| Literature DB >> 25426372 |
Hani Sinno1, Tassos Dionisopoulos1, Sumner A Slavin1, Ahmed M S Ibrahim1, Kevin C Chung1, Samuel J Lin1.
Abstract
SUMMARY: Outcome studies help provide the evidence-based science rationalizing treatment end results that factor the experience of patients and the impact on society. They improve the recognition of the shortcoming in clinical practice and provide the foundation for the development of gold standard care. With such evidence, health care practitioners can develop evidence-based justification for treatments and offer patients with superior informed consent for their treatment options. Furthermore, health care and insurance agencies can recognize improved cost-benefit options in the purpose of disease prevention and alleviation of its impact on the patient and society. Health care outcomes are ultimately measured by the treatment of disease, the reduction of symptoms, the normalization of laboratory results and physical measures, saving a life, and patient satisfaction. In this review, we outline the tools available to measure outcomes in plastic surgery and subsequently allow the objective measurements of plastic surgical conditions. Six major outcome categories are discussed: (1) functional measures; (2) preference-based measures and utility outcome scores; (3) patient satisfaction; (4) health outcomes and time; (5) other tools: patient-reported outcome measurement information system, BREAST-Q, and Tracking Operations and Outcomes for Plastic Surgeons; and (6) cost-effectiveness analysis. We use breast hypertrophy requiring breast reduction as an example throughout this review as a representative plastic surgical condition with multiple treatments available.Entities:
Year: 2014 PMID: 25426372 PMCID: PMC4229293 DOI: 10.1097/GOX.0000000000000104
Source DB: PubMed Journal: Plast Reconstr Surg Glob Open ISSN: 2169-7574
Fig. 1.Tools used in outcome studies. Five general subdivisions can be used to categorize outcome studies. A definition and examples are provided below each subdivision.
Fig. 2.Example of the standard gamble survey for monocular blindness. To the left are smiley faces and Xs that are visual representatives for percentage chance of life and death, respectively. The case scenarios are provided again for each frame.
Fig. 3.Example of the time trade-off survey for monocular blindness. To the left are smiley faces and Xs that are visual representatives for years of life and death, respectively. The case scenarios are provided again for each frame.
Fig. 4.Example of the visual analogue scale for blindness. A horizontal bar with a cursor is provided for the volunteers to slide from 0 to 100. The case scenarios are provided again for each frame.
Fig. 5.Example of EuroQol survey. Five subdivisions of life quality are assessed including (1) mobility, (2) self-care, (3) usual activities, (4) pain/discomfort, and (5) anxiety/depression.