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Article ; Online: How could online NHS 111 reduce demand for the telephone NHS 111 service? Qualitative study of user and staff views.

Sampson, Fiona C / Knowles, Emma L / Long, Jaqui / Turner, Janette / Coster, Joanne

2023 Volume 41, Issue 1, Page(s) 34–39

Abstract: Background: Online NHS111 was introduced in 2018 in response to increasing and unsustainable demand for telephone NHS111. Despite high levels of use, there is little evidence of channel shift from the telephone to the online service. We explored user ... ...

Abstract	Background: Online NHS111 was introduced in 2018 in response to increasing and unsustainable demand for telephone NHS111. Despite high levels of use, there is little evidence of channel shift from the telephone to the online service. We explored user and staff perspectives of online NHS111 to understand how and why online NHS111 is used and whether there may be potential for shift from the telephone to online service. Methods: As part of a wider mixed-methods study, we used qualitative semistructured interviews to explore perspectives of recent users of online 111 who had responded to a user survey (n=32) and NHS 111 staff (n=16) between November 2019 and June 2020. Interviews were recorded and transcribed verbatim. The data sets were analysed separately using framework analysis (user interviews) and thematic analysis (staff interviews). Results: Telephone NHS111 health adviser skills in probing and obtaining 'soft information' were perceived as key to obtaining advice that was considered more appropriate and trusted than advice from online interactions, which relied on oversimplified or irrelevant questions.Online NHS111 was perceived to provide a useful and convenient adjunct to the telephone service and widened access to NHS111 services for some subgroups of users who would not otherwise access the telephone service (eg, communication barriers, social anxiety) or were concerned about 'bothering' a health professional. The nature of the online consultation meant that online NHS111 was perceived as more disposable and used more speculatively. Conclusion: Online 111 was perceived as a useful adjunct but not a replacement for telephone NHS 111 with potential for channel shift hindered by reduced confidence in the online service due to the lack of human interaction. Further development of OL111 algorithms will be required if it is to meet the needs of people with more complex health needs.
MeSH term(s)	Humans ; State Medicine ; Qualitative Research ; Surveys and Questionnaires ; Referral and Consultation ; Telephone
Language	English
Publishing date	2023-12-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2040124-3
ISSN	1472-0213 ; 1472-0205
ISSN (online)	1472-0213
ISSN	1472-0205
DOI	10.1136/emermed-2022-213009
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Article ; Online: The Safety INdEx of Prehospital On Scene Triage (SINEPOST) study: The development and validation of a risk prediction model to support ambulance clinical transport decisions on-scene.

Miles, Jamie / Jacques, Richard / Campbell, Richard / Turner, Janette / Mason, Suzanne

PloS one

2022 Volume 17, Issue 11, Page(s) e0276515

Abstract: One of the main problems currently facing the delivery of safe and effective emergency care is excess demand, which causes congestion at different time points in a patient's journey. The modern case-mix of prehospital patients is broad and complex, ... ...

