Digital Maturity Consulting and Strategizing to Optimize Services: Overview.

The National Health Service (NHS), the health care system of the United Kingdom, is one of the largest health care entities in the world and has been successfully serving the UK population for decades. The NHS is also the fourth-largest employer globally. True to its reputation, some of the most modern and technically advanced medical services are available in the United Kingdom. However, between the acute, primary, secondary, and tertiary care providers of the NHS, there needs to be seamless integration and interoperability to provide timely holistic care to patients at a national level. Various efforts have been taken and programs launched since 2002 to achieve digital transformation in the NHS but with partial success rates. As it is important to understand a problem before trying to solve it, in this paper, we focus on tools used to assess the digital maturity of NHS trusts and organizations. Additionally, we aim to present the impact of ongoing transformation attempts on secondary services, particularly mental health. This paper considered the literature on digital maturity and performed a rapid review of currently available tools to measure digital maturity. We have performed a multivocal literature review that included white papers and web-based documents in addition to peer-reviewed literature. Further, the paper also provides a perspective of the ground reality from a mental health service provider's point of view. Assessment tools adopted from the global market, later modified and tailor-made to suit local preferences, are currently being used. However, there is a need for a robust framework that assesses status, allows target setting, and tracks progress across diverse providers.

Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care.

To evaluate and holistically treat the mental health sequelae and potential psychiatric comorbidities associated with obstetric and gynaecological conditions, it is important to optimize patient care, ensure efficient use of limited resources and improve health-economic models. Artificial intelligence applications could assist in achieving the above. The World Health Organization and global healthcare systems have already recognized the use of artificial intelligence technologies to address 'system gaps' and automate some of the more cumbersome tasks to optimize clinical services and reduce health inequalities. Currently, both mental health and obstetric and gynaecological services independently use artificial intelligence applications. Thus, suitable solutions are shared between mental health and obstetric and gynaecological clinical practices, independent of one another. Although, to address complexities with some patients who may have often interchanging sequelae with mental health and obstetric and gynaecological illnesses, 'holistically' developed artificial intelligence applications could be useful. Therefore, we present a rapid review to understand the currently available artificial intelligence applications and research into multi-morbid conditions, including clinical trial-based validations. Most artificial intelligence applications are intrinsically data-driven tools, and their validation in healthcare can be challenging as they require large-scale clinical trials. Furthermore, most artificial intelligence applications use rate-limiting mock data sets, which restrict their applicability to a clinical population. Some researchers may fail to recognize the randomness in the data generating processes in clinical care from a statistical perspective with a potentially minimal representation of a population, limiting their applicability within a real-world setting. However, novel, innovative trial designs could pave the way to generate better data sets that are generalizable to the entire global population. A collaboration between artificial intelligence and statistical models could be developed and deployed with algorithmic and domain interpretability to achieve this. In addition, acquiring big data sets is vital to ensure these artificial intelligence applications provide the highest accuracy within a real-world setting, especially when used as part of a clinical diagnosis or treatment.

Results of a prospective, mixed methods study to assess feasibility, acceptability and effectiveness of TRIumPH (Treatment and Recovery In PsycHosis): an integrated care pathway for psychosis, compared to usual treatment.

OBJECTIVES: To evaluate whether a newly developed care pathway, Treatment and Recovery In PsycHosis (TRIumPH), is feasible, acceptable and effective in meeting National Institute of Health and Care Excellence (NICE) quality standards in a timely manner. METHODS: This is a pragmatic, non-randomised, prospective, mixed methods study comparing an implementation (TRIumPH) and comparator site (not implementing TRIumPH) across three cohorts to assess feasibility, acceptability and effectiveness of the integrated pathway. SETTING: Early intervention in psychosis (EIP) services at two National Health Service organisations in South of England. PARTICIPANTS: All patients accepted into EIP services between 1 June 2014 and 31 May 2017 were each followed up for 1 year within their respective cohorts. METHODOLOGY: Quantitative data consisted of routinely collected clinical data retrieved from patient records to assess whether the implementation of TRIumPH achieved better concordance to NICE standards. These included time to access services, physical health assessments, clinical outcomes based timeliness of delivery and acute data. The controlled trial has evaluated the effect of TRIumPH (Intervention) with Care As Usual (Comparator). Qualitative measures consisted of questionnaires, interviews and focus groups to assess acceptability and satisfaction. Outcome measures were compared within the baseline, year 1 and year 2 cohorts and between the two sites. Quantitative data were statistically analysed by comparing means and proportions. RESULTS: Time to assessment improved in the implementation site and remained within the target in comparator site. Meeting of quality standards increased substantially in the implementation site but was more variable and reached lower levels in the comparator site especially for physical health standards. Cognitive therapy for psychosis, family intervention and carer and employment support were all offered to a greater extent in the implementation site and uptake increased over the period. CONCLUSIONS: Pathway implementation generally led to greater improvements in achievement of access and quality standards compared with comparator site. TRIAL REGISTRATION NUMBER: UK Clinical Research Network Portfolio (19187).

Protocol for a multicentre study to assess feasibility, acceptability, effectiveness and direct costs of TRIumPH (Treatment and Recovery In PsycHosis): integrated care pathway for psychosis.

INTRODUCTION: Duration of untreated psychosis (time between the onset of symptoms and start of treatment) is considered the strongest predictor of symptom severity and outcome. Integrated care pathways that prescribe timeframes around access and interventions can potentially improve quality of care. METHODS AND ANALYSIS: A multicentre mixed methods study to assess feasibility, acceptability, effectiveness and analysis of direct costs of an integrated care pathway for psychosis. A pragmatic, non-randomised, controlled trial design is used to compare the impact of Treatment and Recovery In PsycHosis (TRIumPH; Intervention) by comparison between NHS organisations that adopt TRIumPH and those that continue with care as usual (Control). Quantitative and qualitative methods will be used. We will use routinely collected quantitative data and study-specific questionnaires and focus groups to compare service user outcomes, satisfaction and adherence to intervention between sites that adopt TRIumPH versus sites that continue with usual care pathways. SETTING: 4 UK Mental health organisations. Two will implement TRIumPH whereas two will continue care as usual. PARTICIPANTS: Staff, carers, individuals accepted to early intervention in psychosis teams in participating organisations for the study period. INTERVENTION: TRIumPH-Integrated Care Pathway for psychosis that has a holistic approach and prescribes time frames against interventions; developed using intelligence from data; co-produced with patients, carers, clinicians and other stakeholders. OUTCOMES: Feasibility will be assessed through adherence to the process measures. Satisfaction and acceptability will be assessed using questionnaires and focus groups. Effectiveness will be assessed through data collection and evaluation of patient outcomes, including clinical, functional and recovery outcomes, physical health, acute care use. Outcome measures will be assessed at baseline, 12 and 24 months to measure whether there is an effect and if so, whether this is sustained over time. Outcomes measures at the adopter sites will be compared to their own baseline and against comparator sites. ETHICS AND DISSEMINATION: Ethics approval was obtained from East of Scotland Research Ethics Service (REC Ref no: LR/15/ES/0091). The results will be disseminated through publications, conference presentations, reports to the organisation. STUDY REGISTRATION: UK Clinical Research Network Portfolio: 19187.