Key factors behind the adoption of a patient-facing technology in primary care: a structured approach to variable importance

ObjectiveTo investigate associations between digital maturity in health and primary health care performance globally.MethodsWe conducted a search of publicly available data on digital maturity in health and primary health care performance for the 194 World Health Organization Member States. We identified 14 indicators of digital maturity in health, covering seven core subcomponents. A digital maturity in health index was derived from these indicators. Primary health care performance was assessed using the universal health coverage effective coverage index.FindingsDigital maturity in health data were missing for 85 of the 194 countries, with considerable variation across subcomponents. The remaining 109 countries were divided into four types by digital maturity in health index. We identified countries leading or lagging in digital maturity and highlighted the strongest and weakest subcomponents. Overall, there was a strong, nonlinear, positive correlation between digital maturity in health and primary health care performance (Spearman correlation: 0.85). However, there were notable exceptions, which indicates digital maturity can enhance primary health care but is not necessary for its improvement. The relationship between health-care expenditure and digital maturity in health and primary health care performance varied among countries with similar spending and digital maturity.ConclusionOverall, primary health care performance was positively associated with digital maturity in health and health-care expenditure. However, some countries had a strong primary health care system despite low digital maturity, and some had high digital maturity but a weak primary health care system. The study’s findings could help policy-makers prioritize investment in digital health.

BackgroundDigital maturity can help primary care facilities enhance their processes, communication, and adaptability to change, thereby fostering trust and job involvement. This study aimed to examine the causal relationships between perceived environmental uncertainty, digital maturity, organizational trust, and job involvement among managers of primary care facilities in the UK. The researchers applied socio-technical theory to examine the consequences of technology implementation on work practices and utilized contingency theory to ensure long-term stability in primary care facilities.MethodsThe study was conducted in the second quarter of 2023, surveying 200 managers from primary care facilities in the UK. The survey was conducted using a computer-assisted web interview (CAWI) method based on a purchased panel of respondents. Data were analyzed using descriptive statistics and structural equation modeling.ResultsThe results showed that perceived environmental uncertainty moderately impacts digital maturity. A greater level of perceived environmental uncertainty is related to greater organizational digital maturity, although perceived environmental uncertainty explains only 15.0% of the variance in digital maturity. The analysis also showed that the impact of digital maturity on organizational trust is positive, significant, and strong, while its impact on job involvement is positive and significant but rather moderate. Moreover, digital maturity mediates the relationship between environmental uncertainty and job involvement among managers of primary care facilities. The weakest link in the model is the connection between organizational trust and job involvement.ConclusionsThe analysis showed that digital maturity is key in shaping organizational trust in primary care facilities and job involvement among their managers. As organizations progress in their digital capabilities, they are better positioned to cultivate trust within their structures. The results of this research contribute to the literature on human resource management in the healthcare sector by deepening knowledge about the impact of environmental uncertainty and digital transformation on organizational trust and job involvement. This study provides important policy information for managers who seek tools to mitigate the adverse effects of environmental uncertainty and want to increase job involvement within primary care facilities.

With rapid global technological innovation in the 21st century, digital transformation has become irreversible. This study combines digital maturity theory and institutional frameworks to look at how companies perform, creating a theoretical framework called "Digital Maturity- Digital Literacy/Organizational Support Attitude - Corporate Operational Performance". Using responses from 1,152 participants in the "Survey on Digital Maturity's Impact on SME Operational Performance", the study uses statistical methods to examine how digital maturity directly and indirectly affects how well companies perform. Results reveal that all five digital maturity dimensions (digital technology capabilities, digital application capabilities, digital infrastructure, digital organizational capabilities, and digital top-level strategy), along with digital literacy, organizational support attitude, transformational leadership, and competitive market environment, significantly positively impact corporate operational performance. ROC analysis identifies digital infrastructure, digital top-level strategy, and digital technology capabilities as the highest-weighted variables. Dual mediation modeling demonstrates that digital maturity has stable, significant positive predictive effects on performance through both digital literacy and organizational support attitude pathways, with digital literacy showing stronger mediation effects. Chain mediation analysis validates the pathway, "Digital Maturity → Organizational Support Attitude → Digital Literacy → Corporate Operational Performance". Moderated mediation results show that transformational leadership and competitive market environment significantly moderate both direct and indirect pathways, enhancing digital maturity's positive effects on corporate operational performance.