Abstract	One of the main problems currently facing the delivery of safe and effective emergency care is excess demand, which causes congestion at different time points in a patient's journey. The modern case-mix of prehospital patients is broad and complex, diverging from the traditional 'time critical accident and emergency' patients. It now includes many low-acuity patients and those with social care and mental health needs. In the ambulance service, transport decisions are the hardest to make and paramedics decide to take more patients to the ED than would have a clinical benefit. As such, this study asked the following research questions: In adult patients attending the ED by ambulance, can prehospital information predict an avoidable attendance? What is the simulated transportability of the model derived from the primary outcome? A linked dataset of 101,522 ambulance service and ED ambulance incidents linked to their respective ED care record from the whole of Yorkshire between 1st July 2019 and 29th February 2020 was used as the sample for this study. A machine learning method known as XGBoost was applied to the data in a novel way called Internal-External Cross Validation (IECV) to build the model. The results showed great discrimination with a C-statistic of 0.81 (95%CI 0.79-0.83) and excellent calibration with an O:E ratio was 0.995 (95% CI 0.97-1.03), with the most important variables being a patient's mobility, their physiological observations and clinical impression with psychiatric problems, allergic reactions, cardiac chest pain, head injury, non-traumatic back pain, and minor cuts and bruising being the most important. This study has successfully developed a decision-support model that can be transformed into a tool that could help paramedics make better transport decisions on scene, known as the SINEPOST model. It is accurate, and spatially validated across multiple geographies including rural, urban, and coastal. It is a fair algorithm that does not discriminate new patients based on their age, gender, ethnicity, or decile of deprivation. It can be embedded into an electronic Patient Care Record system and automatically calculate the probability that a patient will have an avoidable attendance at the ED, if they were transported. This manuscript complies with the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement (Moons KGM, 2015).
MeSH term(s)	Adult ; Humans ; Triage ; Ambulances ; Emergency Medical Services ; Allied Health Personnel
Language	English
Publishing date	2022-11-16
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0276515
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Article ; Online: The Safety INdEx of Prehospital On Scene Triage (SINEPOST) study: the development and validation of a risk prediction model to support ambulance clinical transport decisions on-scene-a protocol.

Miles, Jamie / Jacques, Richard / Turner, Janette / Mason, Suzanne

Diagnostic and prognostic research

2021 Volume 5, Issue 1, Page(s) 18

Abstract: Background: Demand for both the ambulance service and the emergency department (ED) is rising every year and when this demand is excessive in both systems, ambulance crews queue at the ED waiting to hand patients over. Some transported ambulance ... ...

Abstract	Background: Demand for both the ambulance service and the emergency department (ED) is rising every year and when this demand is excessive in both systems, ambulance crews queue at the ED waiting to hand patients over. Some transported ambulance patients are 'low-acuity' and do not require the treatment of the ED. However, paramedics can find it challenging to identify these patients accurately. Decision support tools have been developed using expert opinion to help identify these low acuity patients but have failed to show a benefit beyond regular decision-making. Predictive algorithms may be able to build accurate models, which can be used in the field to support the decision not to take a low-acuity patient to an ED. Methods and analysis: All patients in Yorkshire who were transported to the ED by ambulance between July 2019 and February 2020 will be included. Ambulance electronic patient care record (ePCR) clinical data will be used as candidate predictors for the model. These will then be linked to the corresponding ED record, which holds the outcome of a 'non-urgent attendance'. The estimated sample size is 52,958, with 4767 events and an EPP of 7.48. An XGBoost algorithm will be used for model development. Initially, a model will be derived using all the data and the apparent performance will be assessed. Then internal-external validation will use non-random nested cross-validation (CV) with test sets held out for each ED (spatial validation). After all models are created, a random-effects meta-analysis will be undertaken. This will pool performance measures such as goodness of fit, discrimination and calibration. It will also generate a prediction interval and measure heterogeneity between clusters. The performance of the full model will be updated with the pooled results. Discussion: Creating a risk prediction model in this area will lead to further development of a clinical decision support tool that ensures every ambulance patient can get to the right place of care, first time. If this study is successful, it could help paramedics evaluate the benefit of transporting a patient to the ED before they leave the scene. It could also reduce congestion in the urgent and emergency care system. Trial registration: This study was retrospectively registered with the ISRCTN: 12121281.
Language	English
Publishing date	2021-11-08
Publishing country	England
Document type	Journal Article
ISSN	2397-7523
ISSN (online)	2397-7523
DOI	10.1186/s41512-021-00108-4
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Article ; Online: The Safety INdEx of Prehospital On Scene Triage (SINEPOST) study

Jamie Miles / Richard Jacques / Janette Turner / Suzanne Mason

Diagnostic and Prognostic Research, Vol 5, Iss 1, Pp 1-

the development and validation of a risk prediction model to support ambulance clinical transport decisions on-scene—a protocol

2021 Volume 9

Abstract: Abstract Background Demand for both the ambulance service and the emergency department (ED) is rising every year and when this demand is excessive in both systems, ambulance crews queue at the ED waiting to hand patients over. Some transported ambulance ... ...

