Quality Framework Research Articles

Unlocking Service Provider Excellence: Expanding the Touchpoints, Context, Qualities Framework

Customer reviews offer scope for better understanding the customer experience (CX), which may be leveraged to improve firms' CX performance. We extend the Touchpoints, Context, Qualities (TCQ) nomenclature by integrating it with the ARC value-creation elements and the multiple dimensions of CX. Our extended TCQ framework comprises nine building blocks to delineate dynamic what we term CX performance trajectories. We test our framework by collecting verbatim text-based reviews, and transforming them into two robust data sets (weekly, and monthly), which we examine using a dynamic Hidden Markov Model. We identify three levels of CX performance states and the migrations paths between them. We find that the building blocks coherently express mechanisms that are effective at the weekly and monthly levels for helping firms improve, and prevent deterioration of, CX performance. This research enriches the CX and TCQ literature. In particular, we derive actionable guidance for managers to facilitate the dynamic management of their firm’s CX performance.

Public-Private Partnership in Healthcare is a Necessity in Difficult Times: A case study

Healthcare delivery is a risky enterprise for both public and private systems which may face adversity in a volatile, uncertain, complex, and ambiguous world. There has been a global emergence of Public-Private Partnership (PPP) hospitals to enhance delivery of sustainable healthcare, although its existence in developing countries remains limited. Risk management strongly influences PPP success; few PPP hospitals were able to meet contractually specified quality and performance requirements, creating debate regarding merits of the PPP model. Conversely, we present a case study of the first PPP hospital operated by not-for-profit organisation in New South Wales, Australia, to successfully complete the contract period. A Continuous Quality and Performance Improvement Framework was applied at five stages of organisational growth during the contract term. This case study demonstrates adaptive leadership and just organisational culture are equally important in providing high quality healthcare services to the community. We show the future potential of PPP model for service delivery as a third option to pure public or private sector hospitals, even in the post COVID-19 era when there is likelihood of financial instability in many settings.

The impact of the COVID-19 pandemic on cardiovascular disease prevention and corresponding geographical inequalities in England: interrupted time series analysis

BackgroundThere has been disruption to the detection and management of those with hypertension and atrial fibrillation (AF) during the COVID-19 pandemic. This is likely to vary geographically and could have implications for future mortality and morbidity. We aimed to estimate the change in diagnosed prevalence, treatment and prescription indicators for AF and hypertension and assess corresponding geographical inequalities.MethodsUsing the Quality and Outcomes Framework (2016/17 to 2021/22) and the English Prescribing Datasets (2018 to 2022), we described age standardised prevalence, treatment and prescription item rates for hypertension and AF by geography and over time. Using an interrupted time-series (ITS) analysis, we estimated the impact of the pandemic (from April 2020) on missed diagnoses and on the percentage change in medicines prescribed for these conditions. Finally, we described changes in treatment indicators against Public Health England 2029 cardiovascular risk targets.ResultsWe observed 143,822 fewer (-143,822, 95%CI:-226,144, -61,500, p = 0.001) diagnoses of hypertension, 60,330 fewer (-60,330, 95%CI: -83,216, -37,444, p = 0.001) diagnoses of AF and 1.79% fewer (-1.79%, 95%CI: -2.37%, -1.22%), p < 0.0001) prescriptions for these conditions over the COVID-19 impact period. There was substantial variation across geography in England in terms of the indirect impact of the COVID-19 pandemic on the diagnosis, prescription, and treatment rates of hypertension and AF. 20% of Sub Integrated Care Boards account for approximately 62% of all missed diagnoses of hypertension. The percentage of individuals who had their hypertension controlled fell from 75.8% in 2019/20 to 64.1% in 2021/22 and the percentage of individuals with AF who were risk assessed fell from 97.2% to 90.7%.ConclusionsHypertension and AF detection and management were disrupted during the COVID-19 pandemic. The disruption varied considerably across diseases and geography. This highlights the utility of administrative and geographically granular datasets to inform targeted efforts to mitigate the indirect impacts of the pandemic through applied secondary prevention measures.

