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Management of Severe Hypokalemia in Hospitalized Patients
A Study of Quality of Care Based on Computerized Databases
Ora Paltiel, MD, MSc;
Edouard Salakhov, MD, MPH;
Ilana Ronen, MPH;
David Berg, BSc;
Abraham Israeli, MD, MPH, MSc
Arch Intern Med. 2001;161:1089-1095.
ABSTRACT
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Background While administrative databases are used to assess general indicators
of quality of care, a detailed audit of the process of clinical care usually
requires review of hospital medical records.
Objective To evaluate the feasibility of assessing the management of severe hypokalemia
using computerized administrative and laboratory databases.
Methods The study included all patients hospitalized in 1997 who experienced
serum potassium levels of less than 3.0 mmol/L at Hadassah University Hospital,
Jerusalem, Israel, a tertiary care center. Using the computerized databases,
we measured the following: (1) whether a subsequent serum potassium test was
performed, (2) time to the subsequent test and to normalization of the serum
potassium level, (3) achievement of normokalemia, and (4) in-hospital mortality.
In a random subsample of 100 patients, these measures were compared with the
blinded assessment of the quality of medical management of hypokalemia, as
determined from medical records, using predetermined criteria for adequate
management.
Results The computerized databases revealed that severe hypokalemia occurred
in 866 patients (2.6% of the yearly hospitalizations): 55 patients (6.4%)
had no subsequent serum potassium levels measured, and 260 (30.0%) were discharged
from the hospital with a subnormal potassium level. The mean time to a subsequent
test was 20 hours, and to normokalemia, 50 hours; both intervals varied by
department. In-hospital mortality was 20.4%, or 10-fold that of the entire
hospitalized population. A review of hospital medical records revealed inadequate
clinical management of hypokalemia in 24%, which was associated with nonperformance
of a subsequent test (likelihood ratio, 8.4), failure to normalize the serum
potassium level (likelihood ratio, 4.2), discharge from the hospital with
a subnormal potassium level (likelihood ratio, 2.1), and in-hospital death
(likelihood ratio, 2.5), all of which could be determined by the computerized
databases.
Conclusions The computerized laboratory database is useful in ascertaining the prevalence
of severe hypokalemia and in assessing shortcomings in its management. Databases
can be used to derive valid and efficient measures of the quality of the clinical
management of electrolyte disorders.
INTRODUCTION
EVALUATION of the quality of care is increasingly recognized as an essential
aspect of medical practice. Methods to evaluate medical care range from peer
review based on medical record audit to quality assessment based on computerized
databases. The former, while having the potential to be highly detailed and
specific, is costly in terms of time and other expenses and potentially includes
biases in judgment. The latter may be hampered by poor specificity and a limited
ability to adjust for case mix. All clinical audits or quality assessment
measures are dependent on the quality of data entry. Assessments based on
data that are entered automatically, such as laboratory databases, should
theoretically contain data of higher reliability than other sources. Until
now, computerized audits have mainly been used to assess general indicators
of quality, such as postoperative death or early readmission, but have rarely
been used for the detailed assessment of the management of specific clinical
conditions.
Electrolyte abnormalities are common in hospitalized patients. They
frequently occur as iatrogenic complications of medications and medical procedures.
