Root Cause Analysis of ICU Adverse Events in the Veterans Health Administration

A content analysis of contributory factors reported in serious incident investigation reports in hospital care

BACKGROUND

Serious incident (SI) investigations aim to identify factors that caused or could have caused serious patient harm. This study aimed to use the Human Factors Analysis and Classification System (HFACS) to characterise the contributory factors identified in SI investigation reports.

METHODS

We performed a content analysis of 126 investigation reports from a multi-site NHS trust. We used a HFACS-based framework that was modified through inductive analysis of the data.

RESULTS

Using the modified HFACS framework, 'unsafe actions' were the most commonly identified hierarchical level of contributory factors in investigation reports, which were identified 282 times across 99 (79%) incidents. 'Preconditions to unsafe acts' (identified 223 times in 91 (72%) incidents) included miscommunication and environmental factors. Supervisory factors were identified 73 times across 40 (31%) incidents, and organisational factors 115 times across 59 (47%) incidents. We identified 'extra-organisational factors' as a new HFACS level, though it was infrequently described.

CONCLUSIONS

Analysis of SI investigation reports using a modified HFACS framework allows important insights into what investigators view as contributory factors. We found an emphasis on human error but little engagement with why it occurs. Better investigations will require independence and professionalisation of investigators, human factors expertise, and a systems approach.

Application of the HEART method to enhance patient safety in the intensive care unit

BACKGROUND: The intensive care unit (ICU) is a complex, dynamic, high stress and time-sensitive place. While a variety of rules and regulations provided to reduce medication errors in recent years, many studies have emphasized that medication errors still happen. OBJECTIVE: The purpose of this investigation is to predict, reveal and assess medication errors among surgical intensive care unit (SICU) nurses. METHODS: This study was performed in one of the public hospitals in Shiraz, namely Shahid Faghihi hospital. The human error assessment and reduction technique (HEART) method was adopted to measure and assess medication errors in the ICU. RESULTS: Findings indicate that ICU nurses perform 27 main tasks and 125 sub-tasks. The results also showed that setting and using DC shock task has the highest human error probability value, and assessment of patients by a nutritionist has the lowest human error probability value. CONCLUSION: Medical errors are key challenges in the ICU. Therefore, alternative solutions to mitigate medication errors and enhance patient safety in the ICU are necessary. Although the technique can be used in healthcare; there is a need to localize the coefficients and definitions to achieve more accurate results and take appropriate controls. Employing experienced people and providing conditions that reduce the possibility of errors in nurses, increasing the number of staff, and developing specialized and simulated training were identified as the most important control strategies to reduce errors in nurses.

Development and initial psychometric testing of the Intrahospital Transport Safety Scale in intensive care

OBJECTIVE

To develop and evaluate the psychometric properties of a scale measuring patient safety during the intrahospital transport process for intensive care.

DESIGN

The scale was developed based on a theoretical model of the work system and patient safety, and items generated from participant observations. A Delphi study with international experts was used to establish content validity. Next, a cross-sectional study was undertaken to inform item reduction and evaluate construct validity and internal consistency.

SETTING

The questionnaire was distributed to healthcare practitioners at 12 intensive care units in Sweden.

PARTICIPANTS

A total of 315 questionnaires were completed. Eligible participants were healthcare practitioners in the included units that performed an intrahospital transport during the study period. Inclusion criteria were (1) transports of patients within the hospital to undergo an examination or intervention, and (2) transports performed by staff from the intensive care unit. We excluded transports to a step-down unit or hospital ward.

OUTCOME MEASURES

Psychometric evaluation, including item analysis, validity and reliability testing.

RESULTS

Items were reduced from 55 to 24, informed by distributional statistics, initial reliabilities, factor loadings and communalities. The final factor model consisted of five factors, accounting for 59% of variance. All items loaded significantly on only one factor (>0.35). The original conceptual model of teamwork, transport-related tasks, tools and technologies, environment, and organisation was maintained with regrouping of items. Cronbach's alpha ranged from 0.72 to 0.82 for each subscale (ie, factor).

CONCLUSIONS

The present study provides a self-report questionnaire to assess patient safety during intrahospital transport of patients in intensive care. The results indicate acceptable validity and reliability of the scale among a sample of Swedish healthcare practitioners. If further confirmatory testing supports the present results, this scale could be a useful tool to better understand safety prerequisites and improve clinical practice.

Voluntarily reported prescribing, monitoring and medication transfer errors in intensive care units in The Netherlands

Background Medication errors occur frequently in intensive care units (ICU). Voluntarily reported medication errors form an easily available source of information. Objective This study aimed to characterize prescribing, monitoring and medication transfer errors that were voluntarily reported in the ICU, in order to reveal medication safety issues. Setting This retrospective data analysis study included reports of medication errors from eleven Dutch ICU's from January 2016 to December 2017. Method We used data extractions from the incident reporting systems of the participating ICU's. The reports were transferred into one database and categorized into type of error, cause, medication (groups), and patient harm. Descriptive statistics were used to calculate the proportion of medication errors and the distribution of subcategories. Based on the analysis, ICU medication safety issues were revealed. Main outcome measure The main outcome measure was the proportion of prescribing, monitoring and medication transfer error reports. Results Prescribing errors were reported most frequently (n = 233, 33%), followed by medication transfer errors (n = 85, 12%) and monitoring errors (n = 27, 4%). Other findings were: medication transfer errors frequently caused serious harm, especially the omission of home medication involving the central nervous system and proton pump inhibitors; omissions and dosing errors occurred most frequently; protocol problems caused a quarter of the medication errors; and medications needing blood level monitoring (e.g. tacrolimus, vancomycin, heparin and insulin) were frequently involved. Conclusion This analysis of voluntarily reported prescribing, monitoring and medication transfer errors warrants several improvement measures in these processes, which may help to increase medication safety in the ICU.

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data

IMPORTANCE

Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged.

OBJECTIVE

To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018.

MAIN OUTCOMES AND MEASURES

Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved.

RESULTS

Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results.

CONCLUSIONS AND RELEVANCE

This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.