A spatial mapping of thermal comfort and air quality (SMTC-AQ) framework for the built environment using computational fluid dynamics approach

Indoor environmental quality (IEQ), driven by thermal comfort and indoor air quality (IAQ), is a major factor that impacts occupant's well-being and productivity since people spend 80–90 % of their time indoors. The current approaches for assessing and quantifying IEQ presume fixed values and ranges in naturally ventilated (NV) spaces within the simulation environment. However, such an approach cannot capture point-to-point changes that occur in the built environment due to localized variations of environmental variables such as air velocity and temperature. This study proposes a sensing and simulation-based framework, Spatial Mapping of Thermal Comfort and Air Quality (SMTC-AQ) in a computational fluid dynamics (CFD) environment to address this. Salient characteristics of SMTC-AQ include the modification of predicted mean vote (PMV) for NV spaces, specifically for the Indian context, and the implementation of the under-explored concept of domain-decoupling utilizing the ISHRAE weather file. Using SMTC-AQ, the study determines the optimal window-to-wall ratio (WWR) and opening-to-wall ratio (OWR) for a case study room in an Indian academic building, considering both IAQ and thermal comfort. In the study, indoor air velocity and temperature are first validated with field data, followed by a scenario analysis to assess the impact of opening characteristics on IEQ. The findings show that for building spaces in tropical climates with moderate outdoor temperatures and lower relative humidity, thermal comfort, and IAQ can be improved by implementing higher WWR and OWR. Moreover, WWR is a more relevant criterion for improving thermal comfort and a better OWR design is crucial for enhancing IAQ in NV spaces.

Understanding a Conceptual Framework of Spa Service Quality: An Overview Approach

Understanding a Conceptual Framework of Spa Service Quality: An Overview Approach

Exploring Culturally‐safe Dementia Care Policy in First Nation Community of the James and Hudson Bay Region in Northern Ontario, Canada

AbstractBackgroundCulturally‐safe dementia care (CSDC) is new dynamic concept that empowers clinical and traditional health care practitioners to provide culturally respectful care for older adults with dementia. The World Health Organization’s (WHO) recognized diverse Indigenous local community partners, members and leaders as critical community stakeholders for dementia care and prevention worldwide in 2018. However, there is a critical lack of policy framework and evidence‐based research on CSDC globally. As dementia spreads as a global epidemic, the dementia prevalence among First Nations people over the age of 60 is expected to quadruple by 2031, compared to a 2.3‐fold increase among non‐First Nations people in Canada. The Mamow Ahyamowen Partners (2019) study found a higher dementia mortality rate of 7% in the James and Hudson Bay region of Northern Ontario between 1992 and 2014, compared to 23% in Ontario overall.MethodA qualitative research design is employed in conjunction with a community‐based participatory rural dementia action research approach to conduct four participatory Focus‐Group Discussions with physicians, nurses, caregivers, and community partners with 24 to 32 participants to explore the knowledge, experience, barriers and challenges to develop knowledge of CSDC policy. Thematic analysis and the Total Quality Framework will be used for quality rigour, and a two‐eyed seeing framework and explanatory dementia models will be applied in the perspectives and worldviews of the physician‐patient‐community to honour cultural care, diet, language, ethical and spiritual pathways.ResultThis research will lay foundation for policymakers to develop knowledge of CSDC policy, care plan and guidelines. This will guide the development of educational interventions and curricula and community support systems that are aimed at building and sustaining the capacity of healthcare professionals and community partners to begin integrated biomedical and Indigenous traditional dementia care practices.ConclusionThis research endeavours to equip physicians, nurses, allied health care workers, community partners (Elders, knowledge‐holders and traditional healers) and the community support systems to initiate CSDC on a global scale to implement the WHO Global Action Plan on the Public Health Response to Dementia (2017‐2025). Inclusion of Indigenous community partners as community stakeholder are underpinning to bridge the dementia equity gap.

