Abstract:Although sociological studies of quality and safety have identified competing epistemologies in the attempt to measure and improve care, there are gaps in our understanding of how finance and accounting practices are being used to organise this field. This analysis draws on what others have elsewhere called ‘financialisation’ in order to explore the quantification of qualitatively complex care practices. We make our argument using ethnographic data of a quality improvement programme for acute kidney injury (AK… Show more
“…Measures such as the FFT have been subsumed into the government framework of CQUINs (Commissioning for Quality and Innovation), whereby a proportion of healthcare providers’ income is conditional on demonstrating improvements in quality. Rather than rewarding hospitals for substantive improvements, these have sometimes been focused on response rates, generating a culture of measurement rather than action (Bailey et al 2019). In a first interview about her role, the Head of Patient Experience at one case study site alluded to the way in which CQUINs had shaped patient experience data collection:When we realised that out‐patients was on the horizon and it was obviously a CQUIN target, so we got paid money for it, a lot of money for rolling it out, I obviously had to go out to tender for a company to do that for us [.…”
Patient‐centred care has become the touchstone of healthcare policy in developed healthcare systems. The ensuing commodification of patients’ experiences has resulted in a mass of data but little sense of whether and how such data are used. We sought to understand how front‐line staff use patient experience data for quality improvement in the National Health Service (NHS). We conducted a 12‐month ethnographic case study evaluation of improvement projects in six NHS hospitals in England in 2016–2017. Drawing on the sociology of everyday life, we show how front‐line staff worked with a notion of data as interpersonal and embodied. In addition to consulting organisationally sanctioned forms of data, staff used their own embodied interactions with patients, carers, other staff and the ward environment to shape improvements. The data staff found useful involved face‐to‐face interaction and dialogue; were visual, emotive, and allowed for immediate action. We draw on de Certeau to re‐conceptualise this as ‘wild data’. We conclude that patient experience data are relational, and have material, social and affective dimensions, which have been elided in the literature to date. Practice‐based theories of the everyday help to envision ‘patient experience’ not as a disembodied tool of managerialism but as an embedded part of healthcare staff professionalism.
“…Measures such as the FFT have been subsumed into the government framework of CQUINs (Commissioning for Quality and Innovation), whereby a proportion of healthcare providers’ income is conditional on demonstrating improvements in quality. Rather than rewarding hospitals for substantive improvements, these have sometimes been focused on response rates, generating a culture of measurement rather than action (Bailey et al 2019). In a first interview about her role, the Head of Patient Experience at one case study site alluded to the way in which CQUINs had shaped patient experience data collection:When we realised that out‐patients was on the horizon and it was obviously a CQUIN target, so we got paid money for it, a lot of money for rolling it out, I obviously had to go out to tender for a company to do that for us [.…”
Patient‐centred care has become the touchstone of healthcare policy in developed healthcare systems. The ensuing commodification of patients’ experiences has resulted in a mass of data but little sense of whether and how such data are used. We sought to understand how front‐line staff use patient experience data for quality improvement in the National Health Service (NHS). We conducted a 12‐month ethnographic case study evaluation of improvement projects in six NHS hospitals in England in 2016–2017. Drawing on the sociology of everyday life, we show how front‐line staff worked with a notion of data as interpersonal and embodied. In addition to consulting organisationally sanctioned forms of data, staff used their own embodied interactions with patients, carers, other staff and the ward environment to shape improvements. The data staff found useful involved face‐to‐face interaction and dialogue; were visual, emotive, and allowed for immediate action. We draw on de Certeau to re‐conceptualise this as ‘wild data’. We conclude that patient experience data are relational, and have material, social and affective dimensions, which have been elided in the literature to date. Practice‐based theories of the everyday help to envision ‘patient experience’ not as a disembodied tool of managerialism but as an embedded part of healthcare staff professionalism.
“…In 2017 The Royal Free was found to have breached UK data protection laws in sharing the health records of around 1.6 million patients (Lacobucci, 2017). These events raise important issues about power, privacy and responsibility in relation to such partnerships (Powles and Hodson, 2017), while also articulating a clear link between technology and market-making in public organisations (Bailey et al, 2019).…”
Algorithms are increasingly being adopted in healthcare settings, promising increased safety, productivity and efficiency. The growing sociological literature on algorithms in healthcare shares an assumption that algorithms are introduced to ‘support’ decisions within an interactive order that is predominantly human-oriented. This article presents a different argument, calling attention to the manner in which organisations can end up introducing a non-negotiable disjuncture between human-initiated care work and work that supports algorithms, which the authors call algorithmic work. Drawing on an ethnographic study, the authors describe how two hospitals in England implemented an Acute Kidney Injury (AKI) algorithm and analyse ‘interruptions’ to the algorithm’s expected performance. When the coordination of algorithmic work occludes care work, the study finds a ‘dismembered’ organisation that is algorithmically-oriented rather than human-oriented. In the discussion, the authors examine the consequences of coordinating human and non-human work in each hospital and conclude by urging sociologists of organisation to attend to the importance of the formal in algorithmic work. As the use of algorithms becomes widespread, the analysis provides insight into how organisations outside of healthcare can also end up severing tasks from human experience when algorithmic automation is introduced.
“…14 It highlighted a need for tailored discharge summaries to determine the urgency of review, rather than producing generic instructions driven by tariff-based incentives. 15,16 AKI is a clinical syndrome, not another long-term condition, and offers a lens to promote safer systems of care, particularly for people with multimorbidity. 17,18 A consensus study was conducted to address gaps between work-as-imagined (guidance) and work-as-done (current routine practice).…”
Section: Introductionmentioning
confidence: 99%
“…14 It highlighted a need for tailored discharge summaries to determine the urgency of review, rather than producing generic instructions driven by tariff-based incentives. 15 , 16 …”
BackgroundAcute kidney injury (AKI) is associated with poor health outcomes, including increased mortality and rehospitalisation. National policy and patient safety drivers have targeted AKI as an example to ensure safer transitions of care.AimTo establish guidance to promote high-quality transitions of care for adults following episodes of illness complicated by AKI.Design & settingAn appropriateness ratings evaluation was undertaken using the RAND/UCLA Appropriateness Method (RAM). The Royal College of General Practitioners (RCGP) AKI working group developed a range of clinical scenarios to help identify the necessary steps to be taken following discharge of a patient from secondary care into primary care in the UK.MethodA 10-person expert panel was convened to rate 819 clinical scenarios, testing the most appropriate time and action following hospital discharge. Specifically, the scenarios focused on determining the appropriateness and urgency for planning: an initial medication review; monitoring of kidney function; and assessment for albuminuria.ResultsTaking no action (that is, no medication review; no kidney monitoring; or no albuminuria testing) was rated inappropriate in all cases. In most scenarios, there was consensus that both the initial medication review and kidney function monitoring should take place within 1–2 weeks or 1 month, depending on clinical context. However, patients with heart failure and poor kidney recovery were rated to require expedited review. There was consensus that assessment for albuminuria should take place at 3 months after discharge following AKI.ConclusionSystems to support tailored and timely post-AKI discharge care are required, especially in high-risk populations, such as people with heart failure.
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