Prescription errors and outcomes related to inconsistent information transmitted through computerized order entry: a prospective study

Why Test Results Are Still Getting "Lost" to Follow-up: a Qualitative Study of Implementation Gaps

BACKGROUND

Lack of timely follow-up of abnormal test results is common and has been implicated in missed or delayed diagnosis, resulting in potential for patient harm.

OBJECTIVE

As part of a larger project to implement change strategies to improve follow-up of diagnostic test results, this study sought to identify specifically where implementation gaps exist, as well as possible solutions identified by front-line staff.

DESIGN

We used a semi-structured interview guide to collect qualitative data from Veterans Affairs (VA) facility staff who had experience with test results management and patient safety.

SETTING

Twelve VA facilities across the USA.

PARTICIPANTS

Facility staff members (n = 27), including clinicians, lab and imaging professionals, nursing staff, patient safety professionals, and leadership.

APPROACH

We conducted a content analysis of interview transcripts to identify perceived barriers and high-risk areas for effective test result management, as well as recommendations for improvement.

RESULTS

We identified seven themes to guide further development of interventions to improve test result follow-up. Themes related to trainees, incidental findings, tracking systems for electronic health record notifications, outdated contact information, referrals, backup or covering providers, and responsibility for test results pending at discharge. Participants provided recommendations for improvement within each theme.

CONCLUSIONS

Perceived barriers and recommendations for improving test result follow-up often reflected previously known problems and their corresponding solutions, which have not been consistently implemented in practice. Better policy solutions and improvement methods, such as quality improvement collaboratives, may bridge the implementation gaps between knowledge and practice.

Electronic Medication Management Systems: Analysis of Enhancements to Reduce Errors and Improve Workflow

BACKGROUND

Electronic medication management (eMM) has been shown to reduce medication errors; however, new safety risks have also been introduced that are associated with system use. No research has specifically examined the changes made to eMM systems to mitigate these risks.

OBJECTIVES

To (1) identify system-related medication errors or workflow blocks that were the target of eMM system updates, including the types of medications involved, and (2) describe and classify the system enhancements made to target these risks.

METHODS

In this retrospective qualitative study, documents detailing updates made from November 2014 to December 2019 to an eMM system were reviewed. Medication-related updates were classified according to "rationale for changes" and "changes made to the system."

RESULTS

One hundred and seventeen updates, totaling 147 individual changes, were made to the eMM system over the 4-year period. The most frequent reasons for changes being made to the eMM were to prevent medication errors (24% of reasons), optimize workflow (22%), and support "work as done" on paper (16%). The most frequent changes made to the eMM were options added to lists (14% of all changes), extra information made available on the screen (8%), and the wording or phrasing of text modified (8%). Approximately a third of the updates (37%) related to high-risk medications. The reasons for system changes appeared to vary over time, as eMM functionality and use expanded.

CONCLUSION

To our knowledge, this is the first study to systematically review and categorize system updates made to overcome new safety risks associated with eMM use. Optimization of eMM is an ongoing process, which changes over time as users become more familiar with the system and use is expanded to more sites. Continuous monitoring of the system is necessary to detect areas for improvement and capitalize on the benefits an electronic system can provide.

Comparison of Diagnostic Recommendations from Individual Physicians versus the Collective Intelligence of Multiple Physicians in Ambulatory Cases Referred for Specialist Consultation

BACKGROUND

Studies report higher diagnostic accuracy using the collective intelligence (CI) of multiple clinicians compared with individual clinicians. However, the diagnostic process is iterative, and unexplored is the value of CI in improving clinical recommendations leading to a final diagnosis.

METHODS

To compare the appropriateness of diagnostic recommendations advised by individual physicians versus the CI of physicians, we entered actual consultation requests sent by primary care physicians to specialists onto a web-based CI platform capable of collecting diagnostic recommendations (next steps for care) from multiple physicians. We solicited responses to 35 cases (12 endocrinology, 13 gynecology, 10 neurology) from ≥3 physicians of any specialty through the CI platform, which aggregated responses into a CI output. The primary outcome was the appropriateness of individual physician recommendations versus the CI output recommendations, using recommendations agreed upon by 2 specialists in the same specialty as a gold standard. The secondary outcome was the recommendations' potential for harm.

RESULTS

A total of 177 physicians responded. Cases had a median of 7 respondents (interquartile range: 5-10). Diagnostic recommendations in the CI output achieved higher levels of appropriateness (69%) than recommendations from individual physicians (45%; χ² = 5.95, P = 0.015). Of the CI recommendations, 54% were potentially harmful, as compared with 41% of individuals' recommendations (χ² = 2.49, P = 0.11).

LIMITATIONS

Cases were from a single institution. CI was solicited using a single algorithm/platform.

CONCLUSIONS

When seeking specialist guidance, diagnostic recommendations from the CI of multiple physicians are more appropriate than recommendations from most individual physicians, measured against specialist recommendations. Although CI provides useful recommendations, some have potential for harm. Future research should explore how to use CI to improve diagnosis while limiting harm from inappropriate tests/therapies.

Medication Safety in Two Intensive Care Units of a Community Teaching Hospital After Electronic Health Record Implementation: Sociotechnical and Human Factors Engineering Considerations

OBJECTIVE

The aim of the study was to assess the impact of Electronic Health Record (EHR) implementation on medication safety in two intensive care units (ICUs).

METHODS

Using a prospective pre-post design, we assessed 1254 consecutive admissions to two ICUs before and after an EHR implementation. Each medication event was evaluated with regard to medication error (error type, medication-management stage) and impact on patient (severity of potential or actual harm).

RESULTS

We identified 4063 medication-related events either pre-implementation (2074 events) or post-implementation (1989 events). Although the overall potential for harm due to medication errors decreased post-implementation only 2 of the 3 error rates were significantly lower post-implementation. After EHR implementation, we observed reductions in rates of medication errors per admission at the stages of transcription (0.13-0, P < 0.001), dispensing (0.49-0.16, P < 0.001), and administration (0.83-0.56, P = 0.011). Within the ordering stage, 4 error types decreased post-implementation (orders with omitted information, error-prone abbreviations, illegible orders, failure to renew orders) and 4 error types increased post-implementation (orders of wrong drug, orders containing a wrong start or stop time, duplicate orders, orders with inappropriate or wrong information). Within the administration stage, we observed a reduction of late administrations and increases in omitted administrations and incorrect documentation.

CONCLUSIONS

Electronic Health Record implementation in two ICUs was associated with both improvement and worsening in rates of specific error types. Further safety improvements require a nuanced understanding of how various error types are influenced by the technology and the sociotechnical work system of the technology implementation. Recommendations based on human factors engineering principles are provided for reducing medication errors.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co‐administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

Clinician Perceptions on the Use of Free-Text Communication Orders

OBJECTIVE

The aim of this study was to investigate (1) why ordering clinicians use free-text orders to communicate medication information; (2) what risks physicians and nurses perceive when free-text orders are used for communicating medication information; and (3) how electronic health records (EHRs) could be improved to encourage the safe communication of medication information.

METHODS

We performed semi-structured, scenario-based interviews with eight physicians and eight nurses. Interview responses were analyzed and grouped into common themes.