Perceptions of Data Set Experts on Important Characteristics of Health Data Sets Ready for Machine Learning

The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed clinical AI applications for patient care. To discern what constitutes high-quality and useful data sets for health and biomedical ML research purposes according to subject matter experts. This qualitative study interviewed data set experts, particularly those who are creators and ML researchers. Semistructured interviews were conducted in English and remotely through a secure video conferencing platform between August 23, 2022, and January 5, 2023. A total of 93 experts were invited to participate. Twenty experts were enrolled and interviewed. Using purposive sampling, experts were affiliated with a diverse representation of 16 health data sets/databases across organizational sectors. Content analysis was used to evaluate survey information and thematic analysis was used to analyze interview data. Data set experts' perceptions on what makes data sets AI ready. Participants included 20 data set experts (11 [55%] men; mean [SD] age, 42 [11] years), of whom all were health data set creators, and 18 of the 20 were also ML researchers. Themes (3 main and 11 subthemes) were identified and integrated into an AI-readiness framework to show their association within the health data ecosystem. Participants partially determined the AI readiness of data sets using priority appraisal elements of accuracy, completeness, consistency, and fitness. Ethical acquisition and societal impact emerged as appraisal considerations in that participant samples have not been described to date in prior data quality frameworks. Factors that drive creation of high-quality health data sets and mitigate risks associated with data reuse in ML research were also relevant to AI readiness. The state of data availability, data quality standards, documentation, team science, and incentivization were associated with elements of AI readiness and the overall perception of data set usefulness. In this qualitative study of data set experts, participants contributed to the development of a grounded framework for AI data set quality. Data set AI readiness required the concerted appraisal of many elements and the balancing of transparency and ethical reflection against pragmatic constraints. The movement toward more reliable, relevant, and ethical AI and ML applications for patient care will inevitably require strategic updates to data set creation practices.

Models of care for intrauterine device provision in Australian general practice.

Intrauterine devices (IUDs) are safe and effective forms of long-acting reversible contraception. However, uptake in Australia is low. Although general practitioners (GPs) manage contraceptive provision, little is known about IUD service delivery. This study aims to describe themodels of care (MoC) used in the provision of IUDs by Australian GPs. Semistructured telephone interviews were conducted with 20 GP IUD providers nationwide. Data were deidentified, transcribed, thematically analysed and evaluated using The RoyalAustralian College of General Practitioners' Quality framework for Australian general practice. Three MoC were described: common, streamlined and same-day insertion. Thecommon model involved three to fourappointments but was of the lowest quality. The streamlined MoC had a maximum of two appointments. Few GPs delivered same-day insertion. Task-sharing and adaptable MoC were identified. The quality of current MoC for IUD provision is non-standardised and largely inadequate. Increased GP awareness about and operation of high-quality MoCwill enhance IUD access.

RWD175 A Data Quality Framework to Assess Healthcare Data in Saudi Arabia: An Automated Approach

RWD175 A Data Quality Framework to Assess Healthcare Data in Saudi Arabia: An Automated Approach

An audit of a general practices compliance with national recommendations for the avoidance of complications for type 2 diabetic patients

Abstract Introduction Each week, diabetes leads to more than 700 strokes, almost 600 heart attacks and more than 2000 instances of heart failure, in addition to being the single most common cause of chronic kidney disease in the UK.1 The NHS spends 10% of its annual budget on diabetes with 80% of that treating the complications of diabetes.2 Pharmacists have a crucial role to optimise the medication of diabetic patients and prevent future problems. Aim To assess a general practices (GP) compliance with national recommendations and the Quality and Outcomes Framework for the avoidance of complications for Type 2 Diabetes Mellitus (T2DM) patients. Methods This single-centre, retrospective audit was conducted at a GP in the London Borough of Southwark. Six standards were measured focusing on the prevention of the complications of diabetes. Each standard incorporated an exclusion and inclusion criteria. Standard 1 and 2 reviewed the appropriate management of nephropathy and hypertension respectively. Standard 3 and 4 relate to statin use for primary and secondary prevention. The final standards assess how many patients have documented QRISK2 scores and initiated on a Sodium-Glucose Co-Transporter 2 (SGLT2) inhibitor as per the new NICE guidelines.3 Ethical approval was not deemed necessary for this clinical audit in agreement with the Hurley Group and King’s College Hospital NHS Foundation Trust guidelines. Results Half (50%, n=153/304) of all included T2DM patients at the practice have a blood pressure reading defined as hypertensive. Out of all diabetic patients, 25 of them had clinical proteinuria, micro-albuminuria, or a diagnosis of nephropathy. Of these 25 patients, 19 (76%) were prescribed an angiotensin-converting enzyme inhibitor or angiotensin-receptor blockers. A small portion (7%, n=28/374) of the diagnosed T2DM patients have a documented QRISK2 score. Subsequently, only 32 diabetic patients (9%, n=32/374) are prescribed an SGLT2 inhibitor. For standards 3 and 4, there were 122 patients (73%) who were prescribed a statin for primary prevention and 89 patients (87%) who were prescribed a statin for secondary prevention. Discussion/Conclusion The microvascular and macrovascular complications of diabetes are well documented. The incidence of these complications can be reduced by pharmacological management. Although none of the standards were met, the results are similar to other practices across the country. However, in comparison to the local average, the audited GP underperformed with no standards being better than the average of GPs in the area. Sub-analysis emphasises the disparities in health between various racial and ethnic groups. The results of the two largest demographic groups audited, Caucasian and Caribbean patients, show that the former is more likely to meet the standards. These findings indicate that the processes of the practice require change to meet the needs of our diabetic patients. In particular, work is required to understand the disparities in care for our patients categorised as ethnic minorities. The recommendations fall under 5 main categories – feedback, learn, templates, analyse, and review.