Recent studies1-4
from Europe and North America have shown that the management of these common
abnormalities is frequently suboptimal. Hypokalemia
is defined as a serum potassium level of less than 3.5 mmol/L. It can be life
threatening when severe, due to its association with cardiac arrhythmias and
sudden death.5 Patients with cardiac disease
are at especially high risk of hypokalemia-induced arrhythmias. While muscle
weakness and other symptoms may be experienced by patients with hypokalemia,6 most patients are asymptomatic and, therefore, laboratory
monitoring is essential. Corrective action is simple, consisting of potassium
supplementation or initiation of potassium-sparing medications. There appears
to be agreement that immediate potassium supplementation should be given at
serum levels of less than 3.0 mmol/L,7 because
of the increased risk of arrhythmias below this level.8
Given its clinical significance, ubiquity, and relatively consistent
mode of treatment, the management of hypokalemia is a relevant subject for
clinical audit. We decided to perform an evaluation of the quality of management
of severe hypokalemia (serum potassium level <3 mmol/L) in hospitalized
patients using computerized databases available in our center. Our purpose
was to assess the feasibility of using computerized laboratory data to evaluate
the quality of medical care. The primary hypothesis of this study was that
the pattern of serum potassium test results in patients with an initial level
of less than 3.0 mmol/L, as retrieved from the computerized laboratory database,
could be used as an indicator of the adequacy of the actual clinical management
of severe hypokalemia. Our specific objectives were as follows: (1) to use
the hospital's computerized databases in order to describe the pattern of
potassium test results in terms of performance of a subsequent test, achievement
of normokalemia, and time to a subsequent test and to normokalemia; (2) to
estimate in-hospital mortality for the population with hypokalemia; and (3)
to evaluate the physician's management of hypokalemia using data from the
medical record in a subset of patients, and to assess whether there is an
association between the physician's management based on medical record data
and the pattern of potassium test results (as previously noted) retrieved
from computerized databases.
PATIENTS AND METHODS
PATIENTS
Using the laboratory database, we identified all patients hospitalized
in 1997 in Hadassah Ein Karem (a 650-bed teaching hospital in Jerusalem, Israel,
providing tertiary care services) who experienced at least 1 event of hypokalemia
with a serum potassium level of less than 3.0 mmol/L. This is the critical
level below which the laboratory notifies the physician or ward by telephone.
Only the first episode of severe hypokalemia per hospitalization was considered;
however, some patients experienced more than 1 such hospitalization during
the year. In our hospital, most blood tests are performed by the physicians
themselves.
DATA SOURCES
From the laboratory database, we extracted data on patient identification
number and date, time, and value of the first test showing a serum potassium
level of less than 3.0 mmol/L. For each case identified, all subsequent potassium
test results for that individual were extracted. From the administrative database,
we extracted data on identification, sex, year of birth, date and department
of admission and discharge, status at discharge from the hospital (dead or
alive), and discharge diagnoses by ICD-9. (Medications
and prescriptions are not available on the computerized databases.) Normokalemia was defined as a serum potassium test result
between 3.5 and 5.0 mmol/L, corresponding to the laboratory standard.
We chose a random sample of 100 medical records from the population
who experienced hypokalemia using random numbers derived from Statistical
Product and Service Solutions, version 6.12 (SPSS Inc, Chicago, Ill). The
random sample was chosen to maintain a proportion of 20% who had more than
1 hospitalization with severe hypokalemia and 80% who experienced only 1 such
hospitalization. For this sample, we analyzed the last admissions in 1997
in which severe hypokalemia occurred. These medical records were reviewed
by a physician (E.S.) and nurse who were blinded as to the pattern of potassium
test results. Medical records were reviewed for the presence of drugs that
could be responsible for hypokalemia9; occurrence
of diarrhea and/or vomiting; and indicators of the medical management of hypokalemia,
including mention of hypokalemia in the physician's notes and evidence of
potassium supplementation in the physician's orders and in the medication
records. The medical record review was considered the gold standard for assessing
the adequacy of the clinical management of severe hypokalemia. The criteria
for "appropriate management" included evidence for initiation or increase
of potassium supplementation or initiation of potassium-sparing agents on
the day of or day after the first episode of severe hypokalemia. Discontinuation
of medication causing hypokalemia was not considered an adequate measure if
not accompanied by potassium supplementation. We compared the results of the
computerized databases with the results of the medical record review using
the previously mentioned criteria. The probability of having a poorer outcome
on computer-derived analysis (no subsequent test, failure to normalize the
serum potassium level, discharge from the hospital with an abnormal serum
potassium level, and in-hospital death) in those with inadequate management
as per medical record review yielded estimates of the sensitivity of the computerized
audit. The probability of having these poor outcomes in patients with adequate
management of hypokalemia yielded estimates of the false-positive rate or
1 - specificity. Likelihood ratios were calculated according to the
following formula: sensitivity/(1 - specificity).
