The Impact of an Electronic Medication Management System on Medication Deviations on Admission and Discharge from Hospital.

Medication errors at transition of care remain a concerning issue. In recent times, the use of integrated electronic medication management systems (EMMS) has caused a reduction in medication errors, but its effectiveness in reducing medication deviations at transition of care has not been studied in hospital-wide settings in Australia. The aim of this study is to assess medication deviations, such as omissions and mismatches, pre-EMMS and post-EMMS implementation at transition of care across a hospital. In this study, patient records were reviewed retrospectively to identify medication deviations (medication omissions and medication mismatches) at admission and discharge from hospital. A total of 400 patient records were reviewed (200 patients in the pre-EMMS and 200 patients in the post-EMMS group). Out of 400 patients, 112 in the pre-EMMS group and 134 patients in post-EMMS group met the inclusion criteria and were included in the analysis. A total of 105 out of 246 patients (42.7%) had any medication deviations on their medications. In the pre-EMMS group, 59 out of 112 (52.7%) patients had any deviations on their medications compared to 46 out of 134 patients (34.3%) from the post-EMMS group (p = 0.004). The proportion of patients with medication omitted from inpatient orders was 36.6% in the pre-EMMS cohort vs. 22.4% in the post-EMMS cohort (p = 0.014). Additionally, the proportion of patients with mismatches in medications on the inpatient charts compared to their medication history was 4.5% in the pre-EMMS group compared to 0% in the post-EMMS group (p = 0.019). Similarly, the proportion of patients with medications omitted from their discharge summary was 23.2% in the pre-EMMS group vs. 12.7% in the post-EMMS group (p = 0.03). Our study demonstrates a reduction in medication deviations after the implementation of the EMMS in hospital settings.

Implementation of an Electronic Medication Management System in a large tertiary hospital: a case of qualitative inquiry.

BACKGROUND: Hospitals across Australia are implementing Clinical Information Systems, e.g. Electronic Medication Management Systems (EMMS) at a rapid pace to moderate health services. The benefits of the EMMS depend on the acceptance of the system by the clinicians. The study hospital used a unique patient-centric implementation strategy that was based on the guiding principle of "one patient, one chart" to avoid a patient being on a hybrid medication chart. This paper aims to study the factors facilitating or hindering the adoption of the EMMS as viewed by clinicians and the implementation team. METHODS: Four focus groups (FG), one each for (1) doctors, (2) nurses, (3) pharmacists, and (4) implementation team, were conducted. A guide for the FG was based on the Unified Theory of Acceptance and Use of Technology (UTAUT). RESULTS: A total of 23 unique subthemes were identified and were grouped into five main themes (1) implementation strategy, (2) organisational outcome of EMMS, (3) individual impact of EMMS, (4) IT product, and (5) organisational culture. Clinicians reported improvement in their workflow efficiency post-EMMS implementation. They also reported some challenges in using the EMMS that centered around the area of infrastructure, technical and design issues. Additionally, the implementation team highlighted two crucial factors influencing the success of EMMS implementation, namely: (1) the patient-centric implementation strategy, and (2) the organisation readiness. CONCLUSION: Overall, this study outlines the implementation process of the EMMS in a large healthcare facility from the clinicians' and the implementation team's perspectives using UTAUT model. The result suggests that clinicians' acceptance of the EMMS was highly influenced by the unique implementation strategy (namely, patient-centric approach and clinical leadership in the implementation team). Whereas the level of adoption of EMMS by clinicians was determined by their level of perceived and realised benefits. On the other hand, a number of barriers to the adoption of EMMS were discovered, namely, general training instead of customised training based on local needs, technical and design issues and lack of availability of computer systems. It is suggested that promptly resolving these issues can improve the adoption of the EMMS.

Patient-centric implementation of an electronic medication management system at a tertiary hospital in Western Sydney.

BACKGROUND: Traditional implementations of electronic medication management (EMM) systems have involved two common formats - a 'big bang' approach on the day of go-live, or a phased ward-by-ward approach over months. OBJECTIVE: To describe the patient-centric roll-out, a novel implementation model in converting from paper to EMM. METHOD: This model iteratively converted a large tertiary teaching hospital to electronic from paper medication charts, commencing the roll-out in the emergency department (ED). The tenet of 'one patient, one chart' was maintained with new patients commenced on EMM, while existing inpatients were maintained on paper charts until their discharge. In the second week, all other intake points commenced patients on EMM, and in the third week, all remaining patients were manually converted to EMM. The implementation was assessed with training completion rates, staff satisfaction surveys, focus group interviews and incident logs. RESULTS: At go-live, 79% of doctors, 68% of nurses and 90% of pharmacists were trained in the EMM system. The ED converted to electronic prescribing within 24 hours; by day 20, all patients were on EMM. Two hundred and thirty issues were logged, none critical, of which 22 were escalated. Of the 51,063 medications administered, there were 13 EMM-related clinical incidents including three double dosing errors, none of which led to an adverse event or death. Overall, 77% of staff surveyed were satisfied with the EMM implementation. CONCLUSIONS: The patient-centric roll-out model represents an innovative and safe approach with a single medication chart reducing transcription and improved medication safety for the patient and the organisation.

