Risk Factors for Wrong-Site Surgery: A Study of 1,166 Reports of Informed Consent and Schedule Errors

 

Introduction

Informed consent documents and procedural schedules, in combination with other sources of information, are commonly used by surgical teams to plan for and verify the accuracy of the planned procedure.^1–4 Numerous studies and investigations have shown that the accuracy of a consent document and the procedural schedule are critical components to preventing a wrong-site surgery.^1,5–10

 

Previous studies explored the frequency and/or rates of consent or schedule errors,^{1,2,5–7,11,13,21–23} but we were unable to identify any that measured the occurrence of both consent and schedule errors, error subtypes (e.g., side, procedure, site, and patient), and across a large sample of healthcare facilities. Based on communication with surgical services staff at hospitals and ambulatory surgical facilities (ASFs) in Pennsylvania, consent and schedule errors are a common and ongoing issue.

 

The purpose of this study was to use the Pennsylvania Patient Safety Reporting System (PA-PSRS) database,^[1] which receives event reports from all licensed hospitals and ASFs in Pennsylvania, to explore the occurrence of consent and schedule errors over a four-year period. We also evaluated error subtypes (side, procedure, site, and patient) and error occurrence by facility type (hospital or ASF). Finally, we provide a brief literature review of risk factors and strategies to mitigate risk of consent and schedule errors.

Methods

Data Source and Sample

We used data from reports of patient safety events that were submitted by hospitals and ASFs to the PA-PSRS acute care database, which is affiliated with the mandatory event reporting laws in Pennsylvania. The event reports include structured fields (e.g., event date, patient age, care area) and unstructured fields (i.e., free text), which are used by the reporter to describe the event and actions taken. The reports are often concise and do not include medical records.

The query and review of events for inclusion in the present study consisted of a two-phase process. In the first phase, we queried the PA-PSRS database for events that occurred within a four-year period (1/1/2019 to 12/31/2022) and met one or more of the following inclusion criteria:

• Event was classified within the PA-PSRS taxonomy as an Error Related to Procedure/Treatment/Test - Surgery/Invasive Procedure Problem and one of the following response options was selected: wrong site, wrong side (L vs R), wrong procedure, wrong patient, or preparation inadequate/wrong.

• Event was classified within the PA-PSRS taxonomy as Error Related to Procedure/Treatment/Test - Surgery/Invasive Procedure Problem and at least one of the unstructured fields contained the words “left” and “right” or “incis” and “excis.”^[2]

• Event was classified under the Surgical Services care area group^[3] and at least one of the unstructured fields contained any of the following phrases: “wrong site,” “wrong side,” “wrong level,” “wrong procedure,” “wrong patient,” “time out,” “incorrect side,” “incorrect site,” “incorrect procedure,” “incorrect patient,” “block,” or “mark.”

• Event was classified under the Surgical Services care area group and at least one of the unstructured fields contained any of the following combinations of phrases: “consent” or “schedul” and “wrong,” “incorrect,” or “error.”

In the second phase, one researcher reviewed each report to identify those that met the inclusion criteria by describing a consent and/or schedule error, an error subtype, and that the error corresponded with an invasive operative procedure. We defined an invasive operative procedure as “…skin or mucous membranes and connective tissue is incised or an instrument is introduced through a natural body orifice.”^16,24 We further defined the invasive operative procedure as beginning “regardless of setting, at the point of surgical incision; tissue puncture; or the insertion of an instrument into tissues, cavities, or organs” and ending “after counts have concluded, the surgical incision has been closed, and/or operative device(s) such as probes have been removed, regardless of setting.”^16,24 Based on the query criteria and review of event reports, a total of 1,166 reports were included in the study.

Design, Analysis, and Variables Coded

We used a retrospective mixed-methods design with an exploratory sequential approach,²⁵ where we began with a focus on the qualitative data and then quantified those data for further analysis. The qualitative data from PA-PSRS event reports were processed through a content analysis^26–29 using a framework method^25,30,31 with categories of variables that were developed deductively based on our prior study.³ The variables were measured by frequency and assessed using a descriptive analysis. Descriptive analysis is a quantitative method where phenomena are explored and patterns are identified with the purpose of better understanding and explaining the phenomena occurrence.^3,32 This is often achieved through visual presentation of the data that shows multiple combinations of variables and allows for a triangulation of insights.

