Reported medication errors after introducing an electronic medication management system

Aims and objectives
To explore the effects of introducing an electronic medication management system on reported medication errors.
Background
Computerised medication management systems have been found to improve medication safety; however, introducing medication management system into healthcare environments can create unanticipated or new problems and opportunities for medication error.
Design
Descriptive analysis of medication error reports.
Methods
This was a retrospective analysis of 359 incident reports drawn from the period of 1 May 2005–30 April 2006 across two hospital sites of a single not-for-profit private health service located in metropolitan Melbourne. Site A used a conventional pen and paper system for medication management, and Site B had introduced a computerised medication management system.
Results
Most medication errors occurred at the nurse administration (71·5%) and prescribing (16·4%) stages of delivery. The most common medication error type reported at Site A was omission (33%), and at Site B was wrong documentation (24·2%). A higher proportion of errors at the prescribing phase, and less nurse administration errors, were detected at Site B where the medication management system was in use. The incidence of other, less frequent errors was similar across the two hospital sites.
Conclusions
This examination of medication error reports suggests there are differences in the types of medication errors that are reported in association with the introduction of electronic medication management system compared to pen and paper system systems. The findings provide a new insight into the effects of introducing an electronic medication management system on the types of medication errors reported.
Relevance to clinical practice
The findings provide a new insight into the types of medication errors that are reported during implementation of an electronic medication management system. Extra support for physicians prescribing practices should be considered.

Cost-effectiveness analysis of a hospital electronic medication management system

OBJECTIVE: To conduct a cost-effectiveness analysis of a hospital electronic medication management system (eMMS). METHODS: We compared costs and benefits of paper-based prescribing with a commercial eMMS (CSC MedChart) on one cardiology ward in a major 326-bed teaching hospital, assuming a 15-year time horizon and a health system perspective. The eMMS implementation and operating costs were obtained from the study site. We used data on eMMS effectiveness in reducing potential adverse drug events (ADEs), and potential ADEs intercepted, based on review of 1 202 patient charts before (n = 801) and after (n = 401) eMMS. These were combined with published estimates of actual ADEs and their costs. RESULTS: The rate of potential ADEs following eMMS fell from 0.17 per admission to 0.05; a reduction of 71%. The annualized eMMS implementation, maintenance, and operating costs for the cardiology ward were A$61 741 (US$55 296). The estimated reduction in ADEs post eMMS was approximately 80 actual ADEs per year. The reduced costs associated with these ADEs were more than sufficient to offset the costs of the eMMS. Estimated savings resulting from eMMS implementation were A$63-66 (US$56-59) per admission (A$97 740-$102 000 per annum for this ward). Sensitivity analyses demonstrated results were robust when both eMMS effectiveness and costs of actual ADEs were varied substantially. CONCLUSION: The eMMS within this setting was more effective and less expensive than paper-based prescribing. Comparison with the few previous full economic evaluations available suggests a marked improvement in the cost-effectiveness of eMMS, largely driven by increased effectiveness of contemporary eMMs in reducing medication errors.

Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings

OBJECTIVE: To describe the electronic medical databases used in antiretroviral therapy (ART) programmes in lower-income countries and assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. METHODS: In 15 countries of Africa, South America and Asia, a survey was conducted from December 2006 to February 2007 on the use of electronic medical record systems in ART programmes. Patients enrolled in the sites at the time of the survey but not seen during the previous 12 months were considered lost to follow-up. The quality of the data was assessed by computing the percentage of missing key variables (age, sex, clinical stage of HIV infection, CD4+ lymphocyte count and year of ART initiation). Associations between site characteristics (such as number of staff members dedicated to data management), measures to reduce loss to follow-up (such as the presence of staff dedicated to tracing patients) and data quality and loss to follow-up were analysed using multivariate logit models. FINDINGS: Twenty-one sites that together provided ART to 50 060 patients were included (median number of patients per site: 1000; interquartile range, IQR: 72-19 320). Eighteen sites (86%) used an electronic database for medical record-keeping; 15 (83%) such sites relied on software intended for personal or small business use. The median percentage of missing data for key variables per site was 10.9% (IQR: 2.0-18.9%) and declined with training in data management (odds ratio, OR: 0.58; 95% confidence interval, CI: 0.37-0.90) and weekly hours spent by a clerk on the database per 100 patients on ART (OR: 0.95; 95% CI: 0.90-0.99). About 10 weekly hours per 100 patients on ART were required to reduce missing data for key variables to below 10%. The median percentage of patients lost to follow-up 1 year after starting ART was 8.5% (IQR: 4.2-19.7%). Strategies to reduce loss to follow-up included outreach teams, community-based organizations and checking death registry data. Implementation of all three strategies substantially reduced losses to follow-up (OR: 0.17; 95% CI: 0.15-0.20). CONCLUSION: The quality of the data collected and the retention of patients in ART treatment programmes are unsatisfactory for many sites involved in the scale-up of ART in resource-limited settings, mainly because of insufficient staff trained to manage data and trace patients lost to follow-up.

Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain?

