Emergency admission risk stratification tools in UK primary care: a cross-sectional survey of availability and use

Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation

OBJECTIVES

Risk stratification tools that predict healthcare utilisation are extensively integrated into primary care systems worldwide, forming a key component of anticipatory care pathways, where high-risk individuals are targeted by preventative interventions. Existing work broadly focuses on comparing model performance in retrospective cohorts with little attention paid to efficacy in reducing morbidity when deployed in different global contexts. We review the evidence supporting the use of such tools in real-world settings, from retrospective dataset performance to pathway evaluation.

METHODS

A systematic search was undertaken to identify studies reporting the development, validation and deployment of models that predict healthcare utilisation in unselected primary care cohorts, comparable to their current real-world application.

RESULTS

Among 3897 articles screened, 51 studies were identified evaluating 28 risk prediction models. Half underwent external validation yet only two were validated internationally. No association between validation context and model discrimination was observed. The majority of real-world evaluation studies reported no change, or indeed significant increases, in healthcare utilisation within targeted groups, with only one-third of reports demonstrating some benefit.

DISCUSSION

While model discrimination appears satisfactorily robust to application context there is little evidence to suggest that accurate identification of high-risk individuals can be reliably translated to improvements in service delivery or morbidity.

CONCLUSIONS

The evidence does not support further integration of care pathways with costly population-level interventions based on risk prediction in unselected primary care cohorts. There is an urgent need to independently appraise the safety, efficacy and cost-effectiveness of risk prediction systems that are already widely deployed within primary care.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

Developing Implementation Strategies to Support the Uptake of a Risk Tool to Aid Physicians in the Clinical Management of Patients With Syncope: Systematic Theoretical and User-Centered Design Approach

BACKGROUND

The Canadian Syncope Risk Score (CSRS) was developed to improve syncope management in emergency department settings. Evidence-based tools often fail to have the intended impact because of suboptimal uptake or poor implementation.

OBJECTIVE

In this paper, we aimed to describe the process of developing evidence-based implementation strategies to support the deployment and use of the CSRS in real-world emergency department settings to improve syncope management among physicians.

METHODS

We followed a systematic approach for intervention development, including identifying who needs to do what differently, identifying the barriers and enablers to be addressed, and identifying the intervention components and modes of delivery to overcome the identified barriers. We used the Behaviour Change Wheel to guide the selection of implementation strategies. We engaged CSRS end users (ie, emergency medicine physicians) in a user-centered design approach to generate and refine strategies. This was achieved over a series of 3 qualitative user-centered design workshops lasting 90 minutes each with 3 groups of emergency medicine physicians.

RESULTS

A total of 14 physicians participated in the workshops. The themes were organized according to the following intervention development steps: theme 1-identifying and refining barriers and theme 2-identifying the intervention components and modes of delivery. Theme 2 was subdivided into two subthemes: (1) generating high-level strategies and developing strategies prototypes and (2) refining and testing strategies. The main strategies identified to overcome barriers included education in the format of meetings, videos, journal clubs, and posters (to address uncertainty around when and how to apply the CSRS); the development of a web-based calculator and integration into the electronic medical record (to address uncertainty in how to apply the CSRS); a local champion (to address the lack of team buy-in); and the dissemination of evidence summaries and feedback through email communications (to address a lack of evidence about impact).

CONCLUSIONS

The ability of the CSRS to effectively improve patient safety and syncope management relies on broad buy-in and uptake across physicians. To ensure that the CSRS is well positioned for impact, a comprehensive suite of strategies was identified to address known barriers.

Is bureaucracy being busted in research ethics and governance for health services research in the UK? Experiences and perspectives reported by stakeholders through an online survey

BACKGROUND

It has long been noted that the chain from identification of need (research gap) to impact in the real world is both long and tortuous. This study aimed to contribute evidence about research ethics and governance arrangements and processes in the UK with a focus on: what works well; problems; impacts on delivery; and potential improvements.

METHODS

Online questionnaire widely distributed 20th May 2021, with request to forward to other interested parties. The survey closed on 18th June 2021. Questionnaire included closed and open questions related to demographics, role, study objectives.

RESULTS

Responses were received from 252 respondents, 68% based in universities 25% in the NHS. Research methods used by respondents included interviews/focus groups (64%); surveys/questionnaires (63%); and experimental/quasi experimental (57%). Respondents reported that participants in the research they conducted most commonly included: patients (91%); NHS staff (64%) and public (50%). Aspects of research ethics and governance reported to work well were: online centralised systems; confidence in rigorous, respected systems; and helpful staff. Problems with workload, frustration and delays were reported, related to overly bureaucratic, unclear, repetitive, inflexible and inconsistent processes. Disproportionality of requirements for low-risk studies was raised across all areas, with systems reported to be risk averse, defensive and taking little account of the risks associated with delaying or deterring research. Some requirements were reported to have unintended effects on inclusion and diversity, particularly impacting Patient and Public Involvement (PPI) and engagement processes. Existing processes and requirements were reported to cause stress and demoralisation, particularly as many researchers are employed on fixed term contracts. High negative impacts on research delivery were reported, in terms of timescales for completing studies, discouraging research particularly for clinicians and students, quality of outputs and costs. Suggested improvements related to system level changes / overall approach and specific refinements to existing processes.

CONCLUSIONS

Consultation with those involved in Health Services Research in the UK revealed a picture of overwhelming and increasing bureaucracy, delays, costs and demoralisation related to gaining the approvals necessary to conduct research in the NHS. Suggestions for improvement across all three areas focused on reducing duplication and unnecessary paperwork/form filling and reaching a better balance between risks of harm through research and harms which occur because research to inform practice is delayed or deterred.

Implementing emergency admission risk prediction in general practice: a qualitative study

Background

Using computer software in general practice to predict patient risk of emergency hospital admission has been widely advocated, despite limited evidence about effects. In a trial evaluating the introduction of a Predictive Risk Stratification Model (PRISM), statistically significant increases in emergency hospital admissions and use of other NHS services were reported without evidence of benefits to patients or the NHS.

Aim

To explore GPs’ and practice managers’ experiences of incorporating PRISM into routine practice.

Design and setting

Semi-structured interviews were carried out with GPs and practice managers in 18 practices in rural, urban, and suburban areas of south Wales.

Method

Interviews (30–90 min) were conducted at 3–6 months after gaining PRISM access, and ∼18 months later. Data were analysed thematically using Normalisation Process Theory.

Results

Responders (n = 22) reported that the decision to use PRISM was based mainly on fulfilling Quality and Outcomes Framework incentives. Most applied it to <0.5% practice patients over a few weeks. Using PRISM entailed undertaking technical tasks, sharing information in practice meetings, and making small-scale changes to patient care. Use was inhibited by the model not being integrated with practice systems. Most participants doubted any large-scale impact, but did cite examples of the impact on individual patient care and reported increased awareness of patients at high risk of emergency admission to hospital.

Conclusion

Qualitative results suggest mixed views of predictive risk stratification in general practice and raised awareness of highest-risk patients potentially affecting rates of unplanned hospital attendance and admissions. To inform future policy, decision makers need more information about implementation and effects of emergency admission risk stratification tools in primary and community settings.