The Impact of Flexible Working Arrangements on Work-Life Conflict and Work Pressure in Ireland. ESRI WP192. April 2007

The impetus for this study arose from the need to upgrade the case mix measure of choice in use at the national level in Ireland. Since 1993, various versions of the DRG grouper supported by the Health Care Financing Administration (HCFA) had been in use in Ireland. With improvements in available data, together with developments in the range and quality of alternative groupers available, it was considered timely to test performance of the alternative options on discharge abstract data for Irish hospitals. The groupers selected for testing included four versions of the Australian Refined (AR) DRGs, the AP DRGs (V18.0), CMS DRGs (V20) and IR DRGs (V1.2). Results for the HCFA DRGS (V16.0) were also included for purposes of compariso

Kidney Dataset

This dataset is taken from McGilchrist and Aisbett (1991). It describes the first and second recurrence times of infection in kidney patients together with information on risk variables such as age, sex, and disease type. Source McGilchrist, C. A., & Aisbett, C. W. (1991). Regression with frailty in survival analysis. Biometrics, 47(2), 461-466</p

Measuring Hospital Case Mix : Evaluation of Alternative Approaches for the Irish Hospital System

The impetus for this study arose from the need to upgrade the case mix measure of choice in use at the national level in Ireland. Since 1993, various versions of the DRG grouper supported by the Health Care Financing Administration (HCFA) had been in use in Ireland. With improvements in available data, together with developments in the range and quality of alternative groupers available, it was considered timely to test performance of the alternative options on discharge abstract data for Irish hospitals. The groupers selected for testing included four versions of the Australian Refined (AR) DRGs, the AP DRGs (V18.0), CMS DRGs (V20) and IR DRGs (V1.2). Results for the HCFA DRGS (V16.0) were also included for purposes of comparison. The empirical analysis ranked the AR DRG Groupers highly relative to the alternatives. Additional factors favouring the AR DRG series of Groupers are the fact that they are the more widely used internationally, are updated regularly and supported by Australian government agencies. More support and training opportunities are also available for the use of these Groupers. Given these factors, together with the fact that the ICD-10-AM morbidity coding system is used in Ireland, the AR DRG classification system was recommended as the best option for use at the national level in Ireland.case mix, DRG Groupers, AR DRGs, ICD-10-AM

Describing Iranian hospital activity using Australian Refined DRGs: A case study of the Iranian Social Security Organisation

Objective: To describe Iran's hospital activity with Australian Refined Diagnosis Related Groups (AR-DRGs). Method: A total of 445,324 separations was grouped into discreet DRG classes using AR-DRGs. LH; IQR and 10th-95th percentile were used to exclude outlier cases. Reduction in variance (R) and coefficient of variation (CV) were applied to measure model fit and within group homogeneity. Results: Total hospital acute inpatients were grouped into 579 DRG groups in which 'surgical' cases represented 63% of the total separations and 40% of total DRGs. Approximately 12.5% of the total separations fell into DRGs O60C (vaginal delivery) and 28% of the total separations classified into major diagnostic category (MDC) 14 (pregnancy and childbirth). Although reduction in variance (R) for untrimmed data was low (R = 0.17) for LOS, trimming by LH, IQR, and 10th-95th percentile methods improved the value of R to 0.53, 0.48, and 0.51, respectively. Low value of R for AR-DRGs within several MDCs were identified, and found to reflect high variability in one or two DRGs. High within-DRG variation was identified for 23% of DRGs using untrimmed data. Conclusion: Low quality and incomplete data undermines the accuracy of casemix information. This may require improvement in coding quality or further classification refinement in Iran. Further study is also required to compare AR-DRG performance with other versions of DRGs and to determine whether the low value of R for several MDCs is due to the weakness of the AR-DRG algorithm or to Iranian specific factors

Effects of starting strategy on 5-min cycling time-trial performance

The importance of pacing for middle-distance performance is well recognized, yet previous research has produced equivocal results. Twenty-six trained male cyclists ([Vdot]O2peak 62.8 ± 5.9 ml · kg−1 · min−1; maximal aerobic power output 340 ± 43 W; mean ± s) performed three cycling time-trials where the total external work (102.7 ± 13.7 kJ) for each trial was identical to the best of two 5-min habituation trials. Markers of aerobic and anaerobic metabolism were assessed in 12 participants. Power output during the first quarter of the time-trials was fixed to control external mechanical work done (25.7 ± 3.4 kJ) and induce fast-, even-, and slow-starting strategies (60, 75, and 90 s, respectively). Finishing times for the fast-start time-trial (4:53 ± 0:11 min:s) were shorter than for the even-start (5:04 ± 0:11 min:s; 95% CI = 5 to 18 s, effect size = 0.65, P < 0.001) and slow-start time-trial (5:09 ± 0:11 min:s; 95% CI = 7 to 24 s, effect size = 1.00, P < 0.001). Mean [Vdot]O2 during the fast-start trials (4.31 ± 0.51 litres · min−1) was 0.18 ± 0.19 litres · min−1 (95% CI = 0.07 to 0.30 litres · min−1, effect size = 0.94, P = 0.003) higher than the even- and 0.18 ± 0.20 litres · min−1 (95% CI = 0.5 to 0.30 litres · min−1, effect size = 0.86, P = 0.007) higher than the slow-start time-trial. Oxygen deficit was greatest during the first quarter of the fast-start trial but was lower than the even- and slow-start trials during the second quarter of the trial. Blood lactate and pH were similar between the three trials. In conclusion, performance during a 5-min cycling time-trial was improved with the adoption of a fast- rather than an even- or slow-starting strategy

