PubMed · 13513923
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S S KOMORITA. 1958. Probability learning under equivalent data collection methods.. https://doi.org/10.1037/h0045819
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This paper uses the results of the PERISTAT feasibility study to assess the extent to which the participating countries of Europe were able to provide data to construct the core and recommended indicators of perinatal health defined in the project. After describing the approaches used for data collection in participating countries, this paper describes the extent to which they were able to provide the data requested to construct the indicators. It documents data sources within each country and their characteristics. The paper then discusses influences on the agenda, particularly the extent to which data collection occurs as a by-product of other processes such as civil registration and the administration of health care and how these processes can both enable and impede data collection. It closes by suggesting how data collection in Europe can be improved in order to widen the scope of the agenda for compiling perinatal indicators.
The main purpose of this article is to point out common pitfalls that can confuse comparative analyses of indicators of perinatal health and to discuss ways to overcome or minimize these difficulties. The challenge is to distinguish 'real' variations in the value of an indicator from variations due to differences in registration practices and definitions and from random variation. The first section presents the major properties that are desirable in indicators of perinatal health status and perinatal health care in Europe to be used for comparative purposes. The second section provides specific examples of the types of methodological difficulties encountered in European cross-country comparisons due to variations in the definition, measurement and construction of indicators. The conclusion discusses the PERISTAT project's responses to these difficulties and how these methodological constraints impact on the selection of an appropriate indicator set for Europe today.
OBJECTIVE: To determine the availability of inpatient computerized physician order entry in U.S. hospitals and the degree to which physicians are using it. DESIGN: Combined mail and telephone survey of 964 randomly selected hospitals, contrasting 2002 data and results of a survey conducted in 1997. MEASUREMENTS AVAILABILITY: computerized order entry has been installed and is available for use by physicians; inducement: the degree to which use of computers to enter orders is required of physicians; participation: the proportion of physicians at an institution who enter orders by computer; and saturation: the proportion of total orders at an institution entered by a physician using a computer. RESULTS: The response rate was 65%. Computerized order entry was not available to physicians at 524 (83.7%) of 626 hospitals responding, whereas 60 (9.6%) reported complete availability and 41 (6.5%) reported partial availability. Of 91 hospitals providing data about inducement/requirement to use the system, it was optional at 31 (34.1%), encouraged at 18 (19.8%), and required at 42 (46.2%). At 36 hospitals (45.6%), more than 90% of physicians on staff use the system, whereas six (7.6%) reported 51-90% participation and 37 (46.8%) reported participation by fewer than half of physicians. Saturation was bimodal, with 25 (35%) hospitals reporting that more than 90% of all orders are entered by physicians using a computer and 20 (28.2%) reporting that less than 10% of all orders are entered this way. CONCLUSION: Despite increasing consensus about the desirability of computerized physician order entry (CPOE) use, these data indicate that only 9.6% of U.S. hospitals presently have CPOE completely available. In those hospitals that have CPOE, its use is frequently required. In approximately half of those hospitals, more than 90% of physicians use CPOE; in one-third of them, more than 90% of orders are entered via CPOE.