RESULTS

Participants described eight reasons why clinicians use free-text medication orders, five risks relating to the use of free-text medication orders, and five recommendations for improving EHR medication-related communication. Poor usability, including reduced efficiency and limited functionality associated with structured order entry, was the primary reason clinicians used free-text orders to communicate medication information. Common risks to using free-text orders for medication communication included the increased likelihood of missing orders and the increased workload on nurses responsible for executing orders.

DISCUSSION

Clinicians' use of free-text orders is primarily due to limitations in the current structured order entry design. To encourage the safe communication of medication information between clinicians, the EHR's structured order entry must be redesigned to support clinicians' cognitive and workflow needs that are currently being addressed via the use of free-text orders.

CONCLUSION

Clinicians' use of free-text orders as a workaround to insufficient structured order entry can create unintended patient safety risks. Thoughtful solutions designed to address these workarounds can improve the medication ordering process and the subsequent medication administration process.

Contextual property detection in Dutch diagnosis descriptions for uncertainty, laterality and temporality

Background

Accurate, coded problem lists are valuable for data reuse, including clinical decision support and research. However, healthcare providers frequently modify coded diagnoses by including or removing common contextual properties in free-text diagnosis descriptions: uncertainty (suspected glaucoma), laterality (left glaucoma) and temporality (glaucoma 2002). These contextual properties could cause a difference in meaning between underlying diagnosis codes and modified descriptions, inhibiting data reuse. We therefore aimed to develop and evaluate an algorithm to identify these contextual properties.

Methods

A rule-based algorithm called UnLaTem (Uncertainty, Laterality, Temporality) was developed using a single-center dataset, including 288,935 diagnosis descriptions, of which 73,280 (25.4%) were modified by healthcare providers. Internal validation of the algorithm was conducted with an independent sample of 980 unique records. A second validation of the algorithm was conducted with 996 records from a Dutch multicenter dataset including 175,210 modified descriptions of five hospitals. Two researchers independently annotated the two validation samples. Performance of the algorithm was determined using means of the recall and precision of the validation samples. The algorithm was applied to the multicenter dataset to determine the actual prevalence of the contextual properties within the modified descriptions per specialty.

Results

For the single-center dataset recall (and precision) for removal of uncertainty, uncertainty, laterality and temporality respectively were 100 (60.0), 99.1 (89.9), 100 (97.3) and 97.6 (97.6). For the multicenter dataset for removal of uncertainty, uncertainty, laterality and temporality it was 57.1 (88.9), 86.3 (88.9), 99.7 (93.5) and 96.8 (90.1). Within the modified descriptions of the multicenter dataset, 1.3% contained removal of uncertainty, 9.9% uncertainty, 31.4% laterality and 9.8% temporality.

Conclusions

We successfully developed a rule-based algorithm named UnLaTem to identify contextual properties in Dutch modified diagnosis descriptions. UnLaTem could be extended with more trigger terms, new rules and the recognition of term order to increase the performance even further. The algorithm’s rules are available as additional file 2. Implementing UnLaTem in Dutch hospital systems can improve precision of information retrieval and extraction from diagnosis descriptions, which can be used for data reuse purposes such as decision support and research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01477-y.

Computerized provider order entry-related medication errors among hospitalized patients: An integrative review

The Institute of Medicine estimates that 7,000 lives are lost yearly as a result of medication errors. Computerized physician and/or provider order entry was one of the proposed solutions to overcome this tragic issue. Despite some promising data about its effectiveness, it has been found that computerized provider order entry may facilitate medication errors.The purpose of this review is to summarize current evidence of computerized provider order entry -related medication errors and address the sociotechnical factors impacting the safe use of computerized provider order entry. By using PubMed and Google Scholar databases, a systematic search was conducted for articles published in English between 2007 and 2019 regarding the unintended consequences of computerized provider order entry and its related medication errors. A total of 288 articles were screened and categorized based on their use within the review. One hundred six articles met our pre-defined inclusion criteria and were read in full, in addition to another 27 articles obtained from references. All included articles were classified into the following categories: rates and statistics on computerized provider order entry -related medication errors, types of computerized provider order entry -related unintended consequences, factors contributing to computerized provider order entry failure, and recommendations based on addressing sociotechnical factors. Identifying major types of computerized provider order entry -related unintended consequences and addressing their causes can help in developing appropriate strategies for safe and effective computerized provider order entry. The interplay between social and technical factors can largely affect its safe implementation and use. This review discusses several factors associated with the unintended consequences of this technology in healthcare settings and presents recommendations for enhancing its effectiveness and safety within the context of sociotechnical factors.

The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

BACKGROUND

Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)-facilitated by smart-pump technology-were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital.

OBJECTIVE

The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors.

METHODS

A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized.

RESULTS

A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified.

CONCLUSION

The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

Analysis of medication therapy discontinuation orders in new electronic prescriptions and opportunities for implementing CancelRx

Objective

To illustrate the need for wider implementation of the CancelRx message by quantifying and characterizing the inappropriate usage of new electronic prescription (NewRx) messages for communicating discontinuation instructions to pharmacies.

Materials and Methods

A retrospective analysis on a nationally representative random sample of 1 400 000 NewRx messages transmitted over 7 days to identify e-prescriptions containing medication discontinuation instructions in NewRx text fields. A vocabulary of search terms signifying cancellation instructions was formulated and then iteratively refined. True-positives were subsequently identified programmatically and through manual reviews. Two independent reviewers identified incidences in which these instructions were associated with high-alert or look-alike-sound-like (LASA) medications.

Results

We identified 9735 (0.7% of the total) NewRx messages containing prescription cancellation instructions with 78.5% observed in the Notes field; 35.3% of identified NewRxs were associated with high-alert or LASA medications. The most prevalent cancellation instruction types were medication strength or dosage changes (39.3%) and alternative therapy replacement orders (39.0%).

Discussion

While the incidence of prescribers using the NewRx to transmit cancellation instructions was low, their transmission in NewRx fields not intended to accommodate such information can produce significant potential patient safety concerns, such as duplicate or inaccurate therapies. These findings reveal the need for wider industry adoption of the CancelRx message by electronic health record (EHR) and pharmacy systems, along with clearer guidance and improved end-user training, particularly as states increasingly mandate electronic prescribing of controlled substances.

Conclusion

Encouraging the use of CancelRx and reducing the misuse of NewRx fields would reduce workflow disruptions and unnecessary risks to patient safety.

Electronic Health Records and Use of Clinical Decision Support

In 2009, the Health Information Technology for Economic and Clinical Health (HITECH) Act was signed into law. Along with this initiative came the push for meaningful use of the electronic health record. Clinicians, information technology professionals, and informaticists must partner to create evidence-based clinical decision support models to guide patient care using tools such as structured computerized physician order entry, order sets, templates, alerts, and reminders. Clinical decision support should be used to improve the quality of patient care and compliance with regulatory standards, while inherently following a provider's workflow.

The impact of computerised physician order entry and clinical decision support on pharmacist-physician communication in the hospital setting: A qualitative study

BACKGROUND

The implementation of Computerised Physician Order Entry (CPOE) and Clinical Decision Support (CDS) has been found to have some unintended consequences. The aim of this study is to explore pharmacists and physicians perceptions of their interprofessional communication in the context of the technology and whether electronic messaging and CDS has an impact on this.

