Non-Therapeutic Medication Omissions: Incidence and Predictors at an Australian Hospital
Background The inconsistent definition of non-therapeutic medication omissions, under-reporting, and a poor understanding of their associated factors hamper efforts to improve medication administration practices.AimTo examine the incidence of non-therapeutic medication omissions among acutely ill medical and surgical adult patients; and to identify the patient-, drug- and system-related predictors of these omissions.MethodA medication chart audit of 288 acutely ill adult medical and surgical patients admitted to 4 target wards (2 surgical and 2 medical) at an Australian hospital. Patients admitted to these wards from December 2008 to November 2009, with at least one regularly prescribed medication, were eligible. The sample was stratified according to gender, season and ward. A medication chart audit identified medication omissions, and data were collected on gender, age, length of stay, comorbidities, medication history and clinical pharmacy review.ResultsOf the 288 medication charts audited, 220 (75%) had one or more medication omissions. Of the 15 020 medication administration episodes, there were 1687 omissions, resulting in an omission rate per medication administration episode of 11%. Analgesics and aperients were the most frequently omitted medications, with failure to sign the medication record and patient refusal, the main reasons for omission. Female gender (p < 0.001) and the number of medication administration episodes (p < 0.001) were statistically significant predictors of non-therapeutic medication omissions.Conclusion The high incidence of medication omissions suggests there is need for an agreed definition of medication omission and its inclusion as a reportable incident. Increasing medication reconciliation via implementation of the Medication Management Plan may also reduce the opportunity for error.
Journal of Pharmacy Practice and Research Volume 41, No. 3, 2011.
Sharon L Latimer, RN, BN, MN, MAP (Health Care Research), GradDip Learning
and Teaching, Associate Lecturer, School of Nursing and Midwifery, Griffith
University, Logan Campus, Wendy Chaboyer, BSc (Nurs) (Dist), MN (Research),
PhD, Professor, and Director, NHMRC Centre of Research Excellence in Nursing
Interventions for Hospitalised Patients, Research Centre for Clinical and
Community Practice Innovation, Tony Hall, BPharm (Hons), AdvDip Clin Pharm
Teaching, DipMedSci (Palliative Care), Senior Lecturer, School of Pharmacy,
Griffith University, Gold Coast Campus, Gold Coast, Queensland
Address for correspondence: Sharon Latimer, School of Nursing and Midwifery,
Griffith University, Logan Campus, Southport Qld 4131, Australia.
Non-Therapeutic Medication Omissions:
Incidence and Predictors at an Australian Hospital
Sharon L Latimer, Wendy Chaboyer, Tony Hall
Background: The inconsistent definition of non-therapeutic
medication omissions, under-reporting, and a poor
understanding of their associated factors hamper efforts to
improve medication administration practices.
Aim: To examine the incidence of non-therapeutic medication
omissions among acutely ill medical and surgical adult patients;
and to identify the patient-, drug- and system-related predictors
of these omissions.
Method: A medication chart audit of 288 acutely ill adult medical
and surgical patients admitted to 4 target wards (2 surgical and
2 medical) at an Australian hospital. Patients admitted to these
wards from December 2008 to November 2009, with at least
one regularly prescribed medication, were eligible. The sample
was stratified according to gender, season and ward. A medication
chart audit identified medication omissions, and data were
collected on gender, age, length of stay, comorbidities,
medication history and clinical pharmacy review.
Results: Of the 288 medication charts audited, 220 (75%) had
one or more medication omissions. Of the 15 020 medication
administration episodes, there were 1687 omissions, resulting
in an omission rate per medication administration episode of
11%. Analgesics and aperients were the most frequently omitted
medications, with failure to sign the medication record and
patient refusal, the main reasons for omission. Female gender
(p < 0.001) and the number of medication administration
episodes (p < 0.001) were statistically significant predictors of
non-therapeutic medication omissions.
Conclusion: The high incidence of medication omissions
suggests there is need for an agreed definition of medication
omission and its inclusion as a reportable incident. Increasing
medication reconciliation via implementation of the Medication
Management Plan may also reduce the opportunity for error.
J Pharm Pract Res 2011; 41: 188-91.
Patient safety is a priority for hospital administrators and
Medication administration is
central to contemporary patient management, and is the
second most frequently performed nursing activity in
In Australian hospitals, medication
error is the second most frequently occurring incident,
with patient falls rating as number one.
little was known about the incidence of medication error
and omission. The Institute of Medicine’s report To Err
is Human: Building a Safer Health System estimated
that up to 98 000 patients die annually in US hospitals
because of medication errors.
