Brief Review of Literature

Work 74 (2023) 327–339 DOI:10.3233/WOR-211221 IOS Press

327

How do medication errors occur in the nursing communication process? Investigating the relationship between error types and error factors

Haizhe Jina, Zhibin Xiaoa, Mingming Lia,∗, Quanwei Fub and Vincent G. Duffyc

aDepartment of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, China bDongguan Kanghua Hospital, Dongguan, China cSchool of Industrial Engineering, Purdue University, West Lafayette, IN, USA

Received 17 September 2021 Accepted 20 December 2021

Abstract. BACKGROUND: Human error types and error factors are two important elements of error analysis. Understanding the relationship between them can contribute to new case analyses, the tendency of error occurrence statistics, error factor identification, and prevention of error recurrence. OBJECTIVE: To provide evidence and guidance for the prevention and improvement of medication communication errors by quantitatively exploring the relationship between error types and error factors. METHODS: Data were collected on self-reported errors in the medication administration process by nurses in all departments of three cooperative medical institutions, and an error sheet of specified style was adopted. Error types were determined by the systematic human error reduction and prediction approach method and human cognition processes. Error factors were extracted using the root cause analysis combined with Berlo’s communication model, and the relationship between error types and error factors was quantitatively studied using the partial least-squares regression method. RESULTS: After a one-by-one analysis of 303 error cases, the communication errors occurring in the nursing medication process could be explained by six error types and 12 error factors. In addition, 20 correlation patterns between the error types and error factors were quantitatively obtained, and their path coefficient distributions ranged from 0.088 to 0.467. CONCLUSION: The results of this study may provide reference to understand errors and establish countermeasures from the statistics of error occurrence trends, extract error factors related to error types and determine key error factors.

Keywords: Medication error, nursing communication process, error type, error factor, healthcare

1. Introduction

Healthcare is a complex, variable, and unpre- dictable professional activity system [1, 2]. Medical

∗Address for correspondence: Mingming Li, Doctoral Student, Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195 Chuangxin Road, Hunnan District, Shenyang 110167, China. E-mail: [email protected].

errors occasionally occur when medical personnel conduct complex professional operations during the medical processes and it is mainly caused by human errors [3, 4]. Medication processes refer to the entire operational process of medication, including drug prescription, dispensing, administration, and obser- vation after administration. Medication errors in nursing (MEs-N) account for a high proportion of all medical errors [5, 6]. Multiple departments with

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328 H. Jin et al. / Investigating the relationship between error types and error factors

different operational characteristics coexist within a medication process; therefore, communication is very important in healthcare, and patient safety can be affected by communication errors [7, 8]. A previous report pointed out that MEs-N caused by commu- nication problems were proportionately higher [9]. Therefore, reducing communication errors in the nursing medication process is crucial for ensuring patient safety [9, 10].

The following questions should be answered to improve the understanding of communication errors in the medication administration process. First, which types of errors may occur in the medical communica- tion process? This can be determined by classifying medical errors based on their characteristics (error types). Second, why do such errors occur? Factors that result in errors during the operational process should be extracted to answer this question (error factors).

The error types are used to summarize the errors, the granularity of the error types depends on the expression level of errors [5, 6]. For example, the expression of error types can be systematic, behavioral, or psychological [11]. The nursing com- munication error in the medication administration process is the deviation of the expected commu- nication behavior from the actual communication behavior [12]. Therefore, in this study, communica- tion error types are defined as the classification of error behavior characteristics from the perspective of the deviation between expected communica- tion behavior and actual communication behavior. Observing human errors in healthcare, Mitchell et al. divided these errors into four categories (medi- cal delivery, medical equipment, complications, and care), each with several subcategories [13]. Although these classifications of error types can include com- munication errors, they lack relevance and specificity for research on communication errors. The system- atic human error reduction and prediction approach (SHERPA) is a human error identification technology that proposes error classification and combines hier- archical task analysis to identify possible errors in human activities [14, 15]. It has the characteristics of structure, comprehensiveness, and easy application, and is widely used to identify human error in various fields. Kirwan compared SHERPA, cognitive reliabil- ity error analysis, generic error modeling system, HEI in systems tool, predictive human error analysis, and other human error recognition technologies, and pro- posed that SHERPA has the best overall performance [16]. The SHERPA technology is also widely used in

