Information-theoretic and stochastic methods for managing the quality of service and satisfaction in healthcare systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research investigates and develops a new approach to the management of service quality with the emphasis on patient and staff satisfaction in the healthcare sector. The challenge of measuring the quality of service in healthcare requires us to view the problem from multiple perspectives. At the philosophical level, the true nature of quality is still debated; at the psychological level, an accurate conceptual representation is problematic; whilst at the physical level, an accurate measurement of the concept still remains elusive to practitioners and academics. This research focuses on the problem of quality measurement in the healthcare sector. The contributions of this research are fourfold: Firstly, it argues that from the technological point of view the research to date into quality of service in healthcare has not considered methods of real-time measurement and monitoring. This research identifies the key elements that are necessary for developing a real-time quality monitoring system for the healthcare environment.Secondly, a unique index is proposed for the monitoring and improvement of healthcare performance using information-theoretic entropy formalism. The index is formulated based on five key performance indicators and was tested as a Healthcare Quality Index (HQI) based on three key quality indicators of dignity, confidence and communication in an Accident and Emergency department. Thirdly, using an M/G/1 queuing model and its underlying Little’s Law, the concept of Effective Satisfaction in healthcare has been proposed. The concept is based on a Staff-Patient Satisfaction Relation Model (S-PSRM) developed using a patient satisfaction model and an empirically tested model developed for measuring staff satisfaction with workload (service time). The argument is presented that a synergy between patient satisfaction and staff satisfaction is the key to sustainable improvement in healthcare quality. The final contribution is the proposal of a Discrete Event Simulation (DES) modelling platform as a descriptive model that captures the random and stochastic nature of healthcare service provision process to prove the applicability of the proposed quality measurement models

An Integrated Model of Patient and Staff Satisfaction Using Queuing Theory.

This paper investigates the connection between patient satisfaction, waiting time, staff satisfaction, and service time. It uses a variety of models to enable improvement against experiential and operational health service goals. Patient satisfaction levels are estimated using a model based on waiting (waiting times). Staff satisfaction levels are estimated using a model based on the time spent with patients (service time). An integrated model of patient and staff satisfaction, the effective satisfaction level model, is then proposed (using queuing theory). This links patient satisfaction, waiting time, staff satisfaction, and service time, connecting two important concepts, namely, experience and efficiency in care delivery and leading to a more holistic approach in designing and managing health services. The proposed model will enable healthcare systems analysts to objectively and directly relate elements of service quality to capacity planning. Moreover, as an instrument used jointly by healthcare commissioners and providers, it affords the prospect of better resource allocation.The authors acknowledge the North West London Hospitals NHS Trust for supporting this research. We also give special thanks to the following persons for their various contributions to this work: Justin Gore for being a cosupervisor of the project; Professors Lorraine De Sousa of Brunel University and Janet Smart of Oxford University for their many constructive critiques of the initial work. Finally, the research was in part supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East of England (CLAHRC EoE) at Cambridge and Peterborough NHS Foundation Trust. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.This is the final published version of the article, originally published in IEEE Journal of Translational Engineering in Health and Medicine, 3, 2015, DOI: 10.1109/JTEHM.2015.240043

Information-theoretic and stochastic methods for managing the quality of service and satisfaction in healthcare systems

This research investigates and develops a new approach to the management of service quality with the emphasis on patient and staff satisfaction in the healthcare sector. The challenge of measuring the quality of service in healthcare requires us to view the problem from multiple perspectives. At the philosophical level, the true nature of quality is still debated; at the psychological level, an accurate conceptual representation is problematic; whilst at the physical level, an accurate measurement of the concept still remains elusive to practitioners and academics. This research focuses on the problem of quality measurement in the healthcare sector. The contributions of this research are fourfold: Firstly, it argues that from the technological point of view the research to date into quality of service in healthcare has not considered methods of real-time measurement and monitoring. This research identifies the key elements that are necessary for developing a real-time quality monitoring system for the healthcare environment.Secondly, a unique index is proposed for the monitoring and improvement of healthcare performance using information-theoretic entropy formalism. The index is formulated based on five key performance indicators and was tested as a Healthcare Quality Index (HQI) based on three key quality indicators of dignity, confidence and communication in an Accident and Emergency department. Thirdly, using an M/G/1 queuing model and its underlying Little’s Law, the concept of Effective Satisfaction in healthcare has been proposed. The concept is based on a Staff-Patient Satisfaction Relation Model (S-PSRM) developed using a patient satisfaction model and an empirically tested model developed for measuring staff satisfaction with workload (service time). The argument is presented that a synergy between patient satisfaction and staff satisfaction is the key to sustainable improvement in healthcare quality. The final contribution is the proposal of a Discrete Event Simulation (DES) modelling platform as a descriptive model that captures the random and stochastic nature of healthcare service provision process to prove the applicability of the proposed quality measurement models.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Codesigning a systemic discharge intervention for inpatient mental health settings (MINDS): a protocol for integrating realist evaluation and an engineering-based systems approach