In Australia, there are
approximately 190 000 medication error related hospital
admissions per year at a cost of $660 million.
In patient safety reports, medication administration
is identified as a high-risk activity, although how this
relates to medication omissions is less well known.
to patients’ include medication duplication, omission and
Increased polypharmacy associated with
the ageing population, and chronic disease, further
compounds this issue.
Medication omissions are the
most frequent medication error,
with acutely ill patients
Medication errors are under-
reported, with omissions accounting for 2% to 79% of all
In recent Australian studies, 81%
of all identified medication errors are reported to be
omissions, with 86% of omitted medications placing
patients at some risk of harm.
These results are mirrored
The aim of this study was to examine the incidence
of non-therapeutic medication omissions among acutely
ill medical and surgical adult patients; and to identify
patient-, drug- and system-related predictors of these
A medication chart audit was used to collect data on the
incidence and possible predictors of non-therapeutic
medication omissions. Ethics committee approval was
obtained from Griffith University and Gold Coast Hospital
Human Research Ethics Committes. Adult patients at the
450-bed Gold Coast Hospital were eligible if they were
admitted to the four target wards (2 medical and 2 surgical)
over the 12-month (1 December 2008 to 30 November
2009) study period.
Using an average length of stay of 3 days, it was
estimated that 7680 admissions would occur across the
four target wards during the study period. It was estimated
that a sample size of 288 would provide 15 000 to 22 000
medication prescriptions and provide sufficient
opportunities for medication omissions. The sample size
for multivariate regression analysis was calculated by
allowing nine cases per stratum, providing sufficient
power analysis. A random sample of 288 patients, stratified
according to gender, season and ward were used.
Inclusion criteria were patients aged 18 years and over;
admitted to one of the four target wards; and prescribed
at least one regular medication. Patients were only
included once in the sample and for patients with multliple
admissions, their most recent admission was included.
Prescriptions were excluded if they were: once-only and
variable dose medications; telephone orders; intravenous
and subcutaneous continuous infusions; pro re nata
(as required) and nurse-initiated medicines, because these
are not regularly prescribed medications.
Journal of Pharmacy Practice and Research Volume 41, No. 3, 2011.
Figure 1. Medication classification of the 1687 identified medication omissions.
A non-therapeutic medication omission was defined
as a medication dose not administered before the next
due dose. The absence of a signature or the presence of
a tick ( ) on the medication chart were defined as
omissions due to the lack of administration
A tick ( ) is not an accepted abbreviation
of the organisation, nor is it one of the National Inpatient
Medication Chart’s (NIMC) omission codes. A
therapeutic medication omission was defined as a
medication not administered based on clinical decisions
documented in the medical notes. Therapeutic medication
omissions were not included in the analysis.
The study by Warne et al.
and the NIMC informed
the audit tool design. Eight NIMC codes (A = absent; F
= fasting; L = on leave; N = medication not available; R =
patient refused; S = self-administered; V = vomiting; W
= withheld) and three additional codes were adopted
(Nil = no reason or signature; Acc = no route access
[intravenous]; T = tick [ ] instead of a signature). Data
were collected on nine possible predictors: three patient-
related (age, gender, number of comorbidities), two drug-
related (medication history, medication administration
episodes), and four system-related (clinical pharmacy
review, length of stay, season, ward).
collection, the medical records and clinical notes were
reviewed to determine if the identified medication
omission was supported by documented clinical
decision-making (e.g. aperients withheld due to
diarrhoea). If evident, the omissions were deemed
therapeutic and not included in the analysis.
The characteristics of the first medication omission
experienced by a patient were analysed (this type of
analysis was used in a similar study).
were entered into the Statistical Package for the Social
Sciences (version 17). Descriptive statistics were
performed to describe the sample and identify the
incidence of medication omission. A model building
approach was used to identify the significant predictors
(p < 0.05) of medication omissions. Chi-square analysis
was used to test for association between individual
variables and the outcome – medication omission. All
significant variables from the chi-square analysis were
then entered as predictors in the multivariate logistic
regression analysis. Only variables that were significant
(p < 0.05) were then entered into a second multivariate
logistic regression analysis, to develop a parsimonious
predictive model of medication omission.
