Big 5 Personality Traits and Individual- and Practice-Related Characteristics as Influencing Factors of Digital Maturity in General Practices: Quantitative Web-Based Survey Study

BACKGROUND

Various studies propose the significance of digital maturity in ensuring effective patient care and enabling improved health outcomes, a successful digital transformation, and optimized service delivery. Although previous research has centered around inpatient health care settings, research on digital maturity in general practices is still in its infancy.

OBJECTIVE

As general practitioners (GPs) are the first point of contact for most patients, we aimed to shed light on the pivotal role of GPs' inherent characteristics, especially their personality, in the digital maturity of general practices.

METHODS

In the first step, we applied a sequential mixed methods approach involving a literature review and expert interviews with GPs to construct the digital maturity scale used in this study. Next, we designed a web-based survey to assess digital maturity on a 5-point Likert-type scale and analyze the relationship with relevant inherent characteristics using ANOVAs and regression analysis.

RESULTS

Our web-based survey with 219 GPs revealed that digital maturity was overall moderate (mean 3.31, SD 0.64) and substantially associated with several characteristics inherent to the GP. We found differences in overall digital maturity based on GPs' gender, the expected future use of digital health solutions, the perceived digital affinity of medical assistants, GPs' level of digital affinity, and GPs' level of extraversion and neuroticism. In a regression model, a higher expected future use, a higher perceived digital affinity of medical assistants, a higher digital affinity of GPs, and lower neuroticism were substantial predictors of overall digital maturity.

CONCLUSIONS

Our study highlights the impact of GPs' inherent characteristics, especially their personality, on the digital maturity of general practices. By identifying these inherent influencing factors, our findings support targeted approaches to drive digital maturity in general practice settings.

Perceived Impact of Digital Health Maturity on Patient Experience, Population Health, Health Care Costs, and Provider Experience: Mixed Methods Case Study

BACKGROUND

Health care organizations understand the importance of new technology implementations; however, the best strategy for implementing successful digital transformations is often unclear. Digital health maturity assessments allow providers to understand the progress made toward technology-enhanced health service delivery. Existing models have been criticized for their lack of depth and breadth because of their technology focus and neglect of meaningful outcomes.

OBJECTIVE

We aimed to examine the perceived impacts of digital health reported by health care staff employed in health care organizations across a spectrum of digital health maturity.

METHODS

A mixed methods case study was conducted. The digital health maturity of public health care systems (n=16) in Queensland, Australia, was examined using the quantitative Digital Health Indicator (DHI) self-assessment survey. The lower and upper quartiles of DHI scores were calculated and used to stratify sites into 3 groups. Using qualitative methods, health care staff (n=154) participated in interviews and focus groups. Transcripts were analyzed assisted by automated text-mining software. Impacts were grouped according to the digital maturity of the health care worker's facility and mapped to the quadruple aims of health care: improved patient experience, improved population health, reduced health care cost, and enhanced provider experience.

RESULTS

DHI scores ranged between 78 and 193 for the 16 health care systems. Health care systems in the high-maturity category (n=4, 25%) had a DHI score of ≥166.75 (the upper quartile); low-maturity sites (n=4, 25%) had a DHI score of ≤116.75 (the lower quartile); and intermediate-maturity sites (n=8, 50%) had a DHI score ranging from 116.75 to 166.75 (IQR). Overall, 18 perceived impacts were identified. Generally, a greater number of positive impacts were reported in health care systems of higher digital health maturity. For patient experiences, higher maturity was associated with maintaining a patient health record and tracking patient experience data, while telehealth enabled access and flexibility across all digital health maturity categories. For population health, patient journey tracking and clinical risk mitigation were reported as positive impacts at higher-maturity sites, and telehealth enabled health care access and efficiencies across all maturity categories. Limited interoperability and organizational factors (eg, strategy, policy, and vision) were universally negative impacts affecting health service delivery. For health care costs, the resource burden of ongoing investments in digital health and a sustainable skilled workforce was reported. For provider experiences, the negative impacts of poor usability and change fatigue were universal, while network and infrastructure issues were negative impacts at low-maturity sites.

