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This chapter provides an overview of the role of technology and policy in shaping care plans for patients. Historically, healthcare has lagged behind other industry sectors in adopting and deploying useful technologies, and policy surrounding use is an important component of establishing a long-term strategy. This chapter evaluates the current state of technology in the clinical setting and extends the widely adopted policy-based approaches into the palliative care context.

Characteristics that impact the levels of palliative care are introduced. Patients with the potential to be classified as palliative may be overlooked or simply so not seek medical attention. The population is much higher than those being treated on an annual basis. Data from the American Community Survey (ACS) and the Behavioral Risk Factor Surveillance System (BRFSS) are applied to the characteristics of palliative care and used to estimate the size of the palliative population in the United States (US).

Synthetic patient data produced by Synthea was described in Chapter 6. That data is used to create a baseline for all patients, palliative patients, and deceased palliative patients. Distributions of comorbidities across the patient groups are examined and demographic characteristics. The factors used in palliative care groupings are presented with the synthesized data fields used. The size of the palliative population is again estimated to establish validity.

This study aims to co-develop a Frailty, Health and Care Needs Assessment (FHCNA) questionnaire for people experiencing homelessness and explore the feasibility of its use by non-clinical staff in homeless hostels.

The FHCNA, aimed at identifying frailty and other health and care priorities for people experiencing homelessness, was co-designed in workshops (online and in person) with homelessness and inclusion health staff. Its feasibility was tested by staff and their clients in two hostels, with pre- and post-study focus groups held with hostel staff to gain input and feedback.

The FHCNA was co-developed and then used to collect 74 pairs of resident and key worker inputted data (62% of eligible hostel residents). The mean age of clients was 48 years (range 22–82 years). High levels of unmet need were identified. Over half (53%) were identified as frail. Common concerns included difficulty walking (46%), frequent falls (43%), chronic pain (36%), mental health issues (57%) and dental concerns (50%). In total, 59% of clients reported difficulty in performing at least one basic activity of daily living, while only 14% had undergone a Care Act Assessment. Hostel staff found using the FHCNA to be feasible, acceptable and potentially useful in facilitating explorations of met and unmet health and social care needs of hostel clients. By identifying unmet needs, the FHCNA has the potential to support staff to advocate for access to health and social care support.

To the best of the authors’ knowledge, this is the first study to co-develop and feasibility test a questionnaire for use by non-clinically trained staff to identify frailty and other health and care needs of people experiencing homelessness in a hostel setting.

This chapter discusses the design of the LHS and the steps taken to ensure data privacy and security. Usage of the application programming interface (API) is discussed, paying attention to how an Electronic Health Record (EHR) provider would use the API. Finally, the clinician’s interaction with the system is discussed.

This paper aims to highlight current finding issues relating to the provision of hospice care services which are largely provided by the independent sector and heavily reliant on charitable fund raising. The primary focus is on the UK, but it is an issue of relevance to many other countries around the world.

The paper is an opinion piece informed by contemporary reports, official publications and research findings, as well as the author’s own work within the hospice sector.

As with many other countries around the world, the bulk of hospice funding in the UK comes from charitable donations of various kinds. However, the impact of COVID-19 highlighted both the fragility of this funding model and the precarious nature of hospice sector finances currently.

This is an issue of growing importance that affects older people and their families not only in the UK but in all countries with ageing populations. Hospices play an important role in providing end-of-life care and, with demand for services steadily rising due to demographic trends, there are important questions about the sustainability of the current hospice funding model.

Issues of funding require a much higher level of engagement from policymakers if hospice care is going to continue to play a significant part in achieving a good death for people from all sections of society.

Although hotly debated within the hospice sector and in official reports, this issue has yet to be properly examined within academic circles.

Having provided a feasible framework for the use of big data and a learning health system (LHS) in addressing disparities in access to palliative care, this chapter seeks to substantiate the ethical underpinning of that framework, drawing from well-regarded existing sources. The author will also address issues which will likely arise from a successful transition to LHSs such as the nature of informed consent, the impact it will have on medical decision-making in general, and the transformative effect big data and implementation of LHSs will have on existing data sources.

This study aims to evaluate how a community psychiatry model, referred to as the Mental Health Action Trust (MHAT) in India, provides decentralized care and comprehensive services to people with severe mental illness living in poverty. Using the complex adaptive system (CAS) framework, the authors aim to understand the factors that contribute to the diverse outcomes of the MHAT community mental health programme as observed in four different locations.

Four MHAT clinics were purposively chosen from two districts in Kerala. A comparative case study methodology was used to document each clinic’s MHAT services and activities, as found during field visits and interviews with staff members and volunteers.

The study shows that all four clinics met the basic aim of providing free, quality mental health care to the poorest populations, although not all aspects of the comprehensive model could be equally provided. Alignment with the MHAT vision, appropriate leadership, the relationship with partners and their level of community engagement determined the varied success between clinics.

The current study evaluation stresses that community ownership is crucial. Careful attention must be paid to the characteristics of selected partners, including their leadership styles and ability to garner resources.