Optimizing Throughput in Clinical Practice: Lean Management and Efficient Care in Plastic and Reconstructive Surgery.
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.
[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.
추출된 의학 개체 (NER)
| 유형 | 영어 표현 | 한국어 / 풀이 | UMLS CUI | 출처 | 등장 |
|---|---|---|---|---|---|
| 시술 | flap
|
피판재건술 | dict | 1 | |
| 해부 | Lean
|
scispacy | 1 | ||
| 합병증 | flap type
|
scispacy | 1 | ||
| 약물 | [BACKGROUND]
|
scispacy | 1 | ||
| 약물 | [CONCLUSIONS]
|
scispacy | 1 | ||
| 질환 | Comorbidity
|
C0009488
Comorbidity
|
scispacy | 1 | |
| 기타 | patients
|
scispacy | 1 | ||
| 기타 | patient
|
scispacy | 1 |
MeSH Terms
Adult; Aged; Appointments and Schedules; Efficiency, Organizational; Female; Humans; Male; Middle Aged; Operating Rooms; Operative Time; Outpatient Clinics, Hospital; Practice Patterns, Physicians'; Plastic Surgery Procedures; Retrospective Studies; Surgery, Plastic
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