Surgical Scheduling Errors During Manual Data Transfer.

IF 1.2 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES
Timothy Davis, Tony Ong, Terry Nguyen, Adrienne Dang, Anil Chaganti, Stephanie Jones, Jungjae Lim, Akash Bajaj, Ramana Naidu, Richard Paicius, Sanjay Khurana
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引用次数: 0

Abstract

Background and objectives: Retrospective studies examining errors within a surgical scheduling setting do not fully represent the effects of human error involved in transcribing critical patient health information (PHI). These errors can negatively impact patient care and reduce workplace efficiency due to insurance claim denials and potential sentinel events. Previous reports underscore the burden physicians face with prior authorizations which may lead to serious adverse events or the abandonment of treatment due to these delays. This study simulates the process of PHI transfer during surgical scheduling to examine the error rate of experienced schedulers when manually transferring PHI from surgical forms into electronic health records (EHR).

Methods: Participants (n = 50) manually input PHI from four surgical scheduling forms into a simulated EHR form. Eight critical data points were identified and defined as data that delay claim approvals and payments. Subjects were randomly assigned to either a control (18 minutes) or experimental (10 minutes) group. Transcription errors were flagged to measure the percentage of incorrectly inputted data fields. Two-tailed t-tests were used to determine statistical significance (P < .05).

Results: 100% of subjects in both cohorts had at least one or more errors in every form. The 10-minute cohort had a higher average "critical errors" rate than the 18-minute cohort (P = .03). Of the 200 forms completed, 171 forms contained 1 or more "critical errors," resulting in a potential 85.5% delay or denial in authorization or payments. The highest incidence of critical errors across all fields occurred with ICD-10 codes, CPT codes, authorization number, procedure, and insurance ID number. As critical errors fields of authorization number and insurance ID often lead to automatic denials, not only are they more susceptible to transcription error due to alphanumeric values but more indicative of delays in treatment.

Conclusions: These findings reveal a clear "pain point" in the routine scheduling process that leads to authorization and payment denials. With various touch points of manual data transfer in surgical scheduling, data degradation due to human error may compound at each step. Health care institutions should consider adopting digital solutions and investing in training programs to optimize clinical practice efficiency and reduce the possibility of inaccurate manual PHI transfer. Future case studies on denied payments will help further elucidate the economic impact on practices, as well as inform strategic decisions by those who directly handle health care management.

人工数据传输过程中的手术调度错误。
背景和目的:回顾性研究检查手术调度设置中的错误并不能完全代表转录关键患者健康信息(PHI)中涉及的人为错误的影响。由于保险索赔拒绝和潜在的哨兵事件,这些错误可能会对患者护理产生负面影响,并降低工作效率。以前的报告强调,医生面临的负担是事先批准的,这可能导致严重的不良事件或因这些延误而放弃治疗。本研究模拟了在手术调度过程中PHI转移的过程,以检查有经验的调度人员在手动将PHI从手术表格转移到电子健康记录(EHR)时的错误率。方法:参与者(n = 50)手动将四个手术调度表中的PHI输入到模拟的电子病历表中。确定了8个关键数据点,并将其定义为延迟索赔批准和付款的数据。受试者被随机分为对照组(18分钟)和实验组(10分钟)。转录错误被标记以测量错误输入数据字段的百分比。使用双尾t检验来确定统计显著性(P)结果:两个队列中100%的受试者在每种形式中至少有一个或多个错误。10分钟队列的平均“严重错误”率高于18分钟队列(P = .03)。在完成的200个表单中,171个表单包含一个或多个“严重错误”,导致85.5%的潜在延迟或拒绝授权或付款。在ICD-10代码、CPT代码、授权号、程序和保险ID号的所有字段中,严重错误的发生率最高。由于授权号和保险ID的关键错误字段经常导致自动拒绝,它们不仅更容易由于字母数字值而导致转录错误,而且更容易指示治疗延迟。结论:这些发现揭示了常规调度过程中明显的“痛点”,导致授权和付款拒绝。在手术调度中,由于人工数据传输的接触点不同,由于人为错误导致的数据退化可能在每一步都加剧。医疗机构应考虑采用数字解决方案并投资培训计划,以优化临床实践效率,减少人工PHI传递不准确的可能性。未来关于拒绝付款的案例研究将有助于进一步阐明对做法的经济影响,并为直接处理卫生保健管理的人员的战略决策提供信息。
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来源期刊
Quality Management in Health Care
Quality Management in Health Care HEALTH CARE SCIENCES & SERVICES-
CiteScore
1.90
自引率
8.30%
发文量
108
期刊介绍: Quality Management in Health Care (QMHC) is a peer-reviewed journal that provides a forum for our readers to explore the theoretical, technical, and strategic elements of health care quality management. The journal''s primary focus is on organizational structure and processes as these affect the quality of care and patient outcomes. In particular, it: -Builds knowledge about the application of statistical tools, control charts, benchmarking, and other devices used in the ongoing monitoring and evaluation of care and of patient outcomes; -Encourages research in and evaluation of the results of various organizational strategies designed to bring about quantifiable improvements in patient outcomes; -Fosters the application of quality management science to patient care processes and clinical decision-making; -Fosters cooperation and communication among health care providers, payers and regulators in their efforts to improve the quality of patient outcomes; -Explores links among the various clinical, technical, administrative, and managerial disciplines involved in patient care, as well as the role and responsibilities of organizational governance in ongoing quality management.
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