the medical field. For example, Ghiyasi et al. used the SHERPA method to evaluate and analyze the human error of nurses in the emergency department [17]. The SHERPA model divides human error into five categories: action errors, checking errors, retrieval errors, communication errors, and selection errors, and each category contains several error types. The communication category is divided into three error types: information not obtained, wrong information communicated, and incomplete information commu- nicated [15]. To summarize, the SHERPA model has a wide range of applications in the classification of human errors, and it is also applicable to the medical field.

Here, the phrase “error factors” refers to the causes of errors. Regarding the error factors that influ- ence healthcare, Handayani et al. proposed that the two main factors inducing medication administration errors were the safety culture of medical institutions and the understanding of patients’ families on medi- cal treatment [18]. Thomas et al. proposed that the complexity of nurses’ work, interruption of work, and high workload were the main factors induc- ing medical errors [19]. Brigitta et al. proposed that ineffective communication, work environment, and human factors were the main factors causing the occurrence of medication administration errors in nurses [9]. In conclusion, the current studies on error factors mainly focused on safety culture, organiza- tional management, and work environment, and did not pay enough attention to the operation process. Good results were produced by good operational pro- cesses [20]. Medical errors were the embodiment of operational process defects, and the extraction of error factors from the perspective of operational processes was an effective way to prevent the recur- rence of medical errors [20, 21]. The communication model helped to extract communication error factors from the perspective of the operation process. The Shannon–Weaver model is called the initial model in the field of communication [22]. Berlo extended the Shannon–Weaver model and proposed an SMCR communication model that contains five elements: source, message, channel, receiver, and noise. SMCR model is widely applicable to communication in mul- tiple industries, including medical institutions [23].

To further prevent medication communication errors made during clinical nursing, it is also neces- sary to understand which error factors are associated with specific error types and the strength of these relationships. However, many previous studies have focused only on error types or error factors, rather

H. Jin et al. / Investigating the relationship between error types and error factors 329

Fig. 1. Research framework.

than considering them together [9, 13, 14, 18, 19]. In recent years, quantitative research on medical errors has become a research hotspot [24, 25]. By quantifying the relationship between error types and error factors, we can understand the deep interaction between them and provide quantitative guidance to diagnose and improve errors.

2. Methods

2.1. Aim and research framework

The objective of this study is to provide evidence and guidance for the prevention and improvement of medication communication errors by quantitatively exploring the relationship between error types and error factors. The overall research framework of this study is shown in Fig. 1.

2.2. Study setting

The error cases collected from three participating acute care medical centers (number of beds: 1313, 1228 and 892; location: China) over a one year period (Jan. 2019 to Dec. 2019) were the data sources used in this study. This study collected medical errors related to the nursing administration process from all depart- ments of three cooperative medical institutions.

2.3. Data collection and analysis procedure

The case data for this study were collected using the following procedure. When nurses encountered

an error in the medication process, they recorded the error in the format-specified error sheet, which they submitted to the medical safety administra- tion office (the format-specified error sheet is shown in the attachment). The error data were based on self-reported cases by nurses in all department of cooperative medical institutions. The error data used in the present study were provided by the safety administration office of each participating medical institution. This study was not able to directly contact medical settings or patients. The error-related content is included in our research data and does not contain any personal information of patients or nurses.

