Northwestern University
Using CDSS for Appropriate Dosing of Antibiotics
with Reduced Renal Function
MED INF 406 – Decision Support Systems and Healthcare
Fall 2010
Instructor: Dr. Gerasimos Petratos
KwaviAgbeyegbe, Michael Peterson & Sam Ruffing
Table of Contents
INTRODUCTION...................................................................................................................................................................................... 3
PROBLEM DEFINITION .......................................................................................................................................................................... 3
RENAL FUNCTION ...................................................................................................................................................................................................... 3
ADVERSE DRUG EVENTS (ADES) ......................................................................................................................................................... 4
ANTIBIOTIC DOSING MODEL ............................................................................................................................................................... 4
SYSTEM .................................................................................................................................................................................................... 5
COMPONENTS AND ARCHITECTURE .......................................................................................................................................................................... 5
SYSTEM INPUTS ......................................................................................................................................................................................................... 6
SYSTEM OUTPUTS ..................................................................................................................................................................................................... 7
EVALUATION OF CDSS .......................................................................................................................................................................... 7
VERIFICATION AND VALIDATION ............................................................................................................................................................................... 7
VERIFICATION (ARE WE BUILDING THE PRODUCT RIGHT?)...................................................................................................................................... 7
VALIDATION (ARE WE BUILDING THE RIGHT PRODUCT?) ........................................................................................................................................ 7
SYSTEM LIMITATIONS ........................................................................................................................................................................... 8
CLINICAL EFFICACY ................................................................................................................................................................................ 8
LIMITATIONS .......................................................................................................................................................................................... 9
FUTURE EXTENSIONS .......................................................................................................................................................................... 10
CONCLUSION ........................................................................................................................................................................................ 10
WORKS CITED.................................................................................................................................................................................... 11
APPENDIX ........................................................................................................................................................................................... 13
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Introduction
Antibiotics are one of the most widely used classes of drugs in hospitals and account for one-third of total pharmacy costs (Miwa,
Kennedy, & Friedman, 1992). Suboptimal decisions are the most common reason for inappropriate antibiotic prescribing in the
hospital setting, with the majority of errors occurring in the drug prescribing stage(Bates, Cohen, & Leape, 2001). Our group has
recognized the potential for use of a clinical decision support system (CDSS), to aid physicians when dosing antibiotics that are
renally eliminated. Inappropriate prescribing of antibiotics results in unnecessary exposure of patients to medication adverse drug
events (ADEs), persistent or progressive infection and an increase in healthcare cost; it is also a major risk factor for the emergence
and epidemic spread of infection due to multi-resistant microorganisms, which are associated with higher mortality than infection
due to susceptible strains (Fish & Ohlinger, 2006).
Problem Definition
It is believed that 25-50% of all prescribed antibiotics are inappropriate in respect of drug choice, dose administered or duration of
treatment (Ena, 1998; Wikipedia). Antibiotics are cleared from the body by renal elimination or metabolized by the liver. Our CDSS
will focus on the antibiotics, which are predominately cleared by the kidneys. Physicians often prescribe inappropriate dosages of
antibiotics to their patients with decreased renal function. Dosage reductions are required with elderly patients and patients with a
history of reduce renal function. Monitoring serum concentrations of certain antibiotics is required for avoidance of toxic effects.
When inappropriately dosed, antibiotics may cause adverse drug events. We believe that using a CDSS will improve effectiveness
and efficiency with respects to ordering antibiotics. Our goal is to develop a real-time, evidence based systems that will reduce ADEs
associated with inappropriate dosing.
Renal Function
Renal function slowly reduces over a patient’s life. The need to reduce dosages is directly related to the patient’s renal function.
Renal function is measured by several methods. A commonly used method is the Cockcroft-Gault formula, which estimates the
glomular filtration rate (GFR). This formula uses serum creatinine, age and weight to predict the creatinine clearance (CrCl). The
formula results are expressed as milliliters per minute.(Cockcroft DW, 1976) The normal range of GFR, adjusted for body surface
area is similar in men and women, and is in the range of 100-130 ml/min/1.73m2. After age 40, GFR decreases progressively with
age 0.4 - 1.2 mL/min per year.
