even the most of evidence were produced by using data from high income countries. Conflicting results were produced particularly due to differences in methods of measuring performance. Recently a management approach has been developed to measure the hospital performance. This approach to measure the hospital performance is very useful from policy perspective to improve health system from cost-effective way in low and middle income countries. Measuring hospital performance through management approach has some basic characteristics such as scoring management practices through double blind survey, measuring hospital outputs using various indicators, estimating the relationship between management practices and outputs of the hospitals. This approach has been successfully applied to developed countries; however, some revisions are required without violating the fundamental principle of this approach to replicate in low- and middle-income countries. The process has been clearly defined and applied to Nepal. As the results of this, the approach produced expected results. The paper contributes to improve the approach to measure hospital performance.
*Developing Countries ; Efficiency, Organizational/*classification ; Hospital Administration/*classification ; Hospitals/*classification ; Management Audit/methods/*organization & administration ; Nepal ; Outcome and Process Assessment (Health Care)/methods/*organization & administration

OBJECTIVETo study the emergency management principles of severe trauma in hospital (injury severity score larger than or equal to 16).

METHODSWe used "ATP principle" to manage severe traumatic patients. The ATP principle is composed of: 1) attending surgeons offering initial management (A); 2) teamwork commencement immediately after patients admitted to hospital (T); 3) parallel principle, ie, emergency resuscitation, evaluation and laboratory test performed simultaneously (P). Clinical effects before and after applying ATP principle were retrospectively analyzed and compared.

RESULTSDuring January 1, 2002 to December 31, 2003, 338 patients were treated without applying ATP principle, in which ISS was 25.9+/-6.4, 152 cases died with the mortality being 39.2%, and the time stayed in emergency department and the time to operation room after admission were (102.8+/-16.7) min, (140.3+/-20.6) min, respectively. During January 1, 2004 to December 31, 2005, 438 patients were treated based on ATP principle, in which ISS was 28.6+/-7.8, 87 cases died with the mortality being 19.9%, and the time in emergency department and the time to operation room after admission were (69.5+/-11.5) min, (89.6+/-9.3) min, respectively. ISS showed no significant difference between the two groups (P larger than 0.05) but the mortality, the time stayed in emergency department and the time to operation room after admission were greatly reduced and showed significant difference between the two groups (P less than 0.05).

CONCLUSIONSApplying ATP principle to treat severe traumatic patients can shorten emergency treatment time in hospital and decrease mortality.

Adolescent ; Adult ; Aged ; Aged, 80 and over ; China ; Emergency Service, Hospital ; organization & administration ; Female ; Humans ; Injury Severity Score ; Male ; Middle Aged ; Patient Care Team ; Retrospective Studies ; Triage ; Wounds and Injuries ; classification ; mortality ; therapy

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are established for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The "AUTOGRP System" was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The "Departmental Method" was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying pattern of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among this study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables(i.e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The weighted mean total case cost(TOTC) of the study hospitals for Medicare patients during the study years was $1127.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($745.45). The weighted mean per total cost (DTOC) of the study hospitals for Medicare patients during the study years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the lowest average DTOC($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variable to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of inter-hospital cost variation; 59.1 percent for TOTC and 44.3 percent for DTOC. These results demonstrate that the casemix index is the most important determinant of inter-hospital cost variation. Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix-related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.
Classification ; Connecticut ; Cost Control ; Data Collection ; Dataset ; Diagnosis ; Diagnosis-Related Groups ; Health Facility Size ; Hospital Costs* ; Hospitals, General ; Humans ; Information Systems ; Length of Stay ; Linear Models ; Medicare ; Mortality ; Population Characteristics* ; United States Social Security Administration