Each collected error case was jointly analyzed by two medical error research experts and one medical safety manager. Both medical error research experts and medical safety managers have more than 10 years of work and research experience related to medi- cal safety. To extract communication error cases, we based the definition of medication communication error in nursing and identified cases of communica- tion errors in the nursing medication process based on the content of the error sheet.

2.4. Extraction of communication error types

The error type is the classification of error behavior characteristics from the perspective of the devia- tion between the expected operation behavior and the actual operation behavior [11, 12]. Consider- ing that the three SHERPA communication error types (i.e., information not obtained, wrong infor- mation communicated, and incomplete information communicated) are relatively abstract [15], we com- bined them with the human cognition process [26] to establish six specific error types in this study. The following uses a specific error case to introduce the extraction process of the error type.

Step 1: Summarize error case content. The cases of the analyzed objects are

summarized as follows: A drug that had to be kept refrigerated was removed imme- diately before medication administration. The nurse forgot to prepare the drug before the medication was administered.

Step 2: Determine in which stage of the cognitive process the case occurred.

According to the content of the error case, it is evident that the failure to pre- pare the drug occurred because of a lapse in memory (i.e., forgetting). Therefore, from

330 H. Jin et al. / Investigating the relationship between error types and error factors

the perspective of the human cognitive process, this case belongs to the stage of “Memory of the information.”

Step 3: Establish to which of SHERPA’s three communication error types this case belongs.

From the content of the case, it is clear that the message “Remove medication from the refrigerator before administra- tion” did not get through. Therefore, from the perspective of SHERPA’s three communication error types, this case is classified as “Information not communi- cated.”

Step 4: Determine the expression form of the error type based on the characteristics of error behavior in this case.

This case occurred in the human cogni- tive stage of “Memory of the information,” which belongs to SHERPA’s error type “Information not communicated.” Com- bined with the characteristics of the case, we integrate the above two into the expres- sion “Total lapse of information memory” and regard it as one of the error types in this study.

2.5. Extraction of communication error factors

Communication errors may be caused by various factors [27]. Therefore, even if a particular commu- nication error is identified, effective countermeasures cannot be addressed. Thus, identifying communica- tion error factors and taking countermeasures against them is an effective methodology [15, 25]. Root cause analysis (RCA) is widely used in the field of health- care and can deeply explore the causes of medical errors [28]. In this study, error factors were extracted from the perspective of the operation process based on the RCA method. Error factors were sorted based on five elements of SMCR communication model [23]. A schematic of the SMCR communication model is shown in Fig. 2.

The following steps illustrate the extraction method for error factors using RCA:

Step 1: Select team facilitator and team members. The purpose of this step is to identify

the personnel who will analyze error cases based on RCA. In this study, error cases were jointly analyzed by two medical error research experts and one medical safety manager.

Fig. 2. SMCR communication mode.

Step 2: Identify the error case to be investigated. This step is used to identify specific

error cases to be analyzed. An actual error case is summarized as follows: a drug that had to be kept refrigerated was removed immediately before medication adminis- tration. The nurse forgot to prepare the drug before the medication was adminis- tered.

Step 3: Describe what happened. This step involves combining the time

sequence of the selected error cases to fur- ther clarify the error-inducing process. We conducted time sequence sorting of the error induction process of the above cases, and the results are shown in Step 3 of Fig. 3.

Step 4: Identify the contributing items. In this step, a more in-depth discussion

will be carried out for each stage in Step 3, and the items closely related to the error are proposed. Contributing items for the above case are shown in Step 4 of Fig. 3.

Step 5: Identify the error factors. In this step, we first confirmed the spe-

cific stage of the communication error based on the SMCR model. Second, according to the communication error stage and error contributing items, the error factors are identified by repeatedly asking “Why?”.

In the above case, an error occurred in the nurse’s information reception, which belongs to the “receiver” stage of the SMCR model. Then, according to the information reception stage, we asked “Why?” four times and extracted the error factors as “Depend on memory.” The details are shown in Step 5 of Fig. 3.

