Patient compliance with NHS 111 advice: Analysis of adult call and ED attendance data 2013-2017

Correction: Patient compliance with NHS 111 advice: Analysis of adult call and ED attendance data 2013-2017

[This corrects the article DOI: 10.1371/journal.pone.0251362.].

An analysis of NHS 111 demand for primary care services: A retrospective cohort study

The NHS 111 service triages over 16,650,745 calls per year and approximately 48% of callers are triaged to a primary care disposition, such as a telephone appointment with a general practitioner (GP). However, there has been little assessment of the ability of primary care services to meet this demand. If a timely service cannot be provided to patients, it could result in patients calling 999 or attending emergency departments (ED) instead. This study aimed to explore the patient journey for callers who were triaged to a primary care disposition, and the ability of primary care services to meet this demand. We obtained routine, retrospective data from the Connected Yorkshire research database, and identified all 111 calls between the 1st January 2021 and 31st December 2021 for callers registered with a GP in the Bradford or Airedale region of West Yorkshire, who were triaged to a primary care disposition. Subsequent healthcare system access (111, 999, primary and secondary care) in the 72 hours following the index 111 call was identified, and a descriptive analysis of the healthcare trajectory of patients was undertaken. There were 56,102 index 111 calls, and a primary care service was the first interaction in 26,690/56,102 (47.6%) of cases, with 15,470/26,690 (58%) commenced within the specified triage time frame. Calls to 999 were higher in the cohort who had no prior contact with primary care (58% vs 42%) as were ED attendances (58.2% vs 41.8), although the proportion of avoidable ED attendances was similar (10.5% vs 11.8%). Less than half of 111 callers triaged to a primary care disposition make contact with a primary care service, and even when they do, call triage time frames are frequently not met, suggesting that current primary care provision cannot meet the demand from 111.

Descriptive analysis and evaluation of Health Link referrals to the emergency department before and during the COVID-19 pandemic

BACKGROUND

In Alberta, Health Link (HL) provides a 24-h, nurse-staffed, phone resource to the public for health-care advice. HL directs callers to either seek care in the emergency department (ED), with a primary care provider or provide self-care at home. This work aims to describe HL ED referrals prior to and during the COVID-19 pandemic.

METHODS

Data from January 1, 2018-December 31, 2019, and July 1, 2020-June 30, 2022, were selected. HL calls were categorized as likely appropriate if the patient was referred and presented to the ED within 24 h and had a Canadian Triage and Acuity Scale (CTAS) of 1-3; or a CTAS of 4-5 and the patient was admitted, specialist consulted, or diagnostic imaging or laboratory tests were completed. The primary outcome was the percentage of likely appropriate referrals among all HL ED referrals.

RESULTS

In the 2018-2019 and 2020-2022 samples, respectively, there were 845,372 and 832,730 calls. Of the 211,723 and 213,486 ED referrals, only 140,614 (66.4%) and 143,322 (67.1%) presented to an ED. Of these, 84.3 and 86.7 per 100 patient visits were categorized as likely appropriate referrals. Health Link referrals account for 3.2% and 3.8% of all ED visits.

IMPACT

HL referrals to the ED represent only a small percentage of all ED visits. Based on our definition, most referrals by HL are likely appropriate. The COVID-19 pandemic does not appear to have altered the rates of calls to HL, the number of HL calls referred to the ED, nor the likely appropriateness of those referrals.

Modelling NHS England 111 demand for primary care services: a discrete event simulation

OBJECTIVES

This feasibility study aimed to model in silico the current healthcare system for patients triaged to a primary care disposition following a call to National Health Service (NHS) 111 and determine the effect of reconfiguring the healthcare system to ensure a timely primary care service contact.

DESIGN

Discrete event simulation.

SETTING

Single English NHS 111 call centre in Yorkshire.

PARTICIPANTS

Callers registered with a Bradford general practitioner who contacted the NHS 111 service in 2021 and were triaged to a primary care disposition.

PRIMARY AND SECONDARY OUTCOME MEASURES

Face validity of conceptual model. Comparison between real and simulated data for quarterly counts (and 95% CIs) for patient contact with emergency ambulance (999), 111, and primary and secondary care services. Mean difference and 95% CIs in healthcare system usage between simulations and difference in mean proportion of avoidable admissions for callers who presented to an emergency department (ED).