Purpose This study explores the journey of healthcare organizations towards digital transformation maturity (DTM), focusing on the development and implementation of digital dynamic capabilities. By investigating the microfoundations of these capabilities, this study aims to provide a deeper understanding of the mechanisms. Design/methodology/approach Research reported in this paper employs an abductive approach. Empirically, a qualitative methodology based on a multiple-case study analysis has been conducted on six Italian healthcare organizations through semi-structured interviews and archival data. Findings The findings reveal the microfoundations across digital sensing, seizing and reconfiguring capabilities in healthcare to achieve DTM. The study also identifies three main stages of DTM, demonstrating how different combinations of these capabilities influence the progression towards digital maturity, thereby attaining different innovation outcomes. Research limitations/implications This study offers implications for healthcare managers who want to advance with DT and strategically manage the innovation essential to fully enact it. The research is limited by its focus on Italian healthcare organizations, potentially affecting the generalizability of the findings. Future studies could expand the geographical scope and employ mixed-methods approaches to validate and extend the results achieved in this study. Originality/value The study contributes to the nascent literature on DTM by providing empirical evidence of the microfoundations that enable digital dynamic capabilities, offering practical insights for healthcare managers and policymakers to foster an environment that supports a strategic approach to digital innovation.

The extent to which digital technologies are employed to promote the delivery of high-quality healthcare is known as Digital Maturity. Individual and systemic digital maturity are both necessary to ensure a successful, scalable and sustainable digital transformation in healthcare. However, digital maturity in primary care has been scarcely evaluated. This study assessed the digital maturity in General Practice (GP) globally and evaluated its association with participants' demographic characteristics, practice characteristics and features of Electronic Health Records (EHRs) use. GPs across 20 countries completed an online questionnaire between June and September 2020. Demographic data, practice characteristics, and features of EHRs use were collected. Digital maturity was evaluated through a framework based on usage, resources and abilities (divided in this study in its collective and individual components), interoperability, general evaluation methods and impact of digital technologies. Each dimension was rated as 1 or 0. The digital maturity score was calculated as the sum of the six dimensions and ranged between 0 to 6 (maximum digital maturity). Multivariable linear regression was used to model the total score, while multivariable logistic regression was used to model the probability of meeting each dimension of the score. One thousand six hundred GPs (61% female, 68% Europeans) participated. GPs had a median digital maturity of 4 (P25-P75: 3-5). Positive associations with digital maturity were found with: male gender [B = 0.18 (95% CI 0.01; 0.36)], use of EHRs for longer periods [B = 0.45 (95% CI 0.35; 0.54)] and higher frequencies of access to EHRs [B = 0.33 (95% CI 0.17; 0.48)]. Practicing in a rural setting was negatively associated with digital maturity [B = -0.25 (95%CI -0.43; -0.08)]. Usage (90%) was the most acknowledged dimension while interoperability (47%) and use of best practice general evaluation methods (28%) were the least. Shorter durations of EHRs use were negatively associated with all digital maturity dimensions (aOR from 0.09 to 0.77). Our study demonstrated notable factors that impact digital maturity and exposed discrepancies in digital transformation across healthcare settings. It provides guidance for policymakers to develop more efficacious interventions to hasten the digital transformation of General Practice.

Examining the evidence of the impact of health information technology in primary care: An argument for participatory research with health professionals and patients