2.6. Statistical analysis

Partial least-squares (PLS) regression is a multi- variate statistical analysis method proposed by Wold

H. Jin et al. / Investigating the relationship between error types and error factors 331

Fig. 3. The diagram of error factor extraction.

[29]. PLS combines the advantages of principal component analysis, canonical correlation analysis, and multiple linear regression analysis. Addition- ally, when there is a high degree of correlation between variables or a small sample size, PLS can provide more reliable results than other methods [30]. This study chose PLS to clarify the relationship between error types and error factors for several rea- sons. The dependent and independent variables were extracted by analyzing error cases. Therefore, there may be multicollinearity and nonlinear data distri- butions. Additionally, the sample size was small. In data with these statistical problems, PLS can provide more reliable statistical analysis results than other methods.

3. Results

3.1. Case collection

Using the error sheet designed for this study, we collected 597 MEs-N in three hospitals. Of these cases, 303 (50.8%) were caused by communication errors. The details of these cases are presented in Table 1. The proportion of CE-NMP was highest in hospital C, followed by hospitals B, A.

3.2. Communication error types

To extract error types in the communication pro- cess, based on the method of extracting error types

described above, we analyzed the 303 communi- cation error cases collected in this study one by one and then extracted error types for each case. We then unified these classifications and described the outcome as the study’s error type, as shown in Table 2.

The structure of Table 2 is as follows. The left list shows the three steps of the human cognition pro- cess, the left two columns represent SHERPA’s three error types, the left three columns represent the six new communication error types in this study, and the remaining four columns represent the number of cases. As can be seen from Table 2, the six error types extracted in this study are the materialization of SHERPA’s three error types from a medical per- spective. Theoretically, the three steps in the human cognition process and the three SHERPA error types should produce nine error types. However, some com- binations are not theoretically feasible. For example, for perception of information source, no error type corresponds to the SHERPA error type of incomplete information communicated because the process of perceiving an information source is momentary, and errors occurring at this stage mainly result from a lack of detection or incorrect detection. Therefore, the six kinds of error types described above are con- sistent with the actual error data and with logical reasoning. Table 2 shows that information cogni- tion failure, at 35%, accounted for most cases of all error types, followed by selection of the wrong information source (22.4%) and missing information cognition (17.4%).

332 H. Jin et al. / Investigating the relationship between error types and error factors

Table 1 Characteristics of MEs-N

Hospital Beds Care State Number of Collection Number of CE-NMP/ type MEs-N period CE-NMP MEs-N

A 1313 Acute China 224 Jan. 2019 103 46.0% B 1228 Acute China 197 – 99 50.3% C 892 Acute China 176 Dec. 2019 101 57.4% Total — — — 597 303 50.8%

CE-NMP: Communication Errors in Nursing Medication Process.

Table 2 Communication error types

Human cognition processes

SHERPA’s error types This study’s error types Number of error cases (%)

Perception of information source

Information not communicated Failure to find the information source

45 (14.9%)

Wrong information communicated

Selection of the wrong information source

68 (22.4%)

Cognition of information contents

Wrong information communicated

Information cognition failure 106 (35.0%)

Information communication incomplete

Missing information cognition 53 (17.4%)

Memory of the information

Information communication incomplete

Partial lapse of information memory

15 (5.0%)

Information not communicated Total lapse of information memory

16 (5.3%)

Total — — 303 (100%)

3.3. Communication error factors

The error factors considered in this study are fac- tors in the operational process that often result in errors. To extract error factors in the communica- tion process, based on the method of extracting error factors described above, we analyzed the 303 com- munication error cases collected in this study one by one and then extracted error factors for each case. Then, we combined the error factors with the SMCR communication model elements. The extracted error factors are listed in Table 3.