RESULTS

The simulation of the current system estimated that there would be 39 283 (95% CI 39 237 to 39 328) primary care contacts, 2042 (95% CI 2032 to 2051) 999 calls and 1120 (95% CI 1114 to 1127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean percentage increase of 196.1% (95% CI 192.2% to 199.9%) in primary care contacts, and a mean percentage decrease of 78.0% (95% CI 69.8% to 86.2%) in 999 calls and 88.1% (95% CI 81.7% to 94.5%) in ED attendances. Avoidable ED attendances reduced by a mean of -26 (95% CI -35 to -17).

CONCLUSION

In this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost-effective and acceptable to both patients and primary care clinicians.

A multimethod study of NHS 111 online

Background

NHS 111 online offers 24-hour access to health assessment and triage.

Objectives

This study examined pathways to care, differential access and use, and workforce impacts of NHS 111 online. This study compared NHS 111 with Healthdirect (Haymarket, Australia) virtual triage.

Design

Interviews with 80 staff and stakeholders in English primary, urgent and emergency care, and 41 staff and stakeholders associated with Healthdirect. A survey of 2754 respondents, of whom 1137 (41.3%) had used NHS 111 online and 1617 (58.7%) had not.

Results

NHS 111 online is one of several digital health-care technologies and was not differentiated from the NHS 111 telephone service or well understood. There is a similar lack of awareness of Healthdirect virtual triage. NHS 111 and Healthdirect virtual triage are perceived as creating additional work for health-care staff and inappropriate demand for some health services, especially emergency care. One-third of survey respondents reported that they had not used any NHS 111 service (telephone or online). Older people and those with less educational qualifications are less likely to use NHS 111 online. Respondents who had used NHS 111 online reported more use of other urgent care services and make more cumulative use of services than those who had not used NHS 111 online. Users of NHS 111 online had higher levels of self-reported eHealth literacy. There were differences in reported preferences for using NHS 111 online for different symptom presentations.

Conclusions

Greater clarity about what the NHS 111 online service offers would allow better signposting and reduce confusion. Generic NHS 111 services are perceived as creating additional work in the primary, urgent and emergency care system. There are differences in eHealth literacy between users and those who have not used NHS 111 online, and this suggests that 'digital first' policies may increase health inequalities.

Limitations

This research bridged the pandemic from 2020 to 2021; therefore, findings may change as services adjust going forward. Surveys used a digital platform so there is probably bias towards some level of e-Literacy, but this also means that our data may underestimate the digital divide.

Future work

Further investigation of access to digital services could address concerns about digital exclusion. Research comparing the affordances and cost-benefits of different triage and assessment systems for users and health-care providers is needed. Research about trust in virtual assessments may show how duplication can be reduced. Mixed-methods studies looking at outcomes, impacts on work and costs, and ways to measure eHealth literacy, can inform the development NHS 111 online and opportunities for further international shared learning could be pursued.

Study registration

This study is registered at the research registry (UIN 5392).

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research Programme and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. 5. See the NIHR Journals Library website for further project information.

Impact of Health Link utilization on emergency department visits

OBJECTIVES

Our aim was to compare Health Link utilization in urban and rural Alberta by metrics relevant to the ED.

METHODS

Data on Health Link callers from January 1, 2018-December 31, 2019 was extracted from the National Ambulatory Care Reporting System, including postal code, location of ED attended, Canadian Triage Acuity Scale (CTAS) assigned at ED, age, and self-identified gender. Usage density (presentations/100/year), patient demographics (age, self-identified gender), and ED metrics (CTAS, investigations, admission) were compared for Health Link ED referrals and direct ED visits.

RESULTS

In this period, 900,196 individuals called Health Link, 241,103 were referred to the ED, 58% (140,614) of which presented to the ED within 24 h of their call. These referrals constituted 3.4% of the total ED visit population (4,194,735). Looking at the density of ED utilization, this is greater in rural than urban settings with respect to patients who present directly to the ED (90.9 vs. 36.5 presentations/100/year). There is a sparser density of Health Link ED visits in rural settings than in urban centres (1.5 vs. 1.6). Urban ED presentations were more often triaged as a CTAS 1-3 than a CTAS 4-5 if they had presented after a Health Link referral (76.0% CTAS 1-3) than a direct ED visit (63.0% CTAS 1-3). This effect is greater for rural patients, who also more likely to present as a CTAS 1-3 than a CTAS 4-5 if they were referred through Health Link (61.1% CTAS 1-3) compared to those who directly went to the ED (39.0% CTAS 1-3).

