Identifying Candidate Predictors of Hospital-Acquired Pressure Injuries among Adult, Medical-Surgical Patients Using Clinical Expert Knowledge

PURPOSE: The purpose of this study was to identify clinically important candidate predictors of hospital-acquired pressure injuries among adult, medical-surgical patients. DESIGN: Modified Delphi technique. METHODS: Interdisciplinary clinicians were recruited for the expert panel, and multiple rounds were administered as electronic questionnaires using a modified Delphi approach. The opening round was informed by a literature review that was used to extract candidate predictors from prognostic model development studies of hospital-acquired pressure injury (HAPI). The panel evaluated clinical concepts by answering either "Yes" or "No" to whether each concept was "important" in the assessment of HAPI risk and categorized the concept as a predisposing or precipitating factor. RESULTS: The panel comprised 16 clinicians (8 physical/occupational therapists, 7 registered nurses, and 1 physician) from 2 large academic health care centers located in the US (Florida and California). The Delphi study comprised 3 rounds, with an overall attrition rate of 6.25%. The panel evaluated the clinical importance of 205 concepts that described HAPI risk. More than half of the panel agreed that 132 (64%) concepts were clinically "important," including 99 (75%) predisposing factors and 33 (25%) precipitating factors. Thirteen (6%) concepts reached 100% agreement. CONCLUSION: Variable selection is a key component of prognostic model development study. Based on expert recommendations that highlight the use of clinical expertise in variable selection, we conducted a rigorous consensus study to gather feedback from clinicians who were experts in assessing, preventing, and treating pressure injuries. The final compilation of 132 "important" concepts provides a foundation for designing new or refining existing HAPI risk assessment tools. Future research should focus on identifying which concepts are valid predictors of HAPI and integrating them into standardized risk assessment tools.