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REPORTS OF ORIGINAL INVESTIGATIONS
Avoidable perioperative mortality at the University Teaching
Hospital, Lusaka, Zambia: a retrospective cohort study
Mortalite
´pe
´riope
´ratoire e
´vitable a
`l’ho
ˆpital universitaire de
Lusaka (Zambie): une e
´tude re
´trospective de cohorte
Edwardina Mary Mae Alexandra Lillie, MBChB .Christopher John Holmes, MBChB .
Elizabeth Anne O’Donohoe, MBChB .Lowri Bowen, MBChB .Chadwick L. T. Ngwisha, MBChB .
Yusuf Ahmed, MPH .David Michael Snell, MBBS .John Alexander Kinnear, MBBCh .
M. Dylan Bould, MBChB
Received: 3 April 2015 / Revised: 3 August 2015 / Accepted: 1 September 2015 / Published online: 29 September 2015
Canadian Anesthesiologists’ Society 2015
Abstract
Purpose Perioperative mortality has fallen in both high-
and low-income countries over the last 50 years. An
evaluation of avoidable perioperative mortality can
provide valuable lessons to improve care; however, there
is relatively little recent data from the Least Developed
Countries in the world. We aimed to compare recent
avoidable perioperative mortality in Lusaka, Zambia, with
historical data from 1987.
Methods We conducted a retrospective cohort study by
identifying perioperative deaths within days of surgery and
comparing the operating room and mortuary registers for
the 2012 calendar year. Multiple independent raters from
anesthesiology and surgery/obstetrics gynecology reviewed
case notes, when available, to identify avoidable causes of
death.
Results Of the 18,010 surgical patients in 2012, 114
were identified as having died perioperatively within six
days of surgery. Fifty-nine files were available for further
analysis (52% of identified perioperative deaths). Eighteen
(30%) of these cases were assessed as avoidable, 19 cases
(32%) probably avoidable, 14 cases (24%) unavoidable,
and eight cases (14%) unclear. Thirty-one (53%) cases had
surgical factors contributing to death, 19 (32%) cases had
anesthesia factors, and 18 (30%) cases had systems
factors. Most of the avoidable deaths were attributed to
multiple factors. Key factors leading to the avoidable
deaths were delays in surgery, lack of the availability of
blood, and poor postoperative care.
Conclusions Most deaths were avoidable, suggesting
that patient outcomes in low-resource settings can be
improved within current resources. The multifactorial
Author contributions Edwardina Mary Mae Alexandra Lillie,
Christopher John Holmes, John Alexander Kinnear, and M. Dylan
Bould were involved in the study design. Edwardina Mary Mae
Alexandra Lillie, Christopher John Holmes, Elizabeth Anne
O’Donohoe, and Lowri Bowen were involved in data collection.
Edwardina Mary Mae Alexandra Lillie, Lowri Bowen, and M. Dylan
Bould were involved in the data analysis. Edwardina Mary Mae
Alexandra Lillie wrote the first draft of the manuscript. Christopher
John Holmes, Elizabeth Anne O’Donohoe, Lowri Bowen, and John
Alexander Kinnear were involved in critical review of the
manuscript. Chadwick L.T. Ngwisha,Yusuf Ahmed, and David
Michael Snell were involved in the analysis and critical review of the
manuscript. M. Dylan Bould was involved in revising the manuscript.
This article is accompanied by an editorial. Please see Can J Anesth
2015; 62: this issue.
E. M. M. A. Lillie, MBChB
Department of Anaesthesia, Guys and St Thomas’ Hospital,
London, UK
C. J. Holmes, MBChB E. A. O’Donohoe, MBChB
Department of Anaesthesia, Great Ormond Street Hospital,
London, UK
L. Bowen, MBChB
Department of Anaesthesia, Royal Gwent Hospital, Newport,
UK
C. L. T. Ngwisha, MBChB
Department of Surgery, University Teaching Hospital, Lusaka,
Zambia
Y. Ahmed, MPH
Department of Obstetrics and Gynaecology, University Teaching
Hospital, Lusaka, Zambia
D. M. Snell, MBBS
Department of Anaesthesia, University Teaching Hospital,
Lusaka, Zambia
123
Can J Anesth/J Can Anesth (2015) 62:1259–1267
DOI 10.1007/s12630-015-0483-z
nature of avoidability implies that an interprofessional
approach is required to improve the quality of care.
