The relationship between health IT characteristics and organizational variables among German healthcare workers

Health information technologies (HITs) are widely employed in healthcare and are supposed to improve quality of care and patient safety. However, so far, their implementation has shown mixed results, which might be explainable by understudied psychological factors of human–HIT interaction. Therefore, the present study investigates the association between the perception of HIT characteristics and psychological and organizational variables among 445 healthcare workers via a cross-sectional online survey in Germany. The proposed hypotheses were tested using structural equation modeling. The results showed that good HIT usability was associated with lower levels of techno-overload and lower IT-related strain. In turn, experiencing techno-overload and IT-related strain was associated with lower job satisfaction. An effective error management culture at the workplace was linked to higher job satisfaction and a slightly lower frequency of self-reported medical errors. About 69% of surveyed healthcare workers reported making errors less frequently than their colleagues, suggesting a bias in either the perception or reporting of errors. In conclusion, the study’s findings indicate that ensuring high perceived usability when implementing HITs is crucial to avoiding frustration among healthcare workers and keeping them satisfied. Additionally healthcare facilities should invest in error management programs since error management culture is linked to other important organizational variables.


Measures. Technologies in use.
First, participants were asked to indicate which HITs they use most often during their daily work. They could choose multiple options from a preselection and add technologies if needed (see "Supplementary information" for a full list of survey items). Participants were instructed to refer to the se- Figure 1. Depiction of the proposed structural equation model. The direction of the assumed association is indicated by + for a positive association or by − for a negative association. The null hypothesis for each assumption is that the association between the variables is zero. www.nature.com/scientificreports/ lected technologies when answering all other questions. Focusing on a fixed set of frequently used technologies should promote a consistent response to items.
Usability. Both the conceptualization and scales to assess the digital HITs' usability were adapted from a previous study 10 . To measure the three usability features, usefulness 48 , ease of use 48 , and reliability 49,50 , items were rated on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). The internal consistency of each subscale (α usefulness = 0.94, α ease = 0.77, α reliability = 0.92) can be considered good to excellent.
Technostress. Three technostress creator scales were included in the survey: techno-overload, techno-uncertainty, and techno-insecurity 51 . The two other technostress subscales, techno-invasion and techno-complexity, were not included. The concept techno-invasion, which is the invasive effect of technologies on people's non-working lives, was considered to be irrelevant for the healthcare context because most healthcare workers do not have access to HITs outside the hospital environment. As techno-complexity is very similar to the usability subscale ease of use, we decided to only include the usability subscale to keep the survey reasonably short. The included 13 technostress items were answered on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). The internal consistency of techno-overload (α overload = 0.85) was good, and of techno-uncertainty (α uncertainty = 0.71) was acceptable. However, the internal consistency of the subscale techno-insecurity (α insecurity = 0.64) was below the acceptable threshold of at least 0.70; therefore, it was removed from further analysis.
Technology self-efficacy. Participants' level of technology self-efficacy was measured with a five-item scale 14 on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). The scale showed acceptable internal consistency (α self-efficacy = 0.76).
IT-related strain. Work strain was measured with a scale created by Ayyagari et al. 10 . The response format of the four items was a 7-point Likert scale from 1 (never) to 7 (daily). The internal consistency of the strain scale was excellent (α strain = 0.92).
Job satisfaction. The seven items measuring job satisfaction were adopted from the German version 52 of the Copenhagen Psychosocial Questionnaire (COPSOQ). The items had a 7-point Likert scale answer format from 1 (very unsatisfied) to 7 (very satisfied). The scale showed good internal consistency (α job satisfaction = 0.86).
Error management culture. We created a short, healthcare-specific, error management culture scale vaguely based on an existing scale 45 . The seven items were answered on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). The error management culture scale showed excellent internal consistency (α error management culture = 0.90).
Common types of medical errors. Afterwards, respondents selected the three most common medical errors that occur in their work environment from a list of 11 types of potential errors 53 . This list was presented to give participants an idea of what counts as a medical error before asking them about their own errors.
