March 10, 2014
Medication Administration Errors in Hospitals — Challenges and Recommendations for Their Measurement
By: Monsey McLeod, MPharm, MSc, PhD, Nick Barber, BPharm, PhD, Bryony Dean Franklin, BPharm, PhDMedication
errors are a threat to patient safety. Those that result in patient harm
occur in an estimated 1% to 2% of hospital inpatients (1, 2) and contribute to an increased hospital stay of 4.6 to 10.3 days for each affected patient (3–5).
While errors may arise at any stage of the medication use process
(prescribing, dispensing, administering and monitoring), research
suggests prescribing and administration errors account for the largest
percentage of all (39% and 38%, respectively) (6). However, medication administration errors (MAEs) are least likely to be intercepted before they reach the patient (1, 6).
This is partly due to the narrow window of opportunity for detecting a
MAE, which makes studying MAEs and developing suitable intervention
strategies particularly problematic.
Since the publication of key reports worldwide (7–9),
several attempts have been made to adapt strategies from high-risk
industries, such as aviation, to analyse and reduce risk in healthcare (10, 11). However, there are a number of key differences between such industries and healthcare (7).
First, front-line staff in high-risk industries are usually directly
affected when an accident happens, while in the healthcare setting it is
typically someone else, i.e., the patient, who is affected. Second,
preventable harm in healthcare generally occurs to one patient at a
time, rather than groups of patients, making incidents less visible at
the organisational level unless a patient suffers severe harm. For MAEs,
the problem of visibility is made more challenging by the difficulties
of measuring and reporting MAEs in practice (12, 13).
In this commentary, we highlight some of the main challenges associated
with measuring MAE rates and make suggestions for the development of
more practical proxy measures of MAE rates for use in everyday practice
by healthcare professionals.
Challenges in Measuring MAE Rates
The first challenge is determining what to measure.
In published research studies, MAEs are frequently defined as "a
deviation from the physician's medication order as written on the
patient's chart" (13, 14); however, a number of important methodological differences exist among quantitative studies of MAEs (13, 14).
Our recent systematic literature review explored these and their effect
on reported MAE rates which revealed no single standard for determining
MAE rates, even within one country (14).
Overall, we identified three MAE definitions, 44 MAE subcategories, and
four denominators from 16 direct observation studies. The use of
different denominators and MAE rate calculations not only influenced
reported MAE rates, but made it difficult to interpret the literature
surrounding the problem of MAEs. Furthermore, studies of MAE rates do
not always publish sufficient information to interpret the findings (14).
For example, in the UK, MAEs occur in an estimated 5.6% of
non-intravenous doses and 35% of intravenous doses, with intravenous
doses about five times more likely to have an MAE (14).
If studies do not report the inclusion of intravenous doses, the
conclusions drawn from the presented results can be severely limited.
Other key information that should be reported includes the MAE
definition used, inclusion and exclusion criteria, whether timing errors
were included, and how many MAEs were possible for each dose.
Based on our recent literature review, we made a number of
recommendations to guide future reporting of quantitative studies of
MAEs (14).
For example, we suggest reporting the number of intravenous doses if
intravenous doses were included, and whether or not 'when required'
and/or 'once-only' medication orders were included. We based these
recommendations on evaluating UK studies but believe the principles can
be applied to other countries to help increase the interpretability of
study findings and facilitate comparisons between studies.
The next challenge is how to measure. Within
healthcare practice, incident report data are often used to assess
medication error rates within an organisation. However, numerous reasons
exist why MAEs may not ultimately be reported. Incident data requires
someone to be aware that an error has occurred, know how to and be
willing to report it, and then actually do so. For these reasons, it is
estimated that only a very small proportion of MAEs are collected in
organisational incident reporting systems (15, 16).
We would therefore view incident report data as examples of errors that
have occurred, rather than making any quantitative inferences about the
underlying error rates.
Within the research field, measurement of MAE rates mainly involves
direct observation of medication administration, usually by a pharmacist
or a nurse. This practice allows for the detection of significantly
more MAEs than incident reports or chart review (16, 17) and is generally considered to be the gold standard method (13, 17, 18).
However, like any method, it has a number of limitations. Firstly, it
is possible that observation of an individual may induce behaviour
change that could affect the occurrence of MAEs. Yet, previous research
suggests that using a discreet and non-judgemental approach did not
significantly affect MAE rates (12, 17).
Second, observation is resource-intensive and likely to be impractical
for routine regular monitoring. While in some clinical areas the
majority of doses will be provided at four or five routinely scheduled
times, in practice many are administered throughout the day. Efforts to
maximise the observation of medication administration over long periods
of time or its inclusion at all times of the day may increase the risk
of observer-fatigue and possibly influence detected MAEs. Is there a
more practical approach to measuring MAEs, one that is more quantitative
than incident report data, but less resource intensive than extended
periods of observation?
