PubMed · 9290429
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R Baker. 1997. Quality in general practice.. https://doi.org/10.1177/014107689709000722
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Expert-opinion elicitation (EOE) is a heuristic process for gathering evidence and data or answering questions on issues/problems of concern. The Delphi method (DM) is the most frequent technique used to obtain structured elicitation of expert opinions. It has been increasingly applied in medicine to produce guidelines and to evaluate the appropriateness of diagnostic procedures. In this study, a DM has been used as structured EOE process to assess the appropriateness and clinical priority of a data set-based informative system in the context of the Liguria-Trento Transplant Network (LTTN) Project, funded by Italian Ministry of Health. The original data set was obtained by using an interdisciplinary pool of regional experts (n = 60). This data set held 1506 items stratified in 21 categories at various surgical phases (preoperative, intraoperative, and postoperative) and transplantation types (liver, kidney, and kidney/pancreas) in adult and pediatric recipients. Some categories included cadaveric donor management, organ allocation, and acute liver failure. In the second DM round, the data set was subjected to a panel of extraregional, independent experts (n = 9) to assess scores ranging from 1 to 9 on each item, based on increasing appropriateness/priority, according to RAND/UCLA Appropriateness Method. The overall agreement between experts was 95.88%, whereas disagreement and uncertainty were 0.13% and 3.98%, respectively. A major uncertainty occurred for the data set concerning the multiorgan cadaveric donor, for liver transplantation, and for kidney transplantation in adult recipients. The use of a structured EOE process may represent an effective strategy to define the appropriateness and prioritization criteria of a large data set in the field of solid organ transplantation.
Length of stay in hospital (LOS) is a widely used outcome measure in Health Services research, often acting as a surrogate for resource consumption or as a measure of efficiency. The distribution of LOS is typically highly skewed, with a few large observations. An interesting feature is the presence of multiple outcomes (e.g. healthy discharge, death in hospital, transfer to another institution). Health Services researchers are interested in modeling the dependence of LOS on covariates, often using administrative data collected for other purposes, such as calculating fees for doctors. Even after all available covariates have been included in the model, unexplained heterogeneity usually remains. In this article, we develop a parametric regression model for LOS that addresses these features. The model is based on the time, T, that a Wiener process with drift (representing an unobserved health level process) hits one of two barriers, one representing healthy discharge and the other death in hospital. Our approach to analyzing event times has many parallels with competing risks analysis (Kalbfleisch and Prentice, The Statistical Analysis of Failure Time Data, New York: John Wiley and Sons, 1980)), and can be seen as a way of formalizing a competing risks situation. The density of T is an infinite series, and we outline a proof that the density and its derivatives are absolutely and uniformly convergent, and regularity conditions are satisfied. Expressions for the expected value of T, the conditional expectation of T given outcome, and the probability of each outcome are available in terms of model parameters. The proposed regression model uses an approximation to the density formed by truncating the series, and its parameters are estimated by maximum likelihood. An extension to allow a third outcome (e.g. transfers out of hospital) is discussed, as well as a mixture model that addresses the issue of unexplained heterogeneity. The model is illustrated using administrative data.
OBJECTIVE: To evaluate the Ngati Porou Community Injury Prevention Project based in a rural district in the North Island of New Zealand with an extensive indigenous population (Maori). METHOD: The evaluation design was quasi-experimental and included process, impact and outcome measures. RESULTS: Process evaluation found that the Ngati Porou Community Injury Prevention Project was based on sound principles related to injury prevention, as well as addressing Maori aspirations. The main activities undertaken were: road safety campaigns; alcohol and drug programmes; family violence initiatives; and the development of a playground safety audit. A significant increase in awareness of injury prevention was found among Ngati Porou whanau (families) (pre 17% and post 25%, p < 0.05). Injury morbidity statistics for the period 1996-99 showed a significant decrease in injury rates for all age groups, compared with the comparison community (p < 0.05). CONCLUSION: The Ngati Porou Community Injury Prevention Project successfully applied the principles of role modelling, life span focus, accessibility, acceptability and active participation. This is a promising model that could be repeated in other indigenous communities.