METHOD

This qualitative study was conducted in two acute hospitals: the University Hospitals Birmingham NHS Foundation Trust (UHBFT) and Guy's and St Thomas' NHS Foundation Trust (GSTH). UHBFT use an established locally developed CPOE system that can facilitate pharmacist-physician communication with the ability to assign a message directly to an electronic prescription. In contrast, GSTH use a more recently implemented commercial system where such communication is not possible. Focus groups were conducted with pharmacists and physicians of varying grades at both hospitals. Focus group data were transcribed and analysed thematically using deductive and inductive approaches, facilitated by NVivo 10.

RESULTS

Three prominent themes emerged during the study: increased communication load; impaired decision-making; and improved workflow. CPOE and CDS were found to increase the communication load for the pharmacist owing to a reduced ability to amend electronic prescriptions, new types of prescribing errors, and the provision of technical advice relating to the use of the system. Decision-making was found to be affected, owing to the difficulties faced by pharmacists and physicians when trying to determine the context of prescribing decisions and knowledge of the patient. The capability to communicate electronically facilitated a non-interruptive workflow, which was found to be beneficial for staff time, coordination of work and for limiting distractions.

CONCLUSION

The increased communication load for the pharmacist, and consequent workload for the physician, has the potential to impact on the quality and coordination of care in the hospital setting. The ability to communicate electronically has some benefits, but functions need to be designed to facilitate collaborative working, and for this to be optimised through interprofessional training.

Toward safer health care: a review strategy of FDA medical device adverse event database to identify and categorize health information technology related events

Introduction

Health information technology (HIT) is intended to provide safer and better care to patients. However, poorly designed or implemented HIT poses a key risk to patient safety. It is essential for healthcare providers and researchers to investigate the HIT-related events. Unfortunately, the lack of HIT-related event databases in the community hinders the analysis and management of HIT-related events.

Objectives

Develop a standardized process for identifying HIT-related events from a Federal Drug Administration (FDA) database in order to create an HIT exclusive database for analysis and learning.

Methods

The FDA Manufacturer and User Facility Device Experience (MAUDE) database, containing over 7-million reports about medical device malfunctions and problems leading to serious injury or death, was considered as a potential resource to identify HIT-related events. We developed a strategy of identifying and categorizing HIT-related events from the FDA reports through the application of a keyword filter and standardized expert review. Ten percent identified reports were reviewed to measure the consistency among experts and to initialize a database for HIT-related events.

Results

With the proposed strategy, we initialized an HIT-related event database with over 3500 reports, and updated the estimation of the HIT-related event proportion in the FDA MAUDE database to 0.46∼0.69%, up to 50,000 HIT-related events.

Conclusion

The proposed strategy for HIT-related event identification holds promise in aiding the understanding, characterization, discovery, and reporting of HIT-related events toward improved patient safety. The analysis of contributing factors under the 8-dimensional sociotechnical model shows that hardware and software, clinical content, and human-computer interface were identified more frequently than the other dimensions.

Sociotechnical factors influencing unsafe use of hospital information systems: A qualitative study in Malaysian government hospitals

The objective of this study is to identify factors influencing unsafe use of hospital information systems in Malaysian government hospitals. Semi-structured interviews with 31 medical doctors in three Malaysian government hospitals implementing total hospital information systems were conducted between March and May 2015. A thematic qualitative analysis was performed on the resultant data to deduce the relevant themes. A total of five themes emerged as the factors influencing unsafe use of a hospital information system: (1) knowledge, (2) system quality, (3) task stressor, (4) organization resources, and (5) teamwork. These qualitative findings highlight that factors influencing unsafe use of a hospital information system originate from multidimensional sociotechnical aspects. Unsafe use of a hospital information system could possibly lead to the incidence of errors and thus raises safety risks to the patients. Hence, multiple interventions (e.g. technology systems and teamwork) are required in shaping high-quality hospital information system use.

Quality and Variability of Patient Directions in Electronic Prescriptions in the Ambulatory Care Setting

BACKGROUND

The prescriber's directions to the patient (Sig) are one of the most quality-sensitive components of a prescription order. Owing to their free-text format, the Sig data that are transmitted in electronic prescriptions (e-prescriptions) have the potential to produce interpretation challenges at receiving pharmacies that may threaten patient safety and also negatively affect medication labeling and patient counseling. Ensuring that all data transmitted in the e-prescription are complete and unambiguous is essential for minimizing disruptions in workflow at prescribers' offices and receiving pharmacies and optimizing the safety and effectiveness of patient care.

OBJECTIVES

To (a) assess the quality and variability of free-text Sig strings in ambulatory e-prescriptions and (b) propose best-practice recommendations to improve the use of this quality-sensitive field.

METHODS

A retrospective qualitative analysis was performed on a nationally representative sample of 25,000 e-prescriptions issued by 22,152 community-based prescribers across the United States using 501 electronic health records (EHRs) or e-prescribing software applications. The content of Sig text strings in e-prescriptions was classified according to a Sig classification scheme developed with guidance from an expert advisory panel. The Sig text strings were also analyzed for quality-related events (QREs). For purposes of this analysis, QREs were defined as Sig text content that could impair accurate and unambiguous interpretation by staff at receiving pharmacies.

RESULTS

A total of 3,797 unique Sig concepts were identified in the 25,000 Sig text strings analyzed; more than 50% of all Sigs could be categorized into 25 unique Sig concepts. Even Sig strings that expressed apparently simple and straightforward concepts displayed substantial variability; for example, the sample contained 832 permutations of words and phrases used to convey the Sig concept of "Take 1 tablet by mouth once daily." Approximately 10% of Sigs contained QREs that could pose patient safety risks or workflow disruptions that could necessitate pharmacist callbacks to prescribers for clarification or other manual interventions.

CONCLUSIONS

The quality of free-text patient directions in e-prescriptions can vary dramatically. However, more than half of all patient directions sent in the ambulatory setting can be categorized into only 25 Sig concepts. This suggests an immediate, practical opportunity to improve patient safety and workflow efficiency for both prescribers and pharmacies. Recommendations include implementing enhancements to Sig creation tools in e-prescribing and EHR software applications, adoption of the Structured and Codified Sig format supported by the current national e-prescribing standard, and improved usability testing and end-user training for generating complete and unambiguous patient directions. Such quality improvements are essential for optimizing the safety and effectiveness of patient care as well as for minimizing workflow disruptions to both prescribers and pharmacies.

DISCLOSURES

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Yang, Ward-Charlerie, Dhavle, and Green are employed by Surescripts. Rupp reported receiving consulting fees from Surescripts during the conduct of this study. No other disclosures were reported. The content in this article is solely the responsibility of the authors and does not necessarily represent the official views of Surescripts and Midwestern University or any of the affiliated institutions of the authors. Study concept and design were contributed by all the authors. Yang and Ward-Charlerie collected the data, and data interpretion was performed by Yang, Ward-Charlerie and Dhavle. The manuscript was primarily written by Yang, along with Dhavle and Green, and revised by Yang, Dhavle, Rupp, and Green.

Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review

Objective

To systematically review studies reporting problems with information technology (IT) in health care and their effects on care delivery and patient outcomes.

Materials and methods

We searched bibliographic databases including Scopus, PubMed, and Science Citation Index Expanded from January 2004 to December 2015 for studies reporting problems with IT and their effects. A framework called the information value chain, which connects technology use to final outcome, was used to assess how IT problems affect user interaction, information receipt, decision-making, care processes, and patient outcomes. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

Results

Of the 34 studies identified, the majority ( n  = 14, 41%) were analyses of incidents reported from 6 countries. There were 7 descriptive studies, 9 ethnographic studies, and 4 case reports. The types of IT problems were similar to those described in earlier classifications of safety problems associated with health IT. The frequency, scale, and severity of IT problems were not adequately captured within these studies. Use errors and poor user interfaces interfered with the receipt of information and led to errors of commission when making decisions. Clinical errors involving medications were well characterized. Issues with system functionality, including poor user interfaces and fragmented displays, delayed care delivery. Issues with system access, system configuration, and software updates also delayed care. In 18 studies (53%), IT problems were linked to patient harm and death. Near-miss events were reported in 10 studies (29%).

Discussion and conclusion

The research evidence describing problems with health IT remains largely qualitative, and many opportunities remain to systematically study and quantify risks and benefits with regard to patient safety. The information value chain, when used in conjunction with existing classifications for health IT safety problems, can enhance measurement and should facilitate identification of the most significant risks to patient safety.

Paediatric in-patient prescribing errors in Malaysia: a cross-sectional multicentre study

Background There is a lack of large comprehensive studies in developing countries on paediatric in-patient prescribing errors in different settings. Objectives To determine the characteristics of in-patient prescribing errors among paediatric patients. Setting General paediatric wards, neonatal intensive care units and paediatric intensive care units in government hospitals in Malaysia. Methods This is a cross-sectional multicentre study involving 17 participating hospitals. Drug charts were reviewed in each ward to identify the prescribing errors. All prescribing errors identified were further assessed for their potential clinical consequences, likely causes and contributing factors. Main outcome measures Incidence, types, potential clinical consequences, causes and contributing factors of the prescribing errors. Results The overall prescribing error rate was 9.2% out of 17,889 prescribed medications. There was no significant difference in the prescribing error rates between different types of hospitals or wards. The use of electronic prescribing had a higher prescribing error rate than manual prescribing (16.9 vs 8.2%, p < 0.05). Twenty eight (1.7%) prescribing errors were deemed to have serious potential clinical consequences and 2 (0.1%) were judged to be potentially fatal. Most of the errors were attributed to human factors, i.e. performance or knowledge deficit. The most common contributing factors were due to lack of supervision or of knowledge. Conclusions Although electronic prescribing may potentially improve safety, it may conversely cause prescribing errors due to suboptimal interfaces and cumbersome work processes. Junior doctors need specific training in paediatric prescribing and close supervision to reduce prescribing errors in paediatric in-patients.

Minding the Gaps: Assessing Communication Outcomes of Electronic Preconsultation Exchange

BACKGROUND

Effective communication between referring and specialty providers is key to optimizing patient safety. Communication was assessed in an electronic referral system by review of referrals to a public urban health care system's gastroenterology clinic that were not scheduled for appointments.

METHODS

All electronic referrals to a publicly funded, urban health care system's adult gastroenterology clinic from November 1, 2009, to November 30, 2010, were reviewed that did not result in scheduling of appointments. An assessment was made of whether in-person visits were unnecessary by preconsultation exchange or whether the referrals remained unscheduled for other reasons. For the latter group, reasons why the referrals remained unscheduled were examined, and medical records were reviewed for actual patient harm when sufficient information was present in the chart or for potential harm when no further information about the referral complaint was available.

RESULTS

Eighty-six (32%) of 266 not-scheduled referrals were resolved via preconsultation exchange. For another 96 (36%), patients were not ultimately considered to require appointments or were scheduled via other routes. Nine patients received unplanned care while awaiting scheduling decisions, 5 of whom had harm that was related to referral complaints, although scheduling of appointments may not have avoided this harm. Of 75 patients for whom further information was not available about the referral complaints, most were not seen back in primary care, and 55 (73%) had potential for major harm.

CONCLUSION

Few adverse outcomes in electronic referrals not scheduled for in-person gastroenterology visits were found, and none were clearly due to communication lapses in the referral process. Contributors to the potential for harm in referrals that were unintentionally left unscheduled included discontinuity of care and lack of patient or provider follow-up.

EHR-related medication errors in two ICUs

The objective of this study was to describe the frequency, potential harm, and nature of electronic health record (EHR)-related medication errors in intensive care units (ICUs). Using a secondary data analysis of a large database of medication safety events collected in a study on EHR technology in ICUs, we assessed the EHR relatedness of a total of 1622 potential preventable adverse drug events (ADEs) identified in a sample of 624 patients in 2 ICUs of a medical center. Thirty-four percent of the medication events were found to be EHR related. The EHR-related medication events had greater potential for more serious patient harm and occurred more frequently at the ordering stage as compared to non-EHR-related events. Examples of EHR-related events included orders with omitted information and duplicate orders. The list of EHR-related medication errors can be used by health care delivery organizations to monitor implementation and use of the technology and its impact on patient safety. Health information technology (IT) vendors can use the list to examine whether their technology can mitigate or reduce EHR-related medication errors.

Adverse inpatient outcomes during the transition to a new electronic health record system: observational study

OBJECTIVE

 To assess the short term association of inpatient implementation of electronic health records (EHRs) with patient outcomes of mortality, readmissions, and adverse safety events.

DESIGN

 Observational study with difference-in-differences analysis.

SETTING

 Medicare, 2011-12.

PARTICIPANTS

 Patients admitted to 17 study hospitals with a verifiable "go live" date for implementation of inpatient EHRs during 2011-12, and 399 control hospitals in the same hospital referral region.

MAIN OUTCOME MEASURES

 All cause readmission within 30 days of discharge, all cause mortality within 30 days of admission, and adverse safety events as defined by the patient safety for selected indicators (PSI)-90 composite measure among Medicare beneficiaries admitted to one of these hospitals 90 days before and 90 days after implementation of the EHRs (n=28 235 and 26 453 admissions), compared with the control group of all contemporaneous admissions to hospitals in the same hospital referral region (n=284 632 and 276 513 admissions). Analyses were adjusted for beneficiaries' sociodemographic and clinical characteristics.

RESULTS

 Before and after implementation, characteristics of admissions were similar in both study and control hospitals. Among study hospitals, unadjusted 30 day mortality (6.74% to 7.15%, P=0.06) and adverse safety event rates (10.5 to 11.4 events per 1000 admissions, P=0.34) did not significantly change after implementation of EHRs. There was an unadjusted decrease in 30 day readmission rates, from 19.9% to 19.0% post-implementation (P=0.02). In difference-in-differences analysis, however, there was no significant change in any outcome between pre-implementation and post-implementation periods (all P≥0.13).

CONCLUSIONS

 Despite concerns that implementation of EHRs might adversely impact patient care during the acute transition period, we found no overall negative association of such implementation on short term inpatient mortality, adverse safety events, or readmissions in the Medicare population across 17 US hospitals.