As shown in Table 3, 12 communication error fac- tors in the nursing medication process were identified in the 303 cases. Error factors in the communication process were found from the five elements: source, channel, message, receiver and noise. From the per- spective of the number of cases, the error factor “lack of clarity on changes in information content” accounted for the largest percentage of all errors (18%), which shows that timely information modifi- cation according to the patient’s situation is of major importance in the operational process of healthcare. Because the personnel structure related to infor- mation changes is complex and involves numerous individuals, it is important to consider how to ensure that the relevant operating staff members acquire

new information correctly to reduce communication errors. Additionally, “information in multiple loca- tions,” “instability of the position of information,” “usage of confusing units and figures,” and “occur- rence of information with low appearance frequency” accounted for high percentages of the errors, with each making up over 10%. Addressing these factors should be a high priority in the operating process.

3.4. Relationships between error types and error factors

This study examined the relationships between error types and error factors using PLS analysis. These relationships are presented in Table 4. The table shows that all R2 values of the endogenous variables were satisfactory, demonstrating a high and effective predictive validity. Notably, the R2 value for “selec- tion of the wrong information source” showed that all the exogenous variables together explained 57.9% of the variance in B2. Table 4 can explain the influence of error factors on the error modes. For example, the path coefficients and bootstrapping test results indi- cated that “instability of the position of information”, “information deficiency”, and “irrelevance of related information” had significant direct effects on “failure to find the information source”.

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333 Table 3

Communication error factors

SMCR model elements

Error factors Description Case Proportion (%)

Source Information in multiple locations

Related information isn’t written on one information source, but scattered across multiple information sources

The administration instruction of Sulbacillin was on another instruction list, and the medical staff failed to receive the information.

43 (11%)

Source Information deficiency Information extraction isn’t based on information source or fail to find information source

Due to a large number of parallel jobs, medical staff operated with memories instead of the reference to the information source, resulting in failing to receive information changes and thus operation errors.

24 (6%)

Source Instability of the position of information

Information source has no fixed storage position or isn’t stored on fixed position

Although there are injection instructions of Vancomycin on the instruction list, but medical staff did not find the injection prescription, leading to failure to perform the injection in specified time.

51 (13%)

Channel Oral dissemination of information

Information spread orally Oral transmission of information led to hearing the wrong name of patient.

13 (3%)

Message Irrelevance of related information

Highly related information is scattered on different parts of an information source

There were instructions for both catabon and dobutrex at 17 : 00, but they were not written in one place. The medical staff only saw the instruction from catabon.

15 (4%)

Message Lack of promptness in information sharing when content changes

Information is not shared timely when content changes The changed information was not transmitted to the dispensary. Then the medicine prepared following the instructions before the changes were sent to the nursing station.

26 (7%)

Message Lack of clarity on changes in information content

Information changes isn’t obvious to recognize Decadron was reduced from 2 mg to 1 mg. But the medical staff failed to notice the change and gave the previous administration amount.

71 (18%)

Receiver Similar names Similar font or pronunciation of the patient or medicine’s name

Medical staff read Solita T3 as Solita T3G 26 (7%)

Receiver Usage of confusing units and figures

Usage of confusing units and figures The medical staff mistook the administration time 16 : 00 for 10 : 00, and administration time error happened.

44 (11%)

Receiver Depend on memory The dependence of information on memory to produce information forgetting or bias from prior knowledge

Bactramin was dissolved in the physiological saline instead of the glucose solution. (There were more instructions for antibacterial agents dissolved in the physiological saline; the medical staff depended on memory and mistook it for the same as before.)

42 (11%)

Noise Lighting in the operating environment

The insufficient lighting of night duty environment led to the wrong administration

The insufficient lighting of night duty environment led to the wrong administration.

25 (6%)

Noise Noise in the operating environment

Big noise of operating environment Due to the noise of operating environment, the medical staff misunderstood the doctor’s instructions.

11 (3%)

Total 391 (100%)

Note: The number of cases in Table 3 is larger than 303 because one error case could have more than one error factor.