The patient gender, patient age, event date, and facility type (hospital or ASF) were identified in structured fields of the reports. Through review of the unstructured fields, a researcher identified the error type (consent, schedule, or consent & schedule, which are mutually exclusive categories) and error subtype (side, procedure, site, or patient, which are mutually exclusive categories), which are both defined in Table 1.

Table 1.Definitions and Examples of Error Types and Subtypes.

Note: Details of the PA-PSRS event narratives have been modified for readability and to preserve confidentiality.

Results

Patient Age, Patient Gender, and Facility Type

Among the 1,166 event reports, 81% (950 of 1,166) identified the patient gender; 49% (462 of 950) were male and 51% (488 of 950) were female. Patient age had a mean of 55 years and a median of 61 years (minimum of <1 year, 25^th percentile of 45 years, 75^th percentile of 71 years, and a maximum of 99 years)^[4]. The 1,166 event reports were submitted by 104 hospitals and 56 ASFs.

Error Type and Subtype

See Figure 1 and Figure 2 for graphs that show the distribution of consent and/or schedule errors. The consent or schedule errors were identified as occurring alone in 90% (1,052 of 1,166) of the reports and concurrently in 10% (114 of 1,166) of the reports. Across a four-year period, 66% (772 of 1,166) of the event reports included a schedule error, either alone (56%, 658 of 1,166) or concurrent with a consent error (10%, 114 of 1,166). The consent errors were reported in 44% of the events (34% alone, 394 of 1,166; 10% concurrent with schedule errors, 114 of 1,166). Across each of the error types (consent and/or schedule), Figure 2 shows a year-over-year decrease with a similar pattern and proportion.

Figure 1.Frequency and Percentage of Error Type Across 2019–2022; N=1,166 PA-PSRS Event Reports.

Note: The categories of Error Type and Subtype are mutually exclusive per event report. Consent & Schedule=concurrent occurrence of both consent errors and schedule errors in a single event report.

Figure 2.Frequency of Error Type by Year; N=1,166 PA-PSRS Event Reports.

Note: The categories of Error Type and Subtype are mutually exclusive per event report.
Consent & Schedule=concurrent occurrence of both consent errors and schedule errors in a single event report.

Table 2 shows that error subtypes ranged in percentage and were ranked in the following order: side (69%, n=808), procedure (24%, n=281), site (4%, n=47), and patient (3%, n=30). This ranking of subtypes is identical within each category of error type: schedule, consent, and consent & schedule. Within each category of error subtype, the relative proportion of consent & schedule errors varied. For example, within the side subtype the schedule errors (n=466) were reported nearly two times more than the consent errors (n=252), but within the site subtype the schedule (n=21) and consent (n=23) errors were nearly equal. Across the categories of error type and subtype, the most frequent combination of errors was a schedule error that identified the wrong side (40%, n=466). In contrast, consent & schedule errors and wrong patient errors were the least frequent combination, which had a zero frequency across the total sample of event reports.

Table 2.Percentage and Frequency of Error Type and Subtype Across 2019–2022; N=1,166 PA-PSRS Event Reports.

Note: The categories of Error Type and Subtype are mutually exclusive per event report. The parenthetical numbers represent the frequency.
Consent & Schedule=concurrent occurrence of both consent errors and schedule errors in a single event report.

Facility Type by Error Type and Error Subtype

As presented in Figure 3, 86% (n=1,003) of events were reported by hospitals and 14% (n=163) by ASFs. Readers should note that our results only represent the distribution of events reported to PA-PSRS and may not represent the true distribution of occurrence across facilities.

Figure 3.Percentage and Frequency of Consent and/or Schedule Errors Across 2019–2022; N=1,166 PA-PSRS Event Reports.

Note: The figure only represents the distribution of events reported to PA-PSRS and may not represent the true distribution of occurrence at facilities.

Table 3a and Table 3b correspond with findings from hospitals and ASFs, respectively, and both show the distribution of error type and error subtype. A close review of Table 3a and Table 3b reveal a pattern of findings very similar to those shown in Table 2, which displays the error type and subtype collapsed across facility type. Despite the similarities in findings between the two facility types, there are a few noteworthy differences in the distributions across Table 3a and Table 3b that are highlighted below:

• Schedule errors were reported 9 percentage points greater at hospitals (58%, 578 of 1,003) than at ASFs (49%, 80 or 163).

