Integrating incident reporting into an electronic patient record system

Beyond adverse events in anesthesiology: 'unanticipated events' and strategies for improved reporting

PURPOSE OF REVIEW

Patient safety in anesthesiology has advanced significantly over the past several decades. The current process of improving care is often based on studying adverse events (AEs) and near misses. However, there is a wealth of information not captured by focusing solely on these events, potentially resulting in missed opportunities for care improvements.

RECENT FINDINGS

We review terms such as AEs and nonroutine events (NREs), and introduce the concept of unanticipated events (UEs), defined as events that deviate from intended care that may/may not have been caused by error, may/may not be preventable, and may/may not have caused injury to a patient. UEs incorporate AEs in addition to many other anesthetic events not routinely tracked, allowing for trend analysis over time and the identification of additional opportunities for quality improvement. We review both automated and self-reporting tools that currently exist to capture this often-neglected wealth of data. Finally, we discuss the responsibility of quality/safety leaders for data monitoring.

SUMMARY

Consistent reporting and monitoring for trends related to UEs could allow departments to identify risks and mitigate harm before it occurs. We review various proposed methods to expand data collection, and recommend anesthesia practices pursue UE tracking through department-specific reporting interfaces.

Electronic surveillance of patient safety events using natural language processing

Objective

We describe our approach to surveillance of reportable safety events captured in hospital data including free-text clinical notes. We hypothesize that a) some patient safety events are documented only in the clinical notes and not in any other accessible source; and b) large-scale abstraction of event data from clinical notes is feasible.

Materials and Methods

We use regular expressions to generate a training data set for a machine learning model and apply this model to the full set of clinical notes and conduct further review to identify safety events of interest. We demonstrate this approach on peripheral intravenous (PIV) infiltrations and extravasations (PIVIEs).

Results

During Phase 1, we collected 21,362 clinical notes, of which 2342 were reviewed. We identified 125 PIV events, of which 44 cases (35%) were not captured by other patient safety systems. During Phase 2, we collected 60,735 clinical notes and identified 440 infiltrate events. Our classifier demonstrated accuracy above 90%.

Conclusion

Our method to identify safety events from the free text of clinical documentation offers a feasible and scalable approach to enhance existing patient safety systems. Expert reviewers, using a machine learning model, can conduct routine surveillance of patient safety events.

The Abrupt Expansion of Ambulatory Telemedicine: Implications for Patient Safety

The exponential growth of telemedicine in ambulatory care triggered by the COVID-19 public health emergency has undoubtedly impacted the quality of care and patient safety. In particular, the increased adoption of remote care has impacted communication, care teams, and patient engagement, which are key factors that impact patient safety in ambulatory care. In this perspective, we draw on a scoping review of the literature, our own clinical experiences, and conversations with patient safety experts to describe how changes in communication, care teams, and patient engagement have impacted two high priority areas in ambulatory safety: diagnostic errors and medication safety. We then provide recommendations for research funders, researchers, healthcare systems, policy makers, and healthcare payors for how to improve patient safety in telemedicine based on what is currently known as well as next steps for how to advance understanding of the safety implications of telemedicine utilization.

The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children

Venous thromboembolism (VTE) is a potentially life-threatening condition that includes both deep vein thrombosis (DVT) and pulmonary embolism. We sought to improve detection and reporting of children with a new diagnosis of VTE by applying natural language processing (NLP) tools to radiologists' reports. We validated an NLP tool, Reveal NLP (Health Fidelity Inc, San Mateo, CA) and inference rules engine's performance in identifying reports with deep venous thrombosis using a curated set of ultrasound reports. We then configured the NLP tool to scan all available radiology reports on a daily basis for studies that met criteria for VTE between July 1, 2015, and March 31, 2016. The NLP tool and inference rules engine correctly identified 140 out of 144 reports with positive DVT findings and 98 out of 106 negative reports in the validation set. The tool's sensitivity was 97.2% (95% CI 93-99.2%), specificity was 92.5% (95% CI 85.7-96.7%). Subsequently, the NLP tool and inference rules engine processed 6373 radiology reports from 3371 hospital encounters. The NLP tool and inference rules engine identified 178 positive reports and 3193 negative reports with a sensitivity of 82.9% (95% CI 74.8-89.2) and specificity of 97.5% (95% CI 96.9-98). The system functions well as a safety net to screen patients for HA-VTE on a daily basis and offers value as an automated, redundant system. To our knowledge, this is the first pediatric study to apply NLP technology in a prospective manner for HA-VTE identification.

