BackgroundMany promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level.ObjectiveOur objective was to produce an evidence-based, theory-informed, and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program.MethodsThe study had 2 parallel components: (1) secondary research (hermeneutic systematic review) to identify key domains, and (2) empirical case studies of technology implementation to explore, test, and refine these domains. We studied 6 technology-supported programs—video outpatient consultations, global positioning system tracking for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organizing software, and integrated case management via data sharing—using longitudinal ethnography and action research for up to 3 years across more than 20 organizations. Data were collected at micro level (individual technology users), meso level (organizational processes and systems), and macro level (national policy and wider context). Analysis and synthesis was aided by sociotechnically informed theories of individual, organizational, and system change. The draft framework was shared with colleagues who were introducing or evaluating other technology-supported health or care programs and refined in response to feedback.ResultsThe literature review identified 28 previous technology implementation frameworks, of which 14 had taken a dynamic systems approach (including 2 integrative reviews of previous work). Our empirical dataset consisted of over 400 hours of ethnographic observation, 165 semistructured interviews, and 200 documents. The final nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework included questions in 7 domains: the condition or illness, the technology, the value proposition, the adopter system (comprising professional staff, patient, and lay caregivers), the organization(s), the wider (institutional and societal) context, and the interaction and mutual adaptation between all these domains over time. Our empirical case studies raised a variety of challenges across all 7 domains, each classified as simple (straightforward, predictable, few components), complicated (multiple interacting components or issues), or complex (dynamic, unpredictable, not easily disaggregated into constituent components). Programs characterized by complicatedness proved difficult but not impossible to implement. Those characterized by complexity in multiple NASSS domains rarely, if ever, became mainstreamed. The framework showed promise when applied (both prospectively and retrospectively) to other programs.ConclusionsSubject to further empirical testing, NASSS could be applied across a range of technological innovations in health and social care. It has several potential uses: (1) to inform the desi...

Individuals with potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) do not necessarily develop PCR or antibody positivity, suggesting that some individuals may clear subclinical infection before seroconversion. T cells can contribute to the rapid clearance of SARS-CoV-2 and other coronavirus infections1–3. Here we hypothesize that pre-existing memory T cell responses, with cross-protective potential against SARS-CoV-2 (refs. 4–11), would expand in vivo to support rapid viral control, aborting infection. We measured SARS-CoV-2-reactive T cells, including those against the early transcribed replication–transcription complex (RTC)12,13, in intensively monitored healthcare workers (HCWs) who tested repeatedly negative according to PCR, antibody binding and neutralization assays (seronegative HCWs (SN-HCWs)). SN-HCWs had stronger, more multispecific memory T cells compared with a cohort of unexposed individuals from before the pandemic (prepandemic cohort), and these cells were more frequently directed against the RTC than the structural-protein-dominated responses observed after detectable infection (matched concurrent cohort). SN-HCWs with the strongest RTC-specific T cells had an increase in IFI27, a robust early innate signature of SARS-CoV-2 (ref. 14), suggesting abortive infection. RNA polymerase within RTC was the largest region of high sequence conservation across human seasonal coronaviruses (HCoV) and SARS-CoV-2 clades. RNA polymerase was preferentially targeted (among the regions tested) by T cells from prepandemic cohorts and SN-HCWs. RTC-epitope-specific T cells that cross-recognized HCoV variants were identified in SN-HCWs. Enriched pre-existing RNA-polymerase-specific T cells expanded in vivo to preferentially accumulate in the memory response after putative abortive compared to overt SARS-CoV-2 infection. Our data highlight RTC-specific T cells as targets for vaccines against endemic and emerging Coronaviridae.

