Exploration of understanding of impactibility analysis and application through workshops to inform model design for population health management policy: a qualitative assessment.

OBJECTIVES: Assess understanding of impactibility modelling definitions, benefits, challenges and approaches. DESIGN: Qualitative assessment. SETTING: Two workshops were developed. Workshop 1 was to consider impactibility definitions and terminology through moderated open discussion, what the potential pros and cons might be, and what factors would be best to assess. In workshop 2, participants appraised five approaches to impactibility modelling identified in the literature. PARTICIPANTS: National Health Service (NHS) analysts, policy-makers, academics and members of non-governmental think tank organisations identified through existing networks and via a general announcement on social media. Interested participants could enrol after signing informed consent. OUTCOME MEASURES: Descriptive assessment of responses to gain understanding of the concept of impactibility (defining impactibility analysis), the benefits and challenges of using this type of modelling and most relevant approach to building an impactibility model for the NHS. RESULTS: 37 people attended 1 or 2 workshops in small groups (maximum 10 participants): 21 attended both workshops, 6 only workshop 1 and 10 only workshop 2. Discussions in workshop 1 illustrated that impactibility modelling is not clearly understood, with it generally being viewed as a cross-sectional way to identify patients rather than considering patients by iterative follow-up. Recurrent factors arising from workshop 2 were the shortage of benchmarks; incomplete access to/recording of primary care data and social factors (which were seen as important to understanding amenability to treatment); the need for outcome/action suggestions as well as providing the data and the risk of increasing healthcare inequality. CONCLUSIONS: Understanding of impactibility modelling was poor among our workshop attendees, but it is an emerging concept for which few studies have been published. Implementation would require formal planning and training and should be performed by groups with expertise in the procurement and handling of the most relevant health-related real-world data.

Modifiable risk factors that may be addressed in routine care to prevent progression to and extension of multimorbidity in people with COPD: a systematic literature review.

Chronic obstructive pulmonary disease (COPD) is a multisystem disease, and many patients have multiple conditions. We explored multimorbidity patterns that might inform intervention planning to reduce health-care costs while preserving quality of life for patients. Literature searches up to February 2022 revealed 4419 clinical observational and comparative studies of risk factors for multimorbidity in people with COPD, pulmonary emphysema, or chronic bronchitis at baseline. Of these, 29 met the inclusion criteria for this review. Eight studies were cluster and network analyses, five were regression analyses, and 17 (in 16 papers) were other studies of specific conditions, physical activity and treatment. People with COPD more frequently had multimorbidity and had up to ten times the number of disorders of those without COPD. Disease combinations prominently featured cardiovascular and metabolic diseases, asthma, musculoskeletal and psychiatric disorders. An important risk factor for multimorbidity was low socioeconomic status. One study showed that many patients were receiving multiple drugs and had increased risk of adverse events, and that 10% of medications prescribed were inappropriate. Many patients with COPD have mainly preventable or modifiable multimorbidity. A proactive multidisciplinary approach to prevention and management could reduce the burden of care.

Clinical, humanistic and economic outcomes, including experiencing of patient safety events, associated with admitting patients to single rooms compared with shared accommodation for acute hospital admissions: a systematic review and narrative synthesis.

OBJECTIVES: Assess the impact of single rooms versus multioccupancy accommodation on inpatient healthcare outcomes and processes. DESIGN: Systematic review and narrative synthesis. DATA SOURCES: Medline, Embase, Google Scholar and the National Institute for Health and Care Excellence website up to 17 February 2022. ELIGIBILITY CRITERIA: Eligible papers assessed the effect on inpatients staying in hospital of being assigned to a either a single room or shared accommodation, except where that assignment was for a direct clinical reason like preventing infection spread. DATA EXTRACTION AND SYNTHESIS: Data were extracted and synthesised narratively, according to the methods of Campbell et al. RESULTS: Of 4861 citations initially identified, 145 were judged to be relevant to this review. Five main method types were reported. All studies had methodological issues that potentially biased the results by not adjusting for confounding factors that are likely to have contributed to the outcomes. Ninety-two papers compared clinical outcomes for patients in single rooms versus shared accommodation. No clearly consistent conclusions could be drawn about overall benefits of single rooms. Single rooms were most likely to be associated with a small overall clinical benefit for the most severely ill patients, especially neonates in intensive care. Patients who preferred single rooms tended to do so for privacy and for reduced disturbances. By contrast, some groups were more likely to prefer shared accommodation to avoid loneliness. Greater costs associated with building single rooms were small and likely to be recouped over time by other efficiencies. CONCLUSIONS: The lack of difference between inpatient accommodation types in a large number of studies suggests that there would be little effect on clinical outcomes, particularly in routine care. Patients in intensive care areas are most likely to benefit from single rooms. Most patients preferred single rooms for privacy and some preferred shared accommodation for avoiding loneliness. PROSPERO REGISTRATION NUMBER: CRD42022311689.

Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients.

AIMS: We investigated whether the use of an atrial fibrillation (AF) risk prediction algorithm could improve AF detection compared with opportunistic screening in primary care and assessed the associated budget impact. METHODS AND RESULTS: Eligible patients were registered with a general practice in UK, aged 65 years or older in 2018/19, and had complete data for weight, height, body mass index, and systolic and diastolic blood pressure recorded within 1 year. Three screening scenarios were assessed: (i) opportunistic screening and diagnosis (standard care); (ii) standard care replaced by the use of the algorithm; and (iii) combined use of standard care and the algorithm. The analysis considered a 3-year time horizon, and the budget impact for the National Health Service (NHS) costs alone or with personal social services (PSS) costs. Scenario 1 would identify 79 410 new AF cases (detection gap reduced by 22%). Scenario 2 would identify 70 916 (gap reduced by 19%) and Scenario 3 would identify 99 267 new cases (gap reduction 27%). These rates translate into 2639 strokes being prevented in Scenario 1, 2357 in Scenario 2, and 3299 in Scenario 3. The 3-year NHS budget impact of Scenario 1 would be £45.3 million, £3.6 million (difference ‒92.0%) with Scenario 2, and £46.3 million (difference 2.2%) in Scenario 3, but for NHS plus PSS would be ‒£48.8 million, ‒£80.4 million (64.8%), and ‒£71.3 million (46.1%), respectively. CONCLUSION: Implementation of an AF risk prediction algorithm alongside standard opportunistic screening could close the AF detection gap and prevent strokes while substantially reducing NHS and PSS combined care costs.

Bridging the impactibility gap in population health management: a systematic review.

OBJECTIVES: Assess whether impactibility modelling is being used to refine risk stratification for preventive health interventions. DESIGN: Systematic review. SETTING: Primary and secondary healthcare populations. PAPERS: Articles published from 2010 to 2020 on the use or implementation of impactibility modelling in population health management, reported with the terms 'intervenability', 'amenability', and 'propensity to succeed' (PTS) and associated with the themes 'care sensitivity', 'characteristic responders', 'needs gap', 'case finding', 'patient selection' and 'risk stratification'. INTERVENTIONS: Qualitative synthesis to identify themes for approaches to impactibility modelling. RESULTS: Of 1244 records identified, 20 were eligible for inclusion. Identified themes were 'health conditions amenable to care' (n=6), 'PTS modelling' (n=8) and 'comparison or combination with clinical judgement' (n=6). For the theme 'health conditions amenable to care', changes in practice did not reduce admissions, particularly for ambulatory care sensitive conditions, and sometimes increased them, with implementation noted as a possible issue. For 'PTS modelling', high costs and needs did not necessarily equate to high impactibility and targeting a larger number of individuals with disorders associated with lower costs had more potential. PTS modelling seemed to improve accuracy in care planning, estimation of cost savings, engagement and/or care quality. The 'comparison or combination with clinical judgement' theme suggested that models can reach reasonable to good discriminatory power to detect impactable patients. For instance, a model used to identify patients appropriate for proactive multimorbid care management showed good concordance with physicians (c-statistic 0.75). Another model employing electronic health record scores reached 65% concordance with nurse and physician decisions when referring elderly hospitalised patients to a readmission prevention programme. However, healthcare professionals consider much wider information that might improve or impede the likelihood of treatment impact, suggesting that complementary use of models might be optimum. CONCLUSIONS: The efficiency and equity of targeted preventive care guided by risk stratification could be augmented and personalised by impactibility modelling.

Reasons for discontinuing oral anticoagulation therapy for atrial fibrillation: a systematic review.

