scholarly journals Health service usage and re-referral rates: comparison of a dietitian-first clinic with a medical specialist-first model of care in a cohort of gastroenterology patients

2020 ◽  
pp. flgastro-2020-101435
Author(s):  
Rumbidzai Mutsekwa ◽  
Szymon Ostrowski ◽  
Russell Canavan ◽  
Lauren Ball ◽  
Rebecca Angus
Keyword(s):  
Health Service ◽  
Medical Model ◽  
Traditional Model ◽  
Model Of Care ◽  
Service Usage ◽  
Post Discharge ◽  
Referral Rates ◽  
Significant Difference ◽  
Health Service Usage ◽  
Related Service

BackgroundThe dietitian-first gastroenterology clinic (DFGC) is an expanded scope of practice initiative implemented in response to increased gastroenterology specialist demand. This study examined re-referral rates to gastroenterology and overall health service usage up to 24 months post management in DFGC compared with a traditional, gastroenterology specialist-first model.MethodsPatients discharged from DFGC in the first year were matched with those seen in the traditional model. Demographic, clinical and process-related service characteristics were compared, and logistic regression analysis was undertaken to model re-presentation and model of care (MoC) as the variable of interest considering covariates in univariate analyses. Analyses were performed at 12, 18 and 24 months post discharge.ResultsThe DFGC (122 patients) and traditional-model (62 patients) cohorts had similar baseline demographic characteristics. Wait-times (68.6 vs 272.9 days; p<0.001), treatment-times (89.4 vs 259.9 days; p<0.001) and usage of other services (1.4 vs 2.1 specialities; p=0.01) were lower in DFGC. Re-referral rates were low in both DFGC and traditional models at 12 months (0.82% vs 1.61%), 18 months (2.46% vs 6.45%) and 24 months (4.91% vs 8.06%), respectively, with no significant difference between the models at any time point.ConclusionMost patients do not re-present for similar conditions within 2 years when managed in the DFGC or traditional medical model. Patients managed in DFGC have lower overall health service usage compared with patients managed in the traditional model. These findings support the safety and effectiveness of a DFGC model as one strategy to manage specialist gastroenterology service demands.

Use of mental health services by women in low and middle income countries

2014 ◽  
Vol 13 (4) ◽  
pp. 211-223
Author(s):  
Christine Paula de los Angeles ◽  
William Watkins Lewis ◽  
Ryan McBain ◽  
Mohammad Taghi Yasamy ◽  
Adepeju Aderemi Olukoya ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Health Service ◽  
Health Service ◽  
Service Usage ◽  
Community Based ◽  
Middle Income ◽  
Content Type ◽  
Middle Income Countries ◽  
Significant Difference ◽  
Health Service Usage

Purpose – The purpose of this paper is to examine sex differences in mental health service usage among upper-middle, lower-middle, and low-income countries (LICs). Design/methodology/approach – Data from 62 low- and middle-income countries (LAMICs) were collected with the World Health Organization – Assessment Instrument for Mental Health Systems (WHO-AIMS). Sex differences in mental health service utilization were assessed by comparing the proportion female in the general population with the proportion female treated for mental illness in five different types of mental health facility. Findings – Two-sided t-tests for significance (a=0.05) revealed a significant difference between the proportion female in the population and the proportion treated in inpatient facilities (community-based and mental hospitals) in LICs. There was also a trend toward decreased use of outpatient facilities by women in LICs (p=0.08). Lower-middle and upper-middle income countries showed no differences. In day treatment facilities for the entire sample, there was a significant difference between the proportion female in the population and the proportion treated female (weighted mean difference overall=0.10, p=0.035). Research limitations/implications – The authors found significantly reduced utilization of mental health services by women in LICs in community-based inpatient facilities and mental hospitals and a trend toward decreased use in outpatient facilities. Future studies investigating the factors contributing to the lower utilization of services by women in LICs are essential. Originality/value – This study presents the first comprehensive study of mental health service usage by sex in 62 LAMICs.