Re
´sume
´
Objectif La mortalite´pe´riope´ratoire a chute´ aussi bien
dans les pays de´ veloppe´s que dans les pays a` faible niveau
de vie au cours des 50 dernie`res anne´ es. Une e´ valuation de
la mortalite´pe´riope´ratoire e´vitable peut fournir de
pertinentes lec¸ ons pour l’ame´ lioration des soins;
toutefois, il existe relativement peu de donne´es re´centes
concernant les pays les moins de´ veloppe´s du monde. Nous
avons cherche´a` comparer la mortalite´pe´riope´ratoire
e´ vitable re´cente a` Lusaka (Zambie) a` des donne´es
historiques de 1987.
Me
´thodes Nous avons mene´unee´tude re´ trospective de
cohorte en identifiant les de´ce`s pe´riope´ratoires survenus
dans les jours suivant une chirurgie et en comparant les
registres des salles d’ope´ration et ceux de la morgue pour
l’anne´e 2012. Plusieurs e´valuateurs inde´pendants
(anesthe´siologistes, chirurgiens/obste´triciens-gyne´cologues)
ont analyse´ les dossiers me´dicaux quand ils e´taient
disponibles pour identifier des causes e´vitables de de´ce`s.
Re
´sultats Sur les 18 010 patients chirurgicaux de 2012,
114 ont e´te´ identifie´s comme e´tant de´ce´de´s dans la pe´ riode
pe´ riope´ratoire de six jours suivant l’intervention
chirurgicale. Cinquante-neuf dossiers e´taient disponibles
pour une analyse plus pousse´ e (52 % des de´ce`s
pe´ riope´ratoires identifie
´s). Dix huit (30 %) de ces cas ont
e´te´ juge´s e´vitables, 19 cas (32 %) probablement e´vitables,
14 cas (24 %) ine´vitables et huit cas (14 %) incertains.
Trente et un (53 %) cas pre´ sentaient des facteurs
chirurgicaux contribuant au de´ce` s; 19 (32 %) cas avaient
des facteurs contributifs anesthe´siques et 18 (30 %) cas
avaient des facteurs contributifs syste´miques. La plupart des
de´ce`s e´ vitables ont e´te´ attribue´s a` de multiples facteurs. Les
principaux facteurs contribuant a`desde´ce`s e´ vitables e´taient
les retards dans la chirurgie, le manque de sang disponible
et des soins postope´ratoires insuffisants.
Conclusions La majorite´ des de´ce`s e´tait e´vitable,
sugge´ rant que les re´sultats cliniques des patients vivant
dans un milieu aux ressources limite´es peuvent eˆtre
ame´ liore´s avec les ressources existantes. Le caracte`re
multifactoriel de l’e´vitabilite´ implique qu’une approche
interprofessionnelle est requise pour ame´liorer la qualite´
des soins.
A death is one of the most devastating outcomes of surgery,
and it is particularly tragic if that death could have been
avoided with improved quality of care. Mortality and
avoidable mortality are therefore key indicators of
perioperative outcomes. A recent systematic review and
meta-analysis revealed that total perioperative mortality
has declined over the last 50 years (from 1.06% before the
1970s to 0.45% in the 1970s-1980s and 0.12% in the
1990s-2000s) despite patients’ increased comorbidities.
1
The greatest decline in total perioperative mortality has
been in developed countries; however, countries with a
Human Development Index (HDI) \0.8 (a measure of
development based on per capita income, life expectancy,
literacy, and enrolment in higher education)
2
have also
experienced a reduction in mortality (from 1.14% before
the 1970s to 0.73% in the 1970s-1980s and 0.24% in the
1990s-2000s).
