Digital Maturity as a Strategy for Advancing Patient Experience in US Hospitals.
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ABSTRACT:
SUBMITTER: Snowdon A
PROVIDER: S-EPMC10868476 | biostudies-literature | 2024
REPOSITORIES: biostudies-literature
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Digital Maturity as a Strategy for Advancing Patient Experience in US Hospitals.
Snowdon Anne A Hussein Abdulkadir A Olubisi Ajetunmobi A Wright Alexandra A
Journal of patient experience 20240214
Patient experience is globally recognized as an important indicator of health system performance, linked to health system quality and improving patient outcomes. Post COVID-19, health systems have embraced digital health and advanced digital transformation efforts; however, the relationship between digital health and patient experience outcomes is not well-documented. Using HCAHPS hospital survey data to measure patient experience, and HIMSS EMRAM Maturity Model data to measure digital maturity, ...[more]
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Project description:BackgroundOne 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.ObjectiveThe aim of this review was to evaluate the digital maturity and patient acceptability of real-time patient experience feedback systems.MethodsWe 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.ResultsRTF 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.ConclusionsPatients 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.
| S-EPMC6682271 | biostudies-literature
Project description:BackgroundDigital 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.ObjectiveThe aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals.MethodsA 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.ResultsThe 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.ConclusionsThe maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement.
| S-EPMC9008527 | biostudies-literature
Project description:BackgroundHealth 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.ObjectiveWe 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.MethodsA 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.ResultsDHI 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.ConclusionsThis 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.
| S-EPMC10394505 | biostudies-literature
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| S-EPMC11926443 | biostudies-literature
Project description:BackgroundThe digital transformation of health care is advancing rapidly. A well-accepted framework for health care improvement is the Quadruple Aim: improved clinician experience, improved patient experience, improved population health, and reduced health care costs. Hospitals are attempting to improve care by using digital technologies, but the effectiveness of these technologies is often only measured against cost and quality indicators, and less is known about the clinician and patient experience.ObjectiveThis study aims to conduct a systematic review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals.MethodsThe PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines were followed. The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched from January 2010 to June 2022. Studies that explored multidisciplinary clinician or adult inpatient experiences of digital hospitals (with a full electronic medical record) were included. Study quality was assessed using the Mixed Methods Appraisal Tool. Data synthesis was performed narratively for quantitative studies. Qualitative evidence synthesis was performed via (1) automated machine learning text analytics using Leximancer (Leximancer Pty Ltd) and (2) researcher-led inductive synthesis to generate themes.ResultsA total of 61 studies (n=39, 64% quantitative; n=15, 25% qualitative; and n=7, 11% mixed methods) were included. Most studies (55/61, 90%) investigated clinician experiences, whereas few (10/61, 16%) investigated patient experiences. The study populations ranged from 8 to 3610 clinicians, 11 to 34,425 patients, and 5 to 2836 hospitals. Quantitative outcomes indicated that clinicians had a positive overall satisfaction (17/24, 71% of the studies) with digital hospitals, and most studies (11/19, 58%) reported a positive sentiment toward usability. Data accessibility was reported positively, whereas adaptation, clinician-patient interaction, and workload burnout were reported negatively. The effects of digital hospitals on patient safety and clinicians' ability to deliver patient care were mixed. The qualitative evidence synthesis of clinician experience studies (18/61, 30%) generated 7 themes: inefficient digital documentation, inconsistent data quality, disruptions to conventional health care relationships, acceptance, safety versus risk, reliance on hybrid (digital and paper) workflows, and patient data privacy. There was weak evidence of a positive association between digital hospitals and patient satisfaction scores.ConclusionsClinicians' experience of digital hospitals appears positive according to high-level indicators (eg, overall satisfaction and data accessibility), but the qualitative evidence synthesis revealed substantive tensions. There is insufficient evidence to draw a definitive conclusion on the patient experience within digital hospitals, but indications appear positive or agnostic. Future research must prioritize equitable investigation and definition of the digital clinician and patient experience to achieve the Quadruple Aim of health care.