CONCLUSIONS

This study on Health Link describes how tele-health can often triage higher acuity patients to appropriately receive ED level care, which may be important for future development of health care and ED infrastructure.

Factors associated with longer wait times, admission and reattendances in older patients attending emergency departments: an analysis of linked healthcare data

BACKGROUND AND OBJECTIVE

Care for older patients in the ED is an increasingly important issue with the ageing society. To better assess the quality of care in this patient group, we assessed predictors for three outcomes related to ED care: being seen and discharged within 4 hours of ED arrival; being admitted from ED to hospital and reattending the ED within 30 days. We also used these outcomes to identify better-performing EDs.

METHODS

The CUREd Research Database was used for a retrospective observational study of all 1 039 251 attendances by 368 754 patients aged 75+ years in 18 type 1 EDs in the Yorkshire and the Humber region of England between April 2012 and March 2017. We estimated multilevel logit models, accounting for patients' characteristics and contact with emergency services prior to ED arrival, time variables and the ED itself.

RESULTS

Patients in the oldest category (95+ years vs 75-80 years) were more likely to have a long ED wait (OR=1.13 (95% CI=1.10 to 1.15)), hospital admission (OR=1.26 (95% CI=1.23 to 1.29)) and ED reattendance (OR=1.09 (95% CI=1.06 to 1.12)). Those who had previously attended (3+ vs 0 previous attendances) were more likely to have long wait (OR=1.07 (95% CI=1.06 to 1.08)), hospital admission (OR=1.10 (95% CI=1.09 to 1.12)) and ED attendance (OR=3.13 (95% CI=3.09 to 3.17)). Those who attended out of hours (vs not out of hours) were more likely to have a long ED wait (OR=1.33 (95% CI=1.32 to 1.34)), be admitted to hospital (OR=1.19 (95% CI=1.18 to 1.21)) and have ED reattendance (OR=1.07 (95% CI=1.05 to 1.08)). Those living in less deprived decile (vs most deprived decile) were less likely to have any of these three outcomes: OR=0.93 (95% CI=0.92 to 0.95), 0.92 (95% CI=0.90 to 0.94), 0.86 (95% CI=0.84 to 0.88). These characteristics were not strongly associated with long waits for those who arrived by ambulance. Emergency call handler designation was the strongest predictor of long ED waits and hospital admission: compared with those who did not arrive by ambulance; ORs for these outcomes were 1.18 (95% CI=1.16 to 1.20) and 1.85 (95% CI=1.81 to 1.89) for those designated less urgent; 1.37 (95% CI=1.33 to 1.40) and 2.13 (95% CI=2.07 to 2.18) for urgent attendees; 1.26 (95% CI=1.23 to 1.28) and 2.40 (95% CI=2.36 to 2.45) for emergency attendees; and 1.37 (95% CI=1.28 to 1.45) and 2.42 (95% CI=2.26 to 2.59) for those with life-threatening conditions. We identified two EDs whose patients were less likely to have a long ED, hospital admission or ED reattendance than other EDs in the region.

CONCLUSIONS

Age, previous attendance and attending out of hours were all associated with an increased likelihood of exceeding 4 hours in the ED, hospital admission and reattendance among patients over 75 years. These differences were less pronounced among those arriving by ambulance. Emergency call handler designation could be used to identify those at the highest risk of long ED waits, hospital admission and ED reattendance.

Use of urgent, emergency and acute care by mental health service users: A record-level cohort study

BACKGROUND

People with serious mental illness experience worse physical health and greater mortality than the general population. Crude rates of A&E attendance and acute hospital admission are higher in people with serious mental illness than other hospital users. We aimed to further these findings by undertaking a standardised comparison of urgent and emergency care pathway use among users of mental health services and the general population.