STATISTICAL METHODS
Statistical analyses were performed using Statistical Product and Service
Solutions software, version 6.12 (SPSS Inc) and the PEPI program.10 Dependent variables were categorical (eg, performance
of a subsequent test, achievement of a normal serum potassium test result,
a normal or abnormal last recorded level, and vital status at discharge from
the hospital) or time continuous (eg, to performance of a subsequent test
or to normalization of the serum potassium level). For most analyses, the
unit of analysis was individuals, and we analyzed their last admission in
1997 in which hypokalemia was documented (N = 866). When assessing length
of stay and the distribution of low serum potassium test results, we analyzed
all hospitalizations in 1997 in which hypokalemia occurred (N = 975). The  2 test was used in univariate analysis to test associations between
the dependent variables and sociodemographic and other descriptive variables.
The t test was used for comparison of means. To test
the representativeness of the sample chosen for medical record review compared
with the total population, we used the z test and
the 2 test for goodness of fit.
Multiple logistic regression analysis was used to assess the independent
contribution of predictor variables (age, sex, admission department, discharge
from the hospital, diagnosis, and transfer between departments) to categorical
outcomes (achievement of a normal potassium test result and vital status at
discharge from the hospital). Variables associated with these outcomes in
univariate analysis were entered into regression models by forward stepwise
selection, with an entry criterion of P .10. In
all statistical analyses, P.05 (2-tailed) was
considered statistically significant.
RESULTS
RESULTS OBTAINED FROM THE COMPUTERIZED DATABASES
In 1997, of 37 458 admissions, there were 975 (2.6%) in which severe
hypokalemia (a potassium level of <3.0 mmol/L) was recorded at least once.
This represents 866 patients, of which 780 (90%) experienced severe hypokalemia
on 1 admission during the year and 86 (10%) had 2 or more hospitalizations
with an episode of severe hypokalemia. Of the 975 episodes, 7 (0.7%) had a
serum potassium level of less than 2.0 mmol/L, 83 (8.5%) had a level of 2.0
to 2.4 mmol/L, and 885 (90.8%) had a level of 2.5 to 2.9 mmol/L. Among all
975 admissions, 274 (28.1%) were admitted with a serum potassium level of
less than 3.0 mmol/L, and 701 (71.9%) developed this condition during their
hospitalization. In only 17 cases (1.7%) was the diagnostic code for hypokalemia
mentioned in the discharge summary or administrative database record.
Severe hypokalemia occurred at all ages and in all departments. Table 1 summarizes descriptive characteristics
of affected patients. Women represented 53.5% of the hypokalemic population.
The mean age was significantly older for women (P
= .001) compared with men, and the sex distribution significantly differed
by department (P<.001, with or without the exclusion
of obstetrics and gynecology). The mean length of stay for the population
with severe hypokalemia was 23.7 days (SD, 29.6 days); the median was 13 days.
This is compared with a mean length of stay for the entire hospital population
in 1997 of 6 days (SD, 2.0 days) (P<.001). Patients
with more than 1 hospitalization in which severe hypokalemia occurred were
more likely to be admitted to the hematology, oncology, and bone marrow transplantation
or pediatrics department compared with other wards. Patients with successive
admissions with severe hypokalemia were more likely to have extreme low levels
(<2.5 mmol/L) of serum potassium than those with only 1 hospitalization
(21% vs 7%; P = .001), and to be admitted with hypokalemia
rather than developing it in the hospital (38% vs 26%; P = .02).