Enhancing Patient Safety Event Reporting. A Systematic Review of System Design Features

OBJECTIVES

Electronic patient safety event reporting (e-reporting) is an effective mechanism to learn from errors and enhance patient safety. Unfortunately, the value of e-reporting system (a software or web server based platform) in patient safety research is greatly overshadowed by low quality reporting. This paper aims at revealing the current status of system features, detecting potential gaps in system design, and accordingly proposing suggestions for future design and implementation of the system.

METHODS

Three literature databases were searched for publications that contain informative descriptions of e-reporting systems. In addition, both online publicly accessible reporting forms and systems were investigated.

RESULTS

48 systems were identified and reviewed. 11 system design features and their frequencies of occurrence (Top 5: widgets (41), anonymity or confidentiality (29), hierarchy (20), validator (17), review notification (15)) were identified and summarized into a system hierarchical model.

CONCLUSIONS

The model indicated the current e-reporting systems are at an immature stage in their development, and discussed their future development direction toward efficient and effective systems to improve patient safety.

Medication errors reported to the National Medication Error Reporting System in Malaysia: a 4-year retrospective review (2009 to 2012)

PURPOSE

Reporting and analysing the data on medication errors (MEs) is important and contributes to a better understanding of the error-prone environment. This study aims to examine the characteristics of errors submitted to the National Medication Error Reporting System (MERS) in Malaysia.

METHODS

A retrospective review of reports received from 1 January 2009 to 31 December 2012 was undertaken. Descriptive statistics method was applied.

RESULTS

A total of 17,357 MEs reported were reviewed. The majority of errors were from public-funded hospitals. Near misses were classified in 86.3 % of the errors. The majority of errors (98.1 %) had no harmful effects on the patients. Prescribing contributed to more than three-quarters of the overall errors (76.1 %). Pharmacists detected and reported the majority of errors (92.1 %). Cases of erroneous dosage or strength of medicine (30.75 %) were the leading type of error, whilst cardiovascular (25.4 %) was the most common category of drug found.

CONCLUSIONS

MERS provides rich information on the characteristics of reported MEs. Low contribution to reporting from healthcare facilities other than government hospitals and non-pharmacists requires further investigation. Thus, a feasible approach to promote MERS among healthcare providers in both public and private sectors needs to be formulated and strengthened. Preventive measures to minimise MEs should be directed to improve prescribing competency among the fallible prescribers identified.

A Narrative Review of Meaningful Use and Anesthesia Information Management Systems

The US federal government has enacted legislation for a federal incentive program for health care providers and hospitals to implement electronic health records. The primary goal of the Meaningful Use (MU) program is to drive adoption of electronic health records nationwide and set the stage to monitor and guide efforts to improve population health and outcomes. The MU program provides incentives for the adoption and use of electronic health record technology and, in some cases, penalties for hospitals or providers not using the technology. The MU program is administrated by the Department of Health and Human Services and is divided into 3 stages that include specific reporting and compliance metrics. The rationale is that increased use of electronic health records will improve the process of delivering care at the individual level by improving the communication and allow for tracking population health and quality improvement metrics at a national level in the long run. The goal of this narrative review is to describe the MU program as it applies to anesthesiologists in the United States. This narrative review will discuss how anesthesiologists can meet the eligible provider reporting criteria of MU by applying anesthesia information management systems (AIMS) in various contexts in the United States. Subsequently, AIMS will be described in the context of MU criteria. This narrative literature review also will evaluate the evidence supporting the electronic health record technology in the operating room, including AIMS, independent of certification requirements for the electronic health record technology under MU in the United States.

