Method of improving drug treatment6000828Abstract A computer implemented method and system for improving drug treatment of patients in local communities by providing drug treatment protocols for particular disease states, such as Diagnosis Related Group (DRG) classifications. The protocol contains ranked recommendations for drug treatments of the disease state, and the computer system collects information about the risks and benefits of the drug treatments. The information collected about the treatments is used to modify the rankings of the drug treatments in the protocol. In one specific embodiment of the system, where the disease state has a microbial etiology and the treatments are antimicrobial drugs, the emergence of drug resistance is quickly detected by determining the percentage of microbial isolates that are found to be resistant to antimicrobial therapy in the community where the therapy is being provided (such as a community hospital or city-wide health care system). An increase in the percentage of resistant isolates produces a re-ranking of recommended drug therapies to avoid further use of the drug to which resistance has developed, and helps quickly introduce more effective drugs that will improve the effectiveness and lower the cost of treatment. In yet other embodiments, a sum of medication (e.g. dosing) errors and adverse effects (e.g. allergic reactions) are tracked by the system to identify drugs that are poorly tolerated in particular populations served by the hospital where the treatment is being provided. Data is collected about the safety and effectiveness of all types of drug therapies in the community being served, and this data is used to modify the drug protocols. Claims I claim: Description FIELD OF THE INVENTION
TABLE I
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SAMPLE DIAGNOSIS RELATED GROUPS (DRGs)
AS PUBLISHED IN FEDERAL REGISTER SEPTEMBER 1, 1983
RELATIVE
MEAN
OUTLIER
DRG
MDC SEX
TITLE WEIGHT
LOSS
CUTOFFS
__________________________________________________________________________
31 1 MED
B CONCUSSION AGE >69
0.6051
4.6 25
AND/OR C.C.
32 1 MED
B CONCUSSION AGE 18-69
0.4519
3.3 19
WITHOUT C.C.
33 1 MED
B CONCUSSION AGE 0-17
0.2483
1.6 5
34 1 MED
B OTHER DISORDERS OF
0.9927
7.1 27
NERVOUS SYSTEM AGE
>69 AND/OR C.C.
35 1 MED
B OTHER DISORDERS OF
0.8480
6.2 26
NERVOUS SYSTEM AGE
<70 WITHOUT C.C.
96 4 MED
B BRONCHITIS & ASTHMA
0.7996
6.9 24
AGE >69 AND/OR C.C.
97 4 MED
B BRONCHITIS & ASTHMA
0.7256
6.2 21
AGE 18-69 WITHOUT
C.C.
98 4 MED
B BRONCHITIS & ASTHMA
0.4275
3.7 11
AGE 0-17
261
9 SURG
F BREAST PROC FOR NON-
0.7329
4.8 19
MALIG EXCEPT BIOPSY
& LOC EXC
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Another commonly used coding system for disease is the International Classification of Diseases (ICD) system, which refers to a coding system based on and compatible with the original international version of the ICD coding system provided by the World Health System. The ICD coding system is used in North America, and it classifies diseases, injuries, symptoms, medical procedures, and causes of death. One version of these codes is listed, for example, in a publication by the Commission on Professional and Hospital Activities, Ann Arbor, Mich., entitled "ICD-9-CM" dated Jan. 1, 1979. The ICD codes are divided into Disease and Procedure sections. These sections are further divided into subsections which encompass from 1-999 three digit disease or 1-99 two digit procedure code categories. Within the three digit code categories there can be an additional 1 or 2 decimal digits to divide the codes into subcategories which further define the disease manifestations and/or diagnostic procedures. Only a portion of the ICD codes are relevant to the DRG system. The DRG system involves the coding of diagnostic and procedural information into ICD code numbers by hospitals before a patient can be assigned a DRG. It is possible that a large number of sets of ICD numbers or codes can lead to the same DRG. Table II lists the ICD codes that currently fall within each of a few of some of the DRGs that are used as examples in Table I. The disease conditions of the present invention can be indexed by a diagnosis code that corresponds to either a DRG or an ICD, although the DRG code is used in the preferred embodiment of the invention. The DRG code is particularly convenient to use with the computer implemented system of the present invention, because