Fluctuation scaling in complex systems: Taylor's law and beyond

Complex systems consist of many interacting elements which participate in some dynamical process. The activity of various elements is often different and the fluctuation in the activity of an element grows monotonically with the average activity. This relationship is often of the form "$fluctuations \approx const.\times average^\alpha$", where the exponent $\alpha$ is predominantly in the range $[1/2, 1]$. This power law has been observed in a very wide range of disciplines, ranging from population dynamics through the Internet to the stock market and it is often treated under the names \emph{Taylor's law} or \emph{fluctuation scaling}. This review attempts to show how general the above scaling relationship is by surveying the literature, as well as by reporting some new empirical data and model calculations. We also show some basic principles that can underlie the generality of the phenomenon. This is followed by a mean-field framework based on sums of random variables. In this context the emergence of fluctuation scaling is equivalent to some corresponding limit theorems. In certain physical systems fluctuation scaling can be related to finite size scaling.Comment: 33 pages, 20 figures, 2 tables, submitted to Advances in Physic

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Kuluttajabarometri maakunnittain 2000, 2. neljännes

Suomen virallinen tilasto (SVT

Use of failure-to-rescue to identify international variation in postoperative care in low-, middle- and high-income countries: a 7-day cohort study of elective surgery

This was an investigator-initiated study funded by Nestle Health Sciences through an unrestricted research grant and by a National Institute for Health Research (UK) Professorship held by R.P. The study was sponsored by Queen Mary University of London

Use of failure-to-rescue to identify international variation in postoperative care in low-, middle- and high-income countries: A 7-day cohort study of elective surgery

The incidence and impact of postoperative complications are poorly described. Failure-to-rescue, the rate of death following complications, is an important quality measure for perioperative care but has not been investigated across multiple health care systems. Methods. We analysed data collected during the International Surgical Outcomes Study, an international 7-day cohort study of adults undergoing elective inpatient surgery. Hospitals were ranked by quintiles according to surgical procedural volume (Q1 lowest to Q5 highest). For each quintile we assessed in-hospital complications rates, mortality, and failure-to-rescue. We repeated this analysis ranking hospitals by risk-adjusted complication rates (Q1 lowest to Q5 highest). Results. A total of 44 814 patients from 474 hospitals in 27 low-, middle-, and high-income countries were available for analysis. Of these, 7508 (17%) developed one or more postoperative complication, with 207 deaths in hospital (0.5%), giving an overall failure-to-rescue rate of 2.8%. When hospitals were ranked in quintiles by procedural volume, we identified a threefold variation in mortality (Q1: 0.6% vs Q5: 0.2%) and a two-fold variation in failure-to-rescue (Q1: 3.6% vs Q5: 1.7%). Ranking hospitals in quintiles by risk-adjusted complication rate further confirmed the presence of important variations in failureto- rescue, indicating differences between hospitals in the risk of death among patients after they develop complications. Conclusions. Comparison of failure-to-rescue rates across health care systems suggests the presence of preventable postoperative deaths. Using such metrics, developing nations could benefit from a data-driven approach to quality improvement, which has proved effective in high-income countries