CONCLUSIONS

This is one of the first studies to show differences in the perceived impacts of digital maturity of health care systems at scale. Higher digital health maturity was associated with more positive reported impacts, most notably in achieving outcomes for the population health aim.

Digital Maturity and Its Measurement of General Practitioners: A Scoping Review

The work of general practitioners (GPs) is increasingly characterized by digitalization. Their progress in digitalization can be described by the concept of digital maturity and measured using maturity models. The aim of this scoping review is to provide an overview of the state of research on digital maturity and its measurement in primary care, specifically for GPs. The scoping review was conducted according to Arksey and O'Malley, considering the reporting scheme for PRISMA-ScR. For the literature search, we used PubMed and Google Scholar as the main sources of information. A total of 24 international, mostly Anglo-American studies, were identified. The understanding of digital maturity varied widely. In most studies, it was understood in a highly technical way and associated with the adoption of electronic medical records. More recent, but mostly unpublished, studies have attempted to capture overall digital maturity. So far, the understanding of digital maturity of GPs is still very diffuse-the research literature is still in its infancy. Future research should therefore aim to explore the dimensions of digital maturity of GPs to be able to develop a consistent and validated model for measuring digital maturity.

Digital health and capability maturity models-a critical thematic review and conceptual synthesis of the literature

OBJECTIVE

A literature review of capability maturity models (MMs) to inform the conceptualization, development, implementation, evaluation, and mainstreaming of MMs in digital health (DH).

METHODS

Electronic databases were searched using "digital health," "maturity models," and related terms based on the Digital Health Profile and Maturity Assessment Toolkit Maturity Model (DHPMAT-MM). Covidence was used to screen, identify, capture, and achieve consensus on data extracted by the authors. Descriptive statistics were generated. A thematic analysis and conceptual synthesis were conducted.

FINDINGS

Diverse domain-specific MMs and model development, implementation, and evaluation methods were found. The spread and pattern of different MMs verified the essential DH foundations and five maturity stages of the DHPMAT-MM. An unanticipated finding was the existence of a new category of community-facing MMs. Common characteristics included:1. A dynamic lifecycle approach to digital capability maturity, which is:a. responsive to environmental changes and may improve or worsen over time;b. accumulative, incorporating the attributes of the preceding stage; andc. sequential, where no maturity stage must be skipped.2. Sociotechnical quality improvement of the DH ecosystem and MM, which includes:a. investing in the organization's human, hardware, and software resources andb. a need to engage and improve the DH competencies of citizens.

CONCLUSIONS

The diversity in MMs and variability in methods and content can create cognitive dissonance. A metamodel like the DHPMAT-MM can logically unify the many domain-specific MMs and guide the overall implementation and evaluation of DH ecosystems and MMs over the maturity lifecycle.

Digital maturity and its determinants in General Practice: A cross-sectional study in 20 countries

Background

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.

Objectives

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.

Methods

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.

Results

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).

Conclusion

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.

Which one? A suggested approach for evaluating digital health maturity models

Background

Digital health maturity models allow healthcare organizations to evaluate digital health capability and to develop roadmaps for improving patient care through technology. There are many models available commercially for healthcare providers to use to assess their digital health maturity. Currently, there are limited evidence-based methods to assess the quality, utility, and efficacy of maturity models to select the most appropriate model for the given context.

Objective

To develop a framework to assess digital maturity models and facilitate recommendations for digital maturity model selection.

Methods

A systematic, consultative, and iterative process was used. Literature analyses and a stakeholder needs analysis (n = 23) was conducted to develop content and design considerations. These considerations were incorporated into the initial version of the framework developed by researchers in a design workshop. External stakeholder review (n = 20) and improvements strengthened and finalized the framework.

Results

The criteria of the framework include assessment of healthcare context, feasibility, integrity, completeness and actionability. Users can compare model performance in order to select the most appropriate model for their context.

Conclusion

The framework provides healthcare stakeholders with a consistent and objective methodology to compare digital health maturity models, informing approaches to choosing a suitable model. This is a critical step as healthcare evolves towards a digital health system focused on improving the quality of care, reducing costs and improving the provider and consumer experience.