this system is designed to optimize the cost-effective utilization of medical resources. Hence the allowed cost of treating a disease can be indexed to the DRG, and provided as part of the information provided to a health care provider when making clinical decisions. A principal magnetic disc data file that is part of the system of FIG. 1 contains a listing of all the DRGs. It is accessible by disc drive 28. The DRG file is a static computer database having one record for each DRG number. Table I shows seven fields of information for each of the example DRGs given. This information is published as part of the Federal regulations. The first stored item of information is the DRG number, a one to three digit number. The next item of information, shown in the second column of Table I, is the Major Diagnostic Category (MDC) in which the individual DRG falls. The specific DRGs are grouped by the Federal regulations into MDCs of related DRGs. Each MDC is defined to include the DRGs directed to diseases of different body systems, such as the lung or the Central Nervous System (CNS). The third column of Table I identifies the sex of the patient ("M" for male, "F" for female, and "B" for a diagnosis appropriate for both sexes). The fourth item of information for each DRG maintained in the static database is shown in the third column of Table I, namely the title or textual description of the DRG. The fifth data field, shown in the fifth column of Table I, is a relative weight for each DRG, which determines the amount of relative compensation that a hospital is given for treating a patient having the disease condition indicated by the particular DRG. The column labeled "Mean LOS" refers to the mean length of stay for a patient within this DRG, while "Outlier Cutoffs" refers to the maximum length of stays in the hospital that should be allowed in accordance with the DRG.
TABLE II
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SAMPLE GROUPINGS
OF ICD-9CM CODES INTO DRG CATEGORIES
______________________________________
DRG 31, CONCUSSION AGE = 70 AND/OR C.C.
PRINCIPLE DIAGNOSIS
8500 Concussion w/o Coma
8501 Concussion - Brief Coma
8502 Concussion - Moderate Coma
8503 Concussion - Prolong Coma
8504 Concussion - Deep Coma
8505 Concussion W Coma NOS
8509 Concussion NOS
DRG 32, CONCUSSION AGE 18-69 WITHOUT C.C.
PRINCIPLE DIAGNOSIS
8500 Concussion w/o Coma
8501 Concussion - Brief Coma
8502 Concussion - Moderate Coma
8503 Concussion - Prolong Coma
8504 Concussion - Deep Coma
8505 Concussion W Coma NOS
8509 Concussion NOS
DRG 33, CONCUSSION AGE 0-17
PRINCIPLE DIAGNOSIS
8500 Concussion w/o Coma
8501 Concussion - Brief Coma
8502 Concussion - Moderate Coma
8503 Concussion - Prolong Coma
8504 Concussion - Deep Coma
______________________________________
Etiology and Treatment Files Another magnetic disc data file is provided that lists the presumed etiologies of the disease state indicated by the diagnosis code. The presumed etiologies can initially be ranked in the order that they are presumed to occur in the particular disease state. This ordering of presumed etiologies is important in selecting an empirical initial treatment for a patient, for example pending the outcome of further laboratory tests or awaiting drug response. An example of an entry in this data file is illustrated in Table III, where the diagnosis code 282 corresponds to a presumed pneumonia in a patient who is older than 40 years of age, and who has underlying alcoholism, diabetes or congestive heart failure (CHF). The diagnosis code is used as a key to access other information in the database, such as presumed etiologies, suggested treatments, information about drug cost and toxicity, and other information which is organized into a record, as shown in Table III.
TABLE III
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ANTIBACTERIAL THERAPY BASED ON CLINICAL DIAGNOSIS
__________________________________________________________________________
DIAGNOSIS#: 282 PHYSICIAN: PAGE # 1
PATIENT ID#: 6926
NAME: BOB DOLE
DATE 01-06-97
INFECTION SITE:
LUNG
DIAGNOSIS: LUNG-PNEUMONIA >40 YRS W/ UNDERLYING ALC, DIA, CHF
CIRCUMSTANCES:
>40 YRS W/ UNDERLYING ALCOHOLISM, DIABETES, CHF
ETIOLOGIES
1: KLEBSIELLA PNEUMONIAE
2: ENTEROBACTERIACEAE
3: LEGIONELLA SP.
4: C. PNEUMONIAE
5: STAPH. AUREUS
6:
TREATMENT
PRIMARY
1: ERYTHROMYCIN + CEFTRIAXONE
2: ERYTHROMYCIN + CEFUROXIME
3: ERYTHROMYCIN + IMPIPENEM
4: ERYTHROMYCIN + TICARCILLIN/CLAV.