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Table 1. Comparison of Characteristics in the Entire Population of
Patients Who Experienced Hypokalemia and a Subsample Randomly Selected for
Medical Record Review*
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The management or response to hypokalemia was assessed using data from
the last hospitalization in which severe hypokalemia occurred during the study
period. The response to hypokalemia in terms of performance of subsequent
tests, achievement of normokalemia, and potassium level at discharge from
the hospital as determined by the laboratory computer database is shown in Figure 1. Nonperformance of a subsequent
test was rare (6.4% of the patients), but discharge from the hospital with
a subnormal potassium level (<3.5 mmol/L) occurred in 30% of the patients
because of failure to correct hypokalemia or recurrent decreases in the serum
potassium level after initial correction. Nonperformance of a subsequent test
was not associated with demographic characteristics of the patients, the timing
of development of hypokalemia (on admission or during the hospitalization),
or the initial potassium level. There was a borderline association with department
of admission (P = .05), with the rate of performance
being highest in the intensive care unit and in the internal medicine and
pediatrics departments and lowest in the obstetrics and gynecology wards.
No death occurred on the day that severe hypokalemia was initially recorded
(day 0) such that in every case an opportunity existed to remeasure the potassium
level after an extreme low value.
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Test ordering and results for 866 patients, as assessed by a computerized
laboratory database. Last admissions were analyzed, and all percentages are
based on a denominator of 866.
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The achievement of normokalemia was highest in the intensive care units
(95%) and in the pediatrics department (90.7%) and lowest in the obstetrics
and gynecology departments (69%). Controlling for admission department and
transfer between departments, the only variable found to be associated with
achievement of normokalemia on logistic regression analysis was time to performance
of the first subsequent test after the onset of severe hypokalemia (P = .05).
The median time to performance of the first subsequent potassium test
was 13 hours (mean, 20 hours). These times were shorter in children 15 years
of age and younger (mean, 17 hours; median, 9 hours) compared with adults.
The more severe the hypokalemia, the shorter the time until performance of
a subsequent test. For example, for a serum potassium level of 2.4 mmol/L
or less, the mean and median times were 14 and 9 hours, respectively, as opposed
to 20 and 14 hours, respectively, for serum potassium levels of 2.5 to 2.9
mmol/L. The shortest time from initial severe hypokalemia to performance of
a subsequent test was in the intensive care units (median, 6 hours) vs the
hematology, oncology, and bone marrow transplantation units, where the median
was 22 hours. The time until repetition of the test was shorter in patients
who were admitted with severe hypokalemia (mean, 15 hours; median, 8 hours)
compared with those who developed this condition in the hospital (mean, 22
hours; median, 17 hours) (P<.001). The mean and
median times until achievement of a normal serum potassium test result were
50 and 25 hours, respectively.
Analysis of vital status at discharge from the hospital among the patient
population with severe hypokalemia attests to the fact that this is a population
at high risk of in-hospital death. The crude mortality among 866 patients,
analyzing their last admissions, was 20.4% compared with 1.89% for all 37 458
admissions in 1997. Factors associated with mortality on univariate analysis
were department of admission (P<.001); length
of stay (P = .005); initial serum potassium level
(P = .01), with 31% of those with an initial serum
potassium level of 2.4 mmol/L or less having died in the hospital compared
with 19.4% of those with initial levels of 2.5 to 2.9 mmol/L; and achievement
of normokalemia (P = .03). There was no association
with age, sex, or time of onset of hypokalemia. In a multivariate model (Table 2), admission department, initial
serum potassium level, number of admissions in which severe hypokalemia was
documented, and length of stay remained significantly associated with vital
status at discharge from the hospital, while achievement of normokalemia was
no longer associated with mortality.