METHODS

Retrospective cohort analysis using routine data from 2013-2016 from the CUREd dataset for urgent and emergency care contacts (NHS 111, ambulance, A&E and acute admissions) and linked mental health trust data for Sheffield, England. We compared annual age- and sex-standardised usage rates for each urgent and emergency care service between users of mental health services and those without a recent history of mental health service use.

RESULTS

We found marked differences in usage rates for all four urgent and emergency care services between the general population and users of mental health services. Usage rates and the proportion of users were 5-6 times and 3-4 times higher in users of mental health services, respectively, for all urgent and emergency care services. Users of mental health services were often more likely to experience the highest or lowest acuity usage characteristics.

CONCLUSIONS

Current users of mental health services were heavily over-represented among urgent and emergency care users, and they made more contacts per-person. Higher service use among users of mental health services could be addressed by improved community care, more integrated physical and mental health support, and more proactive primary care. A complex pattern of service use among users of mental health services suggests this will need careful targeting to reduce avoidable contacts and optimise patient outcomes.

Online Symptom Checkers: Recommendations for a Vignette-Based Clinical Evaluation Standard

The use of patient-facing online symptom checkers (OSCs) has expanded in recent years, but their accuracy, safety, and impact on patient behaviors and health care systems remain unclear. The lack of a standardized process of clinical evaluation has resulted in significant variation in approaches to OSC validation and evaluation. The aim of this paper is to characterize a set of congruent requirements for a standardized vignette-based clinical evaluation process of OSCs. Discrepancies in the findings of comparative studies to date suggest that different steps in OSC evaluation methodology can significantly influence outcomes. A standardized process with a clear specification for vignette-based clinical evaluation is urgently needed to guide developers and facilitate the objective comparison of OSCs. We propose 15 recommendation requirements for an OSC evaluation standard. A third-party evaluation process and protocols for prospective real-world evidence studies should also be prioritized to quality assure OSC assessment.

Measuring the impact introducing NHS 111 online had on the NHS 111 telephone service and the wider NHS urgent care system: an observational study

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.

Creating a Real-World Linked Research Platform for Analyzing the Urgent and Emergency Care System

Background

This article describes the development of a system-based data platform for research developed to provide a detailed picture of the characteristics of the Urgent and Emergency Care system in 1 region of the United Kingdom.

Data Set Development

CUREd is an integrated research data platform that describes the urgent and emergency care system in 1 region of the United Kingdom on almost 30 million patient contacts within the system. We describe regulatory approvals required, data acquisition, cleaning, and linkage.

Data Set Analyses

The data platform covers 2011 to 2017 for 14 acute National Health Service (NHS) Hospital Trusts, 1 ambulance service, the national telephone advice service (NHS 111), and 19 emergency departments. We describe 3 analyses undertaken: 1) Analyzing triage patterns from the NHS 111 telephone helpline using routine data linked to other urgent care services, we found that the current triage algorithms have high rates of misclassifying calls. 2) Applying an algorithm to consistently identify avoidable attendances for pediatric patients, we identified 21% of pediatric attendances to the emergency department as avoidable. 3) Using complex systems analysis to examine patterns of frequent attendance in urgent care, we found that frequent attendance is stable over time but varies by individual patient. This implies that frequent attendance is more likely to be a function of the system overall.

Discussion

We describe the processes necessary to produce research-ready data that link care across the components of the urgent and emergency care system. Making the use of routine data commonplace will require partnership between the collectors, owners, and guardians of the data and researchers and technical teams.

Highlights

To what extent do callers follow the advice given by a non-emergency medical helpline (NHS 111): A retrospective cohort study

National Health Service (NHS) 111 helpline was set up to improve access to urgent care in England, efficiency and cost-effectiveness of first-contact health services. Following trusted, authoritative advice is crucial for improved clinical outcomes. We examine patient and call-related characteristics associated with compliance with advice given in NHS 111 calls. The importance of health interactions that are not face-to-face has recently been highlighted by COVID-19 pandemic. In this retrospective cohort study, NHS 111 call records were linked to urgent and emergency care services data. We analysed data of 3,864,362 calls made between October 2013 and September 2017 relating to 1,964,726 callers across London. A multiple logistic regression was used to investigate associations between compliance with advice given and patient and call characteristics. Caller’s action is ‘compliant with advice given if first subsequent service interaction following contact with NHS 111 is consistent with advice given. We found that most calls were made by women (58%), adults aged 30–59 years (33%) and people in the white ethnic category (36%). The most common advice was for caller to contact their General Practitioner (GP) or other local services (18.2%) with varying times scales. Overall, callers followed advice given in 49% of calls. Compliance with triage advice was more likely in calls for children aged <16 years, women, those from Asian/Asian British ethnicity, and calls made out of hours. The highest compliance was among callers advised to self-care without the need to contact any other healthcare service. This is one of the largest studies to describe pathway adherence following telephone advice and associated clinical and demographic features. These results could inform attempts to improve caller compliance with advice given by NHS 111, and as the NHS moves to more hybrid way of working, the lessons from this study are key to the development of remote healthcare services going forward.