Readiness for Integrated Care of Older People: A Cross-Sectional Study in Mexico.

To evaluate the readiness of the Mexican healthcare system to implement the integrated care for older people (ICOPE) approach into an existing healthcare model. We conducted a cross-sectional study with data from 2473 healthcare workers analyzed using the model for understanding success in quality (MUSIQ) framework to gather data from healthcare professionals. Their perceptions regarding the readiness for ICOPE were assessed across five dimensions: team, microsystem, infrastructure, organization, and external environment. Only 717 (29%) of the participants believed ICOPE could be successfully implemented in Mexico without any modifications. A total of 1261 (51%) participants rated the readiness of ICOPE with some barriers. The main barriers were reallocating resources and the external environment. Mexico's healthcare system faces barriers to innovation that could hinder the successful integration of the ICOPE approach. A systematic identification of these barriers provides an opportunity to suggest adaptations and refinements to increase the probability of success. Using the contextual factors identified as facilitators and the proposal of interventions such as the ICOPE app could improve the chances of success. The participants of this study evaluated ICOPE as ready to implement, with some contextual barriers. The readiness evaluation supports the stakeholders' and policymakers' decisions in implementing and monitoring the program in a natural setting. Evaluating the readiness of the intervention increases the possibility of aligning the innovation with contextual factors, increasing the chances of its successful adoption and implementation.

A new framework for water quality forecasting coupling causal inference, time-frequency analysis and uncertainty quantification

Accurate forecasting of water quality variables in river systems is crucial for relevant administrators to identify potential water quality degradation issues and take countermeasures promptly. However, pure data-driven forecasting models are often insufficient to deal with the highly varying periodicity of water quality in today's more complex environment. This study presents a new holistic framework for time-series forecasting of water quality parameters by combining advanced deep learning algorithms (i.e., Long Short-Term Memory (LSTM) and Informer) with causal inference, time-frequency analysis, and uncertainty quantification. The framework was demonstrated for total nitrogen (TN) forecasting in the largest artificial lakes in Asia (i.e., the Danjiangkou Reservoir, China) with six-year monitoring data from January 2017 to June 2022. The results showed that the pre-processing techniques based on causal inference and wavelet decomposition can significantly improve the performance of deep learning algorithms. Compared to the individual LSTM and Informer models, wavelet-coupled approaches diminished well the apparent forecasting errors of TN concentrations, with 24.39%, 32.68%, and 41.26% reduction at most in the average, standard deviation, and maximum values of the errors, respectively. In addition, a post-processing algorithm based on the Copula function and Bayesian theory was designed to quantify the uncertainty of predictions. With the help of this algorithm, each deterministic prediction of our model can correspond to a range of possible outputs. The 95% forecast confidence interval covered almost all the observations, which proves a measure of the reliability and robustness of the predictions. This study provides rich scientific references for applying advanced data-driven methods in time-series forecasting tasks and a practical methodological framework for water resources management and similar projects.