BackgroundCommissioning innovative health technologies is typically complex and multi-faceted. Drawing on the negotiated order perspective, we explore the process by which commissioning organisations make their decisions to commission innovative health technologies. The empirical backdrop to this discussion is provided by a case study exploring the commissioning considerations for a new photoplethysmography-based diagnostic technology for peripheral arterial disease in primary care in the UK.MethodsThe research involved an empirical case study of four Clinical Commissioning Groups (CCGs) involved in the commissioning of services in primary and secondary care. Semi-structured in-depth interviews (16 in total) and two focus groups (a total of eight people participated, four in each group) were conducted with key individuals involved in commissioning services in the NHS including (i) senior NHS clinical leaders and directors (ii) commissioners and health care managers across CCGs and (iii) local general practitioners.ResultsCommissioning of a new diagnostic technology for peripheral arterial disease in primary care involves high levels of protracted negotiations over funding between providers and commissioners, alliance building, conflict resolution and compromise of objectives where the outcomes of change are highly contingent upon interventions made across different care settings. Our evidence illustrates how reconfigurations of inter-organisational relations, and of clinical and related work practices required for the successful implementation of a new technology could become the major challenge in commissioning negotiations.ConclusionsInnovative health technologies such as the diagnostic technology for peripheral arterial disease are commissioned in care pathways where the value of such technology is realised by those delivering care to patients. The detail of how care pathways are commissioned is complex and involves high degrees of uncertainty concerning such issues as prioritisation decisions, patient benefits, clinical buy-in, value for money and unintended consequences. Recent developments in the new care models and integrated care systems (ICSs) in the UK offer a unique opportunity for the successful commissioning arrangements of innovative health technologies in primary care such as the new diagnostic technology for peripheral arterial disease.

Power, paradox and pessimism: On the unintended consequences of digital health technologies in primary care

The goal of this paper is to present contemporary developments in the field of digital maturity models. By conducting a systematic literature review finally 24 relevant studies including 22 different models were identified and various characteristics of different digital maturity models were extracted. Focus was placed on the dimensions used to measure digital maturity in different model approaches. Special light was shed on organizational culture and to what extent it is represented in the models. Among other things, the findings indicate, that dimensions applied in various models can be very different and that just a few models incorporate transformational in addition to digital capabilities. In particular, organizational culture as a dedicated dimension of digital maturity is represented already in a few models, which indicates the growing importance of culture as an enabler of digital transformation efforts. Beside a comprehensive overview of the most widely used dimensions measuring digital maturity, a synthesis of the most frequently addressed cultural attributes is presented in this paper as well. This review finally reveals that most of the existing models give an incomplete picture of digital maturity, that cultural attributes reflecting a digital culture are not integrated systematically, and that digital maturity models specific to the domain of services are clearly under-represented. It also clearly demonstrates that research about digital transformation maturity as a holistic concept is scarce and needs more attention by research in the future.

When implementing a computer-based decision support system for any disease group in a primary health care centre, success will depend on the introductory efforts put into the project. The users must have plenty of information, above all regarding what can and what cannot be done by the computer-based decision support system. A personal introduction including a personal instruction session in front of the computer is imperative. Different aspects of technical maturity of the system must be met. Communication within and outside of the local net must be stable. Using a designated focus group methodology, we studied the introduction of advanced information technology in primary care by applying an inter/intranet decision support system for ambulatory ear, nose and throat diagnostics using a World Wide Web tool at the Skänninge health centre in Ostergötland, Sweden. A computer-based decision support system of the kind studied here may after a refinement period have all the qualities asked for by the users, and this study can be used as part of a user-developer dialogue for a future system.

Artificial Intelligence (AI) is steadily entering and transforming the healthcare and primary care domains. We observe AI-based applications assisting physicians in disease detection, medical advice, triage, clinical decision-making, diagnostics and digital health. Recently literature explored the physicians’ perspective about the potential impact of future technology on key tasks in primary care. However, limited attention has so far been paid to the patients’ perspective about AI acceptance in primary care, specifically during COVID-19 pandemic. Addressing this research gap, we employed a two-phase mixed methods approach to investigate the criteria for patients’ readiness to use AI-based primary care applications by analyzing key factors that affect the adoption of medical technology. First, we conducted a qualitative study which comprised of 18 semi-structured interviews. Second, based on the Technology Readiness and Acceptance Model (TRAM), we conducted an online survey (n=447). Study results indicate that respondents who score high on innovativeness have a higher level of readiness to use AI-based technology in primary care during COVID-19. Surprisingly, we found that patients’ health awareness and socio-demographic factors such as age, gender and education are not significant predictors of AI-based technology acceptance in primary care. Therefore, we suggest exploring the effects of population-specific promotions and individual impediments to speed-up the adoption of AI-based technology in primary care in order to raise usability in complex digital healthcare ecosystems.