The pharmacist and the EHR

The adoption of electronic health records (EHRs) across the United States has impacted the methods by which health care professionals care for their patients. It is not always recognized, however, that pharmacists also actively use advanced functionality within the EHR. As critical members of the health care team, pharmacists utilize many different features of the EHR. The literature focuses on 3 main roles: documentation, medication reconciliation, and patient evaluation and monitoring. As health information technology proliferates, it is imperative that pharmacists' workflow and information needs are met within the EHR to optimize medication therapy quality, team communication, and patient outcomes.

New technologies as a strategy to decrease medication errors: how do they affect adults and children differently?

BACKGROUND

Medication error can occur throughout the drug treatment process, with special relevance in children given the risk of adverse effects resulting from a medication error is more prevalent than in adults. The significance of medication error in children is also greater because small error that would be tolerated in adults can cause significant damage in children. Moreover, the likelihood of injury is higher than in adults.

DATA SOURCES

Based on the data published, most medication errors take place in prescribing and administration stages in both populations. Taking in account that child's risk factors are different from those of adults, with some specific causes to pediatrics, we have reviewed available data about new technologies as a strategy to reduce pediatric medication errors.

RESULTS

Even though there is a lack of standardized definitions and terminology that makes studies difficult to compare, we checked that new technologies have proven to be effectives in reducing medication errors, mainly computerized physician order entry (CPOE) and platforms to aid decision-making. However, we also observed that the use of these informatic tools can also generate new errors.

CONCLUSIONS

Implementation of CPOE programs for pediatrics, communication improvement between healthcare professionals taking care of admitted children and the knowledge of these programs should be the mayor priorities for the safety of hospitalized children.

[Medication errors related to computerized physician order entry at the hospital: Record and analysis over a period of 4 years]

OBJECTIVES

Computerized physician order entry (CPOE) can generate medication errors. It is necessary to identify them and analyse their causes in order to secure the medication use system.

METHODS

Errors were recorded during the pharmaceutical analysis of prescriptions over a period of 4 years on 425 beds. A code frame was provided. Errors were classified according to type, causes and time of detection. The most often drug implicated and the error correction rate were studied. Deep causes were determined and contributing factors were listed.

RESULTS

Among 99,536 prescriptions analyzed, 2636 errors were detected (2.65 errors per 100 orders analyzed). The most common error was omission (31.49%). The most represented cause was redundancy requirement (11.34%). Antibacterials were most commonly involved (224 errors). Exactly 65.9% of the prescriptions were modified by physicians. Three root causes were identified: (1) configuration issues; (2) misuse; (3) design problem. Three types of contributing factors have also been detailed: economic, human and technical factors.

CONCLUSIONS

Identifying root causes has targeted three types of improvement actions: (1) software settings; (2) training of users; (3) requests for improvements. Contributing factors have to be identified to control the generated risk. Some errors related to CPOE may lead to serious side effects for the patient. That is why it is necessary to identify these errors and analyze them in order to implement improvement actions and prevention to secure the prescription.

Classification of antecedents towards safety use of health information technology: A systematic review

OBJECTIVES

This paper provides a systematic review of safety use of health information technology (IT). The first objective is to identify the antecedents towards safety use of health IT by conducting systematic literature review (SLR). The second objective is to classify the identified antecedents based on the work system in Systems Engineering Initiative for Patient Safety (SEIPS) model and an extension of DeLone and McLean (D&M) information system (IS) success model.

METHODS

A systematic literature review (SLR) was conducted from peer-reviewed scholarly publications between January 2000 and July 2014. SLR was carried out and reported based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement. The related articles were identified by searching the articles published in Science Direct, Medline, EMBASE, and CINAHL databases. Data extracted from the resultant studies included are to be analysed based on the work system in Systems Engineering Initiative for Patient Safety (SEIPS) model, and also from the extended DeLone and McLean (D&M) information system (IS) success model.

RESULTS

55 articles delineated to be antecedents that influenced the safety use of health IT were included for review. Antecedents were identified and then classified into five key categories. The categories are (1) person, (2) technology, (3) tasks, (4) organization, and (5) environment. Specifically, person is attributed by competence while technology is associated to system quality, information quality, and service quality. Tasks are attributed by task-related stressor. Organisation is related to training, organisation resources, and teamwork. Lastly, environment is attributed by physical layout, and noise.

CONCLUSIONS

This review provides evidence that the antecedents for safety use of health IT originated from both social and technical aspects. However, inappropriate health IT usage potentially increases the incidence of errors and produces new safety risks. The review cautions future implementation and adoption of health IT to carefully consider the complex interactions between social and technical elements propound in healthcare settings.

Clinical Outcomes of Continuation of Metformin Titration Instructions with Electronic Prescribing

Background

Anecdotal evidence suggests that metformin titration instructions are not being updated and refill requests are approved without modification of the titration instructions such that the titration instructions is continued for patients newly initiated on metformin.

Methods

This was a retrospective cohort analysis of adult patients who received newly initiated metformin pharmacotherapy. Patients were followed from their initial metformin purchase through two subsequent metformin refill purchases. Outcomes, including the 3-year incidence rate of patients with at least one set of continued titration instructions and proportions of patients with at least one gastrointestinal adverse effect (AE) and those with an elevated glucose measurement at follow-up, were assessed during the time period between patients’ second and third metformin purchases. Analyses were performed comparing the exposure (i.e., patients with continued instructions) group to the control (i.e., patients without continued instructions) group.

Results

The exposure group had a higher mean age and chronic disease score but lower metformin starting dose than the control group (all p < 0.05). The 3-year incidence rate of patients with at least one continuation of titration instructions was 60.3 % (95 % CI 58.3–62.3). Gastrointestinal AEs were rare with equivalent proportions of patients in each group experiencing an event (p > 0.05). Control patients (48.7 % of patients with a measurement) were more likely to have had poorly controlled glucose than exposure patients (35.7 % of patients with a measurement) (p < 0.001).

Conclusions

A high rate of continuation of titration instructions for patients newly initiated on metformin was observed; however, such continuation did not negatively affect clinical outcomes.

An analysis of electronic health record-related patient safety concerns

OBJECTIVE

A recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system.

METHODS

The Informatics Patient Safety Office of the Veterans Health Administration (VA) maintains a non-punitive, voluntary reporting system to collect and investigate EHR-related safety concerns (ie, adverse events, potential events, and near misses). We analyzed completed investigations using an eight-dimension sociotechnical conceptual model that accounted for both technical and non-technical dimensions of safety. Using the framework analysis approach to qualitative data, we identified emergent and recurring safety concerns common to multiple reports.

RESULTS

We extracted 100 consecutive, unique, closed investigations between August 2009 and May 2013 from 344 reported incidents. Seventy-four involved unsafe technology and 25 involved unsafe use of technology. A majority (70%) involved two or more model dimensions. Most often, non-technical dimensions such as workflow, policies, and personnel interacted in a complex fashion with technical dimensions such as software/hardware, content, and user interface to produce safety concerns. Most (94%) safety concerns related to either unmet data-display needs in the EHR (ie, displayed information available to the end user failed to reduce uncertainty or led to increased potential for patient harm), software upgrades or modifications, data transmission between components of the EHR, or 'hidden dependencies' within the EHR.