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Project description:IntroductionThis study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity.MethodsWe conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology.ResultsThe findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops.ConclusionOur findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.
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Project description:BackgroundThe adoption and use of technology have significantly changed health care delivery. Patient experience has become a significant factor in the entire spectrum of patient-centered health care delivery. Digital health facilitates further improvement and empowerment of patient experiences. Therefore, the design of digital health is served by insights into the barriers to and facilitators of digital patient experience (PEx).ObjectiveThis study aimed to systematically review the influencing factors and design considerations of PEx in digital health from the literature and generate design guidelines for further improvement of PEx in digital health.MethodsWe performed an umbrella systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched Scopus, PubMed, and Web of Science databases. Two rounds of small random sampling (20%) were independently reviewed by 2 reviewers who evaluated the eligibility of the articles against the selection criteria. Two-round interrater reliability was assessed using the Fleiss-Cohen coefficient (k1=0.88 and k2=0.80). Thematic analysis was applied to analyze the extracted data based on a small set of a priori categories.ResultsThe search yielded 173 records, of which 45 (26%) were selected for data analysis. Findings and conclusions showed a great diversity; most studies presented a set of themes (19/45, 42%) or descriptive information only (16/45, 36%). The digital PEx-related influencing factors were classified into 9 categories: patient capability, patient opportunity, patient motivation, intervention technology, intervention functionality, intervention interaction design, organizational environment, physical environment, and social environment. These can have three types of impacts: positive, negative, or double edged. We captured 4 design constructs (personalization, information, navigation, and visualization) and 3 design methods (human-centered or user-centered design, co-design or participatory design, and inclusive design) as design considerations.ConclusionsWe propose the following definition for digital PEx: "Digital patient experience is the sum of all interactions affected by a patient's behavioral determinants, framed by digital technologies, and shaped by organizational culture, that influence patient perceptions across the continuum of care channeling digital health." In this study, we constructed a design and evaluation framework that contains 4 phases-define design, define evaluation, design ideation, and design evaluation-and 9 design guidelines to help digital health designers and developers address digital PEx throughout the entire design process. Finally, our review suggests 6 directions for future digital PEx-related research.
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Project description:BackgroundDigital 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.ObjectiveThe 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.MethodsWe 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.ResultsWe 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.ConclusionsThe 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 registrationN/A.
| S-EPMC4850277 | biostudies-literature
Project description:While digital cardiac rehabilitation (CR) is an effective alternative to center-based CR, its components and mechanisms of change remain poorly understood. The Multiphase Optimization Strategy (MOST) provides a framework that allows the effects of individual components of complex interventions to be studied. There is limited guidance within MOST on how to develop a conceptual model. This article describes the development of a conceptual model of digital CR. The conceptual model was developed based on several strands of evidence: (i) a systematic review of 25 randomized controlled trials to identify the behavior change techniques in digital CR interventions, (ii) a qualitative study of patients' (n = 11) perceptions of the mechanisms of digital CR, and (iii) a review of international guidelines. Tools and frameworks from behavioral science, including the Behaviour Change Wheel, Capability, Opportunity, Motivation and Behavior model, and Theoretical Domains Framework were used to integrate the findings. An initial conceptual model of digital CR was developed and then refined through discussion. The conceptual model outlines the causal process through which digital CR can enhance outcomes for patients with cardiovascular disease. The model illustrates the key intervention components (e.g. goal setting and self-monitoring, education, exercise training), targeted outcomes (e.g. physical activity, healthy eating, medication adherence), and theorized mediating variables (e.g. knowledge, beliefs about capability). The article provides an example of how behavioral science frameworks and tools can inform the preparation phase of MOST. The developed conceptual model of digital CR will inform guide decision-making in a future optimization trial.
| S-EPMC11756285 | biostudies-literature