Self-reported medical errors. The frequency of medical errors was assessed by asking participants "How often have you made a medical error within the last 3 months?" ranging from 1 (never) to 7 (daily). In previous surveys, a slightly different version of this item has been used, where participants had to answer with yes or no as to whether they are concerned about having made any medical errors in the last 3 months 34,54 . As this binary measure does not provide any information about the frequency of medical errors, we modified the question and its response scale. The item was followed by a question about the consequences their most recent medical error had for the patient involved, ranging from 1 (no effect on the patient's outcome) to 6 (patient died). Healthcare workers also estimated how frequently their colleagues have made medical errors within the last 3 months from 1 (never) to 7 (daily).
Perceived causes for medical errors. Finally, participants were asked to judge the top three causes of medical errors on (a) an individual and organizational level, from a selection of options based on a WHO report on medical errors 55

Results
Descriptive analysis. Technologies in use. The three most widely used HITs were hospital information systems, selected by 80.45% of all participants, image archives (80.00%), and electronic health records (71.24%). The complete breakdown of participants' responses can be found in the "Supplementary information" (Fig. S1).
Common types of medical errors. In total, 51.46% of the surveyed healthcare workers selected 'avoidable delay of a necessary treatment' as one of the three most common medical errors occurring in their work environment, making it the most-reported error. It was followed by 'the results of the examination were not properly responded to, ' selected by 46.52% of participants, and 'inappropriate care (under-or oversupply), ' selected by 42.70% of participants. Together, these three accounted for almost half of all selected types of medical errors, making them stand out considerably above any other option. The least-selected types of medical errors were 'misdiagnosis' (14.61%), and 'an outdated examination technique was used' (4.94%). The full breakdown is reported in Fig. 2A.
Self-reported medical errors. Figure 2B shows participants' reported frequency of making medical errors themselves and errors made by colleagues within the last 3 months. Participants reportedly made an error less than once a month on average (M self = 2.19, SD self = 1.14). Most of the participants' latest medical errors did not harm a patient (49.66%) or only brought minor, temporary harm to a patient (22.47%). Only in 0.45% of the cases was the medical error lethal. Overall, the respondents claimed to make errors less often than their colleagues (M others = 3.48, SD others = 1.58, Wilcoxon test: V = 2508, p < 0.001). There was a strong contrast between the reported frequency of their own errors and the errors of others. A total of 308 (68.90%) participants rated the occurrence of errors made by their colleagues to be higher than their own, 115 (25.73%) regarded the error rate to be the same, and only 22 (4.92%) healthcare workers believed to have made mistakes more often than their colleagues. Figure 3 shows the breakdown of participants' selected causes for medical errors on both an individual/organizational level (Fig. 3A) and on a technical level (Fig. 3B).
SEM analysis. Self-reported frequency of making a medical error was measured on an ordinal scale; therefore, lavaan automatically used the WLSMV estimator. The measurement model of the initially proposed model showed that items from the technology self-efficacy and techno-uncertainty scales had standardized factor loadings below 0.40. Additionally, techno-uncertainty did not load well on the overall technostress scale (0.26). Therefore, a second SEM model was calculated without technology self-efficacy as a moderator between technostress and strain (see a separate analysis below) and without the techno-uncertainty technostress subscale. Moderation analysis. We expected that participants' levels of technology self-efficacy would moderate the relationship between perceived technostress and IT-related strain. The moderation analysis was performed by fitting a multiple regression with strain as the dependent variable and technostress (overload), technology selfefficacy, and the interaction term (technostress × technology self-efficacy) as predictors. We found a statistically significant albeit very small moderation effect b = − 0.07, t(441) = − 2.10, p = 0.030, r = − 0.10, 95% CI [− 0.19, 0.01]. This means that respondents with higher technology self-efficacy report slightly lower levels of strain and vice versa, which confirms the proposed hypothesis.

