An analysis of the segregation of restriction fragment length polymorphisms in an Old Order Amish pedigree has made it possible to localize a dominant gene conferring a strong predisposition to manic depressive disease to the tip of the short arm of chromosome 11.

BackgroundThe time taken, or ‘time lags’, between biomedical/health research and its translation into health improvements is receiving growing attention. Reducing time lags should increase rates of return to such research. However, ways to measure time lags are under-developed, with little attention on where time lags arise within overall timelines. The process marker model has been proposed as a better way forward than the current focus on an increasingly complex series of translation ‘gaps’. Starting from that model, we aimed to develop better methods to measure and understand time lags and develop ways to identify policy options and produce recommendations for future studies.MethodsFollowing reviews of the literature on time lags and of relevant policy documents, we developed a new approach to conduct case studies of time lags. We built on the process marker model, including developing a matrix with a series of overlapping tracks to allow us to present and measure elements within any overall time lag. We identified a reduced number of key markers or calibration points and tested our new approach in seven case studies of research leading to interventions in cardiovascular disease and mental health. Finally, we analysed the data to address our study’s key aims.ResultsThe literature review illustrated the lack of agreement on starting points for measuring time lags. We mapped points from policy documents onto our matrix and thus highlighted key areas of concern, for example around delays before new therapies become widely available. Our seven completed case studies demonstrate we have made considerable progress in developing methods to measure and understand time lags. The matrix of overlapping tracks of activity in the research and implementation processes facilitated analysis of time lags along each track, and at the cross-over points where the next track started. We identified some factors that speed up translation through the actions of companies, researchers, funders, policymakers, and regulators. Recommendations for further work are built on progress made, limitations identified and revised terminology.ConclusionsOur advances identify complexities, provide a firm basis for further methodological work along and between tracks, and begin to indicate potential ways of reducing lags.Electronic supplementary materialThe online version of this article (doi:10.1186/1478-4505-13-1) contains supplementary material, which is available to authorized users.

Objective To examine whether the introduction of payment by results (a fixed tariff case mix based payment system) was associated with changes in key outcome variables measuring volume, cost, and quality of care between 2003/4 and 2005/6.Setting Acute care hospitals in England.Design Difference-in-differences analysis (using a control group created from trusts in England and providers in Scotland not implementing payment by results in the relevant years); retrospective analysis of patient level secondary data with fixed effects models.Data sources English hospital episode statistics and Scottish morbidity records for 2002/3 to 2005/6.Main outcome measures Changes in length of stay and proportion of day case admissions as a proxy for unit cost; growth in number of spells to measure increases in output; and changes in in-hospital mortality, 30 day post-surgical mortality, and emergency readmission after treatment for hip fracture as measures of impact on quality of care.Results Length of stay fell more quickly and the proportion of day cases increased more quickly where payment by results was implemented, suggesting a reduction in the unit costs of care associated with payment by results. Some evidence of an association between the introduction of payment by results and growth in acute hospital activity was found. Little measurable change occurred in the quality of care indicators used in this study that can be attributed to the introduction of payment by results.Conclusion Reductions in unit costs may have been achieved without detrimental impact on the quality of care, at least in as far as these are measured by the proxy variables used in this study.

No abstract