5: ERYTHROMYCIN + AMPICILLIN/SULBACTAM
6:
SECONDARY
1: ERYTHROMYCIN + TMP/SMX
2: IF SPUTUM SHOWS S. PNEUMONIAE W/NO G- BACILLI THEN
PEN G OK
3:
4:
OTHER 1:
2:
__________________________________________________________________________
DOSE DAYS TOTAL
ANTIBIOTIC (MG)
INTERVAL
THERAPY
DOSE
COST
TOXICITY
__________________________________________________________________________
ERYTHROMYCIN 500 MG IV/IM ADV
430
6 5 8600
$25.56
0
CEFTRIAXONE 1 GM IV/IM
2150
24 5 10750
262.58
1
CEFUROXIME 1.5 GM IV/IM
1146
8 5 17200
355.32
1
IMIPENEM CILASTIN 500 MG IV/IM
537
6 5 10750
393.50
3
TICARCILLIN 3 GM IV/IM
4300
6 5 86000
217.78
3
AMPICILLIN/SULBACTAM 3 GM IV/IM
1720
6 5 34400
337.16
3
__________________________________________________________________________
NOTE: This report is designed to assist physicians in antibiotic selectio
based on diagnosis and cost effectiveness of antibiotic therapy
IT SHOULD NOT BE CONSTRUED AS TREATMENT ADVICE
TOXICITY RATING
(1) = <2% & NOT SERIOUS
(2) = >2% & NOT SERIOUS
(3) = <2% & SERIOUS
(4) = >2% & SERIOUS
The etiologies listed for this clinical presentation are those microorganisms that have historically been found to cause the disease state (pneumonia in a patient over 40 years of age with underlying alcoholism, diabetes or CHF). The organisms are preferably listed in a rank order, from the organism most commonly found to cause this disease state, to the organism least commonly found to cause the disease state: 1. Klebsiella pneumoniae 2. Enterobacteriaceae 3. Legionella 4. Chlamydia pneumoniae 5. Staph aureus Historically, these etiologies have been determined based on national statistics. However, one of the advantages of the present invention is that the etiologies may be determined based on a more limited geographic location in which the infection occurs, for example the city, state, or specific hospital where the patient has been admitted and the computer system is in use. This more limited geographic focus can allow the presumed etiologies to more accurately reflect the actual incidence of such infections in the particular population found in that limited geographic location. A more accurate reflection of actual etiologies in turn allows a better empirical treatment to be selected with which to treat the patient, pending the outcome of laboratory tests that will determine the actual organism that is causing the infection. The present invention therefore allows more accurate selection of empirical antibiotic treatment that will adequately treat the infection. Earlier adequate treatment of the infection in turn results in a faster average therapeutic response of the patient to treatment, a shorter length of stay in the hospital, and improved utilization of medical resources at a reduced cost. A characteristic of medical practice that has not been adequately addressed by past computer implemented medical treatment systems is the constantly evolving nature of medical knowledge and microbial resistance. Hence the list of common etiologies in a community will likely change over time, with the seasons of the year or the spread of infections throughout regions of the country. A fixed list of etiologies may represent an average incidence of disease over a large geographic area, while being completely inaccurate at certain times of year, or in a restricted geographic locality that has a population with different characteristics, or a microbial prevalence that is divergent from microbial populations in other geographic regions. The list of primary etiologies may therefore change as the actual incidence of microbial infections in the community changes. The list may be changed in several ways. A therapeutics committee may change the list every few days, weeks or months to reflect new patterns of microbial infection. Alternatively, laboratory data of diagnosed causes of infection for each diagnosis code may be automatically updated as the laboratory data becomes available. For example, the number of positive cultures (those in which an organism is isolated in culture) for each of the organisms within a specified period of time (e.g. 30, 60 or 120 days) can be stored in the database, and culture results prior to the specified period of time are discarded. The number of positive cultures grown for a patient having that particular diagnosis code are then summed, and the organisms ranked from the most common (greatest number of culture proven infections with that organism) to the least common (fewest number of culture proven infections with that organism). The rank of organisms responsible for the infection covered by the DRG condition in the specified time period can then be changed to reflect the new patterns of microbial infection. Treatment Recommendations Another magnetic disk data file is also stored, listing proposed treatments for the particular disease state (e.g. the condition covered by the DRG or ICD code). The proposed treatments can be ranked in a preferred order. The rank order can be from most effective to least effective for the disease condition to which the file corresponds, or ranking can be performed by a weighted combination of effectiveness and cost. The treatments may be ranked in accordance with the rank of presumed etiologies. For example, if Klebsiella if the most commonly encountered etiology in the DRG classification, then the highest ranked primary treatment will be the drug which is considered to most commonly successfully treat patients infected with this microbial pathogen (erythromycin and ceftriaxone in Table III). In time, after