DISCUSSION

EHR-related safety concerns involving both unsafe technology and unsafe use of technology persist long after 'go-live' and despite the sophisticated EHR infrastructure represented in our data source. Currently, few healthcare institutions have reporting and analysis capabilities similar to the VA.

CONCLUSIONS

Because EHR-related safety concerns have complex sociotechnical origins, institutions with long-standing as well as recent EHR implementations should build a robust infrastructure to monitor and learn from them.

Development and field testing of a self-assessment guide for computer-based provider order entry

Despite the benefits of computerized provider order entry (CPOE), numerous reports of unexpected CPOE-related safety concerns have surfaced. As part of a larger project to improve the safety of electronic health records (EHRs), we developed and field tested a CPOE "safety self-assessment" guide through literature searches, expert opinion, and site visits. We then conducted a field test of this guide with nine hospital chief medical informatics officers (CMIOs), who were identified through the Association of Medical Directors of Information Systems. The CPOE safety self-assessment guide was sent electronically to the CMIOs. Once the assessments were returned, we conducted structured telephone interviews for further comments about the guide's format and content. The CMIOs in our study found the CPOE safety guide useful and relatively easy to complete, taking no more than 30 minutes. Analysis of responses to the guide suggest that most recommended practices were implemented inconsistently across facilities. Despite consensus for certain CPOE best practices in the medical literature and among experts, there appeared to be considerable variation among CMIOs' opinions of best practices. Interview data suggested this inconsistency was mostly due to system limitations and/or differing opinions about the necessity of certain EHR-related safety measures. Despite the absence of consensus on best practices, a self-assessment safety guide provides a practical starting point for organizations to assess and improve safety and the effectiveness of their CPOE system.

Evaluation of a user guidance reminder to improve the quality of electronic prescription messages

BACKGROUND

Prescribers' inappropriate use of the free-text Notes field in new electronic prescriptions can create confusion and workflow disruptions at receiving pharmacies that often necessitates contact with prescribers for clarification. The inclusion of inappropriate patient direction (Sig) information in the Notes field is particularly problematic.

OBJECTIVE

We evaluated the effect of a targeted watermark, an embedded overlay, reminder statement in the Notes field of an EHR-based e-prescribing application on the incidence of inappropriate patient directions (Sig) in the Notes field.

METHODS

E-prescriptions issued by the same exact cohort of 97 prescribers were collected over three time periods: baseline, three months after implementation of the reminder, and 15 months post implementation. Three certified and experienced pharmacy technicians independently reviewed all e-prescriptions for inappropriate Sig-related information in the Notes field. A physician reviewer served as the final adjudicator for e-prescriptions where the three reviewers could not reach a consensus. ANOVA and post hoc Tukey HSD tests were performed on group comparisons where statistical significance was evaluated at p<0.05.

RESULTS

The incidence of inappropriate Sig-related information in the Notes field decreased from a baseline of 2.8% to 1.8% three months post-implementation and remained stable after 15 months. In addition, prescribers' use of the Notes decreased by 22% after 3 months and had stabilized at 18.7% below baseline after 15 months.

CONCLUSION

Insertion of a targeted watermark reminder statement in the Notes field of an e-prescribing application significantly reduced the incidence of inappropriate Sig-related information in Notes and decreased prescribers' use of this field.

Effect of EHR user interface changes on internal prescription discrepancies

OBJECTIVE

To determine whether specific design interventions (changes in the user interface (UI)) of an electronic health record (EHR) medication module are associated with an increase or decrease in the incidence of contradictions between the structured and narrative components of electronic prescriptions (internal prescription discrepancies).

MATERIALS AND METHODS

We performed a retrospective analysis of 960,000 randomly selected electronic prescriptions generated in a single EHR between 01/2004 and 12/2011. Internal prescription discrepancies were identified using a validated natural language processing tool with recall of 76% and precision of 84%. A multivariable autoregressive integrated moving average (ARIMA) model was used to evaluate the effect of five UI changes in the EHR medication module on incidence of internal prescription discrepancies.

RESULTS

Over the study period 175,725 (18.4%) prescriptions were found to have internal discrepancies. The highest rate of prescription discrepancies was observed in March 2006 (22.5%) and the lowest in March 2009 (15.0%). Addition of "as directed" option to the <Frequency> dropdown decreased prescription discrepancies by 195 / month (p = 0.0004). An non-interruptive alert that reminded providers to ensure that structured and narrative components did not contradict each other decreased prescription discrepancies by 145 / month (p = 0.03). Addition of a "Renew / Sign" button to the Medication module (a negative control) did not have an effect in prescription discrepancies.

CONCLUSIONS

Several UI changes in the electronic medication module were effective in reducing the incidence of internal prescription discrepancies. Further research is needed to identify interventions that can completely eliminate this type of prescription error and their effects on patient outcomes.

Towards creating the perfect electronic prescription

Significant strides have been made in electronic (e)-prescribing standards and software applications that have further fueled the adoption and use of e-prescribing. However, for e-prescribing to realize its full potential for improving the safety, effectiveness, and efficiency of prescription drug delivery, important work remains to be carried out. This perspective describes the ultimate goal of all e-prescribing stakeholders including prescribers and dispensing pharmacists: a clear, complete, and unambiguous e-prescription order that can be seamlessly received, processed, and fulfilled at the dispensing pharmacy without the need for additional clarification from the prescriber. We discuss the challenges to creating the perfect e-prescription by focusing on selected data segments and data fields that are available in the new e-prescription transaction as defined in the NCPDP SCRIPT Standard and suggest steps that could be taken to move the industry closer to achieving this vision.

A red-flag-based approach to risk management of EHR-related safety concerns

Although electronic health records (EHRs) have a significant potential to improve patient safety, EHR-related safety concerns have begun to emerge. Based on 369 responses to a survey sent to the memberships of the American Society for Healthcare Risk Management and the American Health Lawyers Association and supplemented by our previous work in EHR-related patient safety, we identified the following common EHR-related safety concerns: (1) incorrect patient identification; (2) extended EHR unavailability (either planned or unplanned); (3) failure to heed a computer-generated warning or alert; (4) system-to-system interface errors; (5) failure to identify, find, or use the most recent patient data; (6) misunderstandings about time; (7) incorrect item selected from a list of items; and (8) open or incomplete orders. In this article, we present a "red-flag"-based approach that can be used by risk managers to identify potential EHR safety concerns in their institutions. An organization that routinely conducts EHR-related surveillance activities, such as the ones proposed here, can significantly reduce risks associated with EHR implementation and use.

Exploring the sociotechnical intersection of patient safety and electronic health record implementation

OBJECTIVE

The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS).

METHODS

We conducted a secondary analysis of interview data from a 30-month longitudinal, prospective, case study-based evaluation of EHR implementation in 12 NHS hospitals. We used a framework analysis approach to apply conceptual models developed by Sittig and Singh to understand better EHR implementation and use: an eight-dimension sociotechnical model and a three-phase patient safety model (safe technology, safe use of technology, and use of technology to improve safety).