Safety of Triage Self-assessment Using a Symptom Assessment App for Walk-in Patients in the Emergency Care Setting: Observational Prospective Cross-sectional Study

Background

Increasing use of emergency departments (EDs) by patients with low urgency, combined with limited availability of medical staff, results in extended waiting times and delayed care. Technological approaches could possibly increase efficiency by providing urgency advice and symptom assessments.

Objective

The purpose of this study is to evaluate the safety of urgency advice provided by a symptom assessment app, Ada, in an ED.

Methods

The study was conducted at the interdisciplinary ED of Marburg University Hospital, with data collection performed between August 2019 and March 2020. This study had a single-center cross-sectional prospective observational design and included 378 patients. The app’s urgency recommendation was compared with an established triage concept (Manchester Triage System [MTS]), including patients from the lower 3 MTS categories only. For all patients who were undertriaged, an expert physician panel assessed the case to detect potential avoidable hazardous situations (AHSs).

Results

Of 378 participants, 344 (91%) were triaged the same or more conservatively and 34 (8.9%) were undertriaged by the app. Of the 378 patients, 14 (3.7%) had received safe advice determined by the expert panel and 20 (5.3%) were considered to be potential AHS. Therefore, the assessment could be considered safe in 94.7% (358/378) of the patients when compared with the MTS assessment. From the 3 lowest MTS categories, 43.4% (164/378) of patients were not considered as emergency cases by the app, but could have been safely treated by a general practitioner or would not have required a physician consultation at all.

Conclusions

The app provided urgency advice after patient self-triage that has a high rate of safety, a rate of undertriage, and a rate of triage with potential to be an AHS, equivalent to telephone triage by health care professionals while still being more conservative than direct ED triage. A large proportion of patients in the ED were not considered as emergency cases, which could possibly relieve ED burden if used at home. Further research should be conducted in the at-home setting to evaluate this hypothesis.

Trial Registration

German Clinical Trial Registration DRKS00024909; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00024909

Non-urgent emergency department attendances in children: a retrospective observational analysis

Introduction

A significant proportion of ED attendances in children may be non-urgent attendances (NUAs), which could be better managed elsewhere. This study aimed to quantify NUAs and urgent attendances (UAs) in children to ED and determine which children present in this way and when.

Methods

Dataset extracted from the CUREd research database containing linked data on the provision of care in Yorkshire and Humber. Analysis focused on children’s ED attendances (April 2014–March 2017). Summary statistics and odds ratios (OR) comparing NUAs and UAs were examined by: age, mode and time of arrival and deprivation alongside comparing summary statistics for waiting, treatment and total department times.

Results

NUAs were more likely in younger children: OR for NUA in children aged 1–4 years, 0.82 (95% CI: 0.80 to 0.83), age 15 years, 0.39 (95% CI: 0.38 to 0.40), when compared with those under 1 year. NUAs were more likely to arrive out of hours (OOHs) compared with in hours: OR 1.19 (95% CI 1.18 to 1.20), and OOHs arrivals were less common in older children compared with those under 1 year: age 1–4 years, 0.87 (95% CI: 0.84 to 0.89) age 15 years, 0.66 (95% CI: 0.63 to 0.69). NUAs also spent less total time in the ED, with a median (IQR) of 98 min (60–147) compared with 127 min (80–185) for UAs.

Conclusion

A substantial proportion of ED attendances in children are NUAs. Our data suggest there are particular groups of children for whom targeted interventions would be most beneficial. Children under 5 years would be such a group, particularly in providing accessible, timely care outside of usual community care opening hours.