Medication incident reporting in residential aged care facilities: limitations and risks to residents' safety

BACKGROUND

Medication incident reporting (MIR) is a key safety critical care process in residential aged care facilities (RACFs). Retrospective studies of medication incident reports in aged care have identified the inability of existing MIR processes to generate information that can be used to enhance residents' safety. However, there is little existing research that investigates the limitations of the existing information exchange process that underpins MIR, despite the considerable resources that RACFs' devote to the MIR process. The aim of this study was to undertake an in-depth exploration of the information exchange process involved in MIR and identify factors that inhibit the collection of meaningful information in RACFs.

METHODS

The study was undertaken in three RACFs (part of a large non-profit organisation) in NSW, Australia. A total of 23 semi-structured interviews and 62 hours of observation sessions were conducted between May to July 2011. The qualitative data was iteratively analysed using a grounded theory approach.

RESULTS

The findings highlight significant gaps in the design of the MIR artefacts as well as information exchange issues in MIR process execution. Study results emphasized the need to: a) design MIR artefacts that facilitate identification of the root causes of medication incidents, b) integrate the MIR process within existing information systems to overcome key gaps in information exchange execution, and c) support exchange of information that can facilitate a multi-disciplinary approach to medication incident management in RACFs.

CONCLUSIONS

This study highlights the advantages of viewing MIR process holistically rather than as segregated tasks, as a means to identify gaps in information exchange that need to be addressed in practice to improve safety critical processes.

Interventions to increase clinical incident reporting in health care

BACKGROUND

Reporting of adverse clinical events is thought to be an effective method of improving the safety of healthcare. Underreporting of these adverse events is often said to occur with consequence of missing of opportunities to learn from these incidents. A clinical incident can be defined as any occurrence which is not consistent with the routine care of the patient or the routine operation of the institution.

OBJECTIVES

To assess the effects of interventions designed to increase clinical incident reporting in healthcare settings.

SEARCH METHODS

We searched the the following databases: Cochrane Effective Practice and Organisation of Care Group Specialised Register, the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (OVID), EMBASE (OVID), CINAHL (EBSCO), Social Science Citation Index and Science Citation Index (Web of Knowledge), Healthstar (OVID), INSPEC, DHSS-DATA, SIGLE, ISI Conference Proceedings, Web of Science Conference Proceedings Citation Index (Science), Database of Abstracts of Reviews of Effectiveness (DARE).

SELECTION CRITERIA

Randomised controlled trials (RCT), controlled before-after studies (CBA) and interrupted time series (ITS) of interventions designed to increase clinical incident reporting in healthcare.

DATA COLLECTION AND ANALYSIS

At least two review authors assessed the eligibility of potentially relevant studies, extracted the data and assessed the quality of included studies.

MAIN RESULTS

Four studies (one CBA and three ITS studies) met our inclusion criteria and were included in the review. The CBA study showed a significant improvement in incident reporting rates after the introduction of the new reporting system. Just one of the ITS studies showed a statistically significant improved effectiveness of the new reporting system from nine months. The other two studies reported no statistically significant improvements.

AUTHORS' CONCLUSIONS

Because of the limitations of the studies it is not possible to draw conclusions for clinical practice. Anyone introducing a system into practice should give careful consideration to conducting an evaluation using a robust design.

Clinical factors associated with the non-utilization of an anaesthesia incident reporting system

BACKGROUND

Incident reporting is a widely recommended method to measure undesirable events in anaesthesia. Under-utilization is a major weakness of voluntary incident reporting systems. Little is known about factors influencing reporting practices, particularly the clinical environment, anaesthesia team composition, severity of the incident, and perceived risk of litigation. The purpose of this study was to assess each of these, using an existing anaesthesia database.

METHODS

We performed a retrospective cohort study and analysed 46 207 surgical patients. We used multivariate analysis to identify factors associated with the non-utilization of the reporting system.