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Table 2. Multivariate Logistic Model of Factors Associated With In-Hospital
Death in the Population With a Serum Potassium Level of Less Than 3.0 mmol/L*
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RESULTS OBTAINED FROM MEDICAL RECORD REVIEW
The random sample of 100 patients whose medical records were reviewed
was similar to the total population with hypokalemia for sex; age distribution;
department of admission and discharge; transfer within the hospital; median
length of stay; ICD-9, diagnoses of diabetes mellitus,
ischemic heart disease, leukemia, and kidney disorders; and status at discharge
from the hospital (Table 1). They
were also similar to the entire population for timing of development of severe
hypokalemia (on admission or during the hospitalization), initial serum potassium
level, and achievement of normokalemia. In the sample, 11 (11%) patients did
not have a subsequent test performed after an initial serum potassium level
of less than 3.0 mmol/L, as opposed to 55 (6.4%) patients in the entire population
(P = .06). Furthermore, in the sample, 38 (38%) of
the patients had a last recorded serum potassium level that was not normal,
as opposed to 260 (30%) of the entire population (P
= .08).
In 75 (75%) of the cases, 1 or more drugs that could be causally associated
with hypokalemia were identified. These included furosemide (23%); other diuretics
(13%); corticosteroids (31%); amphotericin B (5%); and other drugs, including
antibiotics, laxatives, and insulin. (These categories are not mutually exclusive.)
Vomiting and diarrhea were noted in 1 and 5 patients, respectively. Written
mention of the serum potassium test result was found in 38 cases in the physician's
notes. Physician's orders indicating potassium supplementation were found
in 24% of the cases, and medication records in which potassium supplementation
was recorded appeared in 76 medical records. In 76% of the cases, the medical
management was considered appropriate according to previously mentioned criteria,
and in 24% it was not. Potassium was administered intravenously in 57 cases
and orally in 50 (not mutually exclusive).
Table 3 shows the association
of outcomes as determined by the computerized audit with appropriateness of
response to hypokalemia as determined by the medical record audit. As shown,
these indicators are highly associated. Likelihood ratios for all 4 computer-derived
measures were greater than 1. Specifically, the likelihood that a patient
with no subsequent test performed would have inadequate management of his
or her hypokalemia according to the medical record was 8.4 times higher than
the likelihood of a similar patient who received appropriate management. Furthermore,
there are strong associations between appropriate management as determined
by the medical record and achievement of normokalemia and discharge from the
hospital with hypokalemia, and there are associations between appropriateness
of management and in-hospital mortality.
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Table 3. Clinical Management of Severe Hypokalemia as Determined by
the Medical Record Compared With Outcomes Derived From the Laboratory Computer
System in a Random Sample of 100 Patients
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COMMENT
In our study, severe hypokalemia occurred in 2.6% of the hospitalized
patients as assessed by the computerized laboratory database. Most cases were
hospital acquired (72%) and associated with potassium-depleting medications
(75%). Patients who experienced severe hypokalemia had a long length of stay
and a high risk of in-hospital death. The computerized record was able to
provide estimates of the prevalence of hypokalemia in this hospitalized population
and clues to its management. The medical record review uncovered deficiencies
in the management of hypokalemia, which were predictable by the pattern of
potassium test results obtained via audit of the laboratory computer database.
Although the sensitivities of the computerized measures were not high, the
likelihood ratios point to the ability of the computer-derived measures to
identify patients with suboptimal clinical management of hypokalemia.
Severe hypokalemia (a potassium level of <3.0 mmol/L) has been previously
reported in 5.2%11 and 3.5%12
of hospitalized patients. In a Scottish series,11
56% of the cases of hypokalemia could be attributed to medication, especially
corticosteroids, insulin, and antibiotics (as opposed to 75% in ours), and
mortality varied between 20% and 34%, depending on the severity of hypokalemia.