BACKGROUND: Follow-up of abnormal outpatient laboratory test results is a major patient safety concern. Electronic medical records can potentially address this concern through automated notification. We examined whether automated notifications of abnormal laboratory results (alerts) in an integrated electronic medical record resulted in timely follow-up actions. METHODS: We studied 4 alerts: hemoglobin A1c > or =15%, positive hepatitis C antibody, prostate-specific antigen > or =15 ng/mL, and thyroid-stimulating hormone > or =15 mIU/L. An alert tracking system determined whether the alert was acknowledged (ie, provider clicked on and opened the message) within 2 weeks of transmission; acknowledged alerts were considered read. Within 30 days of result transmission, record review and provider contact determined follow-up actions (eg, patient contact, treatment). Multivariable logistic regression models analyzed predictors for lack of timely follow-up. RESULTS: Between May and December 2008, 78,158 tests (hemoglobin A1c, hepatitis C antibody, thyroid-stimulating hormone, and prostate-specific antigen) were performed, of which 1163 (1.48%) were transmitted as alerts; 10.2% of these (119/1163) were unacknowledged. Timely follow-up was lacking in 79 (6.8%), and was statistically not different for acknowledged and unacknowledged alerts (6.4% vs 10.1%; P =.13). Of 1163 alerts, 202 (17.4%) arose from unnecessarily ordered (redundant) tests. Alerts for a new versus known diagnosis were more likely to lack timely follow-up (odds ratio 7.35; 95% confidence interval, 4.16-12.97), whereas alerts related to redundant tests were less likely to lack timely follow-up (odds ratio 0.24; 95% confidence interval, 0.07-0.84). CONCLUSIONS: Safety concerns related to timely patient follow-up remain despite automated notification of non-life-threatening abnormal laboratory results in the outpatient setting.

Using Informatics and the Electronic Medical Record to Describe Antimicrobial Use in the Clinical Management of Diarrhea Cases at 12 Companion Animal Practices

Antimicrobial drugs may be used to treat diarrheal illness in companion animals. It is important to monitor antimicrobial use to better understand trends and patterns in antimicrobial resistance. There is no monitoring of antimicrobial use in companion animals in Canada. To explore how the use of electronic medical records could contribute to the ongoing, systematic collection of antimicrobial use data in companion animals, anonymized electronic medical records were extracted from 12 participating companion animal practices and warehoused at the University of Calgary. We used the pre-diagnostic, clinical features of diarrhea as the case definition in this study. Using text-mining technologies, cases of diarrhea were described by each of the following variables: diagnostic laboratory tests performed, the etiological diagnosis and antimicrobial therapies. The ability of the text miner to accurately describe the cases for each of the variables was evaluated. It could not reliably classify cases in terms of diagnostic tests or etiological diagnosis; a manual review of a random sample of 500 diarrhea cases determined that 88/500 (17.6%) of the target cases underwent diagnostic testing of which 36/88 (40.9%) had an etiological diagnosis. Text mining, compared to a human reviewer, could accurately identify cases that had been treated with antimicrobials with high sensitivity (92%, 95% confidence interval, 88.1%-95.4%) and specificity (85%, 95% confidence interval, 80.2%-89.1%). Overall, 7400/15,928 (46.5%) of pets presenting with diarrhea were treated with antimicrobials. Some temporal trends and patterns of the antimicrobial use are described. The results from this study suggest that informatics and the electronic medical records could be useful for monitoring trends in antimicrobial use.

Developing a point-of-care electronic medical record system for TB/HIV co-infected patients: experiences from Lighthouse Trust, Lilongwe, Malawi.

BACKGROUND Implementation of user-friendly, real-time, electronic medical records for patient management may lead to improved adherence to clinical guidelines and improved quality of patient care. We detail the systematic, iterative process that implementation partners, Lighthouse clinic and Baobab Health Trust, employed to develop and implement a point-of-care electronic medical records system in an integrated, public clinic in Malawi that serves HIV-infected and tuberculosis (TB) patients. METHODS Baobab Health Trust, the system developers, conducted a series of technical and clinical meetings with Lighthouse and Ministry of Health to determine specifications. Multiple pre-testing sessions assessed patient flow, question clarity, information sequencing, and verified compliance to national guidelines. Final components of the TB/HIV electronic medical records system include: patient demographics; anthropometric measurements; laboratory samples and results; HIV testing; WHO clinical staging; TB diagnosis; family planning; clinical review; and drug dispensing. RESULTS Our experience suggests that an electronic medical records system can improve patient management, enhance integration of TB/HIV services, and improve provider decision-making. However, despite sufficient funding and motivation, several challenges delayed system launch including: expansion of system components to include of HIV testing and counseling services; changes in the national antiretroviral treatment guidelines that required system revision; and low confidence to use the system among new healthcare workers. To ensure a more robust and agile system that met all stakeholder and user needs, our electronic medical records launch was delayed more than a year. Open communication with stakeholders, careful consideration of ongoing provider input, and a well-functioning, backup, paper-based TB registry helped ensure successful implementation and sustainability of the system. Additional, on-site, technical support provided reassurance and swift problem-solving during the extended launch period. CONCLUSION Even when system users are closely involved in the design and development of an electronic medical record system, it is critical to allow sufficient time for software development, solicitation of detailed feedback from both users and stakeholders, and iterative system revisions to successfully transition from paper to point-of-care electronic medical records. For those in low-resource settings, electronic medical records for integrated care is a possible and positive innovation.