RESULTS

The intersection of patient safety and EHR implementation and use was characterized by risks involving technology (hardware and software, clinical content, and human-computer interfaces), the interaction of technology with non-technological factors, and improper or unsafe use of technology. Our data support that patient safety improvement activities as well as patient safety hazards change as an organization evolves from concerns about safe EHR functionality, ensuring safe and appropriate EHR use, to using the EHR itself to provide ongoing surveillance and monitoring of patient safety.

DISCUSSION

We demonstrate the face validity of two models for understanding the sociotechnical aspects of safe EHR implementation and the complex interactions of technology within a healthcare system evolving from paper to integrated EHR.

CONCLUSIONS

Using sociotechnical models, including those presented in this paper, may be beneficial to help stakeholders understand, synthesize, and anticipate risks at the intersection of patient safety and health information technology.

The safety of electronic prescribing: manifestations, mechanisms, and rates of system-related errors associated with two commercial systems in hospitals

OBJECTIVES

To compare the manifestations, mechanisms, and rates of system-related errors associated with two electronic prescribing systems (e-PS). To determine if the rate of system-related prescribing errors is greater than the rate of errors prevented.

METHODS

Audit of 629 inpatient admissions at two hospitals in Sydney, Australia using the CSC MedChart and Cerner Millennium e-PS. System related errors were classified by manifestation (eg, wrong dose), mechanism, and severity. A mechanism typology comprised errors made: selecting items from drop-down menus; constructing orders; editing orders; or failing to complete new e-PS tasks. Proportions and rates of errors by manifestation, mechanism, and e-PS were calculated.

RESULTS

42.4% (n=493) of 1164 prescribing errors were system-related (78/100 admissions). This result did not differ by e-PS (MedChart 42.6% (95% CI 39.1 to 46.1); Cerner 41.9% (37.1 to 46.8)). For 13.4% (n=66) of system-related errors there was evidence that the error was detected prior to study audit. 27.4% (n=135) of system-related errors manifested as timing errors and 22.5% (n=111) wrong drug strength errors. Selection errors accounted for 43.4% (34.2/100 admissions), editing errors 21.1% (16.5/100 admissions), and failure to complete new e-PS tasks 32.0% (32.0/100 admissions). MedChart generated more selection errors (OR=4.17; p=0.00002) but fewer new task failures (OR=0.37; p=0.003) relative to the Cerner e-PS. The two systems prevented significantly more errors than they generated (220/100 admissions (95% CI 180 to 261) vs 78 (95% CI 66 to 91)).

CONCLUSIONS

System-related errors are frequent, yet few are detected. e-PS require new tasks of prescribers, creating additional cognitive load and error opportunities. Dual classification, by manifestation and mechanism, allowed identification of design features which increase risk and potential solutions. e-PS designs with fewer drop-down menu selections may reduce error risk.

From physician intent to the pharmacy label: prevalence and description of discrepancies from a cross-sectional evaluation of electronic prescriptions

OBJECTIVE

The objectives of this cross-sectional study were to estimate the prevalence of unintended discrepancies between three sources of prescription information and to describe the types of electronic prescribing system vulnerabilities identified.

METHODS

Staff from community pharmacies identified approximately 200 new prescriptions written at three participating ambulatory care clinics (2 adult, 1 paediatric). Unintended discrepancies were identified by comparing three sources of prescription information: (1) the prescriber's note as documented in the patient's chart; (2) the electronic prescription (e-prescription) entered into the clinic's electronic prescribing software; (3) the medication that was ultimately dispensed by the pharmacy as indicated on the prescription label. The discrepancy rate was calculated by dividing the number of discrepancies identified by the number of prescriptions evaluated.

RESULTS

A total of 602 prescriptions written by 33 prescribers were evaluated from the 3 ambulatory care clinics. The discrepancy rate between the prescriber's note and the e-prescription was 1.7%, 0.6% and 3.9% for the three clinics. The discrepancy rate between the e-prescription (clinic) and the prescription label (pharmacy) was 4.2%, 0.9% and 1.5%. Differences between directions for administration was the most common type of discrepancy identified.

CONCLUSIONS

Discrepancy rates between the prescriber's note and the e-prescription were similar to the discrepancy rates between the e-prescription and pharmacy label. To reduce outpatient medication errors, a better understanding is needed of the sources of discrepancies that occur within the prescriber's clinic, and those that occur between the clinic and pharmacy.

Types and origins of diagnostic errors in primary care settings

IMPORTANCE

Diagnostic errors are an understudied aspect of ambulatory patient safety.

OBJECTIVES

To determine the types of diseases missed and the diagnostic processes involved in cases of confirmed diagnostic errors in primary care settings and to determine whether record reviews could shed light on potential contributory factors to inform future interventions.

DESIGN

We reviewed medical records of diagnostic errors detected at 2 sites through electronic health record-based triggers. Triggers were based on patterns of patients' unexpected return visits after an initial primary care index visit.

SETTING

A large urban Veterans Affairs facility and a large integrated private health care system.

PARTICIPANTS

Our study focused on 190 unique instances of diagnostic errors detected in primary care visits between October 1, 2006, and September 30, 2007.

MAIN OUTCOME MEASURES

Through medical record reviews, we collected data on presenting symptoms at the index visit, types of diagnoses missed, process breakdowns, potential contributory factors, and potential for harm from errors.

RESULTS

In 190 cases, a total of 68 unique diagnoses were missed. Most missed diagnoses were common conditions in primary care, with pneumonia (6.7%), decompensated congestive heart failure (5.7%), acute renal failure (5.3%), cancer (primary) (5.3%), and urinary tract infection or pyelonephritis (4.8%) being most common. Process breakdowns most frequently involved the patient-practitioner clinical encounter (78.9%) but were also related to referrals (19.5%), patient-related factors (16.3%), follow-up and tracking of diagnostic information (14.7%), and performance and interpretation of diagnostic tests (13.7%). A total of 43.7% of cases involved more than one of these processes. Patient-practitioner encounter breakdowns were primarily related to problems with history-taking (56.3%), examination (47.4%), and/or ordering diagnostic tests for further workup (57.4%). Most errors were associated with potential for moderate to severe harm.

CONCLUSIONS AND RELEVANCE

Diagnostic errors identified in our study involved a large variety of common diseases and had significant potential for harm. Most errors were related to process breakdowns in the patient-practitioner clinical encounter. Preventive interventions should target common contributory factors across diagnoses, especially those that involve data gathering and synthesis in the patient-practitioner encounter.

[Assessment of pharmaceutical databases available in France]

OBJECTIVE

To assess the relevance of several pharmaceutical databases (PDBs) to be integrated in a computerized prescription system for hospitals.

MATERIALS AND METHODS

Fifty medical prescriptions were designed as tests. They were supposed to answer to a security or a relevance assessment item. They were analyzed using four French PDBs (Claude-Bernard, Thériaque, Thésorimed, Vidal), available online. The outcome was the rate of conformity with the expected answers.

RESULTS

The rate of conformity was: 31% for Claude-Bernard, 30% for Thériaque, 26% for Vidal, and 20% for Thésorimed (no statistical significance).