INTRODUCTION: Atrial fibrillation (AF) is the most common cardiac arrhythmia and can lead to significant comorbidities and mortality. Persistence with oral anticoagulation (OAC) is crucial to prevent stroke but rates of discontinuation are high. This systematic review explored underlying reasons for OAC discontinuation. METHODS: A systematic review was undertaken to identify studies that reported factors influencing discontinuation of OAC in AF, in 11 databases, grey literature and backwards citations from eligible studies published between 2000 and 2019. Two reviewers independently screened titles, abstracts and papers against inclusion criteria and extracted data. Study quality was appraised using Gough's weight of evidence framework. Data were synthesised narratively. RESULTS: Of 6,619 sources identified, 10 full studies and 2 abstracts met the inclusion criteria. Overall, these provided moderate appropriateness to answer the review question. Four reported clinical registry data, six were retrospective reviews of patients' medical records and two studies reported interviews and surveys. Nine studies evaluated outcomes relating to dabigatran and/or warfarin and three included rivaroxaban (n = 3), apixaban (n = 3) and edoxaban (n = 1). Bleeding complications and gastrointestinal events were the most common factors associated with discontinuation, followed by frailty and risk of falling. Patients' perspectives were seldom specifically assessed. Influence of family carers in decisions regarding OAC discontinuation was not examined. CONCLUSION: The available evidence is derived from heterogeneous studies with few relevant data for the newer direct oral anticoagulants. Reasons underpinning decision-making to discontinue OAC from the perspective of patients, family carers and clinicians is poorly understood.

Clinical and budget impacts of changes in oral anticoagulation prescribing for atrial fibrillation.

OBJECTIVE: To assess temporal clinical and budget impacts of changes in atrial fibrillation (AF)-related prescribing in England. METHODS: Data on AF prevalence, AF-related stroke incidence and prescribing for all National Health Service general practices, hospitals and registered patients with hospitalised AF-related stroke in England were obtained from national databases. Stroke care costs were based on published data. We compared changes in oral anticoagulation prescribing (warfarin or direct oral anticoagulants (DOACs)), incidence of hospitalised AF-related stroke, and associated overall and per-patient costs in the periods January 2011-June 2014 and July 2014-December 2017. RESULTS: Between 2011-2014 and 2014-2017, recipients of oral anticoagulation for AF increased by 86.5% from 1 381 170 to 2 575 669. The number of patients prescribed warfarin grew by 16.1% from 1 313 544 to 1 525 674 and those taking DOACs by 1452.7% from 67 626 to 1 049 995. Prescribed items increased by 5.9% for warfarin (95% CI 2.9% to 8.9%) but by 2004.8% for DOACs (95% CI 1848.8% to 2160.7%). Oral anticoagulation prescription cost rose overall by 781.2%, from £87 313 310 to £769 444 028, (£733,466,204 with warfarin monitoring) and per patient by 50.7%, from £293 to £442, giving an incremental cost of £149. Nevertheless, as AF-related stroke incidence fell by 11.3% (95% CI -11.5% to -11.1%) from 86 467 in 2011-2014 to 76 730 in 2014-2017 with adjustment for AF prevalence, the overall per-patient cost reduced from £1129 to £840, giving an incremental per-patient saving of £289. CONCLUSIONS: Despite nearly one million additional DOAC prescriptions and substantial associated spending in the latter part of this study, the decline in AF-related stroke led to incremental savings at the national level.

Budget impacts associated with improving diagnosis and treatment of atrial fibrillation in high-risk stroke patients.

Aim: Estimate the 3-year budget impact in England from 2016/17 of improving nonvalvular atrial fibrillation management in high-risk stroke patients. Materials & methods: The Academic Health Science Network's AF Business Case Model was used to identify detection, protection (risk assessment and treatment initiation) and perfection (optimized treatment) gaps and to project the budget impact of closing these. Results: Closing all gaps over 3 years could prevent 27,550 strokes. Overall, perfection gap savings were £136,650,962 and protection gap savings were £58,146,171. Detection by screening in year one could cost £149,048,676, but with stroke-prevention savings would be £47,081,047 at 3 years. Thus, total potential savings were £194,797,133 and the cost-adjusted budget impact was £147,716,086. Conclusion: The detection and perfection gaps are key areas for investment.

State of the art on alternative methods to animal testing from an industrial point of view: ready for regulation?

Despite changing attitudes towards animal testing and current legislation to protect experimental animals, the rate of animal experiments seems to have changed little in recent years. On May 15-16, 2013, the In Vitro Testing Industrial Platform (IVTIP) held an open meeting to discuss the state of the art in alternative methods, how companies have, can, and will need to adapt and what drives and hinders regulatory acceptance and use. Several key messages arose from the meeting. First, industry and regulatory bodies should not wait for complete suites of alternative tests to become available, but should begin working with methods available right now (e.g., mining of existing animal data to direct future studies, implementation of alternative tests wherever scientifically valid rather than continuing to rely on animal tests) in non-animal and animal integrated strategies to reduce the numbers of animals tested. Sharing of information (communication), harmonization and standardization (coordination), commitment and collaboration are all required to improve the quality and speed of validation, acceptance, and implementation of tests. Finally, we consider how alternative methods can be used in research and development before formal implementation in regulations. Here we present the conclusions on what can be done already and suggest some solutions and strategies for the future.