• Side errors were reported 14 percentage points more at hospitals than at ASFs; however, procedure errors were 18 percentage points higher at ASFs (40%, 65 of 163) than at hospitals (22%, 216 of 1,003).

• Among the ASFs, the percentage of reports with a wrong-side schedule error (25%) was very similar to the percentage with a wrong-side consent error (23%). In contrast, at hospitals the wrong-side schedule errors (42%) were reported twice as often as the wrong-side consent errors (21%).

• For hospitals, the percentage of wrong-procedure schedule errors (11%) were comparable to the wrong-procedure consent errors (9%). The ASFs reported nearly twice as many wrong-procedure schedule errors (23%) than wrong-procedure consent errors (13%).

• Hospitals reported patient errors as being a small percentage of the distribution (3%, 30 of 1,003) and ASFs reported 0.

Table 3a.Hospitals Only: Percentage and Frequency of Error Type and Subtype Across 2019–2022; n=1,003 PA-PSRS Event Reports.

Table 3b.ASFs Only: Percentage and Frequency of Error Type and Subtype Across 2019–2022; n=163 PA-PSRS. Event Reports

Note: The categories of Error Type and Subtype are mutually exclusive per event report. The parenthetical numbers represent the frequency.
Consent & Schedule=concurrent occurrence of both consent and schedule errors in a single event report. The tables only represent the distribution of events reported to PA-PSRS and may not represent the true distribution of occurrence at facilities.

Discussion

Consent and schedule errors create inefficiencies^1,2,11,18,33 and additional costs in patient care^2,11,13 and are a risk factor for wrong-site surgery.^1,5–10 Our analysis, which presents findings across all combinations of error type, error subtype, and facility type, allows for a triangulation of variable relations and a more complete understanding of the distribution of consent and schedule errors. We believe that the results can be used by healthcare organizations as a basis for their own investigation into consent and schedule errors.

Our study revealed that schedule errors occurred more frequently than consent errors, which is inconsistent with previous research.¹ Our study expanded upon much of the previous literature by revealing the distribution of error types and subtypes across hospitals and ASFs. The distribution of error subtypes in our study (side, procedure, site, and patient) is similar with the occurrence reported in prior studies.^2,21,22

When comparing the error subtype distribution between our current study and our previous study on wrong-site surgery,³ we found similarities with side errors being the most frequent and patient errors as the least frequent; however, the occurrence of procedure errors and site errors was inconsistent across studies. This difference in distribution could be attributed to the lack of specificity in describing the site in the consent document and procedural schedule; therefore, a site error would be less likely to be detected.

Our results also show that there has been a decrease in reporting of consent and schedule errors from 2019 to 2022. It is unclear if this finding reflects a true reduction in errors and/or an underreporting of errors. Readers should note that all consent and schedule errors are mandatory reportable events under MCARE (Act 13 of 2002) within the commonwealth of Pennsylvania. Despite the possibility of underreporting,⁶ it remains the responsibility of each healthcare organization to ensure that their processes are adequately designed and staff are making efforts to detect and prevent the errors which create a risk for patient harm.

We recommend that stakeholders view Table 4 and Table 5 for a concise literature review of preprocedural factors (prior to patient’s arrival at procedural facility) that may increase the possibility of consent and schedule errors, and preprocedural strategies for mitigating the risk of those errors, respectively. The PA-PSRS event reports often lacked detail sufficient to pinpoint the factors that contributed to the event occurrence and/or strategies that the organization chose to mitigate risk; therefore, the content listed in the two tables was largely derived from a literature review of articles that ranged in levels of evidence, including expert opinion.³⁴ In addition to the items listed in Table 4 and Table 5, we recommend that readers review references 4, 11, 13, 35, and 36 for additional information related to the processes of informed consent and references 2, 4, 19, and 20 for additional information related to procedural schedules.

Table 4.Preprocedural Risk Factors That May Increase the Likelihood That Consent and Schedule Errors Occur and Are Undetected During the Preprocedural Phase.

Note: This list is comprised of preprocedural risk factors (prior to patient’s arrival at procedural facility) that could contribute to the occurrence of consent and schedule errors and the failure to detect those errors during the preprocedural phase. The risk factors in this list were largely derived from a literature review of articles that ranged in levels of evidence, including expert opinion.³⁴ *“Scheduler” refers to both the person at the provider’s office and the person at the facility where the procedure will be performed. **The risk factors corresponding with the “Both Consent and Schedule” error type could cause, independently or concurrently, consent and schedule errors and prevent detection of those errors.

