Document Type

Dissertation

Degree

Doctor of Business Administration

Major

Business Administration

Date of Defense

7-22-2022

Graduate Advisor

L. Doug Smith, PhD

Committee

Ekin Pellegrini, PhD

Dinesh Mirchandani, PhD

Abstract

Major healthcare systems and hospital organizations face a myriad of challenges in today’s business environment, having to provide very complex and more comprehensive medical care with fewer resources. In this study, we investigate determinants of hospital performance in critical dimensions and propose an information infrastructure intended to promote excellence in clinical performance while sustaining a solid financial footing.

Senior executives must be knowledgeable in both business and clinical aspects of hospital administration because their decisions ultimately affect patient care and clinical outcomes. Key performance indicators (KPI) are necessary on both dimensions to inform their decisions. Financial and operational aspects of hospital performance are tied to physical resources, staffing and services rendered, development projects and growth of the institution. Clinical aspects pertain to the care provided to patients and are represented by metrics such as death rates, infection rates, readmission rates, and patient-satisfaction surveys. These measures are affected by patient characteristics as well as services rendered. A thorough understanding of KPIs and their potential roles in effecting change for excellence in organizational performance is vital for hospital administrators.

We build multivariate statistical models to assess hospital performance considering institutional characteristics and the populations they serve. Deviations from “adjusted norms” derived from these models reveal areas where an institution’s performance exceeds or falls below expectation or national standards. In addition, it allows for true inter-hospital comparisons.

Upper Echelons Theory states that, “organizational outcomes – strategic choices and performance levels – are partially predicted by managerial background characteristics.” To assess extant evidence of this, we identify high and low performing hospitals with our proposed metrics and investigate whether there is a difference between these groups with respect to the training of senior management and the composition of the executive suite.

Using our proposed metrics, we are unable to conclude that the training of senior management or the composition of the executive suite affects hospital performance. To guide strategic initiatives and improve control, we develop an ecosystem using KPIs that align with spheres of managerial responsibility for hospitals and propose them as an alternative to published “hospital star ratings” reported by third parties.

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