Can process mapping and a multisite Delphi of perioperative professionals inform our understanding of system-wide factors that may impact operative risk?

Abstract

Objectives: To examine whether the use of process mapping and a multidisciplinary Delphi can identify potential contributors to perioperative risk. We hypothesised that this approach may identify factors not represented in common perioperative risk tools and give insights of use to future research in this area.

Design: Multidisciplinary, modified Delphi study.

Setting: Two centres (one tertiary, one secondary) in the UK during 2020 amidst coronavirus pressures.

Participants: 91 stakeholders from 23 professional groups involved in the perioperative care of older patients. Key stakeholder groups were identified via process mapping of local perioperative care pathways.

Results: Response rate ranged from 51% in round 1 to 19% in round 3. After round 1, free text suggestions from the panel were combined with variables identified from perioperative risk scores. This yielded a total of 410 variables that were voted on in subsequent rounds. Including new suggestions from round two, 468/519 (90%) of the statements presented to the panel reached a consensus decision by the end of round 3. Identified risk factors included patient-level factors (such as ethnicity and socioeconomic status), and organisational or process factors related to the individual hospital (such as policies, staffing and organisational culture). 66/160 (41%) of the new suggestions did not feature in systematic reviews of perioperative risk scores or key process indicators. No factor categorised as 'organisational' is currently present in any perioperative risk score.

Conclusions: Through process mapping and a modified Delphi we gained insights into additional factors that may contribute to perioperative risk. Many were absent from currently used risk stratification scores. These results enable an appreciation of the contextual limitations of currently used risk tools and could support future research into the generation of more holistic data sets for the development of perioperative risk assessment tools.

Keywords: ANAESTHETICS; QUALITATIVE RESEARCH; Risk management; STATISTICS & RESEARCH METHODS; SURGERY.

Figure 1

Project stages. Process mapping was performed with a steering group of experienced professionals, with maps iterated between brainstorming interviews. At the conclusion of this stage two outputs were generated—the maps themselves and a stakeholder diagram showing the viewpoints we sought to capture in our Delphi. The Delphi was conducted across three rounds with the first seeking free text suggestions from the panel. These were combined with risk factors featuring in a systematic review of common perioperative risk tools. All suggestions were then voted on by the panel across two further rounds to gain consensus. Our final consensus list of risk factors is available in online supplemental file 2. N=number of risk factors gained from each source.

Figure 2

Simplified process map of a patient referred for elective vascular surgery at our institution. Blue boxes highlight preoperative care, green intraoperative care, orange postoperative care. Boxes indicate processes, diamonds indicate decision points. Dashed lines indicate boundary between community and hospital. Stakeholders (eg, anaesthetist) are shown in bold text. Lower panel highlights more granular view of numbered processes including revisions to initial diagram following discussions with a steering group of perioperative professionals. Fully granular maps for elective and emergency pathways are available in the online supplemental file 1. OIR, overnight intensive recovery (level 2 postanaesthesia care unit (PACU) for high-risk patients). GP, General Practitioner; HDU, High Dependency Unit; ITU, Intensive Therapy Uniit; NH, Nursing Home; RH, Residential Home; RRT, Rapid Response Team (Outreach).

Figure 3

Stakeholder diagram. Stakeholder groups identified for representation on a Delphi panel to understand what defines a high-risk surgical patient and impacts on their outcome. All groups were identified by a collaborative process mapping exercise with a steering group of key perioperative professionals. Diagram template adapted from the ‘Improving Improvement Toolkit’ available at www.iitoolkit.com, used with permission. ED, emergency department; HCA, healthcare assistant; OT, occupational therapist; PACU, postanaesthesia care unit; PAU, preassessment unit.

Figure 4

Delphi structure showing main risk factor groups identified through participant suggestions and the literature. The questionnaire enabled people to vote on three broad domains (patient, admission, organisation) and relevant groups (black text in lozenges). Many of these groups had relevant subgroups (white text). Participants could also vote on individual data elements (variables or their definitions) within each of these. Full list of these is available in the online supplemental file 2.

Figure 5

Representation of the Delphi questionnaires as a dendrogram, demonstrating hierarchical organisation of questions. Colours represent broad domains of statements being voted on by the panel; pertaining to a patient, circumstances of admission or those pertaining to the organisation caring for them. Final questions that were voted on are represented by terminal leaves. Branch points represent questionnaire structure. In panel A, expanded nodes represent those variables derived from a systematic review of commonly used perioperative risk scores. In panel B, expanded nodes represent those that reached criteria for consensus inclusion in a data set seeking to understand drivers of perioperative risk in older people.