(Cook, 2007)
There are several other factors, which can cause chronic kidney disease (CKD) including: diabetes, high blood pressure, family
history, ethnic group and smoking. The severity of is described by six stages;
0) Normal kidney function – GFR above 90mL/min/1.73m2
1) CKD1 – GFR above 90mL/min/1.73m2 with evidence of kidney damage
2) CKD2 (Mild) – GFR of 60 to 89 mL/min/1.73m2 with evidence of kidney damage
3) CKD3 (Moderate) – GFR of 30 to 59 mL/min/1.73m2
4) CKD4 (Severe) – GFR of 15 to 29 mL/min/1.73m2
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5) CKD5 Kidney failure - GFR less than 15 mL/min/1.73m2 Some people add CKD5D for those stage 5 patients requiring
dialysis; many patients in CKD5 are not yet on dialysis. (Wikipedia, 2010; Wikipedia)
The estimated prevalence of impaired renal function [estimated glomerular filtration rate <60 ml/min/1.73 m2] is 13% for men and
36% of women over the age of 65(Nitsch & et, 2006). This represents a very large proportion of our population and for whom a
reduced dosage of antibiotics may be required. After the calculation of the loading dose, appropriate monitoring and adjustments
are required.
Adverse Drug Events (ADEs)
The most frequently reported adverse effects associated with gentamicin therapy are ototoxicity and nephrotoxicity. These forms of
toxicity occur more frequently in patients who experience prolonged exposure to serum gentamicin trough concentrations of
greater than 2 mcg/mL. Patients with renal insufficiency are at an increased risk of developing toxicity.
Renal side effects associated with gentamicin use have included nephrotoxicity. The overall incidence of aminoglycoside
nephrotoxicity is 2% to 10%.(Nicholas, Shaw, & Fluck, 2009) Gentamicin nephrotoxicity occurs in two forms: acute renal failure
(ARF), and a more gradual, transient, and reversible azotemia. Fanconi syndrome and Bartter-like syndrome have been reported.
Because of the serious nature of the side effects the manufacturers must include a warning box. The following is from the package
insert from a vial of gentamicin:
WARNINGS
Patients treated with aminoglycosides should be under close clinical observation because of the potential toxicity associated with
their use. As with other aminoglycosides, Gentamicin Sulfate Injection, USP is potentially nephrotoxic. The risk of nephrotoxicity is
greater in patients with impaired renal function and in those who receive high dosage or prolonged therapy. Neurotoxicity
manifested by ototoxicity, both vestibular and auditory, can occur in patients treated with Gentamicin Sulfate Injection, USP,
primarily in those with pre-existing renal damage and in patients with normal renal function treated with higher doses and/or for
longer periods than recommended. Aminoglycoside-induced ototoxicity is usually irreversible. Other manifestations of neurotoxicity
may include numbness; skin tingling, muscle twitching and convulsions.
Renal and eighth cranial nerve function should be closely monitored, especially in patients with known or suspected reduced renal
function at onset of therapy and also in those whose renal function is initially normal but who develop signs of renal dysfunction
during therapy. Urine should be examined for decreased specific gravity, increased excretion of protein, and the presence of cells or
casts. Blood urea nitrogen, serum creatinine, or creatinine clearance should be determined periodically. When feasible, it is
recommended that serial audiograms be obtained in patients old enough to be tested, particularly high risk patients. Evidence of
ototoxicity (dizziness, vertigo, tinnitus, roaring in the ears or hearing loss) or nephrotoxicity requires dosage adjustment or
discontinuance of the drug. As with the other aminoglycosides, on rare occasions changes in renal and eighth cranial nerve function
may not become manifest until soon after completion of therapy.
Vancomycin associated renal failure, principally manifested by increased serum creatinine or BUN concentrations, especially in
patients administered large doses of vancomycin, and has been reported rarely. Cases of interstitial nephritis have also been reported
rarely. Most of these have occurred in patients who were given aminoglycosides concomitantly or who had preexisting kidney
dysfunction. When vancomycin was discontinued, azotemia resolved in most patients. A few dozen cases of hearing loss associated
with vancomycin have been reported. Most of these patients had kidney dysfunction or a preexisting hearing loss or were receiving
concomitant treatment with an ototoxic drug. Vertigo, dizziness, and tinnitus have been reported rarely.(DrugLib.com, 2008)
Antibiotic Dosing Model
Our CDSS will focus on the appropriate dosing and monitoring of aminoglycosides and vancomycin. The CDSS will utilize data-driven
and time-driven configuration.