The randomly selected sample (n = 288) was drawn from
a population of 5654 patients admitted to the four target
wards during the study period. Two hundred and twenty
(76%) patients experienced more than one medication
omissions; more females (n = 122; 55%) than males (n =
98; 45%) comprised this group. The age range was 18 to
95 years (mean 61.3; SD 20.9) and half (n = 147; 51%)
were over 65 years of age. The highest incidence of
omissions (n = 116; 40%) occurred in this older age group
elaM 89 )%43( 64 )%61( 441 )%05(
elameF 221 )%24( 22 )%6.7( 441 )%05(
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01-8 72 )%4.9( 3 )%1( 03 )%01(
11 62 )%9( 0 62 )%9(
On average, patients had 2.8 comorbidities, with half
reporting more than 3 comorbidities (n = 146; 51%), and
the majority having up to 5 comorbidities (n = 256; 89%).
Journal of Pharmacy Practice and Research Volume 41, No. 3, 2011.
Of the 2095 medications prescribed that resulted in
15 020 medication administration episodes, 1687 non-
therapeutic omissions were identified, representing an
omission rate per medication administration episode of
11% or an average of 5.8 (SD 7.9) omissions per patient.
The 1687 non-therapeutic medication omissions were
classified according to the MIMS (Figure 1).
Analgesics (simple analgesics and opiates) were the
most frequently omitted medications (33%) with
alimentary medications (17%) the second most frequently
omitted medications (Figure 1).
The characteristics of the first omission were
examined for statistical significance. There was strong
statistical significance (χ² = 57; df = 5, p < 0.001), between
the number of medication administration episodes and
an omission. Patients with more than 25 medication
administration episodes (n = 146; 66%) were more likely
to experience an omission compared to those with fewer
medication administration episodes. The number of
comorbidities did not increase the likelihood of an
omission (χ² = 2.9, df = 4, p = 0.6).
Of the drug-related factors, most patients
experiencing an omission did not have a medication
history (n = 169; 77%) completed by the clinical
pharmacist. However, there was no statistical significance
between completion of a medication history by the clinical
pharmacist and a medication omission (χ² = 0.5, df = 1, p
= 0.5). The absence of a signature or the use of an NIMC
code (n = 65; 30%) on the medication chart, were the
main reasons for the first medication omission. Patient
refusal (n = 55; 25%), medication unavailability (n = 38;
17%) and withholding a medication (n = 27; 12%) without
a documented clinical reason, were the subsequent
reasons for omissions. Of the patients requiring to fast
for a procedure, 5.9% (n = 13) had medications omitted
without a documented medical order. In 5.5% (n = 12) of
first medication omissions, the presence of a tick ( ) on
the medication chart was identified as omissions. Finally,
a lack of access, either intravenous or gastrointestinal,
accounted for 2.3% (n = 5) of first medication omissions
experienced by a patient.
Of the first omission experienced by a patient, oral
medications (n = 162; 74%) were the largest group, with
the remaining 26% (n = 58) of omissions distributed across
six other routes of administration. Intravenous (n = 24;
11%) and subcutaneous (n = 20; 9.1%) routes were the
second and third, routes omitted, with antimicrobials and
anticoagulants the main medications involved.
Of the system-related factors, patient’s length of stay
ranged from 1 to 31 days (mean 4.8; SD 4.7). For patients
experiencing more than one medication omissions, over
two-thirds (n = 150; 68%) had a length of stay of 3 days
or more (Table 1). The frequency of omissions were closely
distributed across the four seasons, with no statistical
association (χ² = 2.3, df = 3, p = 0.5) between medication
omission and season. The majority of patients (n = 182;
83%) experiencing an omission did not have their
medication chart reviewed by a clinical pharmacist. There
was no statistical significance between these factors (χ²
= 2.1, df = 2, p = 0.4).
The overall predictive model was statistically
significant (χ² = 102, df = 22, p < 0.001). Two independent
variables, gender and medication administration episodes,
were statistically significant in predicting the likelihood
of medication omission. Table 2 represents the results
for predicting the probability of a patient experiencing a
non-therapeutic medication omission.
This final predictive model was statistically significant
(c² = 69, df = 2, p < 0.001). When compared to males,
females were almost 3 times more likely (OR 2.9; 95%CI
1.5–5.3) to experience a medication omission. Medication
administration episodes increased the likelihood of a
patient experiencing a medication omission (OR 1.04
95%CI 1.0–1.1). For each additional medication
administration episode, a patient has a 4% increased
likelihood of experiencing a medication omission.
