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

Using clinical indicators to facilitate quality improvement via the accreditation process: an adaptive study into the control relationship

Objective. The aim of the study was to determine accreditation surveyors’ and hospitals’ use and perceived usefulness of clinical indicator reports and the potential to establish the control relationship between the accreditation and reporting systems. The control relationship refers to instructional directives, arising from appropriately designed methods and efforts towards using clinical indicators, which provide a directed moderating, balancing and best outcome for the connected systems. Design. Web-based questionnaire survey. Setting. Australian Council on Healthcare Standards’(ACHS) accreditation and clinical indicator programmes. Results. Seventy-three of 306 surveyors responded. Half used the reports always/most of the time. Five key messages were revealed: (i) report use was related to availability before on-site investigation; (ii) report use was associated with the use of non-ACHS reports; (iii) a clinical indicator set's perceived usefulness was associated with its reporting volume across hospitals; (iv) simpler measures and visual summaries in reports were rated the most useful; (v) reports were deemed to be suitable for the quality and safety objectives of the key groups of interested parties (hospitals’ senior executive and management officers, clinicians, quality managers and surveyors). Conclusions. Implementing the control relationship between the reporting and accreditation systems is a promising expectation. Redesigning processes to ensure reports are available in pre-survey packages and refined education of surveyors and hospitals on how to better utilize the reports will support the relationship. Additional studies on the systems’ theory-based model of the accreditation and reporting system are warranted to establish the control relationship, building integrated system-wide relationships with sustainable and improved outcomes

Measurement of resilience potential - development of a resilience assessment grid for emergency departments.

BackgroundResilience engineering has been advocated as an alternative to the management of safety over the last decade in many domains. However, to facilitate metrics for measuring and helping analyze the resilience potential for emergency departments (EDs) remains a significant challenge. The study aims to redesign the Hollnagel's resilience assessment grid (RAG) into a custom-made RAG (ED-RAG) to support resilience management in EDs.MethodsThe study approach had three parts: 1) translation of Hollnagel's RAG into Chinese version, followed by generation of a tailored set of ED-RAG questions adapted to EDs; 2) testing and revising the tailored sets until to achieve satisfactory validity for application; 3) design of a new rating scale and scoring method. The test criteria of the ED-RAG questionnaire adopted the modified three-level scoring criteria proposed by Bloom and Fischer. The study setting of the field test is a private regional hospital.ResultsThe fifth version of ED-RAG was acceptable after a field test. It has three sets of open structured questions for the potentials to respond, monitor, and anticipate, and a set of structured questions for the potential to learn. It contained 38 questions corresponding to 32 foci. A new 4-level rating scale along with a novel scaling method can improve the scores conversion validity and communication between team members and across investigations. This final version is set to complete an interview for around 2 hours.ConclusionsThe ED-RAG represents a snapshot of EDs'resilience under specific conditions. It might be performed multiple times by a single hospital to monitor the directions and contents of improvement that can supplement conventional safety management toward resilience. Some considerations are required to be successful when hospitals use it. Future studies to overcome the potential methodological weaknesses of the ED-RAG are needed

Bayesian methods in reporting and managing Australian clinical indicators

Sustained clinical improvement is unlikely without appropriate measuring and reporting techniques. Clinical indicators are tools to help assess whether a standard of care is being met. They are used to evaluate the potential to improve the care provided by healthcare organisations (HCOs). The analysis and reporting of these indicators for the Australian Council on Healthcare Standards have used a methodology which estimates, for each of the 338 clinical indicators, the gains in the system that would result from shifting the mean proportion to the 20^th centile. The results are used to provide a relative measure to help prioritise quality improvement activity within clinical areas, rather than simply focus on "poorer performing" HCOs. The method draws attention to clinical areas exhibiting larger between-HCO variation and affecting larger numbers of patients. HCOs report data in six-month periods, resulting in estimated clinical indicator proportions which may be affected by small samples and sampling variation. Failing to address such issues would result in HCOs exhibiting extremely small and large estimated proportions and inflated estimates of the potential gains in the system. This paper describes the 20^th centile method of calculating potential gains for the healthcare system by using Bayesian hierarchical models and shrinkage estimators to correct for the effects of sampling variation, and provides an example case in Emergency Medicine as well as example expert commentary from colleges based upon the reports. The application of these Bayesian methods enables all collated data to be used, irrespective of an HCO's size, and facilitates more realistic estimates of potential system gains