scholarly journals Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK

2021 ◽  
Author(s):  
Julian Mutz ◽  
Cathryn M. Lewis
Keyword(s):  
Decision Making ◽  
Health Status ◽  
Causes Of Death ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Self Rated Health ◽  
All Cause Mortality ◽  
Cross Classification ◽  
The Uk

AbstractBackgroundRisk stratification is an important public health priority that is central to clinical decision making and resource allocation. The aim of the present study was to examine how different combinations of self-rated and objective health status predict (i) all-cause mortality and (ii) cause-specific mortality from leading causes of death in the UK.MethodsThe UK Biobank study recruited >500,000 participants, aged 37-73, between 2006–2010. The health cross-classification examined incorporated self-rated health (poor, fair, good or excellent) and health status derived from medical history and current disease status, including 81 cancer and 443 non-cancer illnesses. We examined all-cause mortality and six specific causes of death: ischaemic heart disease, cerebrovascular disease, influenza and pneumonia, dementia and Alzheimer’s disease, chronic lower respiratory disease and malignant neoplasm.ResultsAnalyses included >370,000 middle-aged and older adults with a median follow-up of 11.75 (IQR = 1.4) years, yielding 4,320,270 person years of follow-up. Compared to excellent self-rated health and favourable health status, all other levels of the health cross-classification were associated with a greater risk of mortality, with hazard ratios ranging from 1.22 (95% CI 1.15-1.29, pBonf. < 0.001) for good self-rated health and favourable health status to 7.14 (95% CI 6.70-7.60, pBonf. < 0.001) for poor self-rated health and unfavourable health status.ConclusionsOur findings highlight that self-rated health captures additional health-related information and should be more widely assessed across settings. The cross-classification between health status and self-rated health represents a straightforward metric for risk stratification, with applications to population health, clinical decision making and resource allocation.

scholarly journals Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Julian Mutz ◽  
Cathryn M. Lewis
Keyword(s):  
Health Status ◽  
Causes Of Death ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Objective Health ◽  
Self Rated Health ◽  
All Cause Mortality ◽  
Cross Classification ◽  
The Uk

AbstractRisk stratification is an important public health priority that is central to clinical decision making and resource allocation. The aim of this study was to examine how different combinations of self-rated and objective health status predict all-cause mortality and leading causes of death in the UK. The UK Biobank study recruited > 500,000 participants between 2006 and 2010. Self-rated health was assessed using a single-item question and health status was derived from medical history, including data on 81 cancer and 443 non-cancer illnesses. Analyses included > 370,000 middle-aged and older adults with a median follow-up of 11.75 (IQR = 1.4) years, yielding 4,320,270 person-years of follow-up. Compared to individuals with excellent self-rated health and favourable health status, individuals with other combinations of self-rated and objective health status had a greater mortality risk, with hazard ratios ranging from HR = 1.22 (95% CI 1.15–1.29, PBonf. < 0.001) for individuals with good self-rated health and favourable health status to HR = 7.14 (95% CI 6.70–7.60, PBonf. < 0.001) for individuals with poor self-rated health and unfavourable health status. Our findings highlight that self-rated health captures additional health-related information and should be more widely assessed. The cross-classification between self-rated health and health status represents a straightforward metric for risk stratification, with applications to population health, clinical decision making and resource allocation.

Between a logic of disruption and a logic of continuation: Negotiating the legitimacy of algorithms used in automated clinical decision-making

2021 ◽  
pp. 136345932199674
Author(s):  
Rikke Torenholt ◽  
Henriette Langstrup
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Patient Reported Outcomes ◽  
Patient Involvement ◽  
Clinical Decision Making ◽  
Diagnostic Procedures ◽  
Clinical Decision ◽  
Patient Reported ◽  
Pro Tools

In both popular and academic discussions of the use of algorithms in clinical practice, narratives often draw on the decisive potentialities of algorithms and come with the belief that algorithms will substantially transform healthcare. We suggest that this approach is associated with a logic of disruption. However, we argue that in clinical practice alongside this logic, another and less recognised logic exists, namely that of continuation: here the use of algorithms constitutes part of an established practice. Applying these logics as our analytical framing, we set out to explore how algorithms for clinical decision-making are enacted by political stakeholders, healthcare professionals, and patients, and in doing so, study how the legitimacy of delegating to an algorithm is negotiated and obtained. Empirically we draw on ethnographic fieldwork carried out in relation to attempts in Denmark to develop and implement Patient Reported Outcomes (PRO) tools – involving algorithmic sorting – in clinical practice. We follow the work within two disease areas: heart rehabilitation and breast cancer follow-up care. We show how at the political level, algorithms constitute tools for disrupting inefficient work and unsystematic patient involvement, whereas closer to the clinical practice, algorithms constitute a continuation of standardised and evidence-based diagnostic procedures and a continuation of the physicians’ expertise and authority. We argue that the co-existence of the two logics have implications as both provide a push towards the use of algorithms and how a logic of continuation may divert attention away from new issues introduced with automated digital decision-support systems.

scholarly journals Routine Follow-Up Radiographs for Ankle Fractures Seldom Add Value to Clinical Decision-Making: A Retrospective, Observational Study

2018 ◽  
Vol 57 (5) ◽  
pp. 957-960 ◽  
Author(s):  
Pieter van Gerven ◽  
Nikki L. Weil ◽  
Marco F. Termaat ◽  
Sidney M. Rubinstein ◽  
Mostafa El Moumni ◽  
...  
Keyword(s):  
Decision Making ◽  
Observational Study ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Ankle Fractures ◽  
Retrospective Observational Study

