Abstract / Description of output
Breathlessness is a common clinical presentation, accounting for a quarter of all emergency hospital attendances. As a complex undifferentiated symptom, it may be caused by dysfunction in multiple body systems. Electronic health records are rich with activity data to inform clinical pathways from undifferentiated breathlessness to specific disease diagnoses. These data may be amenable to process mining, a computational technique that uses event logs to identify common patterns of activity. We reviewed use of process mining and related techniques to understand clinical pathways for patients with breathlessness.
We searched the literature from two perspectives: studies of clinical pathways for breathlessness as a symptom, and those focussed on pathways for respiratory and cardiovascular diseases that are commonly associated with breathlessness. The primary search included PubMed, IEEE Xplore and ACM Digital Library. We included studies if breathlessness or a relevant disease was present in combination with a process mining concept. We excluded non-English publications, and those focussed on biomarkers, investigations, prognosis, or disease progression rather than symptoms. Eligible articles were screened before full-text review.
Of 1,400 identified studies, 1,332 studies were excluded through screening and removal of duplicates. Following full-text review of 68 studies, 13 were included in qualitative synthesis, of which two (15%) were symptom and 11 (85%) disease focused. While studies reported highly varied methodologies, only one included true process mining, using multiple techniques to explore Emergency Department clinical pathways. Most included studies trained and internally validated within single-centre datasets, limiting evidence for wider generalisability.
Our review has highlighted a lack of clinical pathway analyses for breathlessness as a symptom, compared to disease-focussed approaches. Process mining has potential application in this area, but has been under-utilised in part by data interoperability challenges. There is an unmet research need for larger, prospective multicentre studies of patient pathways following presentation with undifferentiated breathlessness.
We searched the literature from two perspectives: studies of clinical pathways for breathlessness as a symptom, and those focussed on pathways for respiratory and cardiovascular diseases that are commonly associated with breathlessness. The primary search included PubMed, IEEE Xplore and ACM Digital Library. We included studies if breathlessness or a relevant disease was present in combination with a process mining concept. We excluded non-English publications, and those focussed on biomarkers, investigations, prognosis, or disease progression rather than symptoms. Eligible articles were screened before full-text review.
Of 1,400 identified studies, 1,332 studies were excluded through screening and removal of duplicates. Following full-text review of 68 studies, 13 were included in qualitative synthesis, of which two (15%) were symptom and 11 (85%) disease focused. While studies reported highly varied methodologies, only one included true process mining, using multiple techniques to explore Emergency Department clinical pathways. Most included studies trained and internally validated within single-centre datasets, limiting evidence for wider generalisability.
Our review has highlighted a lack of clinical pathway analyses for breathlessness as a symptom, compared to disease-focussed approaches. Process mining has potential application in this area, but has been under-utilised in part by data interoperability challenges. There is an unmet research need for larger, prospective multicentre studies of patient pathways following presentation with undifferentiated breathlessness.
Original language | English |
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Journal | PLOS Digital Health |
DOIs | |
Publication status | Published - 26 May 2022 |