IDF21-0404 Variations in comorbidity burden in patients with type 2 diabetes and impacts on healthcare resource usage and costs

Growing demand for access to NHS primary care means services are under increasing pressure. Many GP providers are using digital technologies (video/email/other online consultations) to try to improve access and efficiency. Alongside this is rapid growth in health technologies, which collect, measure, or interpret health data, and provide health information or advice. Many technologies have positive potential; however, the speed with which they are becoming available, increasingly blurred boundaries between health and lifestyle technologies and traditional healthcare provision, and the confidence and skills GPs have in using digital health technologies, bring new complexities and concerns. Successful adoption of innovative technologies in primary care requires effective preparation of future and current primary care workforce, enabling appropriate use by healthcare professionals, patients, and communities. Although some training programmes do exist, these are not routinely integrated within primary care training. There is a distinct gap in both training and capacity building in this area, and the evidence base to inform development and content of training is limited. In this article we explore risks and challenges of digital technologies in primary care and relate these to training needs for GPs, trainees, and medical students. In this analysis we draw on literature as well as first-hand experience of practising GPs. In June 2019 we conducted two workshops on digital health with approximately 30 GP teachers who supervise medical students’ placements, which informed our understanding of four key areas of digital health risks and challenges in general practice. Based on risks and challenges identified, we present recommendations for training to support the implementation of digital primary care. ### Consultation skills Telephone consultations (TCs) were initially introduced to meet increased patient demand to speak to a doctor. As early as 1978 TCs were described as being as much a part of a doctor’s equipment as a stethoscope, and …

The digitalization of the economy, especially within the framework of the concept of Industry 4.0, has a significant impact on the medical field. In healthcare, digital technologies such as telemedicine technologies, decision support systems and artificial intelligence increase the availability and quality of medical services. The purpose of the study is to develop scientifically based recommendations for improving primary health care using the developed tools for assessing the «digital maturity» of primary care organizations. Materials and methods. To develop recommendations, a methodology was used to assess the «digital maturity» of medical organizations providing primary health care. Experts assessed the indicators of «digital maturity», and their significance was determined through a weighted average. The results of the assessment made it possible to identify the main, additional and excluded indicators, which became the basis for further development of recommendations. Results. Based on the developed methodology, classifications of the levels of «digital maturity» of medical organizations providing primary health care, ranging from low to high levels, were created. These classifications made it possible to identify key aspects that need improvement, including digital infrastructure, information system functionality, the use of artificial intelligence, as well as digital literacy of medical personnel. Conclusions. The digital transformation of primary health care contributes to improving the quality and accessibility of medical services, especially in remote regions. The developed methodology makes it possible to objectively assess the level of digitalization and formulate recommendations for individual digital transformation strategies in the regions of Russia. It is important to continue monitoring and research to assess the long-term effects of digitalization.

Implementing digital health technologies in primary care is anticipated to improve patient experience. We examined the relationships between patient experience and digital health access in primary care settings in Ontario, Canada. We conducted a retrospective cross-sectional study using patient responses to the Health Care Experience Survey linked to health and administrative data between April 2019-February 2020. We measured patient experience by summarizing HCES questions. We used multivariable logistic regression stratified by the number of primary care visits to investigate associations between patient experience with digital health access and moderating variables. Our cohort included 2,692 Ontario adults, of which 63.0% accessed telehealth, 2.6% viewed medical records online, and 3.6% booked appointments online. Although patients reported overwhelmingly positive experiences, we found no consistent relationship with digital health access. Online appointment booking access was associated with lower odds of poor experience for patients with three or more primary care visits in the past 12 months (adjusted odds ratio 0.16, 95% CI 0.02-0.56). Younger age, tight financial circumstances, English as a second language, and knowing their primary care provider for fewer years had greater odds of poor patient experience. In 2019/2020, we found limited uptake of digital health in primary care and no clear association between real-world digital health adoption and patient experience in Ontario. Our findings provide an essential context for ensuing rapid shifts in digital health adoption during the COVID-19 pandemic, serving as a baseline to reexamine subsequent improvements in patient experience.