Clinical prediction rules

Adams, Simon; Leveson, Stephen H.

doi:10.1136/bmj.d8312

Cited by 216 publications

(184 citation statements)

References 44 publications

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“…[61][62][63][64] The Hosmer-Lemeshow goodness-of-fit test was used to measure model calibration. A p-value that is above the threshold for statistical significance, in this case p > 0.05, indicates that the data predicted by the model are not significantly different from the observed data.…”

Section: Analysis For Retention Risk Toolmentioning

confidence: 99%

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Howarth

Apea

Michie

et al. 2017

Health Serv Deliv Res

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BackgroundAntiretroviral therapy (ART) benefits individuals living with human immunodeficiency virus (HIV) through reduced morbidity and mortality, and brings public health gains through a reduction in HIV transmission. People living with human immunodeficiency virus (PLWH) need to know their HIV status and engage in HIV care in order for these individual and public health benefits to be realised.ObjectiveTo explore, describe and understand HIV outpatient attendance in PLWH, in order to develop cost-effective interventions to optimise engagement in care.DesignA mixed-methods study incorporating secondary analysis of data from the UK Collaborative HIV Cohort (UK CHIC) study and primary data collection.MethodsPhase 1 – an engagement-in-care (EIC) algorithm was developed to categorise patients as in care or out of care for each month of follow-up. The algorithm was used in group-based trajectory analysis to examine patterns of attendance over time and of the association between the proportion of months in care before ART initiation and post-ART mortality and laboratory test costs. Phase 2 – a cross-sectional survey was conducted among patients attending seven London HIV clinics. Regular attenders (all appointments attended in past year), irregular attenders (one or more appointments missed in past year) and non-attenders (recent absence of ≥ 1 year) were recruited. A ‘retention risk tool’ was developed to identify those at risk of disengaging from care. Individual in-depth interviews and focus groups were conducted with PLWH. Phase 3 – key informant interviews were conducted with HIV service providers. Interventions were developed from the findings of phases 2 and 3.ResultsPlots from group-based trajectory analysis indicated that four trajectories best fitted the data. Higher EIC is associated with reduced mortality but the association between EIC before starting ART, and post-ART mortality [relative hazard (RH) per 10% increase in EIC 0.29, 95% confidence interval (CI) 0.18 to 0.47] was attenuated after adjustment for fixed covariates and post-ART cluster of differentiation 4 counts and viral loads (RH 0.74, 95% CI 0.42 to 1.30). Small differences were found in pre-ART EIC and the costs of post-ART lab tests. The final model for the retention risk tool included age at diagnosis, having children, recreational drug use, drug/alcohol dependency, insufficient money for basic needs and use of public transport to get to the clinic. Quantitative and qualitative data showed that a range of psychological, social and economic issues were associated with disengagement from care. The negative impact of stigma on attendance was highlighted. Interventions were proposed that support a holistic approach to care including peer support, address stigma by holding clinics in alternative locations and involve training staff to encourage attendance.ConclusionsThe study shows the adverse health impacts of disengaging from HIV care and demonstrates the importance of the wider health and social context in managing HIV effectively. Although phase 1 analysis was based on UK data, phases 2 and 3 were limited to London. The interventions proposed are supported by the data but their cost-effectiveness requires testing. Future research is needed to evaluate the interventions, to validate our retention risk tool across populations and settings, and to fully analyse the economic costs of disengaging from HIV care.FundingThe National Institute for Health Research Health Services and Delivery Research programme. The UK CHIC study is funded by the Medical Research Council UK (grant numbers G0000199, G0600337, G0900274 and M004236).

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Section: Analysis For Retention Risk Toolmentioning

confidence: 99%

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Howarth

Apea

Michie

et al. 2017

Health Serv Deliv Res

View full text Add to dashboard Cite

show abstract

“…The main analytical method was conditional logistic regression. To manage the large quantity of data, and following recognised selection strategies, 21 only variables occurring in at least 2% of either cases or controls with a univariable P-value ≤0.1 entered the multivariable conditional logistic regression analyses.…”

Section: Discussionmentioning

confidence: 99%

Risk of childhood cancer with symptoms in primary care: a population-based case-control study

Dommett¹,

Redaniel²,

Stevens³

et al. 2013

Br J Gen Pract

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“…6 Provision of accurate well-presented literature makes patient choices more informed 7 but of the many resources available it is unclear which are useful in which situations, particularly for patients with multimorbidity. 8 Most symptoms, signs, and test results have low predictive value for disease so it's important to have access to data and decision aids to help weigh benefits and risks; 4,9 and this needs information technology. Biomedical science is beneficial at both individual and population level.…”

Section: Knowledgementioning

confidence: 99%

First do no harm: the e-lephant in the consulting room needs firm handling by the doctor

Treasure¹

2012

Br J Gen Pract

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Clinical prediction rules

Cited by 216 publications

References 44 publications

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Risk of childhood cancer with symptoms in primary care: a population-based case-control study

First do no harm: the e-lephant in the consulting room needs firm handling by the doctor

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