Using shared goal setting to improve access and equity: a mixed methods study of the Good Goals intervention

Background: Access and equity in children’s therapy services may be improved by directing clinicians’ use of resources toward specific goals that are important to patients. A practice-change intervention (titled ‘Good Goals’) was designed to achieve this. This study investigated uptake, adoption, and possible effects of that intervention in children’s occupational therapy services. Methods: Mixed methods case studies (n = 3 services, including 46 therapists and 558 children) were conducted. The intervention was delivered over 25 weeks through face-to-face training, team workbooks, and ‘tools for change’. Data were collected before, during, and after the intervention on a range of factors using interviews, a focus group, case note analysis, routine data, document analysis, and researchers’ observations. Results: Factors related to uptake and adoptions were: mode of intervention delivery, competing demands on therapists’ time, and leadership by service manager. Service managers and therapists reported that the intervention: helped therapists establish a shared rationale for clinical decisions; increased clarity in service provision; and improved interactions with families and schools. During the study period, therapists’ behaviours changed: identifying goals, odds ratio 2.4 (95% CI 1.5 to 3.8); agreeing goals, 3.5 (2.4 to 5.1); evaluating progress, 2.0 (1.1 to 3.5). Children’s LoT decreased by two months [95% CI −8 to +4 months] across the services. Cost per therapist trained ranged from £1,003 to £1,277, depending upon service size and therapists’ salary bands. Conclusions: Good Goals is a promising quality improvement intervention that can be delivered and adopted in practice and may have benefits. Further research is required to evaluate its: (i) impact on patient outcomes, effectiveness, cost-effectiveness, and (ii) transferability to other clinical contexts

Computational challenges in deriving dairy cows' action patterns from accelerometer data

We describe an attempt to build a computational model for deriving dairy cows' action patterns automatically from accelerometer data

Decentralization's impact on the health workforce: Perspectives of managers, workers and national leaders

Designers and implementers of decentralization and other reform measures have focused much attention on financial and structural reform measures, but ignored their human resource implications. Concern is mounting about the impact that the reallocation of roles and responsibilities has had on the health workforce and its management, but the experiences and lessons of different countries have not been widely shared. This paper examines evidence from published literature on decentralization's impact on the demand side of the human resource equation, as well as the factors that have contributed to the impact. The elements that make such an impact analysis exceptionally complex are identified. They include the mode of decentralization that a country is implementing, the level of responsibility for the salary budget and pay determination, and the civil service status of transferred health workers. The main body of the paper is devoted to examining decentralization's impact on human resource issues from three different perspectives: that of local health managers, health workers themselves, and national health leaders. These three groups have different concerns in the human resource realm, and consequently, have been differently affected by decentralization processes. The paper concludes with recommendations regarding three key concerns that national authorities and international agencies should give prompt attention to. They are (1) defining the essential human resource policy, planning and management skills for national human resource managers who work in decentralized countries, and developing training programs to equip them with such skills; (2) supporting research that focuses on improving the knowledge base of how different modes of decentralization impact on staffing equity; and (3) identifying factors that most critically influence health worker motivation and performance under decentralization, and documenting the most cost-effective best practices to improve them. Notable experiences from South Africa, Ghana, Indonesia and Mexico are shared in an annex

Fast Gibbs sampling for high-dimensional Bayesian inversion

Solving ill-posed inverse problems by Bayesian inference has recently attracted considerable attention. Compared to deterministic approaches, the probabilistic representation of the solution by the posterior distribution can be exploited to explore and quantify its uncertainties. In applications where the inverse solution is subject to further analysis procedures, this can be a significant advantage. Alongside theoretical progress, various new computational techniques allow to sample very high dimensional posterior distributions: In [Lucka2012], a Markov chain Monte Carlo (MCMC) posterior sampler was developed for linear inverse problems with $\ell_1$-type priors. In this article, we extend this single component Gibbs-type sampler to a wide range of priors used in Bayesian inversion, such as general $\ell_p^q$ priors with additional hard constraints. Besides a fast computation of the conditional, single component densities in an explicit, parameterized form, a fast, robust and exact sampling from these one-dimensional densities is key to obtain an efficient algorithm. We demonstrate that a generalization of slice sampling can utilize their specific structure for this task and illustrate the performance of the resulting slice-within-Gibbs samplers by different computed examples. These new samplers allow us to perform sample-based Bayesian inference in high-dimensional scenarios with certain priors for the first time, including the inversion of computed tomography (CT) data with the popular isotropic total variation (TV) prior.Comment: submitted to "Inverse Problems

