Selecting and Ranking Time Series Models Using the NOEMON Approach

Abstract. In this work, we proposed to use the NOEMON approach to rank and select time series models. Given a time series, the NOEMON approach provides a ranking of the candidate models to forecast that series, by combining the outputs of different learners. The best ranked models are then returned as the selected ones. In order to evaluate the proposed solution, we implemented a prototype that used MLP neural networks as the learners. Our experiments using this prototype revealed encouraging results.

Challenging the holy grail of hospital accreditation: A cross sectional study of inpatient satisfaction in the field of cardiology

Extent: 7p.Background: Subjective parameters such as quality of life or patient satisfaction gain importance as outcome parameters and benchmarks in health care. In many countries hospitals are now undergoing accreditation as mandatory or voluntary measures. It is believed but unproven that accreditations positively influence quality of care and patient satisfaction. The present study aims to assess in a defined specialty (cardiology) the relationship between patient satisfaction (as measured by the recommendation rate) and accreditation status. Methods: Consecutive patients discharged from 25 cardiology units received a validated patient satisfaction questionnaire. Data from 3,037 patients (response rate > 55%) became available for analysis. Recommendation rate was used as primary endpoint. Different control variables such as staffing level were considered. Results: The 15 accredited units did not differ significantly from the 10 non-accredited units regarding main hospital (i.e. staffing levels, no. of beds) and patient (age, gender) characteristics. The primary endpoint "recommendation rate of a given hospital" for accredited hospitals (65.6%, 95% Confidence Interval (CI) 63.4 - 67.8%) and hospitals without accreditation (65.8%, 95% CI 63.1 - 68.5%) was not significantly different. Conclusion: Our results support the notion that - at least in the field of cardiology - successful accreditation is not linked with measurable better quality of care as perceived by the patient and reflected by the recommendation rate of a given institution. Hospital accreditation may represent a step towards quality management, but does not seem to improve overall patient satisfaction.Cornelia Sack, Peter Lütkes, Wolfram Günther, Raimund Erbel, Karl-Heinz Jöckel and Gerald J Holtman

Evaluating Forecasting Methods

Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods

Golden Rule of Forecasting: Be Conservative

This article proposes a unifying theory, or the Golden Rule, or forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century

An effectiveness analysis of healthcare systems using a systems theoretic approach

<p>Abstract</p> <p>Background</p> <p>The use of accreditation and quality measurement and reporting to improve healthcare quality and patient safety has been widespread across many countries. A review of the literature reveals no association between the accreditation system and the quality measurement and reporting systems, even when hospital compliance with these systems is satisfactory. Improvement of health care outcomes needs to be based on an appreciation of the whole system that contributes to those outcomes. The research literature currently lacks an appropriate analysis and is fragmented among activities. This paper aims to propose an integrated research model of these two systems and to demonstrate the usefulness of the resulting model for strategic research planning.</p> <p>Methods/design</p> <p>To achieve these aims, a systematic integration of the healthcare accreditation and quality measurement/reporting systems is structured hierarchically. A holistic systems relationship model of the administration segment is developed to act as an investigation framework. A literature-based empirical study is used to validate the proposed relationships derived from the model. Australian experiences are used as evidence for the system effectiveness analysis and design base for an adaptive-control study proposal to show the usefulness of the system model for guiding strategic research.</p> <p>Results</p> <p>Three basic relationships were revealed and validated from the research literature. The systemic weaknesses of the accreditation system and quality measurement/reporting system from a system flow perspective were examined. The approach provides a system thinking structure to assist the design of quality improvement strategies. The proposed model discovers a fourth implicit relationship, a feedback between quality performance reporting components and choice of accreditation components that is likely to play an important role in health care outcomes. An example involving accreditation surveyors is developed that provides a systematic search for improving the impact of accreditation on quality of care and hence on the accreditation/performance correlation.</p> <p>Conclusion</p> <p>There is clear value in developing a theoretical systems approach to achieving quality in health care. The introduction of the systematic surveyor-based search for improvements creates an adaptive-control system to optimize health care quality. It is hoped that these outcomes will stimulate further research in the development of strategic planning using systems theoretic approach for the improvement of quality in health care.</p

A prospective, multi-method, multi-disciplinary, multi-level, collaborative, social-organisational design for researching health sector accreditation [LP0560737]

BACKGROUND: Accreditation has become ubiquitous across the international health care landscape. Award of full accreditation status in health care is viewed, as it is in other sectors, as a valid indicator of high quality organisational performance. However, few studies have empirically demonstrated this assertion. The value of accreditation, therefore, remains uncertain, and this persists as a central legitimacy problem for accreditation providers, policymakers and researchers. The question arises as to how best to research the validity, impact and value of accreditation processes in health care. Most health care organisations participate in some sort of accreditation process and thus it is not possible to study its merits using a randomised controlled strategy. Further, tools and processes for accreditation and organisational performance are multifaceted. METHODS/DESIGN: To understand the relationship between them a multi-method research approach is required which incorporates both quantitative and qualitative data. The generic nature of accreditation standard development and inspection within different sectors enhances the extent to which the findings of in-depth study of accreditation process in one industry can be generalised to other industries. This paper presents a research design which comprises a prospective, multi-method, multi-level, multi-disciplinary approach to assess the validity, impact and value of accreditation. DISCUSSION: The accreditation program which assesses over 1,000 health services in Australia is used as an exemplar for testing this design. The paper proposes this design as a framework suitable for application to future international research into accreditation. Our aim is to stimulate debate on the role of accreditation and how to research it.Jeffrey Braithwaite, Johanna Westbrook, Marjorie Pawsey, David Greenfield, Justine Naylor, Rick Iedema, Bill Runciman, Sally Redman, Christine Jorm, Maureen Robinson, Sally Nathan and Robert Gibber

Patient Safety in Internal Medicine

AbstractHospital Internal Medicine (IM) is the branch of medicine that deals with the diagnosis and non-surgical treatment of diseases, providing the comprehensive care in the office and in the hospital, managing both common and complex illnesses of adolescents, adults, and the elderly. IM is a key ward for Health National Services. In Italy, for example, about 17.3% of acute patients are discharged from the IM departments. After the epidemiological transition to chronic/degenerative diseases, patients admitted to hospital are often poly-pathological and so requiring a global approach as in IM. As such transition was not associated—with rare exceptions—to hospital re-organization of beds and workforce, IM wards are often overcrowded, burdened by off-wards patients and subjected to high turnover and discharge pressure. All these factors contribute to amplify some traditional clinical risks for patients and health operators. The aim of our review is to describe several potential errors and their prevention strategies, which should be implemented by physicians, nurses, and other healthcare professionals working in IM wards