Describing Iranian hospital activity using Australian Refined DRGs: A case study of the Iranian Social Security Organisation

Objective To describe Iran's hospital activity with Australian Refined Diagnosis Related Groups (AR-DRGs).Method A total of 445,324 separations was grouped into discreet DRG classes using AR-DRGs. L3H3; IQR and 10th-95th percentile were used to exclude outlier cases. Reduction in variance (R2) and coefficient of variation (CV) were applied to measure model fit and within group homogeneity.Results Total hospital acute inpatients were grouped into 579 DRG groups in which 'surgical' cases represented 63% of the total separations and 40% of total DRGs. Approximately 12.5% of the total separations fell into DRGs O60C (vaginal delivery) and 28% of the total separations classified into major diagnostic category (MDC) 14 (pregnancy and childbirth). Although reduction in variance (R2) for untrimmed data was low (R2 = 0.17) for LOS, trimming by L3H3, IQR, and 10th-95th percentile methods improved the value of R2 to 0.53, 0.48, and 0.51, respectively. Low value of R2 for AR-DRGs within several MDCs were identified, and found to reflect high variability in one or two DRGs. High within-DRG variation was identified for 23% of DRGs using untrimmed data.Conclusion Low quality and incomplete data undermines the accuracy of casemix information. This may require improvement in coding quality or further classification refinement in Iran. Further study is also required to compare AR-DRG performance with other versions of DRGs and to determine whether the low value of R2 for several MDCs is due to the weakness of the AR-DRG algorithm or to Iranian specific factors.

Influence of pacing on reliability of middle-distance cycling performance

The purpose of the present study was to examine the reliability of middle distance cycling time trials using fast-, even-, and slow-starts. Eighteen endurance-trained male cyclists [mean &plusmn; standard deviation; VO2peak 63.1 &plusmn; 6.1 mL&sdot;kg-1&sdot;min-1] performed nine cycling time trials where the total external work (96.5 &plusmn; 11.2 kJ) was identical to the better of two, 5-minute habituation time trials. Power output during the first quarter of the time-trials (24.1 &plusmn; 2.8 kJ) was fixed to induce fast-, even- or slow-starting strategies (60, 75 and 90 s, respectively). In consecutive sessions, participants performed three trials of each pacing condition although the order of these pacing conditions was counterbalanced. Average power output and performance time were unaffected by trial number in the fast- (P = 0.60), even- (P = 0.18) and slow-start (P = 0.53) trials. In all three pacing conditions, average power output was highly reliable and similar between trial 1 to 2 and trial 2 to 3 in fast- (standard error of measurement; SEM=8.3 and 8.2W), even (coefficient of variation; CV=2.8 and 2.4%) and slow-start (CV=2.4 and 1.5%) trials. In conclusion, the reproducibility of 5-min cycling time trials is unaffected by starting strategy and is acceptable following two selfpaced habituation trials. Research examining the influence of pacing strategies may therefore be conducted without the need for familiarisation trials using each individual pacing condition

Pack hike test finishing time for Australian firefighters: Pass rates and correlates of performance

The packhiketest (PHT, 4.83 km hike wearing a 20.4-kg load) was devised to determine the job readiness of USA wildland firefighters. This study measured PHT performance in a sample of Australian firefighters who currently perform the PHT (career land management firefighters, LMFF) and those who do not (suburban/regional volunteer firefighters, VFF). The study also investigated the relationships between firefighters\u27 PHT performance and their performance across a range of fitness tests for both groups. Twenty LMFF and eighteen age-, body mass-, and height-matched VFF attempted the PHT, and a series of muscular endurance, power, strength and cardiorespiratory fitness tests. Bivariate correlations between the participants’ PHT finishingtime and their performance in a suite of different fitness tests were determined using Pearson’s product moment correlation coefficient. The mean PHT finishingtime for LMFF (42.2 ± 2.8 min) was 9 ± 14% faster (p = 0.001) than for VFF (46.1 ± 3.6 min). The passrate (the percentage of participants who completed the PHT in under 45 min) for LMFF (90%) was greater than that of VFF (39%, p = 0.001). For LMFF, VO2peak in L min−1(r = −0.66, p = 0.001) and the duration they could sustain a grip ‘force’ of 25 kg (r = −0.69, p = 0.001) were strongly correlated with PHT finishingtime. For VFF, VO2peak in mL kg−1 min−1(r = −0.75, p = 0.002) and the duration they could hold a 1.2-m bar attached to 45.5 kg in a ‘hose spray position’ (r = −0.69, p = 0.004) were strongly correlated with PHT finishingtime. This study shows that PHT fitness-screening could severely limit the number of VFF eligible for duty, compromising workforce numbers and highlights the need for specific and valid firefighter fitness standards. The results also demonstrate the strong relationships between PHT performance and firefighters’ cardiorespiratory fitness and local muscular endurance. Those preparing for the PHT should focus their training on these fitness components in the weeks and months prior to undertaking the PHT

Influence of all-out and fast start on 5-min cycling time trial performance

The purpose of this article is to examine the influence of two different fast-start pacing strategies on performance and oxygen consumption (V˙O2) during cycle ergometer time trials lasting ∼5 min