SARS-CoV-2 vaccine rollout has coincided with the spread of variants of concern. We investigated if single dose vaccination, with or without prior infection, confers cross protective immunity to variants. We analyzed T and B cell responses after first dose vaccination with the Pfizer/BioNTech mRNA vaccine BNT162b2 in healthcare workers (HCW) followed longitudinally, with or without prior Wuhan-Hu-1 SARS-CoV-2 infection. After one dose, individuals with prior infection showed enhanced T cell immunity, antibody secreting memory B cell response to spike and neutralizing antibodies effective against B.1.1.7 and B.1.351. By comparison, HCW receiving one vaccine dose without prior infection showed reduced immunity against variants. B.1.1.7 and B.1.351 spike mutations resulted in increased, abrogated or unchanged T cell responses depending on human leukocyte antigen (HLA) polymorphisms. Single dose vaccination with BNT162b2 in the context of prior infection with a heterologous variant substantially enhances neutralizing antibody responses against variants.

BackgroundFailures and partial successes are common in technology-supported innovation programmes in health and social care. Complexity theory can help explain why. Phenomena may be simple (straightforward, predictable, few components), complicated (multiple interacting components or issues) or complex (dynamic, unpredictable, not easily disaggregated into constituent components). The recently published NASSS framework applies this taxonomy to explain Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability. This paper reports the first empirical application of the NASSS framework.MethodsSix technology-supported programmes were studied using ethnography and action research for up to 3 years across 20 health and care organisations and 10 national-level bodies. They comprised video outpatient consultations, GPS tracking technology for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organising software and integrated case management via data warehousing. Data were collected at three levels: micro (individual technology users), meso (organisational processes and systems) and macro (national policy and wider context). Data analysis and synthesis were guided by socio-technical theories and organised around the seven NASSS domains: (1) the condition or illness, (2) the technology, (3) the value proposition, (4) the adopter system (professional staff, patients and lay carers), (5) the organisation(s), (6) the wider (institutional and societal) system and (7) interaction and mutual adaptation among all these domains over time.ResultsThe study generated more than 400 h of ethnographic observation, 165 semi-structured interviews and 200 documents. The six case studies raised multiple challenges across all seven domains. Complexity was a common feature of all programmes. In particular, individuals’ health and care needs were often complex and hence unpredictable and ‘off algorithm’. Programmes in which multiple domains were complicated proved difficult, slow and expensive to implement. Those in which multiple domains were complex did not become mainstreamed (or, if mainstreamed, did not deliver key intended outputs).ConclusionThe NASSS framework helped explain the successes, failures and changing fortunes of this diverse sample of technology-supported programmes. Since failure is often linked to complexity across multiple NASSS domains, further research should systematically address ways to reduce complexity and/or manage programme implementation to take account of it.

Establishing and running remote consultation services is challenging politically (interest groups may gain or lose), organizationally (remote consulting requires implementation work and new roles and workflows), economically (costs and benefits are unevenly distributed across the system), technically (excellent care needs dependable links and high-quality audio and images), relationally (interpersonal interactions are altered), and clinically (patients are unique, some examinations require contact, and clinicians have deeply-held habits, dispositions and norms). Many of these challenges have an under-examined ethical dimension. In this paper, we present a novel framework, Planning and Evaluating Remote Consultation Services (PERCS), built from a literature review and ongoing research. PERCS has 7 domains—the reason for consulting, the patient, the clinical relationship, the home and family, technologies, staff, the healthcare organization, and the wider system—and considers how these domains interact and evolve over time as a complex system. It focuses attention on the organization's digital maturity and digital inclusion efforts. We have found that both during and beyond the pandemic, policymakers envisaged an efficient, safe and accessible remote consultation service delivered through state-of-the art digital technologies and implemented via rational allocation criteria and quality standards. In contrast, our empirical data reveal that strategic decisions about establishing remote consultation services, allocation decisions for appointment type (phone, video, e-, face-to-face), and clinical decisions when consulting remotely are fraught with contradictions and tensions—for example, between demand management and patient choice—leading to both large- and small-scale ethical dilemmas for managers, support staff, and clinicians. These dilemmas cannot be resolved by standard operating procedures or algorithms. Rather, they must be managed by attending to here-and-now practicalities and emergent narratives, drawing on guiding principles applied with contextual judgement. We complement the PERCS framework with a set of principles for informing its application in practice, including education of professionals and patients.