RESULTS

We found that in 7022 (15.1%) of the procedures performed, the incident reporting system was not used. Factors associated with the non-use of the system were regional anaesthesia/local anaesthesia, odds ratio (OR) 1.64 [95% confidence interval (CI) 1.03-2.62], emergency procedures OR 1.15 (95% CI: 1.05-1.27), and a consultant anaesthetist working without a trainee, OR 1.71 (95% CI: 1.03-2.82). In contrast, factors such as longer duration of surgery, OR 0.85 (95% CI: 0.76-0.94), the presence of a senior anaesthesia trainee, OR 0.86 (95% CI: 0.81-0.92), and the occurrence of severe complications with a high risk of litigation (i.e. death, nerve injuries) were less associated with a non-use of the reporting system, OR 0.65 (95% CI: 0.44-0.97). Team composition and time of day had no measurable impact on reporting practices.

CONCLUSIONS

Clinical factors play a significant role in the utilization of an anaesthesia incident reporting system and more particularly, severity of complications and higher liability risks which appear more as incentives than barriers to incident reporting.

Development of a validation algorithm for 'present on admission' flagging

BACKGROUND

The use of routine hospital data for understanding patterns of adverse outcomes has been limited in the past by the fact that pre-existing and post-admission conditions have been indistinguishable. The use of a 'Present on Admission' (or POA) indicator to distinguish pre-existing or co-morbid conditions from those arising during the episode of care has been advocated in the US for many years as a tool to support quality assurance activities and improve the accuracy of risk adjustment methodologies. The USA, Australia and Canada now all assign a flag to indicate the timing of onset of diagnoses. For quality improvement purposes, it is the 'not-POA' diagnoses (that is, those acquired in hospital) that are of interest.

METHODS

Our objective was to develop an algorithm for assessing the validity of assignment of 'not-POA' flags. We undertook expert review of the International Classification of Diseases, 10th Revision, Australian Modification (ICD-10-AM) to identify conditions that could not be plausibly hospital-acquired. The resulting computer algorithm was tested against all diagnoses flagged as complications in the Victorian (Australia) Admitted Episodes Dataset, 2005/06. Measures reported include rates of appropriate assignment of the new Australian 'Condition Onset' flag by ICD chapter, and patterns of invalid flagging.

RESULTS

Of 18,418 diagnosis codes reviewed, 93.4% (n = 17,195) reflected agreement on status for flagging by at least 2 of 3 reviewers (including 64.4% unanimous agreement; Fleiss' Kappa: 0.61). In tests of the new algorithm, 96.14% of all hospital-acquired diagnosis codes flagged were found to be valid in the Victorian records analysed. A lower proportion of individual codes was judged to be acceptably flagged (76.2%), but this reflected a high proportion of codes used <5 times in the data set (789/1035 invalid codes).

CONCLUSION

An indicator variable about the timing of occurrence of diagnoses can greatly expand the use of routinely coded data for hospital quality improvement programmes. The data-cleaning instrument developed and tested here can help guide coding practice in those health systems considering this change in hospital coding. The algorithm embodies principles for development of coding standards and coder education that would result in improved data validity for routine use of non-POA information.

Rate of undesirable events at beginning of academic year: retrospective cohort study

OBJECTIVE

To determine whether an increase in the rate of undesirable events occurs after care provided by trainees at the beginning of the academic year.

DESIGN

Retrospective cohort study using administrative and patient record data.

SETTING

University affiliated hospital in Melbourne, Australia.

PARTICIPANTS

19,560 patients having an anaesthetic procedure carried out by first to fifth year trainees starting work for the first time at the hospital over a period of five years (1995-2000).

MAIN OUTCOME MEASURES

Absolute event rates, absolute rate reduction, and rate ratios of undesirable events.