1
Zambia is a country with an estimated population of
14.5 million
3
and an HDI of 0.56 (ranked 141st out of 187
countries) compared with Canada’s HDI of 0.90 (ranked
eighth in the world).
4
The United Nations classifies Zambia
as one of the Least Developed Countries in the world.
5
Gross national income per capita is US$2,898, and
although this places Zambia in the lower middle income
category according to the World Bank classification, 74%
of the population lives on less than US$1.25 a day.
3
The
mortality rate for children under five years is estimated to
be 75 per 1,000 live births; the maternal mortality ratio is
398 per 100,000 live births,
6
and HIV prevalence is
12.7%.
4
The University Teaching Hospital (UTH) is the
largest hospital in Zambia. It not only serves the Lusaka
area population (estimated at 1.7 million)
7
but also
functions as a referral centre for the rest of the country.
Officially, it has 1,655 beds and 250 baby cots, but as
demand far outstrips capacity, floor beds and bed sharing
have been reported.
8
The avoidable perioperative mortality data for UTH was
last collected in 1987
9
when Zambia’s population was 8
million. Mortality was found to be 0.76% with avoidable
mortality 0.33% - i.e., 43% of deaths were considered
avoidable at that time. Anesthesia in Zambia has been
found to be highly underdeveloped and underresourced
10
with less than one physician anesthesiologist per million
population.
11
Our aim was to conduct a retrospective assessment of
avoidable perioperative mortality at UTH for the 2012
calendar year. We aimed to review the circumstances
around every perioperative death to identify avoidable
mortality and any learning points that could be used to
improve the quality of care in the future. A secondary
objective was to compare the six-day perioperative
mortality rate in 2012 with the previous data from 1987.
We hypothesized that the total perioperative mortality rate
J. A. Kinnear, MBBCh
Postgraduate Medical Institute, Anglia Ruskin University, Essex,
UK
M. D. Bould, MBChB (&)
Department of Anesthesiology, Children’s Hospital of Eastern
Ontario, Ottawa, ON, Canada
e-mail: dbould@cheo.on.ca
1260 E. M. M. A. Lillie et al.
123
at the UTH would not have decreased significantly based
on the established global trend in low HDI countries.
1
We
also assumed that avoidable perioperative mortality at the
UTH in Lusaka had not improved since 1987 and that
many perioperative deaths remained avoidable.
Methods
We undertook a retrospective review of case notes involving
inpatient perioperative six-day mortality, i.e., deaths that
occurred between induction of anesthesia and postoperative
day 5 (operation day being day 0) at the UTH, Zambia. The
University of Zambia Biomedical Research Ethics
Committee approved this study in November 2012
(UNZAREC reference number 014-11-12).
A flow chart (Fig. 1) shows how the files were
identified. All patients who died while an inpatient at the
UTH from January 1, 2012 to December 31, 2012 were
identified from the mortuary registers. These registers
(filled in by mortuary technicians) are paper ledgers that
document patient name, gender, date of death, and the
location in the hospital from which the patient was
transferred. The patient’s age, date of birth, and hospital
identification number were sometimes recorded but
without consistency.
Individual patients who underwent surgery during the
study period were identified from operating theatre
registers filled in by theatre or recovery staff. In order to
identify patients suspected of death within six days of
surgery, the patient lists from the mortuary and theatre
registers were entered into an Excel spreadsheet
(Microsoft, Redmond, WA, USA) and compared line by
line for name, age, date of surgery, and date of death,. We
also alerted ward clerks on the surgical wards to advise us
of any perioperative deaths and asked the Department of
Obstetrics and Gynaecology to inform us of any maternal
mortality that may have involved an operative intervention.