Discussion
The current study investigated the associations between perceived HIT characteristics (usability and technostressors) and important organizational variables among German healthcare workers. The results extend the understanding of how the discerned usability of widely used HITs relates to perceived technostress, IT-related strain, job satisfaction, and self-reported medical errors. To the best of our knowledge, this is the first study to show the complex interactions between these variables using a SEM approach. We found that hospital information systems, image archives, and electronic health records were the most widely used HITs. Good perceived usability (i.e., reliability, usefulness, and ease of use) of these HITs was associated with lower levels of techno-overload and IT-related strain. However, good usability of these HITs did not significantly correlate with job satisfaction. Participants who reported experiencing techno-overload (i.e., feeling that the HITs were forcing them to work faster/longer) were more likely to feel strained and slightly less satisfied with their job. The relationship between techno-overload and IT-related strain was somewhat moderated by a person's level of technology self-efficacy. Facing IT-related strain was also directly linked with lower job satisfaction. Against our expectations, healthcare workers' job satisfaction and perceived strain were not related to their self-reported frequency of making medical errors. However, perceiving the workplace's error management www.nature.com/scientificreports/ culture as encouraging to workers to discuss the reasons and consequences of errors and motivating workers to learn from errors was associated with a lower frequency of medical errors. Rating the error management culture at work as constructive was very strongly associated with higher job satisfaction. We want to highlight that the model accounted for 41% of the respondents' job satisfaction variance. Job satisfaction is one of the most widely researched organizational psychology topics, consistently related to subjective wellbeing and many work-related behaviors such as turnover decisions, prosociality, organizational citizenship, counterproductive work behaviors, and job performance 19 . Our findings correspond to other studies that found that technostress and IT-related strain correlate negatively with job satisfaction 8,[16][17][18][20][21][22] . Based on the literature, the direction of effects should be that exposure to techno-stressors leads to IT-related strain, which negatively impacts job satisfaction 11 . Again, in accordance with previous research, we found that good HIT usability is associated with lower levels of perceived technostress and IT-related strain and vice versa 10,20,26,27 . Therefore, HIT designers should focus on making their products reliable, useful for the end user, and easy to operate. Before and during the implementation of new HITs, their usability and potential for causing technostress should be assessed. For instance, in one study, a dashboard providing important data for diabetes care was developed with a user-centered design process, in which the end users were involved in initial focus groups, iterative feedback www.nature.com/scientificreports/ loops, and evaluation actives 59 . The usability evaluation showed that the new dashboard reduced the number of mouse clicks and the time to find all necessary data and increased the accuracy of acquiring data. To ensure that HIT-developers have an incentive to go through rigors pre-testing, policymakers and administrative bodies should set and enforce high usability standards for HITs during the approval process. Workplace error management culture showed the strongest association with job satisfaction. The error management culture scale assessed whether healthcare workers felt that errors are being discussed and communicated openly and causes for errors are identified and resolved. These findings are in line with previous research showing that an effective error management culture is positively related to job satisfaction 47 . It has been argued that an effective error management culture can help employees control negative emotions in response to errors and increase motivation 46 , both of which can contribute to job satisfaction. Therefore, our findings highlight that healthcare facilities should invest in establishing a constructive error management culture in which staff are not afraid of being punished for causing and/or reporting errors.
Having an effective error management culture was not only associated with higher job satisfaction in our data; it was also a significant correlate with self-reported medical errors. This result was expected, considering previous research indicating that effective open error communication allows employees to learn from other people's mistakes, preventing the same error from happening again in the future 45,46 . Other industries' experience shows that an effective error management culture results in lower numbers of incidents. For instance, the aviation industry has a long history of gathering data and implementing effective processes such as checklists for error management, which could also be implemented in medicine and healthcare 60,61 . Scholars of error management have argued that healthcare can learn from the aviation industry's strategies for enhancing teamwork and safety to establish effective error management programs 61 . Therefore, policymakers and administrative bodies should also set and enforce high standards for the reporting, evaluation, and management of medical errors to facilitate an effective error management culture.