Impact of emergency department discharge stream short stay unit performance and hospital bed occupancy rates on access and patient flowmeasures: A single site study.

OBJECTIVE: The ED discharge stream short stay units (EDSSUs) aim to facilitate patient flows through EDs. We investigate the relationship between EDSSU census and hospital bed occupancy rates (BORs) on National Emergency Access Target (NEAT) performance and did-not-wait (DNW) rates at a tertiary metropolitan adult ED in Sydney, Australia. METHODS: We collated data for all ED presentations between 1 January 2012 and 31 December 2014. Daily ED, EDSSU census and ED-accessible hospital BORs were tabulated with daily ED NEAT performance and DNW rates. Non-parametric regression analyses was conducted on cohorts of appropriate, inappropriate, successful and failed EDSSU admissions based on local admission policies and BOR for NEAT and DNW outcomes. RESULTS: Among all presentations (n = 192 506) during the study period, 43.8% of patients were admitted in hospital including 10.4% for EDSSU (n = 20 081). Analyses reveal modest positive correlation of EDSSU admissions with NEAT performance (τ = 0.35, P < 0.001) and weak negative correlation with DNW rates (τ = -0.29, P < 0.001). These associations were more pronounced on days when BOR >100% (τ = 0.39 and τ = -0.36, P < 0.001). BOR of >100% were associated with reduced EDSSU admits, NEAT performance and increased DNW rates (P < 0.001). Appropriate EDSSU admissions had shorter EDSSU length of stay than inappropriate EDSSU admissions (350 vs 557 min, median difference -158 min, P < 0.001). CONCLUSION: Appropriate use of EDSSU provides effective conduit for ongoing patients' management beyond mandated timelines. Health systems should focus on reducing hospital BORs to mitigate exclusive ED pressure to deliver NEAT performance targets.

Systemic inflammatory response syndrome-based severe sepsis screening algorithms in emergency department patients with suspected sepsis.

OBJECTIVE: Systemic inflammatory response syndrome (SIRS)-based severe sepsis screening algorithms have been utilised in stratification and initiation of early broad spectrum antibiotics for patients presenting to EDs with suspected sepsis. We aimed to investigate the performance of some of these algorithms on a cohort of suspected sepsis patients. METHODS: We conducted a retrospective analysis on an ED-based prospective sepsis registry at a tertiary Sydney hospital, Australia. Definitions for sepsis were based on the 2012 Surviving Sepsis Campaign guidelines. Numerical values for SIRS criteria and ED investigation results were recorded at the trigger of sepsis pathway on the registry. Performance of specific SIRS-based screening algorithms at sites from USA, Canada, UK, Australia and Ireland health institutions were investigated. RESULTS: Severe sepsis screening algorithms' performance was measured on 747 patients presenting with suspected sepsis (401 with severe sepsis, prevalence 53.7%). Sensitivity and specificity of algorithms to flag severe sepsis ranged from 20.2% (95% CI 16.4-24.5%) to 82.3% (95% CI 78.2-85.9%) and 57.8% (95% CI 52.4-63.1%) to 94.8% (95% CI 91.9-96.9%), respectively. Variations in SIRS values between uncomplicated and severe sepsis cohorts were only minor, except a higher mean lactate (>1.6 mmol/L, P < 0.01). CONCLUSIONS: We found the Ireland and JFK Medical Center sepsis algorithms performed modestly in stratifying suspected sepsis patients into high-risk groups. Algorithms with lactate levels thresholds of >2 mmol/L rather than >4 mmol/L performed better. ED sepsis registry-based characterisation of patients may help further refine sepsis definitions of the future.

Perceived incivility during emergency department phone consultations.