scholarly journals The relationship between HIV testing, stigma, and health service usage

AIDS Care ◽  
2010 ◽  
Vol 22 (3) ◽  
pp. 373-380 ◽  
Author(s):  
Sean D. Young ◽  
Eran Bendavid
Keyword(s):  
Health Service ◽  
Hiv Testing ◽  
Service Usage ◽  
Health Service Usage ◽  
The Relationship

scholarly journals Loneliness and Patterns of Health Service Usage: Evidence From Healthy Ageing in Scotland

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 642-642
Author(s):  
Elaine Douglas ◽  
David Bell
Keyword(s):  
Health Service ◽  
Older People ◽  
Healthy Ageing ◽  
Descriptive Statistics ◽  
Hospital Services ◽  
Service Usage ◽  
Administrative Health Data ◽  
Health Service Usage ◽  
Hospital Visits ◽  
Ageing Populations

Abstract Loneliness is associated with poorer health status and health outcomes. Yet, little is known about how loneliness in ageing populations is associated with health service usage. Loneliness (UCLA-3) was measured in older people in Scotland (Healthy Ageing in Scotland, HAGIS, n = 1,057). We analysed socio-demographic, perceived health, and health behaviour characteristics using descriptive statistics and logistic regression. The survey data (HAGIS, 2016/17) were linked to retrospective administrative health data to investigate patterns of health service usage (from 2005), such as the number of hospital visits and mean length of stay, and their associated costs. Two-part models were used to highlight variation i) in those who had ever vs never been admitted to hospital, and ii) between those who had been admitted. Our results highlight the variation in hospital service usage in those experiencing loneliness and opens discussion on the implications for older people and hospital services.

scholarly journals SOCIAL ISOLATION AND LONELINESS: A LATENT CLASS APPROACH TO COSTING HEALTH SERVICE ENGAGEMENT IN AGING POPULATIONS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S535-S535
Author(s):  
Elaine Douglas ◽  
David Bell
Keyword(s):  
Health Service ◽  
Social Isolation ◽  
Latent Class ◽  
Health Data ◽  
Service Usage ◽  
Population Groups ◽  
Administrative Health Data ◽  
Service Engagement ◽  
Health Service Usage ◽  
The Impact

Abstract Social isolation and loneliness are associated with poorer health status and poorer health outcomes. Little is known the impact on health service usage, and its inherent cost, although it is considered to be higher. Latent class analysis (LCA) was used to determine profiles (population groups) of loneliness and social isolation in older people (aged 50+, n=1,057) using model-fit criteria. Loneliness was measured using the UCLA Loneliness Scale and social isolation used a measure of social networks and social contact. We then analysed the socio-demographic, perceived health, and health behaviour of these profiles using descriptive statistics and logistic regression. The survey data (HAGIS, 2016/17) were linked to retrospective administrative health data to investigate patterns of repeat prescription use (from 2009) and health service usage (from 2005) and their associated costs. Our results highlight the distinction and inter-relation between social isolation and loneliness (including associations with socio-demographic and health characteristics), and the variation in health service usage and costs between the population groups. LCA profiles may help focussed targeting of these groups for health interventions. Further, the data-driven approach of LCA may overcome some of the limitations of indices of social isolation and loneliness. As such, this will extend the existing methodological approaches to quantitative analyses of social isolation and loneliness and demonstrate the benefits of using linked administrative health data. Significantly, this study incorporates the social and financial cost of social isolation and loneliness on health and its implications for health services.

scholarly journals Quantifying Queensland patients with cancer health service usage and costs: study protocol