Each case file was reviewed by two assessors, an
anesthesiologist (L.B.) and an obstetrician (Y.A.) or a
general surgeon (C.N.), depending on whether the case was
an obstetric or other surgical specialty. Each investigator
independently filled in a data collection form for each
patient and the forms were then compared. The goal of this
review was to identify whether the death was avoidable and
whether surgical care, anesthesia care, or systems issues
had contributed to the avoidable death. Any disagreement
regarding the categorization of cases was resolved through
discussion and, if necessary, additional raters (E.M.M.A.L.,
M.D.B.) until they reached consensus. Consensus was
eventually reached in all cases. An ‘‘avoidable death’’ was
defined as a case where the patient would most likely have
survived if the quality of care was improved within current
resources. A ‘‘probable avoidable death’’ was defined as a
case where it was likely but not certain that the patient
would have survived if the quality of care was improved
within current resources. An ‘‘unavoidable death’’ was
defined as a case where the patient would have died
regardless of the quality of care within available resources.
A categorization of ‘‘unclear’’ was used if the notes did not
provide sufficient detail to comment on avoidability of
death. An anesthetic or surgical contribution to avoidable
death was defined as a case where improved care by either
the anesthesia or surgical team could have prevented death.
A system of care contribution to avoidable death was
designated when avoidability fell outside of the immediate
remit of these teams and included organizational issues and
nursing care.
Statistical analysis
Descriptive statistics were used to report patient
characteristics, postoperative day of death, avoidability of
Fig. 1 Flow chart for a study on perioperative mortality at the
University Teaching Hospital, Lusaka
Perioperative mortality in Zambia 1261
123
death, and contributory causes. A two-tailed Chi square test
was used to compare avoidable mortality and overall
mortality with historical data from 1987.
9
All reported P
values are two sided. SPSS
version 19 (IBM, Armonk,
NY, USA) software was used for analysis.
Our study sample size estimate was calculated in order
to identify a drop in mortality from 0.7% to 0.5%. Using
a conservative estimate based on global trends,
1
assuming
an alpha of 0.05, we needed a denominator of 1,231
operative cases for a power of 80% using G*Power
version 3.1.2 (University of Du
¨sseldorf).
12
We elected to
collect data for a full calendar year in order to have a
number of cases comparable with the historical study and
to maximize the opportunity to learn from avoidable
causes of mortality.
Results
During 2012, 18,010 operations were conducted
throughout the UTH as noted from prospectively
collected official hospital statistics. In spite of this, some
theatre registers were lost entirely, and some had multiple
pages missing or damaged. Patient details of only 11,688
cases were available from these registers. Ninety-five
patients matched the mortuary list and therefore were
suspected of death within six days of surgery. In addition,
ward clerks and the medical records department, whom we
had alerted to our goal of capturing all perioperative
mortality for 2012, identified another 11 patients who died
perioperatively. The Department of Obstetrics and
Gynecology, where maternal mortality is independently
tracked, identified 26 additional patients as perioperative
deaths. Only three of these additional cases had been
previously identified from the search of the theatre and
mortuary registers, resulting in 23 additional cases. Fifteen
of the 129 patients identified in this manner were excluded
on further examination of the case notes which revealed
that the patients had not died, did not have surgery, or the
death was not within the first six days of surgery. This left
an estimated six-day perioperative mortality of 114 cases
(0.98% of patients included on the theatre registers). Fifty-
five patients were excluded from further analysis as their
case notes could not be found, which left 59 case files that
were available and analyzed for the study.
Patient characteristics are shown in Table 1.Of
importance, only 25% of cases involved a consultant
surgeon/obstetrician (i.e., ‘‘consultant’’ was defined as a
senior doctor who completed a locally or internationally
recognized specialty training program), and only 34% of
cases involved a consultant anesthesiologist. Forty-one
deaths (69%) involved patients less than 40 yr old.