This mortality rate was remarkably similar to that in our series, in which
31.9% of those whose serum potassium level was less than 2.4 mmol/L died,
compared with 19.4% of those with a minimal serum potassium level of 2.5 to
2.9 mmol/L. Even at less extreme levels of hypokalemia, a dose response has
been observed between preoperative potassium levels and perioperative deaths
in patients undergoing cardiac surgery.13
Despite the fact that it is a common condition that frequently develops
in the hospital (50% in an Austrian series12
and 72% in ours), few researchers have studied the management of hypokalemia
in hospitalized patients. One reason for this lack may be that the data required
for this are difficult to obtain from medical records—they are often
missing, incomplete, or illegible. Most publications dealing with this subject
offer management guidelines, which are mainly empirical and rarely evidence-based.5-7,14 Despite
the generally recognized potential of adverse events associated with hypokalemia,
in our hospital we found that 24% of patients received inadequate treatment,
ranging from no treatment at all to continuation of a previous low level of
serum potassium supplementation in the face of severe hypokalemia (as assessed
by medical record review). In 6.4% of the patients, no further testing was
carried out following an initial result of severe hypokalemia, and in 30%
of the patients who experienced severe hypokalemia, the last potassium level
before discharge from the hospital was less than 3.5 mmol/L (as assessed by
the computerized databases).
Our findings appear to be similar to those of other studies assessing
management of electrolyte disorders in different settings. Tate and colleagues15 found that the baseline management of disorders of
sodium, potassium, and glucose as assessed by medical record review was inappropriate
in 31.9% of cases. Two recent audits of the management of hypernatremia, one
in a general hospital3 and the other in an
intensive care unit,4 showed similar shortcomings.
Polderman and colleagues4 (in a study in which
hypernatremic cases were identified from the computer and the assessment of
quality of care was by medical record review) found that inadequate steps
were taken to prevent this abnormality even though there were early signs
of its development. Correction was faster when patients were admitted with
the condition, compared with those who developed it during their hospitalization.
These findings are similar to ours, and indicate that more attention is paid
to admission laboratory results than to changes and complications that occur
during the hospitalization, even though hospital-acquired abnormalities are
frequent. Acker and colleagues1 performed an
audit of the management of hyperkalemia by medical record review and found,
as we did, that treatment times and adequacy of treatment were better in the
intensive care units than in the other wards. Moreover, their findings resembled
ours in that they found that the more severe the hyperkalemia, the shorter
the time to treatment. Disappointingly, an intervention designed by these
researchers to improve the management of hyperkalemia by providing written
guidelines to the ward had no effect.1
Few researchers have examined the time until correction of the abnormal
laboratory results. Kuperman and colleagues16
reported a study in which critical values were obtained from the computer
and assessment of outcomes was by medical record review. They found that the
median time to resolution for various laboratory abnormalities was 14.3 hours,
but the specific times for correction of hypokalemia were not reported.
In our study, computer-derived indicators, such as failure to perform
a subsequent test and failure to achieve a normal serum potassium value, were
highly associated with inadequate physician response and treatment, as derived
from the medical record. Thus, they could easily serve as indicators for shortcomings
in the quality of care. Computerized databases are increasingly being used
to evaluate the quality of medical care. Routinely collected data, such as
those included in the National Health Service minimum data set, can be used
for clinical audit of process and outcome and for case finding.17
On the other hand, inaccuracies and artifacts (such as "code creep") limit
the ability to make valid assessments of quality and especially to compare
treatment standards across hospitals.18 Computerized
assessments, while sensitive to the occurrence of each case of hypokalemia,
are not sensitive to the nuances of clinical management, such as decisions
to take a less aggressive approach in terminally ill patients. As such, computerized
audits may underestimate the actual quality of care delivered. These factors,
however, are probably less relevant in the case of electrolyte disturbances,
since presumably if the test was performed, there is still interest in learning
the result and correcting abnormalities. Although our study showed that in-hospital
death was associated with inadequate management of hypokalemia on medical
record review, we did not demonstrate that lack of correction of hypokalemia
was associated with mortality.