The distribution of the medical error items needs further discussion. The participants' reported frequency of making medical errors themselves was skewed towards the right, suggesting that no or only very few errors occurred in the last 3 months. This is somewhat surprising, considering that it was made clear to the participants that even minor mistakes should be viewed as medical errors. For instance, knowing that compliance with hand hygiene guidelines, a preventive behavior that has to occur countless times a day, is below 70% among German physicians 62 , it is unlikely that participants made no error in the last 3 months. Considering that 89.0% of our participants reported having made an error only once a month or even less often, we think it is plausible that the respondents did not account for minor errors when answering the question. This assumption is informed by other research that found only between 8.9 and 14.7% of physicians reported to have made a major medical error in the last 3 months 33,34,54 .
This might help to explain why we did not find significant associations between self-reported medical errors and job satisfaction or IT-related strain. Low job satisfaction and high IT-related strain are associated with the feeling of fatigue, which has been shown to result in errors of omission due to a lack of attention or concentration problems 63 , but might not result in major errors. More research is needed to test whether job satisfaction and IT-related strain might be linked to medical errors after all. Additionally, future research should be conducted to measure the occurrence of medical errors more reliably. Here it should be noted that the reported frequency of observing medical errors made by colleagues is much less skewed. It is not entirely clear why most participants www.nature.com/scientificreports/ think that their colleagues err more often than themselves. There might be well-established cognitive biases at play, such as the "better than average" effect, which describes people's tendency to view their abilities above average, especially compared to their peers 64 . Or it could be that respondents just summed up errors they witnessed in their immediate work environment by multiple colleagues without making a comparison to their own error rate as a single person. Independent of the cause of the discrepancy between errors made by themselves and others, better measurements for the occurrence of medical errors are needed to study their sources. Using automatically collected data from technologies such as decision support systems, which register (potential) errors made by the user such as wrong dosages, might be one possible approach. Several limitations of the present study should be mentioned. First, all measured variables were self-reported by participants and not objectively observed. For most variables, using questionnaire items is the standard way of measuring them. However, we are concerned that participants might have underreported the frequency of their own medical errors, considering how much higher they rated their colleagues' error frequency. Future research on medical errors should try to use observable instead of self-reported data. Second, while we used well-established scales to measure techno-uncertainty, techno-insecurity, and technology self-efficacy, there were some concerns about their psychometric qualities, which led us to exclude them from the SEM. More research is needed to develop and validate scales for a wide range of target groups and multiple languages to ensure their reliability and validity. Third, the survey response rate was low, which is a common issue with online surveys 65 . A low response rate can pose a risk for a non-response bias in the results, which occurs when the group of non-responders differs in a meaningful way from the group of responders. Having a non-response bias in the data might affect the generalizability of the study's results to the entire population. Finally, the study design was cross-sectional, which means that we cannot confirm the causal directions of the reported effects, and in several cases, both directions are theoretically plausible. Longitudinal studies and carefully planned experiments are needed to verify the causal links.
In conclusion, the present study leads to a deeper understanding of the perception of HIT characteristics and their relationship with organizational variables in healthcare. Our findings indicate that ensuring high usability of HITs is crucial to alleviate techno-overload and IT-related strain, which are both negatively linked to healthcare workers' job satisfaction. Additionally, the results suggest that an effective error management culture helps ensure job satisfaction and reduce medical errors. Considering the strongly skewed self-reported frequency of making medical errors, future research needs to establish more objective ways to measure the occurrence of medical errors. Being able to measure medical errors objectively is an important first step towards constructively dealing with them and the basis for an effective error management culture. The present study results should help guide the successful implementation of HITs to realize their full potential for improving the quality of healthcare.

Data availability
The study's pre-registration, data, survey material, and R-script will be made available online upon publication: https:// osf. io/ ekj9p/.