Table 1 Patient characteristics relating to cases with perioperative
mortality
Gender
•Male 16 (27%)
•Female 43 (73%)
Age
•0-9 5 (8%)
•10-19 9 (15%)
•20-29 12 (21%)
•30-39 16 (27%)
•40-49 7 (12%)
•50-59 3 (5%)
•60-69 2 (3%)
•70-79 3 (5%)
•Over 80 1 (2%)
•Not documented 1 (2%)
Urgency of surgery
•Elective 16 (27%)
•Emergency 43 (73%)
Type of surgery
•Minor 16 (27%)
•Major 43 (73%)
Surgical specialty
•General surgery 18 (31%)
•Obstetrics 16 (27%)
•Gynecology 11 (19%)
•Pediatric general surgery 6 (10%)
•Orthopedic 3 (5%)
•Urology 2 (3%)
•Neurology 2 (3%)
•Cardiac 1 (2%)
ASA
•I 6 (10%)
•II 13 (22%)
•III 15 (26%)
•IV 25 (42%)
•V 0 (0%)
Most senior anesthetist present
•Consultant (completed specialist training)20 (34%)
•Registrar (postgraduate trainee) 8 (14%)
•Clinical officer (non-physician) 24 (40%)
•None 1 (2%)
•Not documented 6 (10%)
Most senior surgeon present
•Consultant 15 (25%)
•Registrar (postgraduate trainee) 27 (46%)
•Senior house officer (postgraduate trainee) 6 (10%)
•Clinical officer (non-physician) 8 (14%)
•Not documented 3 (5%)
ASA= American Society of Anesthesiologists
1262 E. M. M. A. Lillie et al.
123
In terms of determining the avoidability of deaths, two
independent reviewers were in agreement in 28 cases
(47%). There was discrepancy in 31cases (53%) so the
initial two reviewers plus two secondary reviewers
discussed these folders and reached consensus for every
case. Eighteen cases (30%) were thought to be avoidable,
19 cases (32%) probably avoidable, 14 cases (24%)
unavoidable, and eight cases (14%) unclear. The deaths
by postoperative day are shown in Fig. 2. Thirty-seven
(63%) of the 59 cases available for review were classified
as either avoidable or probably avoidable. Table 2includes
the factors contributing to avoidable deaths, and Table 3
includes de-identified examples of avoidable deaths. Fig. 3
illustrates the contributions of anesthesia, surgery, and
systems of care to the avoidable deaths. Of the avoidable
and probably avoidable deaths, 13 (35%) had one
contributing factor (either surgery or systems issues), 17
(46%) had two factors, and seven (19%) had all three
contributing factors. If the avoidable and probably
avoidable cases are combined (37 cases), this value is not
statistically significantly different from the previously
described avoidable mortality rate in 1987 (avoidable
mortality rate, 0.21% in 1987 vs 0.33% in 2012; Chi square
= 3.65; df = 1; P= 0.06). Nevertheless, this is most likely
an underestimate as an analysis of avoidability was not
available for 55 of our 114 cases (48.2%).
Based on the annual hospital statistics for 2012, the
actual number of surgical cases was 18,010: 12,954 under
general anesthesia, 1,817 under spinal anesthesia, 3,229
under local anesthesia, and ten under sedation.
Nevertheless, theatre registers were available for only
11,688 (64%) of these cases. If we calculate a ‘‘best
possible case’’ mortality rate - i.e., assuming that there
were no deaths in the patients whose details were missing -
114 deaths from 18,010 procedures represents a six-day
perioperative mortality of 0.63%. There is no statistically
significant difference between this ‘‘best possible case’’
estimate and the actual six-day mortality found in the 1987
report (total mortality, 0.76%; Chi square = 1.29; df = 1; P
= 0.26).
Discussion
Our aim was to review the circumstances around every
perioperative death to identify avoidable mortality and any
learning points that could be used to improve the quality of
care in the future. Unfortunately, this was simply not
possible. Nevertheless, based on the review of available
case notes, almost two-thirds of cases were classified as
avoidable (37 cases, 62.7%). Although only 59 case notes
out of the 114 identified perioperative deaths were
available, we found no indicators of systemic bias in the
non-availability of the missing notes. Even if none of the
outstanding 55 missing cases were classified as
unavoidable, this category still contributes to almost a
third of perioperative deaths (37 cases per 114 deaths,
32.5%). Avoidability due to surgical factors was similar to
that noted in 1987. The most common surgical factors were
related to preoperative care, in particular, failure to book
the operating room with the appropriate urgency and poor
preoperative preparation of the patient. Failure to consult
with a senior colleague was common, and in light of the
scaled up anesthesia training since 2012, it seems likely
that more anesthesia input into preoperative optimization
could potentially improve outcomes.