the program gathers data about actual clinical successes of this treatment, the drug rankings may be changed if it is found that another drug or combination of drugs is more effective in the population at a particular hospital or in the particular health system where the computer system is operating. An example of an entry in this data file is illustrated in Table III, where the diagnosis code 282 corresponds to a presumed pneumonia in a patient who is older than 40 years of age, and who has underlying alcoholism, diabetes or congestive heart failure (CHF). The treatments for this disease condition are divided into a field for primary treatments and a field for secondary treatments. The primary treatments are those treatments that are most preferred. In the given example of a pneumonia in a patient who has the specified clinical and demographic characteristics, a combination of erythromycin and ceftriaxone are ranked first, while erythromycin and cefuroxime are listed second, and erythromycin and imipenem are listed third, etc. These proposed drug treatments are ranked in this order initially based on national recommendations. However the rankings may change in time based on the results of laboratory culture and sensitivity studies in a selected geographic area (for example, the hospital or hospital system in which the patient is being treated). The antibiotics are preferably listed in a rank order, from the antibiotics most commonly found to successfully treat this disease state, to the antibiotics less commonly found to successfully treat the disease state. In the example of Table III, which concerns an infectious disease, the treatments will be determined by laboratory culture and sensitivity results. The rankings will be based (at least in part) on the percentage of organisms for this disease state that are found to be susceptible, as measured by mean inhibitory concentration (MIC) studies, to the proposed drug treatment. A low MIC indicates that the microorganism is susceptible to the antibiotic (a low concentration of the antibiotic inhibits the organism's growth), while a high MIC indicates a microorganism is resistant to the antibiotic (a high concentration of the drug is required to inhibit the organism's growth). When reporting such MIC results, a laboratory often simply records whether an organism is "susceptible" to the antibiotic, "intermediate" in resistance, or "resistant" to a particular antibiotic. Using ceftriaxone as an example, in a standard dilution method (broth, agar, microdilution) wherein the concentration of ceftriaxone is sequentially diluted and growth of microbial growth is monitored, MIC values obtained could be interpreted using the following criteria (where MIC refers to the concentration of the antibiotic in mcg/mL in the culture medium):
______________________________________
MIC (mcg/mL) Interpretation
______________________________________
less than 16 Susceptible
>16-<64 Intermediate
>=64 Resistant
______________________________________
Examples of organisms having measured MIC values, and the interpretation of those values with respect to ceftriaxone, are shown below (where S is "susceptible", "I" is "intermediate" and "R" is resistant):
______________________________________
Organism MIC (mcg/mL)
______________________________________
Staphylococcus aureus ATCC 29213
1-8 (S)
Escherichia coli ATCC 25922
0.03-0.12 (S)
Pseudomonas aeruginosa ATCC 27853
8-32 (I)
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An organism that is "susceptible" to the antibiotic will usually cause an infectious condition that can be successfully treated with the antibiotic to which the organism is shown to be "susceptible" in the laboratory. The ranking of erythromycin and ceftriaxone in the first position in the treatment rankings may therefore be an indication that most organisms cultured from the sputum or blood of patients having this disease condition are found to in fact be susceptible to this drug combination. Alternatively, if different combinations of drugs have equal percentages of success (e.g. 100% rates), then the drugs can be ranked by MIC, with drugs having lower MICs being ranked higher on the list. Also, rankings can be altered by the cost of the drugs in the combination. For example, even though the combination of erythromycin and imipenem may be slightly more effective (e.g. lower MIC for imipenem), the cost of imipenem may be much higher than the cost of ceftriaxone or cefuroxime. In that event, imipenem may be ranked as a less preferred (higher number) choice in spite of its superior efficacy. The rankings can be made automatically by a preselected algorithm. For example, an equation can be used that weights an effectiveness factor and a cost factor, to arrive at a numerical score that is then used to order the drugs in the list. An example of such an algorithm is presented below. Secondary treatments can also be listed in another field, as shown in Table III. These secondary treatments are listed separately from the primary treatments because as a group they have been found to be less effective against the disease condition (DRG or ICD) than the treatments in the primary treatment list. A record is stored for antibiotics that have been found to be effective against particular organisms. Table IIIA, for example, shows a record that is stored for listing antibiotics of choice against Pseudomonas aeruginosa, with an indication in parentheses following the drug indicating whether that drug is a primary "(1)" or secondary "(2)" choice.