Assessing the impact of electronic health record technology adoption on hospital labor efficiency

Information technology (IT) in the hospital organization is fast becoming a key asset, particularly in light of recent reform legislation in the United States calling for expanding the role of IT in our health care system. Future payment reductions to hospitals included in current health reform are based on expected improvements in hospital operating efficiency. Since over half of hospital expenses are for labor, improved efficiency in use of labor resources can be critical in meeting this challenge. Policy makers have touted the value of IT investments to improve efficiency in response to payment reductions. ^ This study was the first to directly examine the relationship between electronic health record (EHR) technology and staffing efficiency in hospitals. As the hospital has a myriad of outputs for inpatient and outpatient care, efficiency was measured using an industry standard performance metric – full time equivalent employees per adjusted occupied bed (FTE/AOB). Three hypotheses were tested in this study.^ To operationalize EHR technology adoption, we developed three constructs to model adoption, each of which was tested by separate hypotheses. The first hypothesis that a larger number of EHR applications used by a hospital would be associated with greater staffing efficiency (or lower values of FTE/AOB) was not accepted. Association between staffing efficiency and specific EHR applications was the second hypothesis tested and accepted with some applications showing significant impacts on observed values for FTE/AOB. Finally, the hypothesis that the longer an EHR application was used in a hospital would be associated with greater labor efficiency was not accepted as the model showed few statistically significant relationships to FTE/AOB performance. Generally, there does not appear a strong relationship between EHR usage and improved labor efficiency in hospitals.^ While returns on investment from EHR usage may not come from labor efficiencies, they may be better sought using measures of quality, contribution to an efficient and effective local health care system, and improved customer satisfaction through greater patient throughput.^

Modeling Depression Progression Dynamics from Electronic Health Record

Thesis (Master's)--University of Washington, 2016-06

Depression Management Using Electronic Health Record: Individual Progression Prediction

Thesis (Master's)--University of Washington, 2016-06

A KM perspective on implementing an electronic patient record within an NHS hospital

The Electronic Patient Record (EPR) is being developed by many hospitals in the UK and across the globe. We class an EPR system as a type of Knowledge Management System (KMS), in that it is a technological tool developed to support the process of knowledge management (KM). Healthcare organisations aim to use these systems to provide a vehicle for more informed and improved clinical decision making thereby delivering reduced errors and risks, enhanced quality and consequently offering enhanced patient safety. Finding an effective way for a healthcare organisation to practically implement these systems is essential. In this study we use the concept of the business process approach to KM as a theoretical lens to analyse and explore how a large NHS teaching hospital developed, executed and practically implemented an EPR system. This theory advocates the importance of taking into account all organizational activities - the business processes - in considering any KM initiatives. Approaching KM through business processes allows for a more holistic view of the requirements across a process: emphasis is placed on how particular activities are performed, how they are structured and what knowledge demanded and not just supplied across each process. This falls in line with the increased emphasis in healthcare on patient-centred approaches to care delivery. We have found in previous research that hospitals are happy with the delivery of patient care being referred to as their 'business'. A qualitative study was conducted over a two and half year period with data collected from semi-structured interviews with eight members of the strategic management team, 12 clinical users and 20 patients in addition to non- participant observation of meetings and documentary data. We believe that the inclusion of patients within the study may well be the first time this has been done in examining the implementation of a KMS. The theoretical propositions strategy was used as the overarching approach for data analysis. Here Initial theoretical research themes and propositions were used to help shape and organise the case study analysis. This paper will present preliminary findings about the hospital's business strategy and its links to the KMS strategy and process.

Implementing a knowledge management system within an NHS hospital:a case study exploring the roll-out of an Electronic Patient Record (EPR)

This research aims to contribute to understanding the implementation of knowledge management systems (KMS) in the field of health through a case study, leading to theory building and theory extension. We use the concept of the business process approach to knowledge management as a theoretical lens to analyse and explore how a large teaching hospital developed, executed and practically implemented a KMS. A qualitative study was conducted over a 2.5 year period with data collected from semi-structured interviews with eight members of the strategic management team, 12 clinical users and 20 patients in addition to non-participant observation of meetings and documents. The theoretical propositions strategy was used as the overarching approach for data analysis. Our case study provides evidence that true patient centred approaches to supporting care delivery with a KMS benefit from process thinking at both the planning and implementation stages, and an emphasis on the knowledge demands resulting from: the activities along the care pathways; where cross-overs in care occur; and knowledge sharing for the integration of care. The findings also suggest that despite the theoretical awareness of KMS implementation methodologies, the actual execution of such systems requires practice and learning. Flexible, fluid approaches through rehearsal are important and communications strategies should focus heavily on transparency incorporating both structured and unstructured communication methods.

Patient and physician characteristics as predictors for consent to participate in an electronic medical record study

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Patient and physician characteristics as predictors for consent to participate in an electronic medical record study

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.