Medication omissions fall under the broad category of
medication errors. Recent studies report omission rates
per patient ranging from 26% to 79% and our study found
an omission rate per patient of 76%.
In our study, the
omission rate per medication dose was 11% suggesting
1 in every 9 doses were omitted. A finding supported by
In our study, analgesics and alimentary medications
were the most frequently omitted, possibly suggesting
pain and bowel management strategies at the research
site may need reviewing. These findings are supported
by studies from Australia and the UK.
92 doses (5.4%) of subcutaneous anticoagulants
(heparin, enoxaparin) were omitted without a valid
documented clinical reason. These omissions are difficult
to explain, especially when the doses were refused by
the patient or withheld by the nurse. Current prescribing
practices, poor knowledge of potential patient harm, a
lack of patient understanding, and reduced reporting of
patient refusal may explain these results.
Drug unavailability has been reported as the foremost
reason for medication omission.
In our study, the
principal reasons for omissions were the absence of a
medication chart signature and patient refusal. During
data collection, the notation ‘all medications
administered’ was frequently observed in the medical
notes, but the medication chart revealed numerous
omissions, making it difficult to ascertain which document
was accurate. The absence of a signature may in part be
a ‘failure to document’ due to distractions rather than a
genuine medication omission.
The major issues of
concern relate to an increased risk of patients receiving
additional medication doses, coupled with a lack of
Our study supports the
development of visual reminders, such as ‘Have you
signed your chart?’ stickers, to change clinician
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Journal of Pharmacy Practice and Research Volume 41, No. 3, 2011.
We also found that pharmacological and manual
thromboprophylactic measures were simultaneously
prescribed on the medication chart, with only one space
for the signature. If the signature was absent, it was
assumed both measures were omitted, which may not
have been the case. Implementation of the Venous
Thromboembolism NIMC with two separate orders for
pharmacological and manual thromboprophylactic
measures, will assist clinicians to know, with greater
certainty, which drugs have been administered.
Of the first medication omission experienced by a
patient, the intravenous route was the second most
frequent route of omission. A lack of intravenous access
was the reason medications were omitted via this route,
suggesting poor timely replacement of the intravenous
device by staff. Antimicrobials were mostly involved in
this route of omission.
The vast majority of patients and more than three
quarters of patients experiencing a medication omission
did not have a medication history completed by a clinical
pharmacist. Medication reconciliation reduces the
opportunity for medication errors, although accurate
information from health professionals and patients
impacts on the robustness of the reconciliation process.
Some studies report that clinical pharmacy services have
a direct impact on clinical and economic outputs, such
as reduced medication errors and patient mortality
Our study found low rates of clinical
pharmacist medication histories, but this variable was
not statistically significant. Despite this, implementation
of the Medication Management Plan will provide a
systematic approach towards medication reconciliation,
reflecting the Pharmaceutical Society of Australia’s
This strategy should increase
medication history completion rates by the
multidisciplinary healthcare team.
Of the data collected on the nine possible patient-,
drug- and system-related predictors, two significant
predictors of omissions were identified: medication
administration episodes and female gender. Medication
administration episodes were a statistically significant
predictor of omissions, i.e. as the number of medication
administration episodes per patient increased, so did the
likelihood of omission. Numerous contributing factors
have been identified and include polypharmacy;
prescribing practices; and system, individual and
Gender too, was a statistically significant predictor
of medication omission with females experiencing an
increased likelihood of omissions. One-third of females
in our study were aged 65 years and over, with more than
80% having one or more comorbidities. These factors
often result in polypharmacy, and possibly higher rates
This study had some limitations. Firstly, only one
research site was used, however, the sample size was
large compared to similar studies.
medications without a signature and those with a tick
( ) were assumed to have not been administered and
this may have not been the case. Finally, many of the
results are representative of the first medication omission
experienced by a patient with extrapolation to
subsequent omissions questionable.
In conclusion, the high incidence of medication
omissions suggests there is need for an agreed definition
of medication omission and its inclusion as a reportable
incident. Increasing medication reconciliation via
implementation of the Medication Management Plan may
also reduce the opportunity for error.
This research project was supported by the DBL Development Fund Grant to
the value of $10 000.