RESULTS

The rate of undesirable events was higher at the beginning of the academic year compared with the rest of the year (absolute event rate 137 v 107 per 1000 patient hours, relative rate reduction 28%, P<0.001). The overall adjusted rate ratio for undesirable events was 1.40, 95% confidence interval 1.24 to 1.58. This excess risk was seen for all residents, regardless of their level of seniority. The excess risk decreased progressively after the first month, and the trend disappeared fully after the fourth month of the year (rate ratio for fourth month 1.21, 0.93 to 1.57). The most important decreases were for central and peripheral nerve injuries (relative difference 82%), inadequate oxygenation of the patient (66%), vomiting/aspiration in theatre (53%), and technical failures of tracheal tube placement (49%).

CONCLUSIONS

The rate of undesirable events was greater among trainees at the beginning of the academic year regardless of their level of clinical experience. This suggests that several additional factors, such as knowledge of the working environment, teamwork, and communication, may contribute to the increase.

The automation of clinical trial serious adverse event reporting workflow

BACKGROUND

The reporting of serious adverse events is a requirement when conducting a clinical trial involving human subjects, necessary for the protection of the participants. The reporting process is a multi-step procedure, involving a number of individuals from initiation to final review, and must be completed in a timely fashion.

PURPOSE

The purpose of this project was to automate the adverse event reporting process, replacing paper-based processes with computer-based processes, so that personnel effort and time required for serious adverse event reporting was reduced, and the monitoring of reporting performance and adverse event characteristics was facilitated.

METHODS

Use case analysis was employed to understand the reporting workflow and generate software requirements. The automation of the workflow was then implemented, employing computer databases, web-based forms, electronic signatures, and email communication.

RESULTS

In the initial year (2007) of full deployment, 588 SAE reports were processed by the automated system, eSAEy. The median time from initiation to Principal Investigator electronic signature was <2 days (mean 7 +/- 0.7 days). This was a significant reduction from the prior paper-based system, which had a median time for signature of 24 days (mean of 45 +/- 5.7 days). With eSAEy, reports on adverse event characteristics (type, grade, etc.) were easily obtained and had consistent values based on standard terminologies.Limitation The automated system described was designed specifically for the workflow at Thomas Jefferson University. While the methodology for system design, and the system requirements derived from common clinical trials adverse reporting procedures are applicable in general, specific workflow details may not be relevant at other institutions.

CONCLUSION

The system facilitated analysis of individual investigator reporting performance, as well as the aggregation and analysis of the nature of reported adverse events.

The value proposition of anesthesia information management systems

Anesthesia information management systems add value to the anesthesiologist and the hospital above that which is provided by manual anesthesia records. The more complete documentation and less biased recording of vital signs in this system, relative to manual records, provide data needed for quality initiatives and operating room management and for clinical research. The system can improve the ability to increase anesthesia charge capture, meet the requirements of pay-for-performance programs, and assist in the defense of malpractice allegations. Realization of value from the anesthesia information management systems requires additional expenditures of resources to adapt the systems to meet specific institutional requirements.

Using electronic medical records to enhance detection and reporting of vaccine adverse events

We implemented an automated vaccine adverse event surveillance and reporting system based in an ambulatory electronic medical record to improve underreporting and incomplete reporting that prevails in spontaneous systems. This automated system flags potential vaccine adverse events for the clinician when a diagnosis is entered, prompts clinicians to consider the vaccine as a cause of the condition, and facilitates reporting of suspected adverse events to the Vaccine Adverse Event Reporting System (VAERS). During five months, a total of 33,420 vaccinations were administered during 14,466 encounters. There were 5,914 follow-up contacts by vaccinees within 14 days of the vaccination visits; 686 (11.6%) generated an alert. Clinicians submitted VAERS reports for 23 of these (0.69 per 1,000 vaccine doses), which is almost 6 times the dose-based reporting rate to VAERS. (1) Clinician surveys indicated that it took a minimal amount of time to respond to the alerts. Of those who felt that an alert corresponded to an actual vaccine adverse event, the majority used the reporting feature to file a VAERS report. We believe that elicited surveillance via real time prompts to clinicians holds substantial promise. By coupling simplified reporting with the initial prompt, clinicians can consider and report a vaccine adverse event electronically in a few moments during the office visit.