NHS England should release trust level data from the Medical Workforce Race Equality Standard

This document addresses medical workforce needs for the speciality of Genitourinary Medicine (GUM) for the next 10 years. Data on current consultant numbers, working patterns and retirement are based on information from the Royal College of Physicians (RCP) Workforce Unit annual census undertaken on 30 September 2000. Information on specialist registrars is from the JCHMT. Senior house officers (SHO) data are from the RCP's General Professional Training department. Data on Non-Consultant Career Grade Doctors is from the Association of Genitourinary Medicine Survey. Data on incidence of Sexually Transmitted Infections (STIs) are from KC60 returns on STIs collected from GUM clinics by CDSC. There is considerable movement of doctors in GUM between countries in the UK both during progression from SpR to consultant and at consultant level. Data are therefore presented as amalgamated UK data and also by country. It is essential that workforce planning takes this lateral movement into consideration when undertaking calculations for future workforce requirements.

Download Full-text

Addressing inequalities in medical workforce distribution: evidence from a quasi-experimental study in Brazil

BMJ Global Health ◽

10.1136/bmjgh-2019-001827 ◽

2019 ◽

Vol 4 (6) ◽

pp. e001827 ◽

Cited By ~ 2

Author(s):

Elisa Maria Maffioli ◽

Thiago Augusto Hernandes Rocha ◽

Gabriel Vivas ◽

Carlos Rosales ◽

Catherine Staton ◽

...

Keyword(s):

Primary Care Physicians ◽

P Value ◽

Medical Workforce ◽

Global Challenge ◽

Infectious Gastroenteritis ◽

Urinary Infections ◽

Level Data ◽

Quasi Experimental ◽

Access To Primary Care ◽

The Government

BackgroundBrazil faces huge health inequality challenges since not all municipalities have access to primary care physicians. The More Doctors Programme (MDP), which started in 2013, was born out of this recognition, providing more than 18 000 doctors in the first few years. However, the programme faced a restructuring at the end of 2018.MethodsWe construct a panel municipality-level data between 2008 and 2017 for 5570 municipalities in Brazil. We employ a difference-in-differences empirical approach, combined with propensity score matching, to study the impacts of the programme on hospitalisations for ambulatory care sensitive conditions and its costs. We explore heterogeneous impacts by age of the patients, type of admissions, and municipalities that were given priority.FindingsThe MDP reduced ambulatory admissions by 2.9 per cent (p value <0.10) and the costs by 3.7 per cent (p value <0.01) over the mean. The reduction was driven by infectious gastroenteritis, bacterial pneumonias, asthma, kidney and urinary infections, and pelvic inflammatory disease. The results held on the subsample of municipalities targeted by the programme. By comparing the benefits of the programme from the reduction in the costs of ambulatory admissions to the total financial costs of the MDP, the impacts allowed the government to save at least BRL 27.88 (US$ 6.9 million) between 2014 and 2017.ConclusionAddressing inequalities in the distribution of the medical workforce remains a global challenge. Our results inform the discussion on the current strategy adopted in Brazil to increase access to primary healthcare in underserved areas.

Download Full-text

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000284 ◽

2017 ◽

Vol 33 (3) ◽

pp. 181-189 ◽

Cited By ~ 2

Author(s):

Christoph J. Kemper ◽

Michael Hock

Keyword(s):

Construct Validity ◽

Anxiety Sensitivity ◽

Latent Class ◽

Dimensional Structure ◽

Sensitivity Index ◽

Response Scale ◽

Established Risk Factor ◽

Irt Models ◽

Level Data ◽

Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

Download Full-text

Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽

10.1027/1614-2241/a000150 ◽

2018 ◽

Vol 14 (3) ◽

pp. 95-108 ◽

Cited By ~ 4

Author(s):

Steffen Nestler ◽

Katharina Geukes ◽

Mitja D. Back

Keyword(s):

Multilevel Model ◽

Multilevel Models ◽

Mixed Effects ◽

Repeated Measurements ◽

Scale Model ◽

Suggested Approach ◽

Psychological Study ◽

Level Data ◽

Ecological Momentary ◽

Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

Download Full-text