The most common anesthesia factors related to
postoperative care included failure to recognize and treat
patient deterioration and failure of intensive care
management when needed. This contrasted with the data
from 1987 when poor airway management was the most
common anesthesia contributor to death. It is not clear why
this is the case, but we suggest that it may be due to better
availability of oximetry, although this is speculative and
we do not have data to confirm this view. The frequency of
suboptimal care in the postoperative period is a major
concern and should be a particular focus for the anesthesia
training program at the UTH.
11
Anecdotally, there was
little improvement in intensive care resources at UTH from
1987 to 2012, e.g., only ten intensive care beds for over
1,600 hospital beds, lack of basic equipment such as
syringe pumps, an open unit with no dedicated intensive
care physicians, and inadequate nursing education and
staffing. Lack of availability of intensive care beds and
poor postoperative nursing care were the most common
systems factors after lack of blood availability, and it
Fig. 2 Avoidability of perioperative death by postoperative day.
Green refers to unavoidable deaths, orange to probably avoidable
deaths, red to avoidable deaths, and grey when it was unclear whether
the death was avoidable. Day 0 refers to the day of surgery
Perioperative mortality in Zambia 1263
123
Table 2 Factors contributing to avoidable or probably avoidable mortality in 1987 and 2012
1987 2012
Cases where surgery contributed to avoidable
mortality
Not reported 31 cases, 53%*
Delay in surgery 11 (31.4%)* 18 (30.5%)*
•Failure to book operating theatre with appropriate
urgency (12)
•Delay in diagnosis (3)
•Incorrect diagnosis (3)
•Failure to review patient by surgical team
Inadequate preparation for surgery/preoperative care 9 (25%) 10 (16.9%)
•Failure to correct anemia/hypovolemia (4)
•Nonsteroidal given inappropriately (2)
•Failure to investigate appropriately (2)
•Failure to recognize unfit for surgery
•Poor preoperative medical care/failure to refer
Poor intraoperative care - 7 (11.8%)
•Poor judgement - should have chosen more conservative
surgical approach (3)
•Unable to achieve hemostasis (2)
•Perforated bowel during Cesarean delivery
(unrecognized)
•Failure to give uterotonics (2)
Failure to call senior surgeon - 5 (8.4%)
Poor postoperative care of critically ill surgical patient 7 (20%) 4 (6.7%)
Inadequate or no surgical documentation - 3 (5%)
Cases where anesthesia contributed to avoidable
mortality
Not reported 19 cases, 32%
Poor preoperative preparation/care 2 (5.7%) 5 (8.4%)
•Failure to investigate appropriately (3)
•Failure to act on investigations (2)
•Delay in getting to theatre
Poor airway management 5 (14.2%) -
Poor intraoperative care 1 (2.9%) 2 (3.3%)
•Failure to administer uterotonics
•Failure to adequately treat hemorrhage
Poor postoperative care 2 (5.7%) 12 (20.3%)
•Failure to transfer to a high-dependency area (7)
•Failure to resuscitate when deteriorating post-op (3)
•Inappropriate discharge from intensive care
•Inappropriate analgesic regimen
No anesthesia documentation - 3 (5%)
Cases where systems of care contributed to avoidable
mortality
Not reported 18 cases, 30%
Lack of availability of blood 10 (28.5%) 8 (13.6%)
Poor recovery facilities 4 (11.4%) -
Poor communications 2 (5.7%) -
Lack of availability of intensive care bed - 2 (3.3%)
Inadequate nursing staffing/care - 2 (3.3%)
Lack of availability of equipment/equipment failure 2 (5.7%) 2 (3.3%)
•No functional sigmoidoscope
•No apnea monitoring
1264 E. M. M. A. Lillie et al.
123
seems likely that the anesthesia care team will need to
work together with nursing teams and hospital
administration in order to ensure adequate nurse
education, staffing, and intensive care resources to care
for critically ill surgical patients.