Managing Directors' Perspectives on Digital Maturity in German Hospitals-A Multi-Point Online-Based Survey Study

BACKGROUND

The digitalization and integration of data are increasingly relevant for hospitals. Several methods exist to assess and structurally develop digital maturity. However, it is notable that German hospitals lag behind the European average with respect to digitalization.

OBJECTIVE

We hypothesized that: (a) the perspective of hospital managing directors regarding the state of digitalization in German hospitals plays an important role in the investigation of barriers, and (b) the Hospital Future Act in 2020 may help to surmount those barriers.

METHODS

Aligned with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES), two online surveys were conducted, one in 2019 and one in 2021.

RESULTS

The first study covered 184/344 hospitals and the second, 83/344. The responsibility for deciding on the implementation of digitalization lay with the management (115/184; 62.5%). About 54.9% (101/184) of the managing directors desired digitally supported workflows, together with employees or users. In total, 74.7% (62/83) of hospital managing directors expressed an increase in digitization compared to 2019, with a percentage increase of 25.4% (SD 14.41). In some cases, we analyzed the data using an ANOVA, chi-squared test and Pearson's correlation, but there was no significant relation identified among the variables.

CONCLUSIONS

This online-based survey study demonstrated that the development of a digitalization strategy is still strongly tied to or dominated by the attitude of the management. One could assume a lack of acceptance among employees, which should be surveyed in future research. The Hospital Future Act, as well as the COVID-19 pandemic, has positively influenced the digital maturity of hospitals.

Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review

Background

Digital health in hospital settings is viewed as a panacea for achieving the “quadruple aim” of health care, yet the outcomes have been largely inconclusive. To optimize digital health outcomes, a strategic approach is necessary, requiring digital maturity assessments. However, current approaches to assessing digital maturity have been largely insufficient, with uncertainty surrounding the dimensions to assess.

Objective

The aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals.

Methods

A systematic literature review was conducted of peer-reviewed literature (published before December 2020) investigating maturity models used to assess the digital maturity of hospitals. A total of 29 relevant articles were retrieved, representing 27 distinct maturity models. The articles were inductively analyzed, and the maturity model dimensions were extracted and consolidated into a maturity model framework.

Results

The consolidated maturity model framework consisted of 7 dimensions: strategy; information technology capability; interoperability; governance and management; patient-centered care; people, skills, and behavior; and data analytics. These 7 dimensions can be evaluated based on 24 respective indicators.

Conclusions

The maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement.

Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review

Currently, the concept of Industry 4.0 is well known; however, it is extremely complex, as it is constantly evolving and innovating. It includes the participation of many disciplines and areas of knowledge as well as the integration of many technologies, both mature and emerging, but working in collaboration and relying on their study and implementation under the novel criteria of Cyber-Physical Systems. This study starts with an exhaustive search for updated scientific information of which a bibliometric analysis is carried out with results presented in different tables and graphs. Subsequently, based on the qualitative analysis of the references, we present two proposals for the schematic analysis of Industry 4.0 that will help academia and companies to support digital transformation studies. The results will allow us to perform a simple alternative analysis of Industry 4.0 to understand the functions and scope of the integrating technologies to achieve a better collaboration of each area of knowledge and each professional, considering the potential and limitations of each one, supporting the planning of an appropriate strategy, especially in the management of human resources, for the successful execution of the digital transformation of the industry.

Technological Capabilities to Assess Digital Excellence in Hospitals in High Performing Health Care Systems: International eDelphi Exercise

BACKGROUND

Hospitals worldwide are developing ambitious digital transformation programs as part of broader efforts to create digitally advanced health care systems. However, there is as yet no consensus on how best to characterize and assess digital excellence in hospitals.

OBJECTIVE

Our aim was to develop an international agreement on a defined set of technological capabilities to assess digital excellence in hospitals.

METHODS

We conducted a two-stage international modified electronic Delphi (eDelphi) consensus-building exercise, which included a qualitative analysis of free-text responses. In total, 31 international health informatics experts participated, representing clinical, academic, public, and vendor organizations.