Table 5.Preprocedural Strategies That May Reduce the Occurrence of Consent and Schedule Errors and Increase the Detection of Those Errors During the Preprocedural Phase

Note: This list is comprised of preprocedural strategies that were largely derived from a literature review of articles that ranged in levels of evidence, including expert opinion.³⁴ **The strategies corresponding with the “Both Consent and Schedule” error type could be effective in preventing and detecting both consent and schedule errors, which may occur independently or concurrently.

Limitations

Prior studies^{2,11,13,21–23} explored the rates of consent and/or schedule errors; however, we chose not to calculate rates for several reasons. First, a rate would reflect a reporting rate, not an occurrence rate, which could be misunderstood by the reader. Additionally, our definition of an invasive operative procedure^16,24 is broader than the inclusion criteria used by our reference procedural volume database (Pennsylvania Department of Health’s annual survey of Health Facilities),⁵² which could cause an erroneous estimation of the rate.

Through our previous study,³ we found that PA-PSRS reports of wrong-site surgery infrequently noted risk factors (i.e., factors that contributed to the occurrence of the event). Therefore, we chose not to explore the relation between consent and schedule errors and wrong-site surgery out of concern that the results would produce a substantial underestimation of the relation between the variables. Finally, we were unable to explore the frequency of consent and schedule errors according to clinician specialty and type of planned procedure due to those variables being infrequently reported in our sample of PA-PSRS reports.

Conclusions

Based on previous research, consent and schedule errors have been shown to create workflow inefficiencies, additional costs, and considerable risk for wrong-site surgery. Our analysis and results expand upon previous studies by showing a triangulation of variables across the occurrence of consent and schedule errors, error subtypes (side, procedure, site, and patient), and facility type. The findings reveal that the errors are an ongoing challenge in Pennsylvania and distribution of error types vary across hospitals and ambulatory surgical facilities. We believe that our data can be used as a basis for staff to investigate the prevalence of errors at their own facilities. We anticipate that provider offices, clinics, and hospitals will find value in Table 4 and Table 5, which provide a brief literature review of risk factors for consent and schedule errors, and strategies for preventing and detecting the occurrence of those errors, respectively. A review of the content in those tables reveals that there are many factors that may contribute to consent and schedule errors and that many of the strategies are interrelated and may require notable resources to implement. Nevertheless, we believe that the efforts and investments required to reduce the occurrence of those errors can both produce net financial benefits and ensure patient safety.

Disclosure

The authors declare that they have no relevant or material financial interests.

About the Authors

Matthew A. Taylor (MattTaylor@pa.gov) is a research scientist for the Patient Safety Authority (PSA), where he conducts research, uses data to identify patient safety concerns and trends, and develops solutions to prevent recurrence. He is a core team member of PSA’s Center of Excellence for Improving Diagnosis. Prior to joining the PSA, Taylor was a scientific writer and research specialist at the University of Pittsburgh School of Pharmacy, and he has served fellowships at the Centers for Disease Control and Prevention (CDC) and the VA Pittsburgh Healthcare System. His expertise in data analysis and research covers a range of topics, including patient safety, public health, employee training, process efficiency, human factors, workplace culture/climate, behavior change interventions, and organizational management.

Robert A. Yonash is a registered nurse and has been with the Patient Safety Authority (PSA) since 2009 as the patient safety advisor for the Southwest region of Pennsylvania, working with his regional medical facilities to assist them in the reduction and elimination of medical errors. In this role, Yonash has been assigned to a number of projects, including the statewide Centers for Medicare & Medicaid Services Partnership for Patients and the Hospital Engagement Networks Wrong-Site Surgery Prevention Collaboration and the PSA/Pennsylvania Society of Anesthesiologists Wrong-Site Block Initiative. He is a Core Team Lead for the PSA’s Center of Excellence for Improving Diagnosis, providing guidance and support for healthcare facilities, systems, providers, and patients to decrease harm from diagnostic errors. Yonash is a member of the American Society of Professionals in Patient Safety and has attained certification as a Certified Professional in Patient Safety (CPPS) and Certified Six Sigma Lean Green Belt in Healthcare. He is also a master trainer in TeamSTEPPS.