Aminoglycosides are antibiotics used to treat gram negative organisms. There are several aminoglycosides including: gentamicin,
tobramycin, streptomycin, neomycin and many others, which are infrequently used. The aminoglycosides are completely eliminated
unchanged in the urine. The main disadvantage of the aminoglycosides is their association with nephrotoxicity and ototoxicity, both
of which are associated with elevated trough levels and sustained elevated peak levels. Dosing of the aminoglycosides is very
complex; it requires accurate measurement of the patients’ height, weight, age, renal function and many other variables.
Maintaining a therapeutic concentration in the blood stream is just as complex; there are several kinetic models and dosing
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regimens available. Below is a dosing chart, with the parameters our model will use to dose aminoglycosides. Our dosing algorithm
can be viewed in Appendix A.
After the calculation of the loading dose, appropriate monitoring and adjustments are required. The following patient parameters
should be monitored during aminoglycoside therapy:(Rxkinetics, 2009)
a.
b.
c.
d.
e.
Aminoglycoside peak and trough levels
Obtain levels 24 hours after initiating therapy, at steady state (approximately four half-lives), and every 2 to 3 days.
Measure SrCr every two days, or every day in unstable renal function.
Weigh patient every two to seven days.
Measure and monitor urine output daily
Baseline and weekly audiograms, and check for tinnitus or vertigo daily.
Dosing of aminoglycosides is very complex, it is estimated that 18-26% of patients are dosed incorrectly and many of these patients
do suffer from ADEs.(Nicholas, Shaw, & Fluck, 2009). Dosing of vancomycin requires complex calculations and also requires
continuous monitoring. Appendix A contains the detailed dosing algorithm with all of our models dosing specifications. With the
complexity arises the need for a CDSS. Physicians need appropriate information; they require decision support to make accurate
dosing and monitoring decisions.
System
Components and architecture
The institution we intend on installing our CDSS currently has 2 interfaced systems, HMS and Epic.
Health Management System (HMS)-modules in use include ADT, nursing documentation, HIM coding and EMR. Health Management
System (HMS) is ODBC compliant database on IBM system I and provides easy access to all data fields in the system.
EPIC System-modules include Outpatient Clinic, Radiology, Pharmacy and Beaker Lab Information System.
The CDSS system we want to install is TheraDoc; it employs a Clinically Intelligent Platform and real time interface from HMS and
Epic to operate. (Appendix B)TheraDoc uses on line Knowledge Processing™ decision repository based on an enterprise class
database system and adheres to national messaging and vocabulary standards including HL7, LOINC, NHSN, PHIN, MS, SnoMed-CT
and RXNorm. The platform consists of three (3) Assistants (Rounds, Intervention and EZ Alert). Our project will utilize the EZ Alert
assistant for the messaging functions. In addition, there are five (5) Knowledge modules are designed to be “plug and play”. Our
project will use modules named Antibiotic Assistant, Infection Control Assistant, Clinical Alerts Assistant, and ADE Assistant.
EZ Alerts provides 500 alerts to choose from, provides access to information in a single view with single click access to additional
details for lab, microbiology, pathology, pharmacy and radiology. Additional optional interfaces for vital signs, radiology and
anatomic pathology will be utilized for our project. Alerts need to be interfaced into the communication system of choice (pager,
email, etc) for the institution.
Antibiotic Assistant module provides IV to PO switches, optimizing drug therapy, dose adjustments and actively monitors data. It
informs the physician of antimicrobial resistant pathogens and “drug-bug” mismatches as soon as the data become available.
ADE Assistant module is a trigger tool that automates the detection of actual and potential ADEs for intervention, documenting and
reporting. In addition it has a voluntary reporting interface. Its goal is to prevent, recognize, treat and mitigate ADEs.
Clinical Alert Assistant module uses electrolyte, hematology, Chemistry, Liver Function test, endocrinology, IV to PO switch, drug
level monitoring, targeted drugs, and renal function monitoring, toxicology and dietary/nutrition data to keep the physician
informed.