The most common systems of care failures were related
to the timely availability of correctly cross-matched blood
products (eight of 37 cases, 22%), a problem often due to
organizational issues and communication breakdown rather
than an absolute scarcity of blood products. The most
common ‘‘administrative’’ factor contributing to mortality
in 1987 was ‘‘insufficient or no blood’’ (ten of 35 cases,
29%). This has also been found to be the most common
systems factor in other developing countries and was
implicated in ten of 30 perioperative deaths in Togo in
2005.
13
Inability to manage severe hemorrhage was the
most common avoidable factor in perioperative deaths in a
study in Zimbabwe in 1995,
14
and inadequate blood bank
services was a key factor in a Nigerian tertiary teaching
centre in 2007.
15
This was the only ‘‘administrative’’ cause
of avoidable death in a study in Malawi in 2000, although
that study described the situation at that time as having no
blood bank and all blood was donated by relatives.
16
This
is very different from the situation in Zambia where the
Lusaka-based Zambia National Blood Transfusion Service
is 100% dependent on volunteer donations. Our data and
the existing literature urgently warrant further collaborative
research and quality improvement by anesthesia, surgical
specialties, and transfusion medicine on how best to
manage, process, and distribute this scarce resource in a
low-income context.
Categorization of cause of death into surgical,
anesthesia, or systems issues is subjective. Nevertheless,
consensus was eventually achieved in all cases. The key
point here is the fact that most avoidable deaths involved a
combination of factors, suggesting that improved
interprofessional and interspecialty collaboration (e.g.,
joint mortality and morbidity meetings, a combined audit,
and jointly developed clinical and logistic protocols) is
likely necessary to achieve a significant reduction in
avoidable mortality. The high total perioperative mortality
Table 2 continued
1987 2012
Operating theatre not available in timely manner - 1 (1.7%)
Lack of availability of investigations
(ultrasound scan)
- 1 (1.7%)
Wrong blood given - 1 (1.7%)
Oxygen failure in theatre - 1 (1.7%)
* Percentages do not add up to 100% as many cases had multiple contributing causes, including multiple subcategories within surgery,
anesthesia, and systems of care
Table 3 De-identified examples of avoidable mortality
Avoidable mortality attributed to surgery (and systems of care).
A young male (ASA III), admitted with an unrelated problem, died after a suspected gastrointestinal bleed whilst an inpatient. Surgery had
reviewed the patient and noted the hemoglobin to be 28 gL
-1
, but no effort was made to investigate or treat the cause of the bleed.
Avoidable mortality attributed to anesthesia (and systems of care).
An ASA I female in her 20 s who had a Cesarean delivery died on the ward of respiratory failure. Her trachea was extubated at the end of the
procedure despite low intraoperative oxygen saturations and having been given aminophylline. Her trachea was re-intubated in extremis in
recovery, but as no intensive care beds were available, her trachea was extubated and she was sent to the ward.
Avoidable mortality attributed to systems of care.
An ASA II female in her 30 s who had a Cesarean delivery followed by hemorrhage died of pulmonary edema and shock. There had been more
than a three-hour delay in getting blood when her hemoglobin was 35 gL
-1
; incompatible blood was delivered.
ASA = American Society of Anesthesiologists
Fig. 3 The contributions of surgery, anesthesia, and administrative
issues to avoidable mortality. Red refers to avoidable deaths and
orange to probably avoidable deaths
Perioperative mortality in Zambia 1265
123
and avoidable mortality are significant concerns and, in
light of other data showing underresourced anesthesia
services across Zambia,
10
they signify a mandate for
greater investment in perioperative care.
