HSA fosters hospitals' voluntary cooperation in areawide planning

An HSA convinced the 31 hospitals in its health service area to participate in a voluntary moratorium on expansion and a voluntary planning process through which their long-range institutional plans are reviewed for incorporation into the HSA's areawide plans.     

An investigation of recall bias in the reporting of past food intake among breast cancer cases and controls.

A nested case-control study was conducted within the Canadian National Breast Screening Study to examine whether there was evidence for biased reporting of past food intake. A total of 325 case patients with breast cancer and 628 matched control subjects completed a self-administered food frequency questionnaire in 1988, recalling their diets originally reported on enrollment into the National Breast Screening Study between 1982 and 1985. Recall of food items was very similar for case patients and control subjects. The magnitude of the odds ratios for the association between these food groups and breast cancer from the prospectively and retrospectively collected data was not systematically different. There was little evidence for recall bias in the reporting of past food intake from these data.     

Novel presentational approaches were developed for reporting network meta-analysis

ObjectivesTo present graphical tools for reporting network meta-analysis (NMA) results aiming to increase the accessibility, transparency, interpretability, and acceptability of NMA analyses.Study Design and SettingsThe key components of NMA results were identified based on recommendations by agencies such as the National Institute for Health and Care Excellence (United Kingdom). Three novel graphs were designed to amalgamate the identified components using familiar graphical tools such as the bar, line, or pie charts and adhering to good graphical design principles.ResultsThree key components for presentation of NMA results were identified, namely relative effects and their uncertainty, probability of an intervention being best, and between-study heterogeneity. Two of the three graphs developed present results (for each pairwise comparison of interventions in the network) obtained from both NMA and standard pairwise meta-analysis for easy comparison. They also include options to display the probability best, ranking statistics, heterogeneity, and prediction intervals. The third graph presents rankings of interventions in terms of their effectiveness to enable clinicians to easily identify “top-ranking” interventions.ConclusionsThe graphical tools presented can display results tailored to the research question of interest, and targeted at a whole spectrum of users from the technical analyst to the nontechnical clinician.     

Improved results in acute appendicitis care following areawide review

The Wisconsin Professional Review Organization compared acute appendectomies being performed in 1981 to those done in 1978 in 32 Wisconsin hospitals. In both years approximately 75 percent of primary appendectomies were in patients 5 to 30 years of age, one-fourth were in patients 15 to 19 years of age, and the majority were in males. Incidence of normal appendices dropped from 16.1 percent in 1978 to 11.4 percent in 1981 (p less than 0.005). The number of patients with normal appendices who did not meet symptom criteria dropped from 37.3 percent to 9.5 percent (p less than 0.05). Incidence of normal appendices was highest in small hospitals. Severity and ruptures or perforations increased, but not significantly. Postoperative complications and mortality decreased. Average length of stay decreased overall, but increased for patients with complications and ruptures or perforations. These data suggest that areawide reviews assure quality and help contain costs. Physician self-regulation using areawide studies may produce desirable change.     

Forecasting areawide hospital utilization: a comparison of five univariate time series techniques.

Time series analysis is one of the methods health services researchers, managers and planners have to examine and predict utilization over time. The focus of this study is univariate time series techniques, which model the change in a dependent variable over time, using time as the only independent variable. These techniques can be used with administrative healthcare databases, which typically contain reliable, time-specific utilization variables, but may lack adequate numbers of variables needed for behavioral or economic modeling. The inpatient discharge database of the Department of Veterans Affairs, the Patient Treatment File, was used to calculate monthly time series over a six-year period for the nation and across US Census Bureau regions for three hospital utilization indicators: average length of stay, discharge rate, and multiple stay ratio, a measure of readmissions. The first purpose of this study was to determine the accuracy of forecasting these indicators 24 months into the future using five univariate time series techniques. In almost all cases, techniques were able to forecast the magnitude and direction of future utilization within a 10% mean monthly error. The second purpose of the study was to describe time series of the three hospital utilization indicators. This approach raised several questions concerning Department of Veterans Affairs hospital utilization.