Specifying content and mechanisms of change in interventions to change professionals’ practice : an illustration from the Good Goals study in occupational therapy

PMID: 23078918 [PubMed - indexed for MEDLINE] PMCID: PMC3502268 Free PMC Article The study was funded by the Chief Scientist Office of the Scottish Government Health Directorates (ref: CZF/1/38). The views expressed in this paper are those of the authors. The funder was not involved in the conduct of the study or preparation of the manuscript.Peer reviewedPublisher PD

Clinicians' caseload management behaviours as explanatory factors in patients' length of time on caseloads : a predictive multilevel study in paediatric community occupational therapy

Peer reviewedPublisher PD

As a Matter of Factions: The Budgetary Implications of Shifting Factional Control in Japan’s LDP

For 38 years, the Liberal Democratic Party (LDP) maintained single-party control over the Japanese government. This lack of partisan turnover in government has frustrated attempts to explain Japanese government policy changes using political variables. In this paper, we look for intraparty changes that may have led to changes in Japanese budgetary policy. Using a simple model of agenda-setting, we hypothesize that changes in which intraparty factions “control” the LDP affect the party’s decisions over spending priorities systematically. This runs contrary to the received wisdom in the voluminous literature on LDP factions, which asserts that factions, whatever their raison d’être, do not exhibit different policy preferences. We find that strong correlations do exist between which factions comprise the agenda-setting party “mainstream” and how the government allocates spending across pork-barrel and public goods items

Molecular characterization in the prediction of disease extent in endometrial carcinoma

Objective: Patients with endometrial carcinoma are usually triaged to staging lymphadenectomy selectively based on estimated risk of lymphatic spread. The risk is generally assessed by the presence of uterine risk factors, but their preoperative and intraoperative identification remain a challenge. The objective of this study was to assess the capability of molecular classification, described by The Cancer Genome Atlas (TCGA), to predict the stage of endometrial carcinoma. Study design: Sequencing of polymerase-epsilon (POLE) and immunohistochemistry of mismatch repair (MMR) proteins and p53 were performed to stratify endometrial carcinomas into subgroups of POLE exonuclease domain mutation (EDM), MMR deficiency, abnormal p53 (p53 abn) and 'no specific molecular profile' (NSMP). NSMP was the reference subgroup for comparisons. Associations of molecular subgroups and uterine risk factors with stage were examined in univariable and multivariable analyses. Results: Six hundred and four patients were included in the study. None of the POLE EDM tumours extended beyond the uterine cervix. In an unadjusted analysis, p53 abn was associated with increased risk for stage IIIC-IV disease [odds ratio (OR) 4.6, 95% confidence interval (CI) 2.3-9.2; p <0.0005]. When controlling for uterine risk factors (histotype and grade, depth of myometrial invasion, tumour size, lymphovascular space invasion), p53 was not an independent predictor of advanced disease. In contrast, POLE EDM independently predicted local disease (OR 0.12, 95% CI 0.015-0.99; p = 0.049 for stage II-IV cancer). Of the molecular subgroups, p53 abn was most strongly associated with the presence of high-risk uterine factors (ORs between 2.2 and 19; p Conclusion: Of the TCGA-based molecular subgroups, POLE EDM independently predicted early stage endometrial carcinoma. Although p53 abn was not an independent predictor of advanced disease, its association with uterine risk factors could allow utilization of molecular data in deciding the type of staging surgery if knowledge of uterine factors is deficient. (C) 2020 Elsevier B.V. All rights reserved.Peer reviewe