Healthcare professional and manager perceptions on drivers, benefits, and challenges of telemedicine: results from a cross-sectional survey in the Italian NHS.

BACKGROUND: The Covid-19 pandemic provided new challenges and opportunities for patients and healthcare providers while accelerating the trend of digital healthcare transformation. This study explores the perspectives of healthcare professionals and managers on (i) drivers to the implementation of telemedicine services and (ii) perceived benefits and challenges related to the use of telemedicine across the Italian National Health Service. METHODS: An online cross-sectional survey was distributed to professionals working within 308 healthcare organisations in different Italian regions. Quantitative and qualitative data were collected through a self-administered questionnaire (June-September 2021). Responses were analysed using summary statistics and thematic analysis. RESULTS: Key factors driving the adoption of telemedicine have been grouped into (i) organisational drivers (reduce the virus spread-80%; enhance care quality and efficiency-61%), (ii) technological drivers (ease of use-82%; efficacy and reliability-64%; compliance with data governance regulations-64%) and (iii) regulatory drivers (regulations' semplification-84%). Nearly all respondents perceive telemedicine as useful in improving patient care (96%). The main benefits reported by respondents are shorter waiting lists, reduced Emergency Department attendance, decreased patient and clinician travel, and more frequent patient-doctor interactions. However, only 7% of respondents believe that telemedicine services are more effective than traditional care and 66% of the healthcare professionals believe that telemedicine can't completely substitute in-person visits due to challenges with physical examination and patient-doctor relationships. Other reported challenges include poor quality and interoperability of telemedicine platforms and scarce integration of telemedicine with traditional care services. Moreover, healthcare professionals believe that some groups of patients experience difficulties in accessing and using the technologies due to socio-cultural factors, technological and linguistic challenges and the absence of caregivers. CONCLUSIONS: Respondents believe that telemedicine can be useful to complement and augment traditional care. However, many challenges still need to be overcome to fully consider telemedicine a standard of care. Strategies that could help address these challenges include additional regulations on data governance and reimbursements, evidence-based guidelines for the use of telemedicine, greater integration of tools and processes, patient-centred training for clinicians, patient-facing material to assist patients in navigating virtual sessions, different language options, and greater involvement of caregivers in the care process.

How Can Interactive Process Discovery Address Data Quality Issues in Real Business Settings? Evidence from a Case Study in Healthcare.

The focus of this paper is on how data quality can affect business process discovery in real complex environments, which is a major factor determining the success in any data-driven Business Process Management project. Many real-life event logs, especially healthcare ones, can suffer from several data quality issues, some of which cannot be solved by pre-processing or data cleaning techniques, leading to inaccurate results. We take an innovative Process Mining (PM) approach, termed Interactive Process Discovery (IPD), which combines domain knowledge with available data. This approach can overcome the limitations of noisy and incomplete event logs by putting "humans in the loop", leading to improved business process modelling. This is particularly valuable in healthcare, where physicians have a tacit domain knowledge not available in the event log, and, thus, difficult to elicit. We conducted a two-step approach based on a controlled experiment and a case study in an Italian hospital. At each step, we compared IPD with traditional PM techniques to assess the extent to which domain knowledge helps to improve the accuracy of process models. The case study tests the effectiveness of IPD to uncover knowledge-intensive processes extracted from noisy real-life event logs. The evaluation has been carried out by exploiting a real dataset of an Italian hospital, involving the medical staff. IPD can produce an accurate process model that is fully compliant with the clinical guidelines by addressing data quality issues. Accurate and reliable process models can support healthcare organizations in detecting process-related issues and in taking decisions related to capacity planning and process re-design.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.