A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia

Objective: To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters’ models. Methods: Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters’ models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Results: Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters’ method. Conclusion: VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand

Time series analysis of HIV incidence cases in Ghana : trends, predictions and impact of interventions

The HIV/AIDS epidemic is one of the world’s leading causes of death, particularly in sub-Saharan African nations like Ghana, and threatens socio-economic development in many developing countries. In this thesis Ghanaian HIV data, comprising monthly number of serologically confirmed reported new HIV cases since 1996, was subdivided into northern and southern sectors based on the geographical location of the ten administrative regions. Potential bias in the collection is considered given the strategic location of the two specialist teaching hospital, one in each sector, which receive referrals from the regions. Time series modelling was applied to the monthly number of new HIV cases in each sector. Moving average of time series analysis of equal weight was applied to determine the trend for cases of incidence of HIV infection in the northern and southern sectors while Box-Jenkins modelling identification and Holt’s (double) exponential smoothing modelling methods were employed to predict of new incidence of HIV cases for both sectors in respect to sex and age groups. The effectiveness of three existing major interventions was examined using intervention modelling whereas cointegration modelling was used to determine the long-run impact of condom utilisation on the incidence cases of HIV infection. The trend analysis and predictions for the next three years reveal a slow increase in the number of new incidence of HIV cases. Although, various interventions have influenced the number of cases of HIV infection, the magnitude of impact fluctuated and declined with time. The analysis of the long-run impact of condom utilisation, on the reduction of new HIV incidence cases, indicates that new cases of infection will actually increase monthly by factor of 0.4 -0.6 for every 1000 condoms issued. These perplexing results may be because issuing of condoms does not ensure usage

Application of four-dimension criteria to assess rigour of qualitative research in emergency medicine

Background The main objective of this methodological manuscript was to illustrate the role of using qualitative research in emergency settings. We outline rigorous criteria applied to a qualitative study assessing perceptions and experiences of staff working in Australian emergency departments. Methods We used an integrated mixed-methodology framework to identify different perspectives and experiences of emergency department staff during the implementation of a time target government policy. The qualitative study comprised interviews from 119 participants across 16 hospitals. The interviews were conducted in 2015–2016 and the data were managed using NVivo version 11. We conducted the analysis in three stages, namely: conceptual framework, comparison and contrast and hypothesis development. We concluded with the implementation of the four-dimension criteria (credibility, dependability, confirmability and transferability) to assess the robustness of the study, Results We adapted four-dimension criteria to assess the rigour of a large-scale qualitative research in the emergency department context. The criteria comprised strategies such as building the research team; preparing data collection guidelines; defining and obtaining adequate participation; reaching data saturation and ensuring high levels of consistency and inter-coder agreement. Conclusion Based on the findings, the proposed framework satisfied the four-dimension criteria and generated potential qualitative research applications to emergency medicine research. We have added a methodological contribution to the ongoing debate about rigour in qualitative research which we hope will guide future studies in this topic in emergency care research. It also provided recommendations for conducting future mixed-methods studies. Future papers on this series will use the results from qualitative data and the empirical findings from longitudinal data linkage to further identify factors associated with ED performance; they will be reported separately

Additional file 1: of Application of four-dimension criteria to assess rigour of qualitative research in emergency medicine

Appendix 1. Interview form. Text. (PDF 445 kb