BMJ Open ◽  
2017 ◽  
Vol 7 (1) ◽  
pp. e014030 ◽  
Author(s):  
Emily Callander ◽  
Stephanie M Topp ◽  
Sarah Larkins ◽  
Sabe Sabesan ◽  
Nicole Bates
Keyword(s):  
Health Service ◽  
Study Protocol ◽  
Service Usage ◽  
Patients With Cancer ◽  
Health Service Usage

scholarly journals Effects of an Adolescent Sexual and Reproductive Health Intervention on Health Service Usage by Young People in Northern Ghana: A Community-Randomised Trial

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0125267 ◽  
Author(s):  
Gifty Apiung Aninanya ◽  
Cornelius Y. Debpuur ◽  
Timothy Awine ◽  
John E. Williams ◽  
Abraham Hodgson ◽  
...  
Keyword(s):  
Young People ◽  
Reproductive Health ◽  
Health Service ◽  
Sexual And Reproductive Health ◽  
Randomised Trial ◽  
Health Intervention ◽  
Northern Ghana ◽  
Service Usage ◽  
Health Service Usage

scholarly journals Association of comorbidity and health service usage among patients with dementia in the UK: a population-based study

BMJ Open ◽  
2017 ◽  
Vol 7 (3) ◽  
pp. e012546 ◽  
Author(s):  
Jorge Browne ◽  
Duncan A Edwards ◽  
Kirsty M Rhodes ◽  
D James Brimicombe ◽  
Rupert A Payne
Keyword(s):  
Health Service ◽  
Population Based ◽  
Service Usage ◽  
Population Based Study ◽  
Health Service Usage ◽  
The Uk

scholarly journals Using Linked Health Service Data in The Evaluation of Innovative Models of Healthcare

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Rebecca Kwok-yee Pang ◽  
Velandai Srikanth ◽  
Gary Braun ◽  
Fergus McGee ◽  
Belinda Berry ◽  
...  
Keyword(s):  
At Risk ◽  
Health Service ◽  
Propensity Score ◽  
Readmission Rate ◽  
Intervention Group ◽  
Cox Proportional Hazards ◽  
Model Of Care ◽  
Post Discharge ◽  
Community Based ◽  
Risk Algorithm

IntroductionAgeing populations place considerable burden on healthcare systems. Innovative methods to implement and evaluate new care models to reduce unwarranted hospital presentations, are needed. Objectives and ApproachTo use linked Electronic Medical Record (EMR) data to evaluate a pilot community-based model of care to reduce hospital presentations in a cohort of patients at-risk of hospital representations following an acute admission. Patients admitted to a metropolitan hospital with a non-surgical condition andidentified as being at-risk of readmission using a state-wide risk algorithm, were eligible to receive a 30-day care navigation model of care. The intervention group were matched to similar eligible patients, who received usual care using propensity score matching. Linked data were obtained from the EMR based Data Warehouse to provide information on subsequent readmissions and community-based health service contacts. Readmission rates were compared at 30, 60, and 90-days post-discharge using Cox Proportional Hazards Regression, adjusted for confounders and weighted by the propensity score. Descriptive analyses were used to compare demographics and healthcare utilisations. ResultsData from 412,971 potentially eligible patients were extracted. Sixty-five received the intervention of which 63 were matched to 280 controls (aged 51-91 years, 54% female, 63% lived alone). At 30-days post-discharge (during intervention delivery) an 80% reduction in readmission rate in the intervention group was observed (Hazard Ratio [HR] 0.20; 95%Confidence Interval (CI) [0.01, 4.20]). At 60-days (HR 0.48; 95%CI [0.03, 8.05]) and 90-days (HR 0.83; 95%CI [0.06, 11.36]), readmission rate reductions decreased to 52% and 17% respectively. In the intervention group, 68.9% received an out-patient appointment compared to 40% of controls (P<0.001) and 7.7% received allied health compared to none of the controls (p=0.003) within 90-days post-discharge. Conclusion/ImplicationsResults have informed hospital-wide service implementation thereby demonstrating the value of linked EMR data and advanced statistical methods in the evaluation of real-world healthcare.

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