Pine and colleagues19 have recently shown
that the addition of laboratory data, including serum potassium test results,
to administrative data improves the ability to predict in-hospital mortality
and between-hospital comparisons. When laboratory values were combined with
secondary diagnoses available on the administrative data set, they improved
the prediction of mortality for 3 primary diagnoses (acute myocardial infarction,
congestive heart failure, and pneumonia) such that additional clinical data
obtained by data extraction from medical records contributed little to predictive
power. Furthermore, Mozes and colleagues20
have shown that low potassium test results combined with age are powerful
predictors of length of stay. The use of laboratory data to augment predictive
ability can only be efficient when the data are computerized—examining
medical records to abstract laboratory data is fraught with errors, omissions,
and prohibitive costs.21
There are several advantages of using computerized laboratory data in
a clinical audit. First, data entry is automated with no delay between obtaining
the results and reporting. Second, data accuracy (reliability and validity)
is likely to be high since there are fewer coding errors (because of automation)
and because the built-in quality assurance mechanisms that are in place in
the laboratory, such as frequent recalibration, reperformance of tests with
abnormal results, and participation in external quality assurance programs
in which blind samples are tested, tend to minimize problems of validity.
Third, the computerized database provides a complete data set for case finding.
As Iezzoni18(p672) noted, "by knowing actual
hematocrits, we could decide ourselves if anemia is present" and not have
to rely on diagnostic codes. In our case, without the use of the laboratory
database, an audit on the management of hypokalemia would have been impossible,
since only 1.7% of cases ascertained through the database received a diagnostic
code for hypokalemia in the administrative database. Unlike clinical conditions
such as congestive heart failure or habits such as tobacco use, which are
frequently missing from administrative and insurance claims databases,22-23 all measured laboratory results are
included in the laboratory database. Finally, as our audit has shown, the
pattern of the test results themselves, as summarized from the computerized
database, highly reflects the clinical management of the electrolyte disorders
(as obtained from the medical record). Our results suggest that a computerized
audit for the management of electrolyte disorders could be incorporated into
the routine quality assurance procedures in the hospital. Since the time available
to perform assessments of clinical performance is a major constraint,24 an audit technique that streamlines the ability to
collect and analyze available data is sorely needed.
Laboratory alerting systems that monitor decreasing potassium levels
and other laboratory abnormalities have been found to improve the quality
of care15 and to decrease the rate of adverse
drug reactions25 and the length of stay.15 Further studies to investigate the impact of such
laboratory audit systems on the management of hypokalemia and other electrolyte
disorders in hospitalized patients should be undertaken.
AUTHOR INFORMATION
Accepted for publication November 21, 2000.
We thank Michael Mayer, MD, for his input and cooperation; and the manuscript's
reviewers for their constructive comments.
Corresponding author: Ora Paltiel, MD, MSc, Department of Social
Medicine, PO Box 12000, Hadassah Medical Center, Jerusalem 91120, Israel
(e-mail: ora{at}vms.huji.ac.il).
From the Departments of Social Medicine (Dr Paltiel and Ms Ronen),
Information Systems (Mr Berg), and Administration (Dr Israeli), Hadassah Medical
Center/Hadassah-Hebrew University and Braun School of Public Health (Dr Israeli),
Jerusalem, Israel.
REFERENCES
| |
1. Acker C, Johnson JP, Palevsky PM, Greenberg A. Hyperkalemia in hospitalized patients. Arch Intern Med. 1998;158:917-924.
FREE FULL TEXT
2. Lane N, Allen K. Hyponatremia after orthopaedic surgery [editorial]. BMJ. 1999;318:1363-1364.
FREE FULL TEXT
3. Palevsky PM, Bhagrath R, Greenberg A. Hypernatremia in hospitalized patients. Ann Intern Med. 1996;124:197-203.
FREE FULL TEXT
4. Polderman KH, Shreuder WO, Strade van Shyndel RJM, Thys LG. Hypernatremia in the intensive care unit: an indicator of quality of
care? Crit Care Med. 1999;27:1105-1108.