TheraDoc uses N-Tier architecture. This is a client server architecture in which the presentation, the application processing and the
data management are logically separate processes. The user interface, functional process logic, computer data storage and the data
5
access are developed and maintained as independent modules. By doing so it allows any of the three tiers to be upgraded or
replaced as requirements or technology changes. (Theradoc)
Standards used by the system are HL7-which is an application protocol for electronic data exchange and ASC X 12 ensures the
accuracy of data by allowing the receiving party to validate when data is received.
RXNorm is the standardized nomenclature for clinical drugs and drug delivery devices and is produced by the National Library of
Medicine. The goal of RXNorm is to allow various systems using different drug nomenclatures to share data efficiently at the
appropriate level of abstraction.
Clinical Context Object Workgroup (CCOW) is an HL7 standard protocol designed to enable disparate applications to synchronize in
real time and at the user level interface. It is vendor independent and allows applications to present information at the desktop
and/or portal level in a unified way. It facilitates a process called “context management” which is a process of using particular
“subjects of interest” to virtually link disparate applications so that the end user sees them operate in a unified, cohesive way. (EPIC,
HMS and TheraDoc) It exists to facilitate a more robust and near “plug and play” interoperability across different applications.
(Wikipedia)
Open Database Connectivity (ODBC) provides standard software interface for accessing database management system. It is designed
to be independent of programming languages, database systems, and operating systems. Any application can use ODBC to query
data from a database regardless of the database it uses or platforms it’s on. (Wikipedia)
Architecture for TheraDoc includes a communication engine to access disparate date, vocabulary engine for semantic
interoperability, decision support optimized patient database, modular knowledge base and interface engines that interpret and
filter patient data and knowledge.
Infectious disease domain specific features include antibiotic selection rules, mitigating factor rules, equivalent and alternative agent
rules, contraindication rules and drug interaction rules, dosing rules, duration of use rules, explicit logic and caveat statements, and
structured feedback tailored at the syndrome, disease and recommendations level.
. In addition to the HMS/Epic interfaces, two other interfaces will be needed-one from the combined systems to TheraDoc and the
second between the alerting system and TheraDoc.
It is our intent to build a tool that will automatically present itself in the workflow of the physicians once the physician orders an
antibiotic on their initial order. The system will auto fill information below to provide the proper antibiotic with recommended
dosages and monitoring for that antibiotic. Additional alerts will occur once the culture and sensitivities are complete. In addition,
we will pull information from documentation to use to alert the physician and pharmacist of signs/symptoms of toxicity. (Appendix
C)
System Inputs
(See Appendix D)








Outpatient system: Problem list and medication list for the patient
Lab results: BUN, Creatinine, Peak and Trough levels, microbiology reports for the type of organism, urinalysis, Pathology
data and any other data pertinent to the susceptibility/resistance of the organism.
ADT to include patient name, DOB, admitting physician, gender
EMar-populated from Pharmacy after prospective review
Nursing Documentation system –vital signs, intake/output measurements, weight, allergies, discrete data element that
indicates signs and symptoms of toxicity.
Pharmacy data would include formulary, alternatives for aminoglycosides, and all order details.
Order Entry-drug order details to include the drug, strength, route, frequency and ordering physician. Data needs to track
duration and proper corollary orders (as in renal functioning monitoring), lab orders, radiology orders
Radiology data that would indicate the presence of an infection.
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System Outputs
(See Appendix D)






Proper antibiotic choice based on renal function testing results. Important to display the date and time of results of lab
tests to further strengthen confidence of ordering provider. (Miller, et al, 2005).
Verification after the infecting organism is identified that the proper antibiotic is in use and if not the physician will be
notified for identification of the proper drug to use.
Alerts to nurses/phlebotomist of the need to draw peak and trough.
Alerts to the nurses for on time drug delivery so peaks and troughs are accurate.
Alerts if the nurse or physician evidences ototoxicity or renal toxicity via lab results or documentation.
Automatic orders for BUN and Creatinine levels every 2-3 days or more frequently if indicated with concurrent dose
adjustment recommended to physician.
Evaluation of CDSS
Verification and Validation
To implement a knowledge-based clinical decision support system for clinical information systems, it is crucial to verify and validate
the knowledge base.(Kim, Kim, Cho, Lee, & Kim, 2010).