Abstract	Abstract Background Demand for both the ambulance service and the emergency department (ED) is rising every year and when this demand is excessive in both systems, ambulance crews queue at the ED waiting to hand patients over. Some transported ambulance patients are ‘low-acuity’ and do not require the treatment of the ED. However, paramedics can find it challenging to identify these patients accurately. Decision support tools have been developed using expert opinion to help identify these low acuity patients but have failed to show a benefit beyond regular decision-making. Predictive algorithms may be able to build accurate models, which can be used in the field to support the decision not to take a low-acuity patient to an ED. Methods and analysis All patients in Yorkshire who were transported to the ED by ambulance between July 2019 and February 2020 will be included. Ambulance electronic patient care record (ePCR) clinical data will be used as candidate predictors for the model. These will then be linked to the corresponding ED record, which holds the outcome of a ‘non-urgent attendance’. The estimated sample size is 52,958, with 4767 events and an EPP of 7.48. An XGBoost algorithm will be used for model development. Initially, a model will be derived using all the data and the apparent performance will be assessed. Then internal-external validation will use non-random nested cross-validation (CV) with test sets held out for each ED (spatial validation). After all models are created, a random-effects meta-analysis will be undertaken. This will pool performance measures such as goodness of fit, discrimination and calibration. It will also generate a prediction interval and measure heterogeneity between clusters. The performance of the full model will be updated with the pooled results. Discussion Creating a risk prediction model in this area will lead to further development of a clinical decision support tool that ensures every ambulance patient can get to the right place of care, first time. If this study is ...
Keywords	Ambulance ; EMS ; Emergency ; Triage ; Acuity ; Machine learning ; Medicine (General) ; R5-920
Subject code	310
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A History of Regulatory Animal Testing: What Can We Learn?

Swaters, Doortje / van Veen, Anne / van Meurs, Wim / Turner, Janette Ellen / Ritskes-Hoitinga, Merel

Alternatives to laboratory animals : ATLA

2022 Volume 50, Issue 5, Page(s) 322–329

Abstract: The contemporary pharmaceutical industry is voicing growing concerns about the translatability and reproducibility of animal models. In addition, the usefulness of certain of the required regulatory safety tests in animals is being increasingly ... ...

Abstract	The contemporary pharmaceutical industry is voicing growing concerns about the translatability and reproducibility of animal models. In addition, the usefulness of certain of the required regulatory safety tests in animals is being increasingly questioned. It remains difficult, however, to make the move toward alternative testing methods, not least because of legislative demands. A historical analysis was performed, in order to study how the mandatory animal studies in legislative requirements came about. This article reflects on the role that specific public health disasters played in the creation of (more) regulatory requirements for animal testing. It will show how the regulatory changes prompted by the sulfanilamide elixir disaster in the 1930s and the thalidomide disaster in the early 1960s were based on the belief that extensive animal testing would prevent similar future human health tragedies. As scientists increasingly highlight issues with translatability between non-human animals and humans, the belief that current regulatory requirements ensure safety becomes more difficult to maintain. In addition, it means that some of the regulations now in place require animal tests that do not contribute to the safety of a drug, as shown in a third case study of the court case by Vanda industries against the FDA. We finally argue that regulations should be critically examined and altered where necessary, so that they are no longer a barrier in the transition toward animal-free testing and more human-relevant science.
MeSH term(s)	Animal Testing Alternatives ; Animals ; Animals, Laboratory ; Reproducibility of Results ; Sulfanilamides ; Thalidomide
Chemical Substances	Sulfanilamides ; Thalidomide (4Z8R6ORS6L)
Language	English
Publishing date	2022-08-19
Publishing country	England
Document type	Journal Article
ZDB-ID	605800-0
ISSN	0261-1929
ISSN	0261-1929
DOI	10.1177/02611929221118001
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Article ; Online: Measuring the impact introducing NHS 111 online had on the NHS 111 telephone service and the wider NHS urgent care system: an observational study.