334 H. Jin et al. / Investigating the relationship between error types and error factors

Table 4 Path coefficients and bootstrapping test (t-value)

Endogenous R2 Path Path Bootstrapping (mean, STDEV, T-value) variables coefficient Original Sample Standard T-value

sample mean deviation

Failure to find the information source

0.423 Instability of the position of information −→ Failure to find the information source

0.378∗∗∗ 0.378 0.377 0.065 5.854

Information deficiency −→ Failure to find the information source

0.332∗∗∗ 0.332 0.331 0.067 4.951

Irrelevance of related information −→ Failure to find the information source

0.172∗∗∗ 0.172 0.173 0.048 3.595

Selection of the wrong information source

0.579 Information in multiple locations −→ Selection of the wrong information source

0.467∗∗∗ 0.467 0.470 0.062 7.513

Instability of the position of information −→ Selection of the wrong information source

0.217∗∗∗ 0.217 0.219 0.064 3.415

Lack of promptness in information sharing when content changes −→ Selection of the wrong information source

0.162∗∗ 0.162 0.163 0.053 3.077

Information cognition failure

0.476 Usage of confusing units and figures −→ Information cognition failure

0.330∗∗∗ 0.330 0.331 0.045 7.349

Occurrence of information with low appearance frequency −→ Information cognition failure

0.258∗∗∗ 0.258 0.256 0.052 4.984

Lighting in the operating environment −→ Information cognition failure

0.125∗∗ 0.125 0.123 0.043 2.893

Similar names −→ Information cognition failure

0.088∗ 0.088 0.090 0.044 1.983

Missing information cognition

0.410 Lack of clarity on changes in information content −→ Missing information cognition

0.381∗∗∗ 0.381 0.382 0.068 5.568

Oral dissemination of information −→ Missing information cognition

0.127∗ 0.127 0.125 0.059 2.141

Partial lapse of information memory

0.415 Similar names −→ Partial lapse of information memory

0.359∗∗∗ 0.359 0.358 0.056 6.437

Information deficiency −→ Partial lapse of information memory

0.260∗∗∗ 0.260 0.261 0.073 3.542

Noise in the operating environment −→ Partial lapse of information memory

0.226∗∗∗ 0.226 0.223 0.060 3.765

Oral dissemination of information −→ Partial lapse of information memory

0.159∗∗ 0.159 0.153 0.057 2.776

Usage of confusing units and figures −→ Partial lapse of information memory

0.125∗∗ 0.125 0.121 0.043 2.891

Total lapse of information memory

0.327 Information deficiency −→ Total lapse of information memory

0.348∗∗∗ 0.348 0.348 0.081 4.299

Oral dissemination of information −→ Total lapse of information memory

0.225∗∗ 0.225 0.227 0.076 2.941

Depend on memory −→ Total lapse of information memory

0.135∗∗ 0.135 0.136 0.047 2.855

Note. *t-value>1.96 at p < 0.05, **t-value>2.58 at p < 0.01, ***t-value>3.29 at p < 0.001; two-tailed tests.

Based on Table 4, the following steps can be fol- lowed to provide quantitative guidance for preventing errors.

In the first step, given the occurrence of errors in the medical field, the type of error to be improved is determined from the type of error in Table 4. For

example, the type of error to be improved in a hospital is “failure to find the information source”.

The second step checks the types of failure factors that induce “failure to find the information source”. For example, from Table 4 it shown that the error fac- tors closely related to “failure to find the information

H. Jin et al. / Investigating the relationship between error types and error factors 335

source” are “instability of the position of informa- tion”, “information deficiency”, and “irrelevance of related information”.

The third step is to check the contribution of each error factor to the type of error. For example, from Table 4 the contribution rate of the error factor “instability of the position of information” is 0.378, “information deficiency” is 0.332, and “irrelevance of related information” is 0.172.