Reversibility of Delirium in Palliative Care (DRAFT)

2018 ◽  
Author(s):  
Tiffany Shaw ◽  
Eric Prommer
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Palliative Care ◽  
Clinical Case ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Factors Associated ◽  
Frequent Event ◽  
Study Intervention

Delirium is a frequent event in patients with advanced cancer. Untreated delirium affects assessment of symptoms, impairs communication including participation in clinical decision-making. This study used specific diagnostic criteria for delirium and prospectively identified precipitating causes of delirium. The study identified factors associated with reversible and irreversible delirium. Impact of delirium on prognosis was evaluated. This chapter describes the basics of the study, including funding, year study began, year study was published, study location, who was studied, who was excluded, how many patients, study design, study intervention, follow-up, endpoints, results, and criticism and limitations. The chapter briefly reviews other relevant studies and information, gives a summary and discusses implications, and concludes with a relevant clinical case. Topics covered include delirium, neoplasms, palliative care, polypharmacy, risk factors, and therapeutics.

scholarly journals INNV-34. PATTERNS OF FAILURE AND DEVELOPMENT OF A NOVEL PROGNOSTIC SCORING SYSTEM IN ELDERLY PATIENTS WITH GLIOBLASTOMA – FOLLOW UP ON 10 YEAR ANALYSIS OF THE BC CANCER AGENCY POPULATION

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi137-vi137
Author(s):  
Jonathan Zeng ◽  
Kimberly DeVries ◽  
Andra Krauze
Keyword(s):  
Decision Making ◽  
Scoring System ◽  
Clinical Decision Making ◽  
Radiographic Progression ◽  
Clinical Decision ◽  
Patient Stratification ◽  
Patterns Of Failure ◽  
Resection Status ◽  
Cancer Agency

Abstract PURPOSE Glioblastomas (GBM) are the most common primary brain tumour recurring in most patients despite maximal management. Patient selection for appropriate treatment modality remains challenging resulting in heterogeneity in management. We examined the patterns of failure and developed a scoring system for patient stratification to optimise clinical decision making. METHODS 822 adults (BC Cancer Agency registry) diagnosed 2005–2015 age ≥60 with histologically confirmed GBM ICD-O-3 codes (9440/3, 9441/3, 9442/3) were reviewed. Univariate and Kaplan-Meier analysis were performed. Performance status (PS), age and resection status were assigned a score, cummulative maximal (favorable) score of 10 and minimum (unfavorable) score of 3. Patterns of failure were further analysed in the subset of patients with radiographic follow-up. RESULTS PS score of 3(KPS >80, ECOG 0/1), 2 (KPS 60–70, ECOG 2), 1 (KPS < 60, ECOG 3/4) (median OS 11, 6, 3 months respectively), age score and resection status were prognostic for OS with PS resulting in the most significant curve separation (p< 0.0001). Biopsy as compared to STR/GTR resulted in poorer OS in patients over 70 (age score 1/2) but had less impact in patients younger than 70 (age scores 3/4). The median OS for cumulative scores of 9/10 (123 patients), 7/8 (286 patients), 5/6 (313 patients), and 3/4 (55 patients) were 14, 8, 4 and 2 months respectively (p< 0.0001) allowing for stratification into 4 prognostic groups. 133 patients had >3 MRIs following diagnosis allowing for clinical and radiographic analysis of progression. Clinical/radiographic progression occurred within 3 months (29%/45%), 6 months (50%/66%), 9 months (70%/81%). Progression type (radiographic, clinical, both was not associated with OS. CONCLUSION Our novel prognostic scoring system is effective in achieving patient stratification and may guide clinical decision making. Early radiographic progression appears to precede clinical deterioration and may represent true progression in the elderly.

scholarly journals Clinical decision making in the provision of audiovisual care for upper limb trauma: a survey of UK experiences

Hand Therapy ◽  
2020 ◽  
pp. 175899832097213
Author(s):  
Emily McMullen ◽  
Megan Robson ◽  
Mark Paul Brewin ◽  
Poonam Valand ◽  
Leela Sayed ◽  
...  
Keyword(s):  
Decision Making ◽  
Upper Limb ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Service Planning ◽  
Cross Sectional Survey ◽  
Visual Technology ◽  
Limb Trauma ◽  
The Uk ◽  
Decision Making Tool

Introduction For many patients, audio-visual appointments have provided a timely and efficient way of seeking advice, assessment and treatment for their hand injuries during the NHS response to COVID-19. This study aimed to explore the experience of hand units across the UK in determining the safe and judicious use of audio-visual outpatient care for the management of acute upper limb trauma. Methods An online cross-sectional survey was sent to the therapy leads of hand units across the UK. Questions focused on the experience of using audio-visual technology in the management of upper limb trauma, and the relevant factors in determining its appropriate use. A deductive mixed methods analysis was used to identify both common themes and capture community experience and characteristics. Results A total of 51 out of 76 hand therapy units completed the survey; a response rate of 67%. Of these, 82% (42/51) reported using audio-visual technology to manage upper limb trauma during the UK COVID-19 lockdown. When determining patient suitability for audio-visual consultations, 73% (37/51) of respondents reported the use of COVID-19 guidelines, but only 35% (18/51) reported the use of a clinical decision-making tool. In agreement with our experience at Salisbury Hospital Foundation Trust, 92% (47/51) had concerns relating to the use of audio-visual care. Conclusion The choice of safely managed remote care or in-person consultation has, to date, largely relied on the discretion of the clinician. A carefully designed clinical decision-making tool for the management of upper limb trauma is needed for use both in clinical practice and in future service planning.

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