For a variety of reasons, software verification and validation has proven to be one of the more challenging and nebulous areas of
compliance for companies regulated by the FDA (Chojnowski, 2008). It is important to establish very early on, the product
requirements of the CDSS and make sure it not only meets the user requirements but also satisfies all the regulatory specifications.
Methods and techniques used in the Verification and Validation process should be designed carefully with verification taking place
before validation. Verification and Validation processes go hand in hand.
Software verification and validation can help to reduce business costs. The verification and validation process help to achieve
compliance and can affect the total cost of ownership. This result is accomplished through two primary verification and validation
outcomes: defect reduction and improved focus on the key purposes of the system (Chojnowski, 2008). (See Appendix E)
The CDSS, TheraDoc will be evaluated a little differently, since it is a commercial CDSS product and not one custom-built. Essentially
we will be trying to find out if TheraDoc will be able to meet our requirements.
Verification (Are we building the product right?)
Verification is a process that makes sure that the CDSS is developed in the correct way. The software should confirm to the
predefined specifications. The CDSS product will go through different stages, to ensure that all required specifications are satisfied.
Verification activities that will be applied to the CDDS will include, requirements specification functional design, internal system
design specification and code verification. Walkthroughs, buddy checks and inspections are methods that will be used to verify
documents and specifications of the CDSS and make sure they match up to the initial requirements specified by the user. These
steps are more suited to a custom-built CDSS.
Since TheraDoc is considered an off-the-shelf product it will be verified in a slightly different way. Requirements specification and
functional design will be used to verify the product to make sure it fulfills the user requirements.
Validation (Are we building the right product?)
Validation is a process that provides evidence that the software specifications, conform to the needs of the users. The developers of
TheraDoc will provide an audit of the organization to determine how best to develop test plans, test suits and test cases to provide
evidence that the software specifications conform to the needs of the users. The testing strategy that will be utilized for validation
will be black box testing and equivalence partitioning strategy.
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Black box testing. This entails testing is solely focused on the requirements and functionality of the CDSS. This method will be utilized
for the first round of tests.
Equivalence partitioning testing. This involves the process of methodically reducing the huge (or infinite) set of possible test cases
into a small, but equally effective, set of test cases. This strategy will be used for the second round of tests.
The validation tests that will be used to validate the CDSS include, requirements validation/testing, user acceptance
validation/testing, functional validations/testing, integration validation/testing, coding validation/testing. Stress testing and
performance testing will also be applied to make sure that complex numerical values, large number of inputs, large number of
queries which are required to calculate dosage, can be handled efficiently by the system.
More often than not, complex software nearly always has bugs. It is not possible to test every possible scenario against the code, so
it is important to ensure that the high-risk and critical functions are defect free. Chojnowski suggests that an 80/20 rule be applied.
This rule states that you can test 80% of the primary intended functionality during 20% of the testing effort. (Chojnowski, 2008). Kim
et al conclude that the knowledge base become more accurate and practical through the testing process.(Kim, Kim, Cho, Lee, & Kim,
2010)
However, the FDA is realistic enough to recognize that a developer cannot test forever. In large measure, therefore, software
validation is a matter of developing a "level of confidence" that the device meets all requirements and user expectations for the
software automated functions and features of the device.(Nadler, 2010) There has to be a balance as over-testing or under-testing
(see Appendix F) can ensue and either option fails to satisfy the goal for the user.
During the process of validation and verification, it is imperative that stakeholders are kept informed and actively involved in the
process. From the beginning stages, when the user requirements are established to the process of validating and verifying the
system. Their input and feedback is essential to the success of the CDSS implementation and usage.
System Limitations
The CDSS will provide clinicians with knowledge and person-specific information, intelligently, filtered and presented at appropriate
times, to assist with decision-making in dosing antibiotics that are renally eliminated. It is important to note that the role of the
CDSS is to advise the clinician. Computer provider order entry (CPOE) with clinical decision support (CDS), can improve patient safety
and lower medication-related costs (Kuperman, et al., 2007). TheraDoc will help to reduce ADEs associated with inappropriate
dosing of antibiotics. However it is important to note that in order to achieve the goal of reduced ADEs the clinicians must be willing
and encouraged to use the CDSS.