The fourth step is to consider the strategies for improving errors according to the contribution rate of the error factors. For example, for failure type “failure to find the information source”, it is recommended to first consider the countermeasures against the insta- bility of the position of information, followed by information deficiency, and finally, irrelevant infor- mation.

4. Discussion

Healthcare features, such as being characterized by emergency situations, high variability, and mul- tiplicity of collaboration, lead to the high frequency and great importance of communication in this field [1, 2]. Ensuring the quality of communication is an important part of maintaining patient safety [7, 8]. Therefore, the present study not only examined com- munication errors in the medication process but also had the following significance.

This study is based on actual medical error cases and the extraction of error types and error factors. Yao et al. pointed out that low-quality error data will seriously affect the development of RCA and analysis of error factors, and we encountered the same issues while developing this research [31]. To ensure the quality of case analysis, this research set the following settings. First, we designed a format-specified error sheet. Second, this study clarifies the scope of the collection of error cases. The source of the error was medication errors during nurses’ work. For exam- ple, dose errors caused by a nurse reading the wrong prescription information fall under the scope of this research, but wrong medication information provided by a doctor or pharmacist is not included in this research. Third, medical safety managers from rel- evant medical institutions participated in the analysis of the error cases. This is helpful for RCA analysis of medical error cases and the extraction of error factors.

Medical errors are complex and diverse, and can- not be generalized; thus, they should be classified and further discussed [15, 17, 25]. Among them, medi-

cation administration error is a high-frequency error closely related to patient safety, and it is meaning- ful to explore the factors that induce errors from the perspective of prevention [5, 6]. There are two main aspects of medication error research. One is from the physiological and psychological perspectives of the nurse, and the other is from the operational process perspective [9, 10]. When error factors are extracted from the former perspective, the improvement direc- tion of the error is more related to the physiological and psychological aspects of the parties, and the error prevention effect is not ideal [4, 21]. Based on the total quality management concept that good operation results are guaranteed by a good operation process [20], error factors should contribute to the improvement of operation process defects, and the countermeasures against it will be more effective in preventing the recurrence of medical errors.

To extract error factors from the perspective of the operational process, RCA analysis was used in this study. In addition to the RCA method, FMEA (failure mode and effect analysis), 4M4E, SHEL (Software, Hardware, Environment, Liveware), and CREAM (cognitive reliability and error analysis method) were used to extract error factors. FMEA is a method for analyzing and evaluating the reliability and safety of the system, and it pays more attention to the level of risk [32]. 4M4E is a method to analyze errors related to the four Ms in “Man, Machine, Media, and Management” from the four Es in “Education, Engineering, Environment, and Enforcement” [33]. It provides a wealth of analytical views, but does not provide enough guidance on the depth of anal- ysis [34]. Similar to the 4M4E method, the SHEL model provides an analysis view of software, hard- ware, environment, and liveware [35]. The CREAM method is established based on the situational depen- dence model, which is a method for retrospective analysis and prediction of the influence of situations on human reliability and error [36]. It mainly focuses on the influence of the situational environment on human behavior [37]. Compared with the above anal- ysis methods, RCA pays more attention to the sorting of the error-inducing process and can deeply ana- lyze the causes of the error through repeated “why” questions, which is helpful in identifying the essen- tial defects of the medication administration process [28]. However, this study encountered the time- consuming problem of using RCA to analyze error cases. Yanagikawa et al. also reported the above prob- lems in the RCA analysis process, which we believe is a common problem [38].