TABLE IIIA
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ANTIBIOTICS CHOICE AGAINST SELECTED ORGANISMS
__________________________________________________________________________
DATE:
PATIENT ID#:
4121 6929 FIRST: TOM LAST: SMITH
WT: 80 KG
HT: 71 IN
DOB: 11/21/56
SEX: M
DR.: DEPPER, JOEL
MICROORGANISM: PSEUDOMONAS AERUGINOSA
INFECTION SITE: UT1,WOUNDS,HEART,GI,CNS,SEPTICEMIA GRAM STAIN G- RODS
PRESCRIBED THERAPY:
ALERNATIVE ANTIBIOTICS
1: AZLOCILLIN (1)
8: NETILMICIN (1) 15: CIPROFLOXACIN (2)
2: MEZLOCILLIN (1)
9: TOBRAMYCIN (1) 16: CARBENICILLIN (u)
3: PIPERACILLIN (1)
10: TICARCILLIN/CLAV (2)
17:
4: TICARCILLIN (1)
11: AZTREONAM (2) 18:
5: CEFTAZIDIME (1)
12: IMPENEM (2) 19:
6: AMIKACIN (1)
13: PIPERACILLIN/TZ (2)
20:
7: GENTAMICIN (1)
14: CEFOPERAZONE (2)
21:
__________________________________________________________________________
PIPERACILLIN 2GM IV/IM ADV DRUG#:4071813
M/C: 0. S/C: 0.
M/A: 200.
S/A: 250.
CHOOSE ONE: 0.
WT: DAYS THERAPY: 5
TOTAL DOSE: 0
COST/MG: 0.004297 HR: 4.
INTERVAL: 6
SEV: 4 COST: $12.87
RECOMMENDED DOSE: 0.
TOXIC: 3
__________________________________________________________________________
This record can be retrieved for infections which are believed to be caused by this organism, such as a nosocomial infection in a neutropenic patient, or a respiratory infection associated with cystic fibrosis. Table IIIA shows a display screen in which piperacillin has been selected, and the total suggested days of therapy (5) are displayed, along with the dosage interval (every six hours), the cost of each dose ($0.52) and the toxicity level of the drug (3, which indicates toxicity in less than 2% of the population, with serious clinical consequences). Cost Information Another feature of the present computer system is that it is able to predict the estimated cost of treating a patient with a given drug, or combination of drugs. This prediction of cost often requires additional patient specific information that is stored in the database, and is electronically retrieved for calculating the total dose and cost of a proposed drug treatment. An example of a patient record having fields useful in computing total dosages of drugs in shown in Table IV. In one field of the record is a patient A identification number, which can be used to point to the other fields in that patient record, such as the date of birth (from which patient age is calculated), weight (in both pounds and kilograms), and serum creatinine (which is a measure of renal function that is useful in predicting the pharmacokinetics of drugs), and may be used to calculate the total dose of a drug that is administered based on a dosage per unit weight of the patient. Another important field is the identification of any drug allergies (for example an allergy to penicillin), so that any attempt to prescribe a drug that is entered in the allergy field will prompt a warning from the system that the patient is allergic to that drug. The patient identification form is linked to a listing of DRG classifications, and the DRG classifications can be accessed from the patient identification form shown in Table IV.