Physicians and other clinicians need to be involved throughout the whole process of finding, designing, implementing, and improving
such a system. Their input and support is critical because of the significant role that physicians play in the health care delivery
process.
Even with the benefits mentioned of a CDSS, there are some limitations. Cost has been cited as one of the deterrents for the
adoption of CPOE by hospitals. According to the New England Healthcare Institute journal, the acquisition cost for a CPOE system is
about $2.1 million, and hospitals can expect annual operating expenses of about $450,00 a year (Massachusetts Technology
Collaborative and New England Healthcare Institute, 2008)
Failures occur when physician fail to see the benefit of the CDSS. Acceptance relies heavily on the acceptance by physicians; it is
important that they see the value of the system to them and to their patients as this affects the quality of patient care and the
physician-patient relationship.
Clinical Efficacy
Thursky states that the most effective CDSS were those that coupled to an electronic medical record and/or CPOE (Thursky, 2006).
Randomized and non-randomized studies of CDSSs across a broad range of clinical targets including diagnosis, prevention, disease
8
management, drug dosing and drug prescribing will be reviewed to measure the clinical efficacy. Reviews will also focus on system
and organizational features of the CDSS. A systematic review of CDSS that aided drug dosing (e.g., anticoagulants, aminoglycosides)
(Walton, Dovey, & Freemantle, 1999) demonstrated an overall benefit of these types of systems.
Prior to implementation the prescribing patterns of physicians should be documented as a baseline for comparison during postimplementation. It is important to document and review complaints, recommendations and comments by clinicians during usage of
the CDSS, especially in the early stages. The reporting function of TheraDoc will also be used as a tool to review patterns of usage.
A CDC sponsored survey published in JAMA revealed the following, “with detailed information placed at their fingertips
participating physicians aided by TheraDoc’s software made better-informed and more-appropriate treatment decisions, decreasing
inappropriate antibiotic prescribing by thirty-two percent (32%)”. Clinicians in a comparative group of another six communities were
supported only by a community intervention campaign that was concurrently launched to educate residents about the hazards of
misusing antibiotics. The comparative group did not have access to a CDSS and realized only a five percent (5%) prescription
reduction (CDC, 2005).
Limitations
Physician autonomy
There should be no threat of Physician autonomy by the CDSS. Physicians have long enjoyed the freedom to make their own decision
based on their acquired knowledge, and past experiences. Autonomy, for physician and patient, is central to the medical profession
and dates back to Hippocrates. The CDSS has to flexible enough to allow for the physician to accept suggestions, ignore it or override
the advice.
Computer literacy
Different levels of computer expertise and confidence levels amongst clinicians can also cause usability issues and prevent usage of
the CDSS. Clinicians who were comfortable using computers in their daily practice adapted better.
IT Support Availability
There has to be a technical support available at 24/7 preferably to accommodate the clinician’s schedule. There should be easy
access to technical support by the clinicians. IT staff should be knowledgeable enough to fix the issue expeditiously.
Impact on workflow
A recent editorial suggests that health information technologies are tools whose value is influenced by how clinicians modify their
work practices to use them and how organizational change is enacted when they are adopted(Chaudhry, 2008). In order for the
CDSS to be effective it needs to be incorporated directly into the CPOE. It cannot be perceived as extra work load by the clinicians. It
is imperative to engage clinicians at every stage of the implementation process. The workflow of clinicians, CDSS timing,
development and implementation and acceptance of the system have a direct influence on the acceptance of the system.
Training
Adequate time must be provided for training using various formats. Increased training time and IT support also aided in the
successful implementation. Overall, clinicians reported finding the CDSS to be a useful tool in providing good clinical care (Trivedi,
Daly, Kern, Grannemann, Sunderajan, & Claassen, 2009). Training must be delivered in various formats to accommodate different
learning styles. Physician task forces and "physician champions" should be utilized to encourage usage and participation.
Buy-in from clinicians and administrative staff
Buy-in must be achieved from all the stakeholders. This includes physicians, nurses, health technicians, administrative staff and
patients.
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Future Extensions
The future of the CDSS will depend greatly on development in reducing barriers to implementation. The future should provide a
unified real-time system that is easily accessed by healthcare professionals anytime anywhere. Physicians involved in a patient’s care
should have access to the patient’s medical information at the point of care if needed.