The impact of need-based care on formal caregivers' wellbeing in nursing homes: A cluster randomized controlled trial

BackgroundNeed-based care is a structured and standardized model that supports formal caregivers in nursing homes in delivering person-centered care by responding with tailored non-pharmacological interventions on residents' unmet needs as well as having positive effects on behavioral and psychological symptoms on residents with dementia. However, limited resources as well as the shortage of caregivers in nursing homes make the implementation of need-based care challenging, especially when it comes to finding ways to spend more time with residents. The aim of this study is to evaluate the impact of the implementation of need-based care in nursing homes on formal caregivers' wellbeing. MethodsA three-arm cluster randomized controlled trial was set up in 24 Belgian nursing homes: formal caregivers in the ‘need-based care’ group (intervention; n = 195) spent time twice a week with residents who had behavioral and psychological symptoms according to the principles of need-based care while formal caregivers in the ‘time’ group (n = 257) filled in the way they spent time twice a week; a third group delivered standard care (n = 299). An implementation strategy was built upon the Implementation Quality Framework and used in the ‘need-based care group’. A total of 741 formal caregivers completed the digital questionnaire at one or more of the five time points (every nine weeks) between November 2021 and July 2022; they rated their sense of competence in dementia care, level of burnout, and, level of engagement. Moments of time were registered in a printed registration book. ResultsOnly formal caregivers from the ‘need-based care’ group experienced a higher sense of competence in dementia care at time points three (p = 0.010) and four (p = 0.001) compared with baseline with an increase of respectively 1.5 (95 % confidence interval [0.25, 2.84]) and 2.4 (95 % confidence interval [0.77, 4.04]) points. No differences in scores on burnout and engagement were found. ConclusionDespite challenging workforce circumstances in nursing homes, caregivers in the need-based care group as well as in the time group were able to spend time twice a week with residents with behavioral and psychological symptoms. No negative effects were found on formal caregivers' wellbeing after the implementation of need-based care in nursing homes. However, it requires strong leadership and the use of well-considered implementation strategies including reflective practice. Trial registryTrial registration number ISRCTN56768265 (10/08/2023).

Enhancing Aerospace Industry Efficiency and Sustainability: Process Integration and Quality Management in the Context of Industry 4.0

This paper delves into the multifaceted domain of the aerospace industry, examining its evolution, current challenges, and imperative focus on quality management and process integration. The aerospace sector, driven by technological advancements and a burgeoning global demand for air travel and freight transport, necessitates a thorough analysis of its industrial fabric and operational intricacies. This research endeavors to analyze the dynamics of the aerospace industry, pinpoint its challenges, and propose an integrated approach to enhance efficiency, quality, and sustainability. The primary goals encompass understanding the evolving industry landscape, identifying critical challenges, and offering innovative solutions by amalgamating the principles of Industry 4.0 into quality management and processes within the aerospace sector. Through an in-depth exploration of various facets, this research underscores the pivotal role of efficient processes and integrated quality management in achieving sustainable growth and competitiveness in the aerospace industry. By aligning with the paradigm of Industry 4.0, organizations can optimize their operations and contribute to the industry’s advancement, delivering safer and more cost-effective aerospace products. The study adopts a multifaceted approach, incorporating an extensive literature review, a critical analysis of industry trends, the examination of quality management frameworks, and a thorough evaluation of the integration potential of Industry 4.0 technologies. The research also involves case studies and expert insights to validate the proposed approach. The investigation reveals that by leveraging Industry 4.0 technologies and embracing an integrated approach to quality management, the aerospace industry can significantly enhance operational efficiency, product quality, and overall sustainability. The seamless integration of processes and the implementation of advanced quality frameworks pave the way for a more competitive and future-ready aerospace industry, meeting the evolving demands of a globalized world.