Simpson, Rebecca M / Jacques, Richard M / Nicholl, Jon / Stone, Tony / Turner, Janette

BMJ open

2022 Volume 12, Issue 7, Page(s) e058964

Abstract: Objectives: To explore what impact introducing the National Health Service (NHS) 111 online service had on the number of phone calls to the NHS 111 telephone service and the NHS urgent care system.: Design: Observational study using a dose-response ... ...

Abstract	Objectives: To explore what impact introducing the National Health Service (NHS) 111 online service had on the number of phone calls to the NHS 111 telephone service and the NHS urgent care system. Design: Observational study using a dose-response interrupted time series model and random-effects meta- analysis to estimate the average effect. Setting and participants: NHS 111 telephone and online contacts for 18 NHS 111 area codes in England. NHS 111 telephone and online contacts data were collected between October 2010 to December 2019 and January 2018 to December 2019, respectively. Primary and secondary outcome measures: Primary outcome: the number of triaged calls to the NHS 111 telephone service following the introduction of NHS 111 online. Secondary outcomes: total calls to the NHS 111 telephone service, total number of emergency ambulance referrals or advice to contact 999, total number of advice to attend an emergency department or other urgent care treatment facility, and total number of advice to contact primary care. Results: For triaged calls, the overall incidence rate ratio (IRR) per 1000 online contacts was 1.013 (95% CI: 0.996 to 1.029, p=0.127). For total calls, the overall IRR per 1000 online contacts was 1.008 (95% CI: 0.992 to 1.025, p=0.313). For emergency ambulance referrals or advice to contact 999, the overall IRR per 1000 online contacts was 1.067 (95% CI: 1.035 to 1.100, p<0.001). For advice to attend an emergency department or other urgent care treatment facility, the overall IRR per 1000 online contacts is 1.050 (95% CI: 1.010 to 1.092, p=0.014). And finally, for those advised to contact primary care, the overall IRR per 1000 online contacts is 1.051 (95% CI: 1.027 to 1.076, p<0.001). Conclusions: It was found that the NHS 111 online service has little impact on the number of triaged and total calls, suggesting that the workload for the NHS 111 telephone service has not increased or decreased as a result of introducing NHS 111 online. However, there was evidence to suggest an increase in the overall number of disposition recommendations (ambulance, emergency department and primary care) for NHS 111 telephone and online services combined following the introduction of the NHS 111 online service.
MeSH term(s)	Ambulatory Care ; Humans ; Referral and Consultation ; State Medicine ; Telephone ; Triage
Language	English
Publishing date	2022-07-12
Publishing country	England
Document type	Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't
ZDB-ID	2599832-8
ISSN	2044-6055 ; 2044-6055
ISSN (online)	2044-6055
ISSN	2044-6055
DOI	10.1136/bmjopen-2021-058964
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Article: A History of Regulatory Animal Testing: What Can We Learn?

Swaters, Doortje / van Veen, Anne / van Meurs, Wim / Turner, Janette Ellen / Ritskes-Hoitinga, Merel

ATLA. Alternatives to laboratory animals. ,

2022

Abstract	The contemporary pharmaceutical industry is voicing growing concerns about the translatability and reproducibility of animal models. In addition, the usefulness of certain of the required regulatory safety tests in animals is being increasingly questioned. It remains difficult, however, to make the move toward alternative testing methods, not least because of legislative demands. A historical analysis was performed, in order to study how the mandatory animal studies in legislative requirements came about. This article reflects on the role that specific public health disasters played in the creation of (more) regulatory requirements for animal testing. It will show how the regulatory changes prompted by the sulfanilamide elixir disaster in the 1930s and the thalidomide disaster in the early 1960s were based on the belief that extensive animal testing would prevent similar future human health tragedies. As scientists increasingly highlight issues with translatability between non-human animals and humans, the belief that current regulatory requirements ensure safety becomes more difficult to maintain. In addition, it means that some of the regulations now in place require animal tests that do not contribute to the safety of a drug, as shown in a third case study of the court case by Vanda industries against the FDA. We finally argue that regulations should be critically examined and altered where necessary, so that they are no longer a barrier in the transition toward animal-free testing and more human-relevant science.
Keywords	Vanda ; animals ; case studies ; human health ; laboratories ; pharmaceutical industry ; public health ; sulfanilamide
Language	English
Dates of publication	2022-0819
Publishing place	SAGE Publications
Document type	Article
ZDB-ID	605800-0
ISSN	0261-1929
ISSN	0261-1929
DOI	10.1177/02611929221118001
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Effects of service changes affecting distance/time to access urgent and emergency care facilities on patient outcomes: a systematic review.

