Looking for harm in healthcare : can Patient Safety Leadership Walk Rounds help to detect and prevent harm in NHS hospitals? A case study of NHS Tayside

Today, in 21st century healthcare at least 10% of hospitalised patients are subjected to some degree of unintended harm as a result of the treatment they receive. Despite the growing patient safety agenda there is little empirical evidence to demonstrate that patient safety is improving. Patient Safety Leadership Walk Rounds (PSLWR) were introduced to the UK, in March 2005, as a component of the Safer Patients Initiative (SPI), the first dedicated, hospital wide programme to reduce harm in hospital care. PSLWR are designed, to create a dedicated ‘conversation’ about patient safety, between frontline staff, middle level managers and senior executives. This thesis, explored the use of PSLWR, as a proactive mechanism to engage staff in patient safety discussion and detect patient harm within a Scottish healthcare system- NHS Tayside. From May 2005 to June 2006, PSLWR were held on a weekly basis within the hospital departments. A purposive sample, (n=38) of PSLWR discussions were analysed to determine: staff engagement in the process, patient safety issues disclosed; recognition of unsafe systems (latent conditions) and actions agreed for improvement. As a follow-up, 42 semi-structured interviews were undertaken to determine staff perceptions of the PSLWR system. A wide range of clinical and non-clinical staff took part (n=218) including medical staff, staff in training, porters and cleaners, nurses, ward assistants and pharmacists. Participants shared new information, not formally recorded within the hospital incident system. From the participants perspectives, PSLWR, were non threatening; were easy to take part in; demonstrated a team commitment, from the Board to the ward for patient safety and action was taken quickly as a result of the ‘conversations’. Although detecting all patient harm remains a challenge, this study demonstrates PSLWR can be a useful tool in the patient safety arsenal for NHS healthcare organisations

Inclusive Learning Initiative Library Training Programme

NUI Maynooth Teaching and Learning Showcase 2012/1

Supporting Health Equity and Affordable Health Coverage for Immigrant Populations: CHIP Coverage Option for Pregnant Immigrants and their Children

Access to affordable health coverage and healthcare is critical for pregnant individuals and translates to better outcomes for their children. Immigrants who are subject to Medicaid's five-year bar or who are undocumented are less likely than U.S. citizens or those with a legal status to have health coverage, including adequate prenatal care, in part due to more limited interactions with the healthcare system as a result of previous public charge and other exclusionary immigration policies. Healthcare for all immigrants is imperative to advancing health equity and reducing disparities between immigrant and U.S. born individuals.Under federal regulations, states may provide pregnancy-related care through the Children's Health Insurance Program (CHIP) state plan to targeted low-income children from conception to birth (the so called "unborn child" option). This option–referred to in this brief as the CHIP coverage option for pregnant immigrants and their children–enables states to provide prenatal, labor and delivery, and postpartum services to pregnant individuals, regardless of immigration status. As of January 2021, approximately one-third of states had pursued this coverage mechanism, meaning many more states could still elect to draw down available federal funding to strengthen access to care for their pregnant residents and prioritize the health of children who will become U.S. citizens at birth. This issue brief–the second in a series, "Supporting Health Equity and Affordable Health Coverage for Immigrant Populations"–offers considerations for policymakers around the CHIP coverage option for pregnant immigrants and their children, regardless of immigration status

Supporting Health Equity and Affordable Health Coverage for Immigrant Populations: State-Funded Affordable Coverage Programs for Immigrants

This issue brief—the first in a series "Supporting Health Equity and Affordable Health Coverage for Immigrant Populations"—provides an overview of the national immigrant health coverage landscape and offers considerations for policymakers related to state-funded affordable coverage programs for low-income individuals who do not qualify for subsidized health insurance under the ACA or other public programs due to immigration status

Some analytical studies on sensors and speciation

This thesis is divided into two parts. Part A describes the development o f some biosensors based on the immobilisation o f enzymes, tissue, microbes and plant materials in carbon paste. The performance characteristics o f these biocatalytic devices were investigated in both batch and flowing systems for the detection o f neurotransmitters, mono-phenols and glucose using amperometry. A new immobilisation procedure involving the use o f spectroscopic graphite and silicone grease is also described. Anodic Stripping Voltammetry was employed to illustrate the detection o f Pb(II) and Cu(II) at lichen-modified carbon paste electrodes. Continuing the theme o f metal analysis in Part B, comparison o f chromatographic and spectrometric methods is described for the detection o f Fe(III) and Al(III) in soils and clays. Information regarding speciation o f these metals within the matrices o f soils and clays was obtained. Subsequently, a chromatographic method for the separation o f Fe(II) and Fe(III) was investigated involving the use o f an ion-pairing reagent

Real-time head nod and shake detection for continuous human affect recognition

Human affect recognition is the field of study associated with using automatic techniques to identify human emotion or human affective state. A person’s affective states is often communicated non-verbally through body language. A large part of human body language communication is the use of head gestures. Almost all cultures use subtle head movements to convey meaning. Two of the most common and distinct head gestures are the head nod and the head shake gestures. In this paper we present a robust system to automatically detect head nod and shakes. We employ the Microsoft Kinect and utilise discrete Hidden Markov Models (HMMs) as the backbone to a to a machine learning based classifier within the system. The system achieves 86% accuracy on test datasets and results are provided