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Factors Associated with Operative Mortality in Medium Volume Congenital Heart Surgery Centers: A Mixed-Methods
Karl F Welke1, Erle H Austin2, Subramanyan R Kumar3
1Atrium Health Levine Children's Hospital, Wake Forest University School of Medicine.
Background:
An inverse relationship exists between congenital heart surgery center volume and mortality. However, mortality rates are heterogeneous within volume strata, and intra-stratum variability has not been studied. We studied medium volume centers (MVC, 75-200 annualized index cases/year) to identify factors associated with center-level mortality.
Methods:
We identified MVC from The STS Congenital Heart Surgery Public Reporting website (7/2019-6/2023). Surgical leaders were asked to complete a survey and a semi-structured interview. Topics included hospital demographics, organizational structure, resources, partner relationships, and multidisciplinary collaboration. A codebook was developed using a combined deductive-inductive approach. Interview transcripts were analyzed using reflexive thematic analysis. Centers were then stratified by overall O/E mortality ratios (> or < 1.0). Stratified data were reviewed, code summaries generated, and overarching patterns and themes identified.
Results:
Forty-two MVC were identified. Surgeon leaders from 36 centers (86%) completed the survey and 32 the interview (76%). Regardless of observed-to-expected (O/E) mortality ratios, team cohesion, technical skill, and experience, as well as accessible, supportive hospital administrations were considered critical. Leaders from centers with O/E<1 had stronger administrative support, funding, and dedicated resources, whereas leaders of programs with O/E>1 reported more communication challenges and administrative disconnects. Staffing shortages and inexperienced personnel were common challenges for both groups.
Conclusions:
Alignment with and support from hospital administration and provider team composition are associated with center-level mortality in MVC, yet these factors are not in databases used to evaluate performance. Understanding these factors is essential for defining program quality and guiding strategies to enhance performance.