Chambers, Duncan / Cantrell, Anna / Baxter, Susan / Turner, Janette / Booth, Andrew

BMC medicine

2020 Volume 18, Issue 1, Page(s) 117

Abstract: Background: Reconfiguration of urgent and emergency care services often increases travel time/distance for patients to reach an appropriate facility. Evidence of the effects of reconfiguration is important for local communities and commissioners and ... ...

Abstract	Background: Reconfiguration of urgent and emergency care services often increases travel time/distance for patients to reach an appropriate facility. Evidence of the effects of reconfiguration is important for local communities and commissioners and providers of health services. Methods: We performed a systematic review of the evidence regarding effects of service reconfigurations that increase the time/distance for some patients to reach an urgent and emergency care (UEC) facility. We searched seven bibliographic databases from 2000 to February 2019 and used citation tracking and reference lists to identify additional studies. We included studies of any design that compared outcomes for people with conditions requiring emergency treatment before and after service reconfiguration with an associated change in travel time/distance to access UEC. Studies had to be conducted in the UK or other developed countries. Data extraction and quality assessment (using the Joanna Briggs Institute checklist for quasi-experimental studies) were undertaken by a single reviewer with a sample checked for accuracy and consistency. We performed a narrative synthesis of the included studies. Overall strength of evidence was assessed using a previously published method that considers volume, quality and consistency. Results: We included 12 studies, of which six were conducted in the USA, two in the UK and four in other European countries. The studies used a variety of observational designs, with before-after and cohort designs being most common. Only two studies included an independent control site/sites where no reconfiguration had taken place. The reconfigurations evaluated in these studies reported relatively small effects on average travel times/distance. Discussion: For studies of general UEC populations, there was no convincing evidence as to whether reconfiguration affected mortality risk. However, evidence of increased risk was identified from studies of patients with acute myocardial infarction, particularly 1 to 4 years after reconfiguration. Evidence for other conditions was inconsistent or very limited. Conclusions: We found insufficient evidence to determine whether increased distance to UEC increases mortality risk for the general population of people requiring UEC, although this conclusion may not extend to people with specific conditions.
MeSH term(s)	Ambulatory Care/standards ; Emergency Service, Hospital/standards ; Health Facilities/standards ; Humans ; Patient Outcome Assessment
Keywords	covid19
Language	English
Publishing date	2020-05-20
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Systematic Review
ISSN	1741-7015
ISSN (online)	1741-7015
DOI	10.1186/s12916-020-01580-3
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Article ; Online: Using machine-learning risk prediction models to triage the acuity of undifferentiated patients entering the emergency care system: a systematic review.

Miles, Jamie / Turner, Janette / Jacques, Richard / Williams, Julia / Mason, Suzanne

Diagnostic and prognostic research

2020 Volume 4, Page(s) 16

Abstract: Background: The primary objective of this review is to assess the accuracy of machine learning methods in their application of triaging the acuity of patients presenting in the Emergency Care System (ECS). The population are patients that have contacted ...