Conclusion
Unlike other healthcare technologies that have been easier to catch on, the same cannot be said about CDSS. One reason for this is
the fact that these systems, including decision support systems affect the long history of traditional medical practices. New systems
are changing the ways physicians think and behave (Anderson, 1994).
However a CDSS such as the one we have selected, that can connect seamlessly with a CPOE are more likely to be used by physician
as it does very little to interrupt the workflow. Implementation of a CDSS is a work in progress. Once Theradoc is implemented,
follow-up, review of the product and training will help to overcome stumbling blocks that will need to be addressed along the way.
Trivedi et al summarizes some lessons (see Appendix G) learned during their implementation that can be applied to any organization
implementing a CDSS (Trivedi, Daly, Kern, Grannemann, Sunderajan, & Claassen, 2009)(Appendix G). The lessons learned listed in
Appendix G will not promise smooth sailing during the implementation, however it will put us on the right track towards a successful
implementation.
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Chojnowski, B. (2008). Software Validation: Turning Concepts into Business Benefits. MDDI .
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Appendix
Appendix A
Cockcroft &Gault
Infusion time (ti) Sample recommendations Aminoglycosides: (All doses) 0.5 Vancomycin
(0 - 500mg/ 0.5) 0.5 501 - 1250 mg 1 1251 -1750 mg 1.5 - 2.0 1751 - 2250 mg 2 - 2.5
Aminoglycoside-VancomycinDosing Patient Name:
Select drug:
Location:
Need dosing information for once daily dosing?
Age:
Gender:
Male
Infusion time:
SCR:
0.5
Height:
Centimeters
hoursVolume of distribution:
0.25
Kg
Weight:
Desired peak:
Desired trough:
L/kg
Background information (Equations listed are calculated by the program)
Obtain baseline data:
Patient age, sex, height, weight, allergies, diagnosis, infection site, current
drug therapy, I/O's for past 24 hours, Tmax, WBC with diff, albumin,
Past medical history, Lab work-up: Scr, Bun, cultures etc.
Estimate Ideal body weight in (kg)
Males: IBW = 50 kg + 2.3 kg for each inch over 5 feet.
Females: IBW = 45.5 kg + 2.3 kg for each inch over 5 feet.
If the actual body weight is greater than 25% of the calculated IBW, calculate the
adjusted body weight (ABW):
ABW = IBW + 0.4(Total body weight - IBW)
Estimate Creatinine Clearance: (ml/min)
Cockcroft and Gault equation:
CrCl = [(140 - age) x IBW] / (Scr x 72)
(x 0.85 for females)
Note: if the ABW (actual body weight) is less than the IBW use the
actual body weight for calculating the CRCL. If the patient is >65yo and
creatinine<1, use 1 to calculate the creatinine clearance
Estimate kel (Elimination rate constant):
Amikacin /Gentamicin/Tobramycin:Kel = (0.00285 x CrCl) + 0.015
May also use: (0.003 x CrCl) + 0.01
Vancomycin: kel = (0.00083 x CRCL) + 0.0044 (used by program)
Equation used by the Detroit VA Medical Center: CRCL x 0.0012
The above equations provide an estimate of the elimination rate
constant based on population kinetics. The following may decrease
the usefulness of these equations:
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*Renal failure, CHF, Burn patients, cystic fibrosis, severe
hypotension, rapidly changing renal function. (Burn victims
and patients with cystic fibrosis usually have increased
rates of elimination. Patients with CHF or severe hypotension
will have decreased rates of elimination due to decreased
renal perfusion).
Estimate half-life (T1/2) in hours:
T1/2 = 0.693 / Kel
Estimate Volume of Distribution (Vd): (Liters)
Aminoglycosides:
Use IBW unless obese, then use ABW= 0.4 x (TBW-IBW) + IBW
Vd (Normal) = 0.25 to 0.3 L/kg
Vancomycin:
[Use actual body weight in all cases]
Vd (Normal): 0.6 to 0.7 L/kg
Select Time of Infusion (ti):
(a) Aminoglycosides: 30 minutes (0.5 hrs)
(b) Vancomycin: 0-500 mg/ 0.5 hrs ; 501 to 1250 mg/ 1 hour ;
1251 to 1750/ 1.5 hrs ; >1750/ 2 hours
Calculate Dosing Interval (T) hrs.
