What patient assessment skills do pharmacist independent prescribers require to prescribe immunomodulators in myeloma?

AIM: To gain consensus on the patient assessment skills required by pharmacist independent prescribers prescribing immunomodulators in myeloma across National Health Service Scotland. METHODS: This was a two-phase study which used nominal group technique to gain local consensus followed by a two-round eDelphi questionnaire to gain national consensus across all cancer networks. SETTING: This project was conducted across the three cancer networks within NHS Scotland: South East Scotland Cancer Network; West of Scotland Cancer Network and North Cancer Alliance. SUBJECTS: Participants were invited from each cancer network (South East Scotland Cancer Network, West of Scotland Cancer Network and North Cancer Alliance) and included haematology consultants, haematology specialist registrars, haematology advanced nurse practitioners and haematology pharmacists. RESULTS: There were five participants in the nominal group technique. Twenty-two out of 31 patient assessment skills gained local consensus, seven patient assessment skills did not gain consensus and two patient assessment skills were deemed irrelevant. There were 12 and 14 participants in round one and two of the eDelphi questionnaire, respectively. Twenty-nine patient assessment skills were included in the first-round questionnaire and 21 gained consensus. The remaining eight patient assessment skills were included in round two where seven did not achieve consensus and one achieved disagreement consensus. CONCLUSION: This research outlines 21 patient assessment skills required for pharmacist independent prescribers to prescribe immunomodulators for myeloma patients according to haematology specialists in Scotland. Discussion on patient assessment skills without consensus showed that the pharmacist independent prescribers would have a shared responsibility with the consultant. This work should inform the development of a competency framework to allow training of pharmacist independent prescribers in Scotland. Some patient assessment skills could be transferrable for pharmacist independent prescribers prescribing systemic anti-cancer therapy for other haematological malignancies.

Aboriginal mothers in prison in Australia: a study of social, emotional and physical wellbeing.

OBJECTIVE: To describe the social, emotional and physical wellbeing of Aboriginal mothers in prison. METHODS: Cross-sectional survey, including a Short Form Health Survey (SF-12) and Kessler Psychological Distress Scale (5-item version) administered to Aboriginal women who self-identified as mothers. RESULTS: Seventy-seven Aboriginal mothers in New South Wales (NSW) and 84 in Western Australia (WA) participated in the study. Eighty-three per cent (n=59) of mothers in NSW were in prison for drug-related offences, 64.8% (n=46) of mothers in WA were in prison for offences committed under the influence of alcohol. Sixty-eight per cent (n=52) of mothers in NSW and 35% (n=28) of mothers in WA reported mental health problems. Physical (PCS) and Mental (MCS) component scores of SF-12 varied for mothers in NSW and WA. Mothers in NSW experienced poorer health and functioning than mothers in WA (NSW: PCS 49.5, MCS 40.6; WA: PCS 54.4, MCS 48.3) and high levels of psychological distress (NSW: 13.1; WA 10.1). CONCLUSIONS: Aboriginal mothers in prison have significant health needs associated with physical and mental health, and psychological distress. Implications for public health: Adoption of social and emotional wellbeing as an explanatory framework for culturally secure healthcare in prison is essential to improving health outcomes of Aboriginal mothers in prison in Australia.

Disparities in spread and control of influenza in slums of Delhi: findings from an agent-based modelling study.

OBJECTIVES: This research studies the role of slums in the spread and control of infectious diseases in the National Capital Territory of India, Delhi, using detailed social contact networks of its residents. METHODS: We use an agent-based model to study the spread of influenza in Delhi through person-to-person contact. Two different networks are used: one in which slum and non-slum regions are treated the same, and the other in which 298 slum zones are identified. In the second network, slum-specific demographics and activities are assigned to the individuals whose homes reside inside these zones. The main effects of integrating slums are that the network has more home-related contacts due to larger family sizes and more outside contacts due to more daily activities outside home. Various vaccination and social distancing interventions are applied to control the spread of influenza. RESULTS: Simulation-based results show that when slum attributes are ignored, the effectiveness of vaccination can be overestimated by 30%-55%, in terms of reducing the peak number of infections and the size of the epidemic, and in delaying the time to peak infection. The slum population sustains greater infection rates under all intervention scenarios in the network that treats slums differently. Vaccination strategy performs better than social distancing strategies in slums. CONCLUSIONS: Unique characteristics of slums play a significant role in the spread of infectious diseases. Modelling slums and estimating their impact on epidemics will help policy makers and regulators more accurately prioritise allocation of scarce medical resources and implement public health policies.

EpiCaster: An Integrated Web Application For Situation Assessment and Forecasting of Global Epidemics.

Public health decision makers need access to high resolution situation assessment tools for understanding the extent of various epidemics in different regions of the world. In addition, they need insights into the future course of epidemics by way of forecasts. Such forecasts are essential for planning the allocation of limited resources and for implementing several policy-level and behavioral intervention strategies. The need for such forecasting systems became evident in the wake of the recent Ebola outbreak in West Africa. We have developed EpiCaster, an integrated Web application for situation assessment and forecasting of various epidemics, such as Flu and Ebola, that are prevalent in different regions of the world. Using EpiCaster, users can assess the magnitude and severity of different epidemics at highly resolved spatio-temporal levels. EpiCaster provides time-varying heat maps and graphical plots to view trends in the disease dynamics. EpiCaster also allows users to visualize data gathered through surveillance mechanisms, such as Google Flu Trends (GFT) and the World Health Organization (WHO). The forecasts provided by EpiCaster are generated using different epidemiological models, and the users can select the models through the interface to filter the corresponding forecasts. EpiCaster also allows the users to study epidemic propagation in the presence of a number of intervention strategies specific to certain diseases. Here we describe the modeling techniques, methodologies and computational infrastructure that EpiCaster relies on to support large-scale predictive analytics for situation assessment and forecasting of global epidemics.