Wales has ambitious health, wealth, and innovation policies and a clear goal to use the economic muscle of the Welsh National Health Service (NHS) to support its strong life sciences sector. Health Technology Wales (HTW) has a clear remit to appraise technologies over the span of their lifecycle from innovation to obsolescence. HTW is collaborating with the Bevan Commission through their national Health Technology Exemplars (HTEs), which partners NHS and industry stakeholders to strengthen innovation within the Welsh health system.

Health technology assessment (HTA) methods were used to produce topic exploration reports for assessing the evidence underpinning applicant innovations. A “Dragons’ Den” expert panel was convened to select the successful HTEs.

Fourteen Bevan HTEs were awarded funds, which were matched by industry partners. Application of HTA methods resulted in more critical consideration of technology value propositions, including: developing pull models of innovation focused on delivering health technology solutions for current problems facing NHS Wales; supporting early dialogue between the NHS and industry partners around demonstrating evidence of improved patient outcomes; and focusing on transformative rather than incremental innovation. The most promising innovations will progress to rapid HTA, where the evidence generated will be used to develop guidance for NHS Wales.

HTA methods were productively deployed at the innovation phase of the technology lifecycle to support evidence-informed allocation of scarce innovation resources. In this way, HTW is working with key stakeholders to identify and offer early support to the most promising innovations, with the aim of expediting their adoption and realizing health benefits for patients as quickly as possible. The Bevan Commission has partnered with HTW to routinely build in HTA and evidence considerations in its future innovation calls and competitions. Thus, HTW has established a “feeder” pipeline for assessing bottom-up service-led innovations and encouraging evidence consideration throughout the lifecycle of innovative technologies.

New approaches are needed to safely reduce emergency admissions to hospital by targeting interventions effectively in primary care. A predictive risk stratification tool (PRISM) identifies each registered patient's risk of an emergency admission in the following year, allowing practitioners to identify and manage those at higher risk. We evaluated the introduction of PRISM in primary care in one area of the United Kingdom, assessing its impact on emergency admissions and other service use.

We conducted a randomized stepped wedge trial with cluster-defined control and intervention phases, and participant-level anonymized linked outcomes. PRISM was implemented in eleven primary care practice clusters (total thirty-two practices) over a year from March 2013. We analyzed routine linked data outcomes for 18 months.

We included outcomes for 230,099 registered patients, assigned to ranked risk groups.

Overall, the rate of emergency admissions was higher in the intervention phase than in the control phase: adjusted difference in number of emergency admissions per participant per year at risk, delta = .011 (95 percent Confidence Interval, CI .010, .013). Patients in the intervention phase spent more days in hospital per year: adjusted delta = .029 (95 percent CI .026, .031). Both effects were consistent across risk groups.

Primary care activity increased in the intervention phase overall delta = .011 (95 percent CI .007, .014), except for the two highest risk groups which showed a decrease in the number of days with recorded activity.

Introduction of a predictive risk model in primary care was associated with increased emergency episodes across the general practice population and at each risk level, in contrast to the intended purpose of the model. Future evaluation work could assess the impact of targeting of different services to patients across different levels of risk, rather than the current policy focus on those at highest risk.

A predictive risk stratification tool (PRISM) to estimate a patient's risk of an emergency hospital admission in the following year was trialled in general practice in an area of the United Kingdom. PRISM's introduction coincided with a new incentive payment (‘QOF’) in the regional contract for family doctors to identify and manage the care of people at high risk of emergency hospital admission.

Alongside the trial, we carried out a complementary qualitative study of processes of change associated with PRISM's implementation. We aimed to describe how PRISM was understood, communicated, adopted, and used by practitioners, managers, local commissioners and policy makers. We gathered data through focus groups, interviews and questionnaires at three time points (baseline, mid-trial and end-trial). We analyzed data thematically, informed by Normalisation Process Theory (1).

All groups showed high awareness of PRISM, but raised concerns about whether it could identify patients not yet known, and about whether there were sufficient community-based services to respond to care needs identified. All practices reported using PRISM to fulfil their QOF targets, but after the QOF reporting period ended, only two practices continued to use it. Family doctors said PRISM changed their awareness of patients and focused them on targeting the highest-risk patients, though they were uncertain about the potential for positive impact on this group.

Though external factors supported its uptake in the short term, with a focus on the highest risk patients, PRISM did not become a sustained part of normal practice for primary care practitioners.