Proxy Measures of Patient Safety Associated with Medication Administration
In patient safety terms, MAEs are a proxy measure for actual patient
harm; depending on the definitions used, research suggests that 0.6% to
21% of MAEs may lead to patient harm that could either result in
prolonged hospitalisation or be considered potentially life-threatening (19).
However, MAEs are just one type of proxy measure. It has been suggested
that approaches for identifying measures for improvement need to be
both reactive and proactive (20).
Based on the concept of institutional resilience in healthcare,
reactive measures, such as MAEs (proxy measure of harm) and adverse drug
events (actual measure of harm), provide important information about
incidents that have occurred in the past so that lessons may be learnt.
By contrast, proactive proxy measures act as an early warning indicator
of potential problems and underlying conditions that may contribute to
future incidents. While there is clearly a place for using direct
observation to study MAEs, more practical methods to regularly monitor
the quality and safety of the medication administration process are
required.
Proactive measures involve regular monitoring of the essential processes and defences (20)
which relate to the prevention or amelioration of risk from potential
and actual patient harm. This approach therefore requires an
understanding of the conditions and specific factors associated with
future incidents that occur locally. Acquiring and understanding the
context in which incidents occur is vital, and thus identifying
appropriate proxy measures requires local knowledge and expertise. Based
on our clinical and research experience, we suggest exploring measures
such as duration of scheduled drug administration rounds and number of
pedometer steps as potential proactive measures of patient safety
associated with medication administration. To determine whether or not
such measures and other potential proxy measures of patient safety for
medication administration might be useful in practice, we recommend the
consideration of the following factors:
- Evidence of a relationship between the proxy measure and the quality or safety of medication administration
- Time required to collect data
- Training required to collect data
- Time to report the data
- Reports that are intuitive and facilitate interpretation and analysis
process control (SPC), which has been used with demonstrable benefits in
healthcare (21, 22). Benneyan et al (21)
provides a useful overview of SPC and its application in healthcare.
Briefly, the SPC approach would facilitate interpretation of what would
otherwise be potentially crude measures, such as duration of drug
administration rounds, by factoring in the inherent day-to-day
variations associated with drug administrations. Consequently, this
method enables the identification of potential problems when the
parameter being measured falls over or under the expected limits of
variation.
The increasing use of computerised prescriber order entry and
electronic medication administration systems provides an opportunity to
incorporate regular monitoring (using SPC or other approaches) of other
patient safety measures that are less practical to assess with paper
systems; for example, some specialized health information systems
automatically flag and report timeliness of time-critical dose
administrations and dose omissions. Given the challenges of measuring
MAEs in healthcare, a medication administration 'dashboard,' which shows
the results from routine proxy measures monitored in a way that is
easily accessible and viewable by relevant staff, may offer healthcare
professionals a better way to 'see' medication administration problems
in a more timely manner, thus enabling action to be taken to reduce the
risk of MAEs.
Conclusions
Patient safety is a global priority, and MAEs remain an important
proxy measure of patient harm. However, a number of challenges
associated with MAE measurement exist. In this commentary, we summarise
what we believe are the main challenges in understanding and
interpreting published MAE rates. Additionally, by applying concepts
from institutional resilience and SPC to the assessment of medication
administration, we make suggestions towards future research and the
development of more practical proxy measures for routine monitoring of
the safety of medication administration. More collaborative work between
researchers and healthcare service providers is now required to
translate such theory into the practice of increasing patient safety.
Authors
Monsey McLeod, MPharm, MSc, PhD
Centre for Medication Safety and Service Quality, Imperial College
Healthcare NHS Trust and The UCL School of Pharmacy, London, UK
Nick Barber, BPharm, PhD
Centre for Medication Safety and Service Quality, Imperial College
Healthcare NHS Trust and The UCL School of Pharmacy, London, UK
Bryony Dean Franklin, BPharm, PhD
Centre for Medication Safety and Service Quality, Imperial College
Healthcare NHS Trust and The UCL School of Pharmacy, London, UK
Disclaimer
The views and opinions expressed are those of the author and do not
necessarily state or reflect those of the National Quality Measures
Clearinghouse™ (NQMC), the Agency for Healthcare Research and Quality
(AHRQ), or its contractor ECRI Institute.
Potential Conflicts of Interest
Dr. McLeod and Professor Barber state no personal or family
financial, business or professional conflicts of interest with respect
to this expert commentary.
Professor Franklin states no personal financial or family
financial/other conflict of interest with respect to this expert
commentary. Professor Franklin reports the following
business/professional interest: expert advisor for the Royal
Pharmaceutical Society of Great Britain.
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