Our secondary objective was to identify the six-day
perioperative mortality rate. Disappointingly, deficiencies in
the completeness of the data available for review precluded
an accurate estimate of perioperative mortality at the UTH in
Zambia. The failure to identify many perioperative deaths is
likely due to our inability to compare the mortuary register
with the 5,636 cases missing from the theatre registers. As
we are relatively confident in our denominator, it is almost
certain that our ‘‘best possible case’’ mortality rate is an
underestimate. Therefore, despite a global trend towards
reducing perioperative mortality, it is extremely unlikely
that there was a decrease in perioperative mortality at the
UTH since the 1980s - in fact, it is possible that it has actually
increased. It is difficult to determine from our data why this
would be the case, but we point out that, as one of the United
Nation’s designated Least Developed Countries, Zambia
lacks the infrastructure and strong healthcare systems
necessary for safe timely surgical care. Bainbridge noted
key factors that may have led to improvements in
perioperative mortality since the 1970s, including
advancements in training in anesthesia and surgery,
improved selection of patients, advances in aseptic
technique and sterilization, increased use of antibiotics,
improved postoperative care, improved monitoring, fluid
and blood administration, and improvements in team work.
1
Anecdotally, there has been little improvement in these
factors at UTH since 1987, and these would be ideal areas to
focus attention for the future.
In common with historical data from the UTH but in
contrast with data from the developed world,
17
perioperative deaths were most common in young
patients (younger than 40 yr),
9
which also has significant
economic implications for the families of the deceased.
Improved audits and reporting appear to be essential first
steps in improving perioperative care; otherwise, it is
difficult to advocate to governments and funding
organizations for the necessary investment to improve
outcomes. We would suggest that the World Health
Organization include perioperative statistics in its Global
Health Observatory data bank. This would encourage
institutions to upgrade their recordkeeping and provide
ongoing robust data for measurement.
Although any audit of perioperative mortality must be
retrospective, we were further limited by having to identify
the deaths retrospectively, whereas the deaths in the
previous study at the UTH were identified prospectively.
This may have contributed to the significant amount of
missing data. Ideally, the perioperative mortality rate
should include all deaths up to 30 days postoperatively in
order to capture important late deaths; however, in our
study, we chose six-day mortality to allow a comparison
with historical data. Future research should endeavour to
determine the 30-day mortality rate, or at least all deaths
before discharge, as post-discharge follow-up is often
unfeasible in low- and middle-income countries.
In conclusion, we were unable to show a decrease in the
total perioperative mortality rate at the UTH during 1987 to
2012. This was due in part to an inability to review over
half of the files of perioperative deaths in 2012.
Nevertheless, considering even a ‘‘best case scenario’’, it
is extremely unlikely that mortality has improved over this
period of time. In the files reviewed, the factors leading to
avoidable deaths were delays in surgery, lack of
availability of blood products, and poor postoperative
care. We recommend a multiprofessional approach to the
review of morbidity and mortality and a collaborative
approach to quality improvement and patient safety. These
initiatives are likely necessary to reduce avoidable
perioperative deaths.
Acknowledgements We sincerely thank Dr. L. Kasonka, Managing
Director of the University Teaching Hospital and Dr. J. Kasonde,
Minister of Health, for their permission to publish this data. We are
also grateful to Dr. I. Wilson, Consultant Anaesthetist Royal Devon
and Exeter NHS Foundation Trust, Lancet Commissioner on Global
Surgery, for his advice in preparation of the study protocol; Yona
Mofu, Research Assistant, University Teaching Hospital, Lusaka, for
data collection; Colin Dawes for his assistance with the analysis; and
Dr. Feruza Ismailova for her advice.
Conflicts of interest None declared.
Funding This work was supported by a grant from the International
Relations Committee of the Association of Anaesthetists of Great
Britain and Ireland and funding from a Tropical Health and Education
Trust Health Partnership Scheme Grant that supported visiting
lectureships at University Teaching Hospital for EMMAL, EAO,
and LB.
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