Using league tables to reduce missed dose medication errors on mental healthcare of older people wards

Prevalence, nature and predictors of omitted medication doses in mental health hospitals: A multi-centre study

Objective

Limited evidence concerning the burden and predictors of omitted medication doses within mental health hospitals could severely limit improvement efforts in this specialist setting. This study aimed to determine the prevalence, nature and predictors of omitted medication doses affecting hospital inpatients in two English National Health Service (NHS) mental health trusts.

Methods

Over 6 data collection days trained pharmacy teams screened inpatient prescription charts for scheduled and omitted medication doses within 27 adult and elderly wards across 9 psychiatric hospitals. Data were collected for inpatients admitted up to two weeks prior to each data collection day. Omitted doses were classified as ‘time critical’ and ‘preventable’ based on established criteria. Omitted dose frequencies were presented with 95% confidence intervals (CI). Multilevel logistic regression analyses determined the predictors of omitted dose occurrence, with omission risks presented as adjusted odds ratios (OR) with 95% CI.

Results

18,664 scheduled medication doses were screened for 444 inpatients and 2,717 omissions were identified, resulting in a rate of 14.6% (95% CI 14.1–15.1). The rate of ‘time critical’ omitted doses was 19.3% (95% CI 16.3–22.6%). ‘Preventable’ omitted doses comprised one third of all omissions (34.5%, 930/2694). Logistic regression analysis revealed that medicines affecting the central nervous system were 55% less likely to be omitted compared to all other medication classes (9.9% vs. 18.8%, OR 0.45 (0.40–0.52)) and that scheduled doses administered using non-oral routes were more likely to be omitted compared the oral route (inhaled OR 3.47 (2.64–4.57), topical 2.71 (2.11–3.46), ‘other’ 2.15 (1.19–3.90)). ‘Preventable’ dose omissions were more than twice as likely to occur for ‘time critical’ medications than non-time critical medications (50.4% vs. 33.8%, OR 2.24 (1.22–4.11)).

Conclusions

Omitted medication doses occur commonly in mental health hospitals with ‘preventable’ omissions a key contributor to this burden. Important targets for remedial intervention have been identified.

Prevalence, nature and risk factors for medication administration omissions in English NHS hospital inpatients: a retrospective multicentre study using Medication Safety Thermometer data

OBJECTIVE

To determine the prevalence, nature and predictors of patients having medication administration omissions in hospitals.

METHODS

All medication administration omissions data collected using the standardised methodology of the Medication Safety Thermometer in January 2015 were examined. Hospital inpatients prescribed at least one medication were included in the analysis. Multilevel logistic regression models ascertained the effects of patients' gender, age, number of prescribed medicines, ward specialty and medicines reconciliation initiation status on the likelihood of having omissions. Valid clinical reasons (VCRs) were excluded from regression models. A sensitivity analysis, excluding patient refusal (PR) omissions, was also conducted.

RESULTS

The final study sample included 5708 patients from 320 wards in 37 hospitals. Excluding VCRs, 30% of patients had medication administration omissions (95% CI 29 to 30). Approximately half of patients with omissions had refused medicines (51%, 95% CI 49 to 53). Univariable analysis suggested that all variables were significantly associated with omissions. However, in the multivariable model, significant differences were only observed regarding the numbers of medicines patients were prescribed and their ward specialty. Patients prescribed more than 20 medications were approximately five times more likely to have had omissions than patients prescribed one to four medications (OR 4.99, 95% CI 3.22 to 7.73). Patients on surgical wards were also more likely to have had omissions than those on medical wards (OR 1.58, 95% CI 1.14 to 2.18, p=0.006), but there was no significant difference when PRs were excluded (OR 0.5, 95% CI 0.27 to 1.22, p=0.473).

CONCLUSION

Medication administration omissions are a substantial problem that affect many hospital patients, and certain patient groups are at higher risk. Specific interventions are required targeting the underlying reasons for medication omissions for different patient subgroups.

Low stimulus environments: reducing noise levels in continuing care

In the low stimulus environment project, we aimed to reduce the levels of intrusive background noise on an older adult mental health ward, combining a very straightforward measure on decibel levels with a downstream measure of reduced distress and agitation as expressed in incidents of violence. This project on reducing background noise levels on older adult wards stemmed from work the team had done on reducing levels of violence and aggression.

We approached the problem using quality improvement methods. Reducing harm to patients and staff is a strategic aim of our Trust and in our efforts we were supported by the Trust's extensive programme of quality improvement, including training and support provided by the Institute for Healthcare Improvement and the trust's own Quality Improvement team.

Prior to the project we were running a weekly multi-disciplinary quality improvement group on the ward. We established from this a sub-group to address the specific problem of noise levels and invited carers of people with dementia on our ward to the group. The project was led by nursing staff. We used a noise meter app readily downloadable from the internet to monitor background noise levels on the ward and establish a baseline measure. As a group we used a driver diagram to identify an overall aim and a clear understanding of the major factors that would drive improvements. We also used a staff and carer survey to identify further areas to work on. Change ideas that came from staff and carers included the use of the noise meter to track and report back on noise levels, the use of posters to remind staff about noise levels, the introduction of a visual indication of current noise levels (the Yacker Tracker), the addition of relaxing background music, and adaptations to furniture and environment. We tested many of these over the course of nine months in 2015, using the iterative learning gained from multiple PDSA cycles.

The specific aim was a decrease from above 60dB to below 50dB in background noise on the wards. Following our interventions, we have managed to decrease noise levels on the ward to 53dB on average.

The success of this project to date has relied on the involvement of ward staff and carers - those most affected by the problem - in generating workable local solutions. As many of the change ideas amounted to harm free interventions it was easier for us to make a case to test them out in the real-life setting. Nevertheless we were surprised at how effective such seemingly simple ideas have been in improving the environment on the ward. We have incorporated the change ideas into routine practice and are advising other wards on similar projects.