DISCUSSION

The PDBs easily detect interactions between different pharmacological class drugs but redundancies and illogical situations are poorly intercepted. They seem to manage medicines only by the active ingredient, irrespective of the dose or the indication. The knowledge of the patient profile and the context are not really enriched by the content of the prescription.

CONCLUSION

The efficacy of these PDB has to be improved.

Perspectives on electronic prescribing and terminologies

Electronic medical records provide potential benefits and also drawbacks. Potential benefits include increased patient safety and efficiency. Potential drawbacks include newly introduced errors and diminished workflow efficiency. In the patient safety context, medication errors account for significant patient harm. Electronic prescribing (e-prescribing) offers the promise of automated drug interaction and dosage verification. In addition, the process of enabling e-prescriptions also provides access to an often unrecognized benefit, that of viewing the dispensed medication history. This information is often critical to understanding patient symptoms. Obtaining significant value from electronic medical records requires use of standardized terminology for both targeted decision support and population-based management. Further, generating documentation for a billable encounter requires usage of proper codes. The emergence of International Classification of Diseases (ICD)-10 holds promise in facilitating identification of a more precise patient code while also presenting drawbacks given its complexity. This article will focus on elements of e-prescribing and use of structured chart content, including diagnosis codes as they relate to physician office practices.

Dose omissions in hospitalized patients in a UK hospital: an analysis of the relative contribution of adverse drug reactions

BACKGROUND

The omission of charted (prescribed) doses for hospitalized patients is an important problem in the UK. Inappropriate drug omission can clearly lead to harm from lack of therapeutic effect. However, healthcare professionals administering medicines may decide that omission of a dose is appropriate in certain circumstances, e.g. when patients show signs of a possible adverse drug reaction (ADR).

OBJECTIVE

The aim of this study was to characterize dose omissions to understand the factors that influence non-administration of therapy and to determine the proportion of doses that are appropriately omitted due to ADRs.

METHODS

We used data from a bespoke hospital-wide electronic prescribing and administration system at University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK. We extracted data on 6.01 million drug administrations during 2010 and then randomly selected four 7-day periods, concentrating on doses that were charted but not given. Omitted medicines were counted if either there was a charted 'non-administration' (i.e. an active acknowledgement of the omitted dose) or there was no charting of that dose (i.e. no record of either administration or omission). Paused medicines were not counted. When a dose was omitted, staff indicated the reasons for non-administration using codes ('hard coded') or free text in the electronic system. We used both to compare the contribution of different factors, including ADRs, to the total rates of dose omissions.

RESULTS

In the four 7-day periods analysed, 60 763 (12.4%) of the 491 894 charted doses were omitted. The most common code was 'patient refused drug' (45.4%). Only 1.6% of doses were omitted for reasons of patient safety, of which 4 in 1000 omissions were coded as directly due to an ADR.

CONCLUSIONS

Measures to improve the quality of care should seek to reduce dose omissions, but in some cases omission may be rational. Electronic medication administration records allow for detailed analysis of decisions made by healthcare professionals at the point of administration. While dose omissions related to ADRs are uncommon, they are important both for patient safety and for therapeutic decision making.

Electronic health records and national patient-safety goals

Hospitals and clinics are adapting to new technologies and implementing electronic health records, but the efforts need to be aligned explicitly with goals for patient safety. EHRs bring the risks of both technical failures and inappropriate use, but they can also help to monitor and improve patient safety.

How many medication orders are entered through free-text in EHRs?--a study on hypoglycemic agents

Computerized Provider Order Entry (CPOE) can reduce medication errors; however, its benefits are only achieved when data are entered in a structured format and entries are properly coded. This paper aims to explore the incidence of free-text medication order entries involving hypoglycemic agents in an ambulatory electronic health record (EHR) system with CPOE. Our results showed that free-text order entry continues to be frequent. During 2010, 9.3% of hypoglycemic agents were entered as free-text for 2,091 patients. 17.4% of the entries contained misspellings. The highest proportion of free-text entries were found in urgent care clinics (49.4%) and among registered nurses (31.5%). Additionally, 92 drug-drug interaction alerts were not triggered due to free-text entries. Only 25.9% of the patients had diabetes recorded in their problem list. Solutions will require policy to enforce structured entry, ongoing improvement in user-interface design, improved training for users, and strategies for maintaining a complete medication list.

Transmitting and processing electronic prescriptions: experiences of physician practices and pharmacies

OBJECTIVE

A core feature of e-prescribing is the electronic exchange of prescription data between physician practices and pharmacies, which can potentially improve the efficiency of the prescribing process and reduce medication errors. Barriers to implementing this feature exist, but they are not well understood. This study's objectives were to explore recent physician practice and pharmacy experiences with electronic transmission of new prescriptions and renewals, and identify facilitators of and barriers to effective electronic transmission and pharmacy e-prescription processing.

DESIGN

Qualitative analysis of 114 telephone interviews conducted with representatives from 97 organizations between February and September 2010, including 24 physician practices, 48 community pharmacies, and three mail-order pharmacies actively transmitting or receiving e-prescriptions via Surescripts.

RESULTS

Practices and pharmacies generally were satisfied with electronic transmission of new prescriptions but reported that the electronic renewal process was used inconsistently, resulting in inefficient workarounds for both parties. Practice communications with mail-order pharmacies were less likely to be electronic than with community pharmacies because of underlying transmission network and computer system limitations. While e-prescribing reduced manual prescription entry, pharmacy staff frequently had to complete or edit certain fields, particularly drug name and patient instructions.

CONCLUSIONS

Electronic transmission of new prescriptions has matured. Changes in technical standards and system design and more targeted physician and pharmacy training may be needed to address barriers to e-renewals, mail-order pharmacy connectivity, and pharmacy processing of e-prescriptions.

An analysis of the usability of inpatient insulin ordering in three computerized provider order entry systems

BACKGROUND

Insulin is a highly scrutinized drug in hospitals since it is both frequently used and high risk. As the insulin ordering process makes a transition from pen and paper to computerized provider order entry (CPOE) systems, the effective design of these systems becomes critical. There are fundamental usability principles in the field of human-computer interaction design, which help make interfaces that are effective, efficient, and satisfying. To our knowledge, there has not been a study that specifically looks at how these principles have been applied in the design of insulin orders in a CPOE system.

METHOD

We analyzed the usability of inpatient insulin ordering in three widely deployed CPOE systems-two commercially marketed systems and the U.S. Department of Veterans Affairs VistA Computerized Patient Record System. We performed a usability analysis using aspects of three different methods. Our first goal was to note each instance where a usability principle was either upheld or not upheld. Our second goal was to discover ways in which CPOE designers could exploit usability principles to make insulin ordering safer and more intuitive in the future.

RESULTS

Commonly encountered usability principles included constraints, obviousness/self-evidence, natural mapping, feedback, and affordance. The three systems varied in their adherence to these principles, and each system had varying strengths and weaknesses.

CONCLUSION

Adherence to usability principles is important when building a CPOE system, yet designers observe them to varying degrees. A well-designed CPOE interface allows a clinician to focus more of his or her mental energy on clinical decisions rather than on deciphering the system itself. In the future, intelligent design of CPOE insulin orders can be used to help optimize and modernize management of hyperglycemia in the hospital.