Sincerest thanks to Professor Ruth Endacott for allowing us to use her
medication omission audit tool as a basis for our audit tool design
Competing interests: None declared
1. The Joint Commission. Sentinel event statistics as of March 31, 2009.
Washington DC: The Joint Commission; 2009.
2. Kohn LT, Corrigan JM, Donaldson MS, editors. To err is human: building a
safer health system. Washington: National Academy Press; 2000.
3. Leape LL. Reporting of adverse events. N Engl J Med 2002; 347: 1633-8.
4. Hughes CF. Medication errors in hospitals: what can be done? Med J Aust
2008; 188: 267-8.
5. Chaboyer W, Wallis M, Duffield C, Courtney M, Seaton P, Holtzhauser K, et
al. Comparison of activities undertaken by enrolled and registered nurses on
medical wards in Australia: an observational study. Int J Nurs Stud 2008; 45:
6. Roughead EE, Semple SJ. Medication safety in acute care in Australia: where
are we now? Part 1: a review of the extent and causes of medication problems
2002–2008. Aust N Z Health Policy 2009; 6: 18.
7. Picone DM, Titler MG, Dochterman J, Shever L, Kim T, Abramowitz P, et al.
Predictors of medication errors among elderly hospitalized patients. Am J Med
Qual 2008; 23: 115-27.
8. Lawler C, Welch SA, Brien JE. Omitted medication doses: frequency and
severity. J Pharm Pract Res 2004; 34: 174-7.
9. Roughead EE, Semple S. Second national report on patient safety: improving
medication safety. Canberra: Australian Council for Safety and Quality in Health
Care; 2002. Available from <www.safetyandquality.gov.au/>.
10. Warne S, Endacott R, Ryan H, Chamberlain W, Hendry J, Boulanger C, et al.
Non-therapeutic omission of medication in acutely ill patients. Nurs Crit Care
2010; 15: 112-17.
11. Caughey GE, Vitry AI, Gilbert AL, Roughead, EE. Prevalence of comorbidity
of chronic diseases in Australia. BMC Public Health 2008; 8: 221. Available
12. Bohomol E, Ramos LH, D’Innocenzo M. Medication errors in an intensive
care unit. J Adv Nurs 2009; 65: 1259-67.
13. O’Shea TJ, Spalding AR, Carter FA. Impact of nurse education on the
incidence of omitted medication doses in hospital inpatients. J Pharm Pract Res
2009; 39: 114-16.
14. Etchells E, Juurlink D, Levinson W. Medication errors: the human factor.
CMAJ 2008; 178: 63-4.
15. Endacott R, Boulanger C, Chamberlain W, Hendry J, Ryan H, Viner JE. Missed
medications and clinical cues in patients admitted unexpectedly to intensive
care. Intensive Care Med 2006; 32: 5-13.
16. McBride-Henry K, Foureur M. A secondary care nursing perspective on
medication administration. J Adv Nurs 2007: 60: 58-66.
17. O’Laughlen MC, Hollen P, Ting S; National Asthma Education and
Prevention Program. An intervention to change clinician behavior: conceptual
framework for the multicolored simplified asthma guideline reminder. J Am Acad
Nurs Pract 2009; 21: 417-22.
18. Maskerine C, Loeb M. Improving adherence to hand hygiene among health
care workers. J Contin Educ Health Prof 2006; 26: 244-251.
19. National Health and Medical Research Council. Clinical practice guidelines
for the prevention of venous thromboembolism in patients admitted to Australian
hospitals. Melbourne: National Health and Medical Research Council; 2009.
Available from <www.nhmrc.gov.au/_files_nhmrc/file/nics/programs/vtp/
20. Hasan S, Duncan GT, Neill DB, Padman R. Towards a collaborative filtering
approach to medication reconciliation. Proceedings of the American Medical
Informatics Association Annual Symposium; 2008 Nov 8-12; Washington DC,
Washington. Washington: The Association; 2008. p. 288-92.
21. Bond CA, Raehl CL. Clinical pharmacy services, pharmacy staffing and
hospital mortality rates. Pharmacotherapy 2007; 27: 481-93.
22. Pharmaceutical Society of Australia. Professional practice standards. Version
4. Deakin West: Pharmaceutical Society of Australia; 2010. Available from
23. Reason J. Achieving a safe culture: theory and practice. Work Stress 1998;
Received: 31 May 2011
Revisions requested after external review: 26 July 2011
Revised version received: 30 August 2011
Accepted for publication: 1 September 2011