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Brigitta et al. proposed that ineffective com- munication was the main contributing factor for medication administration errors, but did not conduct further analyses on specific error factors [9]. John- son et al. proposed that interruption was the main cause of communication errors [39]. Budihardjo et al. proposed that communication management defects are the main cause of communication errors [40]. In conclusion, as an important factor affecting med- ication administration errors, an in-depth analysis of ineffective communication can establish effective error prevention countermeasures. The communi- cation error factors proposed in this study can be regarded as defects in the communication process and contribute to the construction of good communica- tion rules. As shown in Table 3, information source contains three specific error factors of “Informa- tion in multiple locations,” “Information deficiency,” and “Instability of the position of information,” and accounts for 30% of the overall errors. Through the extraction of these specific error factors, error pre- vention countermeasures can be considered from the perspective of eliminating error factors in the opti- mization of communication processes in the future. For example, with “Information in multiple loca- tions,” we can think about how to express relevant information on a single source. Therefore, the guiding significance of our results for reducing communica- tion errors in healthcare is not to make humans adapt to the operational process, but rather to improve the process by bringing it more in line with human oper- ational characteristics.

5. Limitations and future research

This study had several limitations. First, the results of this work apply only to the communication pro- cess in the nursing medication process, which we selected to examine MEs-N deeply and investigate their characteristics in detail. If the results are applied to other medical processes, the error types and error factors presented here may be incomplete. However, the ideas presented in this study can be applied to other healthcare processes. Second, the usability and effectiveness of the research methods and results sug- gested in this study should be tested and verified after long-term application in various types of med- ical institutes over a long period. Subsequently, the approach will be modified and improved using feed- back and experiences from actual situations, which will be presented in further research. Third, the trust-

worthiness assessment of the data was not performed in this study. At this point, using a panel of experts may lead to more reliable results when identifying error types and factors. Finally, the present study focused on the errors that had already occurred. However, in the medical field, error prevention is important. The key issues of how the results can be used to diagnose and address problems in the oper- ational process to avoid errors occurring in advance will be considered in the future.

Future research should first verify the results of this study in more hospitals to test the applicability of our findings. Next, the research ideas and methods should be applied to types of hospital operations other than the communication process to verify the usability of this approach for other medical processes. Finally, the comparative study on the error case number, error types and error factors in different department of medical institutions needs to be carried out in the future.

6. Conclusion

This study took medication communication errors in nursing as the research object, based on a one- by-one analysis of 303 error cases in three medical institutions, and the following conclusions were obtained. First, six types of communication errors in the nursing medication process were extracted based on the combination of the medication communication process and the SHERPA model. Second, 12 types of error factors closely related to nursing medica- tion errors were extracted. Finally, based on a PLS analysis, it quantitatively explored the influence rela- tionship between error types and error factors, which provides a basis for error occurrence mechanism anal- ysis and error prevention.

Conflict of interest

The authors declare that they have no conflict of interest to disclose.

Funding

This work was supported by the National Natural Science Foundation of China (Grant nos 72171042 and 71701039) and the Fundamental Research Funds for the Central Universities (Grant no. N2106007).

H. Jin et al. / Investigating the relationship between error types and error factors 337

Acknowledgments

This research was carried out under the support and cooperation of three medical institutions in China and has received valuable views and suggestions from experts in the medical care field. The authors would like to express their sincere gratitude to all experts and scholars for their help in completing this thesis.

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Appendix: Medication error sheet

Part A Staff Staff name; Gender: Age:

Designation;Total number of years worked: Department; Number of years worked in the department:

Patient Name of the patient: Age: Error

Symptoms:Date of admission: Gender:

Time of occurrence; Time of discovery: Place;

Part B • Expected implementation content Name of the patient; Names of the drugs; Dosage; Administration time; Administration speed (injection); Administration method; �Predetermined administration �No predetermined administration �Others

• Actual implementation content Name of the patient; Names of the drugs; Dosage; Administration time; Administration speed (injection); Administration method; �Implemented �Unimplemented �Others

Part C Operation phase Actual operation 1. Indicating phase: 2. Preparation of the drug phase: 3. Administration of the drug phase: 4. Observation and management after the administration phase:

Part D How to find the error: Why did the error occur: Operation characteristics: Whether the operation process is observed or not: Others:

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