Development of a tool for assessing the performance of long-term care systems in relation to care transition: Transitional Care Assessment Tool in Long-Term Care (TCAT-LTC)

BackgroundImproving the quality and safety of care transitions is a priority in many countries. Carrying out performance measurements play a significant role in improving quality of decisions undertaken by different actors involved in reforms. Therefore, the main objective of this paper is to present the development of an evaluation tool for assessing the performance of long-term care systems in relation to care transition, namely the Transitional Care Assessment Tool in Long-Term Care (TCAT-LTC). This study is performed as part of a larger European TRANS-SENIOR project.MethodsThe development of the TCAT-LTC involved three steps. First, we developed a conceptual model based on Donabedian’s quality framework and literature review. Second, we carried out a thorough process of item pool generation using deductive (systematic literature review) and deductive-inductive methods (in-depth interviews) with experts in the field of long-term care. Third, we conducted preliminary validation of the tool by asking experts in research and practice to provide an opinion on a tool and to assess content validity. Future fourth step will involve a tool’s pilot with country experts from Germany, the Netherlands and Poland.ResultsBy applying methodological triangulation, we developed the TCAT-LTC, which consists of 2 themes, 12 categories and 63 items. Themes include organizational and financial aspects. Organizational aspects include categories such as communication, transfer of information, availability and coordination of resources, training and education of staff, education/support of the patient/informal caregiver, involvement of the patient/informal caregiver, telemedicine and e-Health, and social care. Financial aspects include categories such as primary care, hospital, and long-term care. We also present the instructions on the application of the TCAT-LTC.ConclusionsIn this paper, we presented the development of the TCAT-LTC evaluation tool for assessing the performance of long-term care systems in relation to care transition. The TCAT-LTC is the first tool to assess the performance of long-term care systems in relation to care transition. Assessments can be carried out at the national and international level and enable to monitor, evaluate, and compare performance of the long-term care systems in relation to care transition within and across countries.

A Prediction Hybrid Framework for Air Quality Integrated with W-BiLSTM(PSO)-GRU and XGBoost Methods

Air quality issues are critical to daily life and public health. However, air quality data are characterized by complexity and nonlinearity due to multiple factors. Coupled with the exponentially growing data volume, this provides both opportunities and challenges for utilizing deep learning techniques to reveal complex relationships in massive knowledge from multiple sources for correct air quality prediction. This paper proposes a prediction hybrid framework for air quality integrated with W-BiLSTM(PSO)-GRU and XGBoost methods. Exploiting the potential of wavelet decomposition and PSO parameter optimization, the prediction accuracy, stability and robustness was improved. The results indicate that the R2 values of PM2.5, PM10, SO2, CO, NO2, and O3 predictions exceeded 0.94, and the MAE and RMSE values were lower than 0.02 and 0.03, respectively. By integrating the state-of-the-art XGBoost algorithm, meteorological data from neighboring monitoring stations were taken into account to predict air quality trends, resulting in a wider range of forecasts. This strategic merger not only enhanced the prediction accuracy, but also effectively solved the problem of sudden interruption of monitoring. Rigorous analysis and careful experiments showed that the proposed method is effective and has high application value in air quality prediction, building a solid framework for informed decision-making and sustainable development policy formulation.

Development of a sports technology quality framework

ABSTRACT Identifying tools and processes to effectively and efficiently evaluate technologies is an area of need for many sport stakeholders. This study aimed to develop a standardised, evidence-based framework to guide the evaluation of sports technologies. In developing the framework, a review of standards, guidelines and research into sports technology was conducted. Following this, 55 experts across the sports industry were presented with a draft framework for feedback. Following a two-round Delphi survey, the final framework consisted of 25 measurable features grouped under five quality pillars. These were 1) Quality Assurance & Measurement (Accuracy, Repeatability, Reproducibility, Specifications), 2) Established Benefit (Construct Validity, Concurrent Validity, Predictive Validity, Functionality), 3) Ethics & Security (Compliance, Privacy, Ownership, Safety, Transparency, Environmental Sustainability), 4) User Experience (Usability, Robustness, Data Representation, Customer Support & Training, Accessibility) & 5) Data Management (Data Standardisation, Interoperability, Maintainability, Scalability). The framework can be used to help design and refine sports technology in order to optimise quality and maintain industry standards, as well as guide purchasing decisions by organisations. It may also serve to create a common language for organisations, manufacturers, investors, and consumers to improve the efficiency of their decision-making relating to sports technology.