OBJECTIVE: Perceived incivility during ED medical phone consultations is poorly researched. We aimed to determine frequency and factors influencing perceived incivility during ED phone consultations. METHODS: We conducted a prospective self-reported survey of 40 consecutive phone consultations for 21 ED volunteer doctors. Consultations were classified based on the aim of consultation and deemed as 'positive', 'neutral' or 'negative' based on the perceptions of the consulting doctor. Training levels, time bands and specialty data were collected for both consulting and consulted parties. RESULTS: Fifty-seven of 714 included consultations (7.98%, 95% CI 6.2-10.2%) were reported as negative by ED medical staff. Factors associated with significant incidence of negative grading of consultation involved requests for investigations (19.3% vs 5.3%, P < 0.01), consultations with specialist trainees postgraduate year > 4 (9.1% vs 3.8%, P < 0.01) and those involving radiology specialty (18% vs 5.32%, P < 0.01). The risk was lower when the consulted professional was a specialist medical practitioner as compared to specialist trainee (4.1% vs 9.4%, P = 0.02). Multiple logistical modelling suggests that female (adjusted OR 2.4, 95% CI 1.1-5.2) medical staff are more likely to report perceived incivility during ED phone consultations. CONCLUSIONS: Perceived incivility occurs infrequently during ED phone consultations. ED female medical staff are at an increased risk of perceived incivility during phone consultations with non-ED medical professionals. Health organisations should actively pursue programmes to investigate the occurrence of incivility during healthcare consultations and implement programmes to mitigate the risk of developing a negative workplace culture.

Age and admission times as predictive factors for failure of admissions to discharge-stream short-stay units.

OBJECTIVE: Discharge-stream emergency short-stay units (ESSU) improve ED and hospital efficiency. Age of patients and time of hospital presentations have been shown to correlate with increasing complexity of care. We aim to determine whether an age and time cut-off could be derived to subsequently improve short-stay unit success rates. METHODS: We conducted a retrospective audit on 6703 (5522 inclusions) patients admitted to our discharge-stream short-stay unit. Patients were classified as appropriate or inappropriate admissions, and deemed successful if discharged out of the unit within 24 h; and failures if they needed inpatient admission into the hospital. We calculated short-stay unit length of stay for patients in each of these groups. A 15% failure rate was deemed as acceptable key performance indicator (KPI) for our unit. RESULTS: There were 197 out of 4621 (4.3%, 95% CI 3.7-4.9%) patients up to the age of 70 who failed admission to ESSU compared with 67 out of 901 (7.4%, 95% CI 5.9-9.3%, P < 0.01) of patients over the age of 70, reflecting an increased failure rate in geriatric population. When grouped according to times of admission to the ESSU (in-office 06.00-22.00 hours vs out-of-office 22.00-06.00 hours) no significant difference rates in discharge failure (4.7% vs 5.2%, P = 0.46) were noted. CONCLUSION: Patients >70 years of age have higher rates of failure after admission to discharge-stream ESSU. Although in appropriately selected discharge-stream patients, no age group or time-band of presentation was associated with increased failure rate beyond the stipulated KPI.

The emergency department prediction of disposition (EPOD) study.

BACKGROUND: Emergency departments (ED) continue to evolve models of care and streaming as interventions to tackle the effects of access block and overcrowding. Tertiary ED may be able to design patient-flow based on predicted dispositions in the department. Segregating discharge-stream patients may help develop patient-flows within the department, which is less affected by availability of beds in a hospital. We aim to determine if triage nurses and ED doctors can predict disposition outcomes early in the patient journey and thus lead to successful streaming of patients in the ED. METHODS: During this study, triage nurses and ED doctors anonymously predicted disposition outcomes for patients presenting to triage after their brief assessments. Patient disposition at the 24-h post ED presentation was considered as the actual outcome and compared against predicted outcomes. RESULTS: Triage nurses were able to predict actual discharges of 445 patients out of 490 patients with a positive predictive value (PPV) of 90.8% (95% CI 87.8-93.2%). ED registrars were able to predict actual discharges of 85 patients out of 93 patients with PPV of 91.4% (95% CI 83.3-95.9%). ED consultants were able to predict actual discharges of 111 patients out of 118 patients with PPV 94.1% (95% CI 87.7-97.4%). PPVs for admission among ED consultants, ED registrars and Triage nurses were 59.7%, 54.4% and 48.5% respectively. CONCLUSIONS: Triage nurses, ED consultants and ED registrars are able to predict a patient's discharge disposition at triage with high levels of confidence. Triage nurses, ED consultants, and ED registrars can predict patients who are likely to be admitted with equal ability. This data may be used to develop specific admission and discharge streams based on early decision-making in EDs by triage nurses, ED registrars or ED consultants.