Abstract	Background: The primary objective of this review is to assess the accuracy of machine learning methods in their application of triaging the acuity of patients presenting in the Emergency Care System (ECS). The population are patients that have contacted the ambulance service or turned up at the Emergency Department. The index test is a machine-learning algorithm that aims to stratify the acuity of incoming patients at initial triage. This is in comparison to either an existing decision support tool, clinical opinion or in the absence of these, no comparator. The outcome of this review is the calibration, discrimination and classification statistics. Methods: Only derivation studies (with or without internal validation) were included. MEDLINE, CINAHL, PubMed and the grey literature were searched on the 14th December 2019. Risk of bias was assessed using the PROBAST tool and data was extracted using the CHARMS checklist. Discrimination (C-statistic) was a commonly reported model performance measure and therefore these statistics were represented as a range within each machine learning method. The majority of studies had poorly reported outcomes and thus a narrative synthesis of results was performed. Results: There was a total of 92 models (from 25 studies) included in the review. There were two main triage outcomes: hospitalisation (56 models), and critical care need (25 models). For hospitalisation, neural networks and tree-based methods both had a median C-statistic of 0.81 (IQR 0.80-0.84, 0.79-0.82). Logistic regression had a median C-statistic of 0.80 (0.74-0.83). For critical care need, neural networks had a median C-statistic of 0.89 (0.86-0.91), tree based 0.85 (0.84-0.88), and logistic regression 0.83 (0.79-0.84). Conclusions: Machine-learning methods appear accurate in triaging undifferentiated patients entering the Emergency Care System. There was no clear benefit of using one technique over another; however, models derived by logistic regression were more transparent in reporting model performance. Future studies should adhere to reporting guidelines and use these at the protocol design stage. Registration and funding: This systematic review is registered on the International prospective register of systematic reviews (PROSPERO) and can be accessed online at the following URL: https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020168696This study was funded by the NIHR as part of a Clinical Doctoral Research Fellowship.
Language	English
Publishing date	2020-10-02
Publishing country	England
Document type	Journal Article
ISSN	2397-7523
ISSN (online)	2397-7523
DOI	10.1186/s41512-020-00084-1
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Article ; Online: Effects of service changes affecting distance/time to access urgent and emergency care facilities on patient outcomes

Duncan Chambers / Anna Cantrell / Susan Baxter / Janette Turner / Andrew Booth

BMC Medicine, Vol 18, Iss 1, Pp 1-

a systematic review

2020 Volume 10

Abstract: Abstract Background Reconfiguration of urgent and emergency care services often increases travel time/distance for patients to reach an appropriate facility. Evidence of the effects of reconfiguration is important for local communities and commissioners ... ...

Abstract	Abstract Background Reconfiguration of urgent and emergency care services often increases travel time/distance for patients to reach an appropriate facility. Evidence of the effects of reconfiguration is important for local communities and commissioners and providers of health services. Methods We performed a systematic review of the evidence regarding effects of service reconfigurations that increase the time/distance for some patients to reach an urgent and emergency care (UEC) facility. We searched seven bibliographic databases from 2000 to February 2019 and used citation tracking and reference lists to identify additional studies. We included studies of any design that compared outcomes for people with conditions requiring emergency treatment before and after service reconfiguration with an associated change in travel time/distance to access UEC. Studies had to be conducted in the UK or other developed countries. Data extraction and quality assessment (using the Joanna Briggs Institute checklist for quasi-experimental studies) were undertaken by a single reviewer with a sample checked for accuracy and consistency. We performed a narrative synthesis of the included studies. Overall strength of evidence was assessed using a previously published method that considers volume, quality and consistency. Results We included 12 studies, of which six were conducted in the USA, two in the UK and four in other European countries. The studies used a variety of observational designs, with before–after and cohort designs being most common. Only two studies included an independent control site/sites where no reconfiguration had taken place. The reconfigurations evaluated in these studies reported relatively small effects on average travel times/distance. Discussion For studies of general UEC populations, there was no convincing evidence as to whether reconfiguration affected mortality risk. However, evidence of increased risk was identified from studies of patients with acute myocardial infarction, particularly 1 to 4 years ...
Keywords	Ambulance services ; Distance to care ; Emergency care ; Emergency departments ; Service reconfiguration ; Systematic review ; Medicine ; R
Subject code	310
Language	English
Publishing date	2020-05-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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