Embedding a Quality Framework for medication safety standards in delirium and dementia: A Singapore Study in a geriatric psychiatry liaison service

Introduction Research on prescribing processes for psychotropic medication review in older adult patients with severe behavioural symptoms of delirium and dementia appears limited. We aimed to improve and achieve 100% clinical documentation of psychotropic medication reviews against defined medication safety standards in older adult patients in geriatric wards with delirium occurrence and dementia without delirium referred to the geriatric psychiatry liaison service. The secondary aim evaluated any reduction in psychotropic medications as defined by medication safety standards by comparing pre-and post-assessments. Methods A baseline measurement in April 2022 showed no documentation records of the study’s first three standards. PDSA methodology was employed to evaluate whether a medication review occurred following the creation and implementation of medication safety standards 1 to 4 in cycle one and adding the fifth standard in cycle 2. The first, second and third standards were medication reviews of all hypnotics, antipsychotics, and psychotropic polypharmacy. The fourth standard reviewed the anticholinergic burden scores measured by the Anticholinergic Effect on Cognition scale. The fifth standard reviewed blood pressure and postural hypotension monitoring. Results Using a quality improvement framework that embeds defined medication safety standards as an intervention, we have demonstrated good documentation records for a medication review to improve psychotropic prescribing processes in the older adult’s psychiatry liaison service in geriatric wards in all standards in the 2 study cycles. There was a reduction in all psychotropic medications at post-assessment as defined by the medication safety standards 1 to 4 in at least one cycle in delirium occurrence and dementia without delirium, except for zopiclone in delirium. Conclusions The study’s findings in a geriatric ward setting in a public hospital in Singapore support the feasibility of embedding medication review using defined medication safety standards to improve psychotropic medication prescribing processes in older adults with delirium occurrence and dementia without delirium.

MOBI-Qual: a common framework to manage the product-service system quality of shared mobility

AbstractShared mobility is transforming urban transportation. The increasing demand for more efficient and sustainable transportation options has driven the growth of the shared mobility sector, attracting operators ranging from new entrants to traditional manufacturers looking to diversify their markets. Despite its popularity, there is currently a lack of tools to support the design and management of the quality of shared mobility. Seeking to contribute towards bridging this gap, this paper presents a comprehensive quality framework, refereed as MOBI-Qual. MOBI-Qual was developed using a bottom-up approach, wherein quality determinants were defined based on an extensive analysis of digital Voice-of-Customer data, specifically customer review. A topic modelling algorithm was utilized to extract the quality determinants for the most prevalent shared mobility modes. Following this, a common framework was established through a comparison of these quality determinants. The proposed framework comprises eleven quality determinants that comprehensively cover various aspects of shared mobility.

Strengthening provider accountability: A scoping review of accountability/monitoring frameworks for quality of RMNCH care.

Increasing health providers' accountability is an important element in improving quality of care (QoC) for reproductive, maternal, neonatal, and child health (RMNCH), so as to improve health outcomes of the population in many low- and middle-income countries (LMICs). Implemented RMNCH monitoring initiatives vary in their settings, methods of data collection, and indicators selected for monitoring. The purpose of this study is to evaluate the monitoring/accountability frameworks used by key global monitoring initiatives and provide insights for countries to develop context-customized indicators for RMNCH monitoring and accountability in middle-income countries. The authors conducted a scoping review of key global monitoring initiatives on their monitoring/accountability framework and associated indicators. Data was extracted into a spreadsheet template for analysis. Monitoring/accountability frameworks corresponding to the selected global RMNCH initiatives were described, analyzed, and then categorized the monitoring indicators used by the initiatives according to the type of indicators, quality domains, monitoring levels, and type of services. The results showed that all frameworks regarded developing quality indicators and their monitoring as important elements of accountability and emphasized the role of health systems blocks as inputs for QoC. The researchers demonstrated the importance of measuring quality through both condition-specific and general health system indicators. However, given the different purposes of global monitoring initiatives, the indicators they used varied. We found a lack of indicators measuring QoC of reproductive health. In terms of quality domains, the timeliness and efficiency of RMNCH services were neglected, as few of these indicators were selected for monitoring. Global monitoring initiatives provide valuable frameworks for countries to understand which key indicators need to be tracked to achieve global objectives and develop the foundation for their own accountability/monitoring systems. Gaps in quality indicator design and use emphasize countries need to build on what the global initiatives have achieved to systematically examine quality concerns, develop a tailored and effective accountability/monitoring framework, and improve population health.