© 2023 The Author(s). Published by BMJ. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Introduction: Transition following discharge from mental health hospital is high risk in terms of relapse, readmission and suicide. Discharge planning supports transition and reduces risk. It is a complex activity involving interacting systemic elements. The codesigning a systemic discharge intervention for inpatient mental health settings (MINDS) study aims to improve the process for people being discharged, their carers/supporters and staff who work in mental health services, by understanding, co-designing and evaluating implementation of a systemic approach to discharge planning. Methods and analysis: The MINDS study integrates realist research and an engineering-informed systems approach across three stages. Stage 1 applies realist review and evaluation using a systems approach to develop programme theories of discharge planning. Stage 2 uses an Engineering Better Care framework to codesign a novel systemic discharge intervention, which will be subjected to process and economic evaluation in stage 3. The programme theories and resulting care planning approach will be refined throughout the study ready for a future clinical trial. MINDS is co-led by an expert by experience, with researchers with lived experience co-leading each stage. Ethics and dissemination: MINDS stage 1 has received ethical approval from Yorkshire & The Humber—Bradford Leeds (Research Ethics Committee (22/YH/0122). Findings from MINDS will be disseminated via high-impact journal publications and conference presentations, including those with service user and mental health professional audiences. We will establish routes to engage with public and service user communities and National Health Service professionals including blogs, podcasts and short videos. Trial registration number: MINDS is funded by the National Institute of Health Research (NIHR 133013) https://fundingawards.nihr.ac.uk/award/NIHR133013. The realist review protocol is registered on PROSPERO. PROSPERO registration number: CRD42021293255.Peer reviewe

Design as a quality improvement strategy: The case for design expertise.

Bad design in safety-critical environments like healthcare can lead to users being frustrated, excluded or injured. In contrast, good design can make it easier to use a service correctly, with impacts on both the safety and efficiency of healthcare delivery, as well as the experience of patients and staff. The participative dimension of design as an improvement strategy has recently gained traction in the healthcare quality improvement literature. However, the role of design expertise and professional design has been much less explored. Good design does not happen by accident: it takes expertise and the specific reasoning that expert designers develop through practical experience and training. Here, we define design, show why poor design can be disastrous and illustrate the benefits of good design. We argue for the recognition of distinctive design expertise and describe some of its characteristics. Finally, we discuss how design could be better promoted in healthcare improvement

Joining forces: the value of design partnering with operational research to improve healthcare delivery

International audienceA wide range of disciplines are directing their methods and tools to help address the challenges of healthcare. Chief among these are design and operational research (OR). Though they have much in common, these two disciplines have existed in isolation for most of their history and there is currently a gulf between the two research communities. In this position paper, we rapidly review the contributions of design and OR in healthcare. We then identify similarities and complementarities between the two disciplines and communities when they consider healthcare systems. Finally, we propose practical steps to enable better collaboration. Our focus is on finding ways in which the two disciplines complement each other. When applying design to healthcare services, designers may wish to learn from OR, which has a long history of supporting improvements in healthcare organisation and services, particularly using quantitative data and analysis and modelling methods. In return, design has distinctive qualities that could augment the OR approach, such as its emphasis on wide and creative search for potential solutions, and iterative co-production and prototyping of solutions with clients. Better collaboration will require a coordinated effort but could yield a more comprehensive and effective approach to improving healthcare systems

Design as a quality improvement strategy: The case for design expertise.

Bad design in safety-critical environments like healthcare can lead to users being frustrated, excluded or injured. In contrast, good design can make it easier to use a service correctly, with impacts on both the safety and efficiency of healthcare delivery, as well as the experience of patients and staff. The participative dimension of design as an improvement strategy has recently gained traction in the healthcare quality improvement literature. However, the role of design expertise and professional design has been much less explored. Good design does not happen by accident: it takes expertise and the specific reasoning that expert designers develop through practical experience and training. Here, we define design, show why poor design can be disastrous and illustrate the benefits of good design. We argue for the recognition of distinctive design expertise and describe some of its characteristics. Finally, we discuss how design could be better promoted in healthcare improvement

Systems approaches to healthcare systems design and care delivery: An overview of the literature

The healthcare sector is facing significant challenges that require a systems approach, resulting in a rapid growth in the application of systems approaches in healthcare since the beginning of the 21st century. Consequently, healthcare practitioners and policymakers now desire to understand the evidence-base for the approach, but little evidence of the kind desired exists. This paper is a first step in conducting a narrative review of the application of systems approaches in healthcare based on a systematic review of the academic and grey literature. First, the emergence of the approach in healthcare is explored. Second, specific examples of applications of systems approaches in healthcare are examined to identify any missing elements in current practice. Third, fourteen reviews of the approach in healthcare published in the last ten years are analysed. The results suggest that the use of the approach in healthcare will most likely continue to increase, however, significant work remains for the design and systems community to demonstrate the effectiveness of systems approaches, specifically in providing convincing measures of impact on patient and service outcomes.Multi Actor SystemsPolicy AnalysisApplied Ergonomics and Desig