RESULTS

We identified 35 technological capabilities that indicate digital excellence in hospitals. These are divided into two categories: (a) capabilities within a hospital (n=20) and (b) capabilities enabling communication with other parts of the health and social care system, and with patients and carers (n=15). The analysis of free-text responses pointed to the importance of nontechnological aspects of digitally enabled change, including social and organizational factors. Examples included an institutional culture characterized by a willingness to transform established ways of working and openness to risk-taking. The availability of a range of skills within digitization teams, including technological, project management and business expertise, and availability of resources to support hospital staff, were also highlighted.

CONCLUSIONS

We have identified a set of criteria for assessing digital excellence in hospitals. Our findings highlight the need to broaden the focus from technical functionalities to wider digital transformation capabilities.

Evaluating Digital Maturity and Patient Acceptability of Real-Time Patient Experience Feedback Systems: Systematic Review

Background

One of the essential elements of a strategic approach to improving patients’ experience is to measure and report on patients’ experiences in real time. Real-time feedback (RTF) is increasingly being collected using digital technology; however, there are several factors that may influence the success of the digital system.

Objective

The aim of this review was to evaluate the digital maturity and patient acceptability of real-time patient experience feedback systems.

Methods

We systematically searched the following databases to identify papers that used digital systems to collect RTF: The Cochrane Library, Global Health, Health Management Information Consortium, Medical Literature Analysis and Retrieval System Online, EMBASE, PsycINFO, Web of Science, and CINAHL. In addition, Google Scholar and gray literature were utilized. Studies were assessed on their digital maturity using a Digital Maturity Framework on the basis of the following 4 domains: capacity/resource, usage, interoperability, and impact. A total score of 4 indicated the highest level of digital maturity.

Results

RTF was collected primarily using touchscreens, tablets, and Web-based platforms. Implementation of digital systems showed acceptable response rates and generally positive views from patients and staff. Patient demographics according to RTF responses varied. An overrepresentation existed in females with a white predominance and in patients aged ≥65 years. Of 13 eligible studies, none had digital systems that were deemed to be of the highest level of maturity. Three studies received a score of 3, 2, and 1, respectively. Four studies scored 0 points. While 7 studies demonstrated capacity/resource, 8 demonstrated impact. None of the studies demonstrated interoperability in their digital systems.

Conclusions

Patients and staff alike are willing to engage in RTF delivered using digital technology, thereby disrupting previous paper-based feedback. However, a lack of emphasis on digital maturity may lead to ineffective RTF, thwarting improvement efforts. Therefore, given the potential benefits of RTF, health care services should ensure that their digital systems deliver across the digital maturity continuum.

A Patient-Centered Framework for Evaluating Digital Maturity of Health Services: A Systematic Review

Background

Digital maturity is the extent to which digital technologies are used as enablers to deliver a high-quality health service. Extensive literature exists about how to assess the components of digital maturity, but it has not been used to design a comprehensive framework for evaluation. Consequently, the measurement systems that do exist are limited to evaluating digital programs within one service or care setting, meaning that digital maturity evaluation is not accounting for the needs of patients across their care pathways.

Objective

The objective of our study was to identify the best methods and metrics for evaluating digital maturity and to create a novel, evidence-based tool for evaluating digital maturity across patient care pathways.

Methods

We systematically reviewed the literature to find the best methods and metrics for evaluating digital maturity. We searched the PubMed database for all papers relevant to digital maturity evaluation. Papers were selected if they provided insight into how to appraise digital systems within the health service and if they indicated the factors that constitute or facilitate digital maturity. Papers were analyzed to identify methodology for evaluating digital maturity and indicators of digitally mature systems. We then used the resulting information about methodology to design an evaluation framework. Following that, the indicators of digital maturity were extracted and grouped into increasing levels of maturity and operationalized as metrics within the evaluation framework.

Results

We identified 28 papers as relevant to evaluating digital maturity, from which we derived 5 themes. The first theme concerned general evaluation methodology for constructing the framework (7 papers). The following 4 themes were the increasing levels of digital maturity: resources and ability (6 papers), usage (7 papers), interoperability (3 papers), and impact (5 papers). The framework includes metrics for each of these levels at each stage of the typical patient care pathway.

Conclusions

The framework uses a patient-centric model that departs from traditional service-specific measurements and allows for novel insights into how digital programs benefit patients across the health system.

Trial Registration

N/A