FULL TEXT
|
ISI
| PUBMED
5. Gennari FJ. Hypokalemia. N Engl J Med. 1998;339:451-458.
FREE FULL TEXT
6. Newmark SR, Dluhy RG. Hyperkalemia and hypokalemia. JAMA. 1975;231:631-633.
FULL TEXT
|
ISI
| PUBMED
7. Saggar-Malik AK, Cappuccio FP. Potassium supplements and potassium-sparing diuretics: a review and
guide to appropriate use. Drugs. 1993;46:986-1008.
ISI
| PUBMED
8. Holland OB, Nixon JV, Kuhnert L. Diuretic-induced ventricular ectopy. Am J Med. 1981;70:762-768.
FULL TEXT
|
ISI
| PUBMED
9. Speicher CE, Smith JW. Choosing Effective Laboratory Tests. London, England: WB Saunders Co; 1983:339-340.
10. Abramson JH, Gahlinger PM. Statistical Programs for Epidemiologists: PEPI: Version
3.0. Stone Mountain, Ga: SDI; 1995.
11. Paice BJ, Paterson KR, Onyanga-Omara F, Donnelly T, Gray JMB, Lawson DH. Record linkage study of hypokalaemia in hospitalized patients. Postgrad Med J. 1986;62:187-191.
ABSTRACT
12. Janko O, Seier J, Zazgornik J. Hypokalemia: incidence and severity in a general hospital [in German]. Wien Med Wochenschr. 1992;142:78-81.
ISI
| PUBMED
13. Wahr JA, Parks R, Boisvert D, et al for the Multicenter Study of Perioperative Ischemia Research Group. Perioperative serum potassium levels and perioperative outcomes in
cardiac surgery patients. JAMA. 1999;281:2203-2210.
FREE FULL TEXT
14. Freedman BI, Burkart JM. Hypokalemia. Crit Care Clin. 1991;7:143-153.
ISI
| PUBMED
15. Tate KE, Gardner RM, Weaver LK. A computer laboratory alerting system. MD Comput. 1990;7:296-301.
PUBMED
16. Kuperman GJ, Boyle D, Jah A, et al. How promptly are inpatients treated for critical laboratory results. J Am Med Inform Assoc. 1998;5:112-119.
FREE FULL TEXT
17. McKee M. Routine data: a resource for clinical audit? Qual Health Care. 1993;2:104-111.
PUBMED
18. Iezzoni LI. Assessing quality using administrative data. Ann Intern Med. 1997;127:666-674.
FREE FULL TEXT
19. Pine M, Jones B, Lou YB. Laboratory values improve predictions of hospital mortality. Int J Qual Health Care. 1998;10:491-501.
FREE FULL TEXT
20. Mozes B, Easterling MJ, Sheiner LB, et al. Case mix adjustment using objective measures of severity: the case
for laboratory data. Health Serv Res. 1994;28:689-712.
ISI
| PUBMED
21. McDonald CJ, Overhage JM, Paul P, Takesue BY, Dwyer DM. A framework for capturing clinical data sets from computerized sources. Ann Intern Med. 1997;127:675-682.
FREE FULL TEXT
22. Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaaier LH, Mark DB. Discordance of databases designed for claims payment versus clinical
information systems. Ann Intern Med. 1993;119:844-850.
FREE FULL TEXT
23. Dans PE. Looking for answers in all the wrong places [editorial]. Ann Intern Med. 1993;119:855-856.
FREE FULL TEXT
24. Oxman AS, Davis DA, Feightner JW, et al. Evidence-based care, 3: measuring performance: how are we managing
this problem? CMAJ. 1994;150:1575-1579.
ABSTRACT
25. Rind DM, Safran C, Phillips RS, et al. Effect of computer-based alerts on the treatment and outcomes of hospitalized
patients. Arch Intern Med. 1994;154:1511-1517.
ABSTRACT
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