T = Ln (Cmax/Cmin) / kel + ti or estimated T = 3 x T1/2
Calculate Maintenance dose (MD):_____mg.
MD = [(kel) x (Vd) x (ti) x (Cpeak desired) x (1 - e-kT)] / (1 - e-kti)
or MD = (Cpeak desired) x Vd (eg: C = D/V, therefore D=C*V)
Calculate Predicted Peak and Trough at Steady State.
Cmax = [Dose * 1-e-kti] / (kel)(Vd)(ti) 1-e-kT
Cmin = Cmax * e-k(T-ti)
(Pharmacokinetic dosing, 2009)
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Appendix B
Epic
Clinic
EPIC
Radiology
EPIC
Pharmacy
EPIC
Beaker LIS
Interface
Engine
TheraDoc
Knowledge Base
Antibiotic Assistant
Clinical Alerts
ADE Assist
ICP Assist
HMS
ADT
HMS
EMR
HMS
Nursing
Doc
Physician/
Pharmacist
Alerts
15
Appendix C
1. Physician selects an
Antibiotic-Initial Order
2. All known needed data elements
are pulled to one screen:
•Allergies
•Current/Past Renal Dx
•Serum Creatinine, BUN, WBC
w/diff and albumin results
•Demographics
•Radiology results-Chest X-rays
findings
•Pathology findings if relevant
3. Recommendations include
Antibiotic dosage/ selection
Peak / trough levels ordered
Repeat BUN/Creatinine ordered
4. Physician selects agree/change
If order selection is changed drop
down box with reasons will require
completion
Once order is completed:
Peak and trough dates and times
will be ordered
eMAR will populate Antibiotic
Selections with peak and trough
draw times
16
Appendix D
Data Elements for Inputs and Outputs
ADT
Patient Name, admitting physician, date of birth, gender
Order Entry
Lab-BUN, Creatinine, culture, sensitivity, Peak/trough, Uri analysis, WBC with diff, albumin, diagnosis
LIS
Lab results for all tests listed above, pathology report findings
eMAR
Populated from Pharmacy post prospective review, lab peak and trough draw times
Radiology
Results that may impact drug choice
TheraDoc
Alerts to physicians, pharmacists, nurses; alert acknowledgment, ADE monitoring
Nursing documentation
Intake and Output, Height, Weight, allergies, temperature; prompts for signs/symptoms of toxicity to include: nausea,
phlebitis, vertigo, tinnutitis, bouncing vision
Pharmacy
Formulary, Prescription data to include drug name, dose, route, frequency
Clinic Records
Appropriate problem list and medication list
Neuro Records
Results of audiometry
17
Appendix E
Benefits of Verification and Validation
(Chojnowski, 2008)
18
Appendix F
(Nadler, 2010)
19
Appendix G
Table 1: Lessons learned during implementation of a computerized decision support system
Lesson Learned
Variation in computer literacy may affect adherence.
Adequate IT requirements to support the program need to be in place.
Availability of on-site technical support needed.
Management and administrative support and involvement essential to assist with impact on
workflow.
Software may need to be adapted to specific site workflow/ administrative issues.
The need to allow clinicians flexibility and autonomy in the use of the algorithm.
Clinician feedback essential to making the program more usable.
Solution Proposed
Enhanced training on the computer program, so that clinicians achieve necessary competence
and have used program on multiple simulated cases.
Prior to and following implementation, appropriate IT support to maintain server/network is
crucial.
Training of individuals at site who can provide extended support for clinicians and support staff
as needed.
Include management and administrative staff in planning to assist with issues such as visit
frequency and other potential workflow issues.
Prior to implementation, work with site personnel to evaluate specific site requirements and
allow customization.
The algorithm provides clinicians with recommendations that they can choose to over-ride.
Prior to implementation, a period of testing allows clinician feedback and any necessary program
modification.
A summary of lessons learned during initial testing of the Computerized Decision Support System for Depression
(CDSS-D) in real world clinical settings (Trivedi, Daly, Kern, Grannemann, Sunderajan, & Claassen, 2009)
20