1. Optimizing Throughput in Clinical Practice: Lean Management and Efficient Care in Plastic and Reconstructive Surgery
- Author
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David H. Song, Jenna C. Bekeny, Kenneth L. Fan, Doron Klein, and Elizabeth Malphrus
- Subjects
Adult ,Male ,Operating Rooms ,Outpatient Clinics, Hospital ,Operative Time ,MEDLINE ,030230 surgery ,Efficiency, Organizational ,Lean manufacturing ,03 medical and health sciences ,Appointments and Schedules ,0302 clinical medicine ,Health care ,Medicine ,Outpatient clinic ,Humans ,Operations management ,Time point ,Practice Patterns, Physicians' ,Surgery, Plastic ,Throughput (business) ,Point of care ,Aged ,Retrospective Studies ,business.industry ,Retrospective cohort study ,Middle Aged ,Plastic Surgery Procedures ,030220 oncology & carcinogenesis ,Surgery ,Female ,business - Abstract
BACKGROUND As the cost of health care continues to rise, the role of medical providers has evolved to include the duties of an operations manager. Two theories of operations management can be readily applied to health care-lean management, the process of identifying and eliminating waste; and Little's law, the idea that throughput is maximized by changing the capacity to host patients or the time they spend in the system. Equipped with theories of operations management, providers are better able to identify and address flow limitations in their own practices. METHODS Operations flow data were collected from three areas of care-clinic, surgical booking, and the operating room-for one provider. Variables of interest included visit or procedure characteristics and operations flow characteristics, such as different time points involved in the sector of care. RESULTS Clinic data were collected from 48 patients. Variables with a significant relationship to total clinic visit time included afternoon appointments (p = 0.0080) and visit type (p = 0.0114). Surgical booking data were collected for 127 patients. Shorter estimated procedure length (p = 0.0211) decreased time to surgery. Operating room data were collected for 65 cases. Variables with a significant relationship to total operating room time were patient age (p = 0.0325), Charlson Comorbidity Index (p = 0.0039), flap type (p = 0.0153), and number of flaps (p < 0.0001). CONCLUSIONS This brief single-provider study provides examples of how to apply operations management theories to each point of care within one's own practice. Although longitudinal data following patients through each point of care are the next step in operations flow analysis, this work lays the foundation for evaluation at each time point with the goal of developing practical strategies to improve throughput in one's practice.
- Published
- 2021