RESUMO
PURPOSE: Clinic members reported slower patient flow in the mornings at a multidisciplinary oncology clinic. This study identified the causes of clinic bottlenecking via analysis of patient schedules and transit times, then corrected discrepancies through a quality improvement program. METHODS: Transit times were measured using tracking cards handed out at check-in, marked by each clinic member throughout the encounter, and collected upon discharge. Data were analyzed for differences between morning and afternoon patients, and a Pareto chart was formulated to assess for discrepancies in distribution. Repeat plan-do-study-act (PDSA) cycles were conducted, implementing two changes to redistribute appointments to optimize clinic workflow. RESULTS: A total of 2951 patient appointments were analyzed: 589 at baseline, 277 following an initial intervention, and 2085 following a subsequent intervention. Analysis of patient transit times revealed no significant differences between morning and afternoon patient groups (t-test, p=.13-.99), with no transit interval markedly longer than others (t-test, p=.32-.83). However, upon evaluation of appointment times, a maldistribution was noted with 57% of patients concentrated between 9:00 am to 12:00 pm, accounting for the perception of bottlenecking. An initial intervention offering patients afternoon appointments on a voluntary basis was insufficient for rebalancing distribution (chi-square test, p=.299); however, an electronic medical record (EMR) intervention with rigid appointment templates was successful (chi-square test, p<.001). CONCLUSION: An imbalance of appointment times contributed to the perception of slow clinic throughput. This study emphasizes the importance of systematically investigating even consensus observations for validity prior to costly interventions. Furthermore, these results support the utility of information technology in optimizing clinic workflow.
RESUMO
Large herbivore populations respond strongly to remotely sensed measures of primary productivity. Whereas most studies in seasonal environments have focused on the effects of spring plant phenology on juvenile survival, recent studies demonstrated that autumn nutrition also plays a crucial role. We tested for both direct and indirect (through body mass) effects of spring and autumn phenology on winter survival of 2315 mule deer fawns across a wide range of environmental conditions in Idaho, USA. We first performed a functional analysis that identified spring and autumn as the key periods for structuring the among-population and among-year variation of primary production (approximated from 1 km Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (NDVI)) along the growing season. A path analysis showed that early winter precipitation and direct and indirect effects of spring and autumn NDVI functional components accounted for 45% of observed variation in overwinter survival. The effect size of autumn phenology on body mass was about twice that of spring phenology, while direct effects of phenology on survival were similar between spring and autumn. We demonstrate that the effects of plant phenology vary across ecosystems, and that in semi-arid systems, autumn may be more important than spring for overwinter survival.