TABLE IV
__________________________________________________________________________
PATIENT IDENTIFICATION FORM
__________________________________________________________________________
IDENTIFICATION NUMBER: 6929
LAST NAME: SMITH
FIRST NAME: TOM
OUTPATIENT FULL NAME: SMITH TOM
DOB: 11/21/56
ADDRESS: 1256 COPELAND TERRERBONNE, OR 97760
ROOM#: 120-1
ALLERGY: PENICILLIN
SEX: M WEIGHT LBS: 178 KG: 80 HT (IN): 71 SERUM CREAT: 1.2
DIET: REGULAR DIET
__________________________________________________________________________
Once the DRG classification has been determined, the linked lists of suspected etiologies and treatments are retrieved and displayed on the monitor screen in association with the infection site, diagnosis and associated clinical circumstances. A matrix is then displayed, similar to the matrix shown at the bottom of Table III, in which the drugs included in the primary treatments are listed in a first column, followed by columns showing the dose (per administration), the interval (between doses), and the total days of therapy. The dose, interval and days of therapy are specific to the disease condition and the patient being treated. For example, ceftriaxone in a dose of 1 gram per day will be administered intravenously (IV) or intramuscularly (IM) for 5 days when treating pneumonia, but a single IM dose of 250 mg will be given for treating uncomplicated gonococcal urethritis, and for treatment of meningitis a daily dose of 100 mg/kg (not to exceed 4 grams) is given in divided doses every 12 hours. The total dose is calculated by dividing 24 by the interval (to determine the number of doses administered per day), which will be multiplied by the dose and the days of therapy. The cost per unit dosage is then multiplied by the total dose to provide an estimated cost of treatment with the drug. The estimated cost of treatment for each drug in the list is then displayed in a column so that the comparative costs of each treatment can immediately be available to assist in selection of the therapy. Once a therapy is selected, a screen (Table IVA) is displayed which calculates the total expected dose of the antibiotic, based on the weight of the patient (86 kg), the projected number of days of therapy (5 days), the interval between doses (24 hours), the cost per mg of the drug, the recommended dose, and the anticipated cost of prescribing this therapy (including nursing cost and other costs associated with administering the drug parenterally).
TABLE IVA
__________________________________________________________________________
TREATMENT `Y` TO REVIEW MICROBE: N .sub.--
1ST 1: ERYTHROMYCIN + CEFTRIAXONE
MICROBES
2: ERYTHROMYCIN + CEFUROXIME KLEBSIELLA
3: ERYTHROMYCIN + IMPIPENEM ENTEROBACTERIACEAE
4: ERYTHROMYCIN + TICARCILLIN/CLAV.
LEGIONELLA SP.
5: ERYTHROMYCIN + AMPICILLIN/SULBACTAM
C. PNEUMONIAE
2ND:1 ERYTHROMYCIN + TMP/SMX STAPH. AUREUS
2: IF SPUTUM SHOWS S. PNEUMONIAE W/NO G- BACILLI THEN
3: Weight: 75 kg
CEFAZOLIN (1) CEFACLOR (1) CEPHRADINE (1) CEFMETAZOLE (1) CEFOTETAN (1)
CEFOXITIN (1) CEFUROXIME (1) CEFTAZIDIME (1) CEFTRIAZONE (1)
CIPROFLOXACIN (1)
NORFLOXACIN (1) (U) AMOXICILLIN/CLAV (2) AMPICILLIN/SULB (2)
TICARCILLIN/CLAV (2)
IMPENEM (2) PIPERACILLIN/TZ (2) CEPHALEXIN (2) AMIKACIN (2) GENTAMICIN
(2) TOBRA
BACTRIM (2) END -0- -0- -0-
__________________________________________________________________________
ENTER `Y` TO REVIEW MICROBE N ACINETOBACTER SP.
CEFTRIAXONE 1 GM IV/IM CODE: 4079966
M/C: 50. S/C: 75. M/A: 25. S/A:40. CHOOSE ONE: 40.
WT: 86 DAYS THERAPY: 5. TOTAL }DOSE: 17200 COST/MG: 0.024378
INTERVAL: 24 HOURS SEV: 12 HOURS: 1. COST: $419.82 282 6928
RECOMMENDED DOSE: 3440. MG TOXICITY: 1 ACTUAL THERAPY (=a):
__________________________________________________________________________
.sub.--
If the actual therapy selected by a physician or other health care provider is not one of the primary or secondary treatments listed in the approved treatments field, then a message is sent to the prescriber alerting him or her to this discrepancy, and asking the prescriber to justify the departure from the approved treatment. If such a justification can be made, then the non-approved therapy is allowed to continue. If no justification is provided, the prescriber is required to change the therapy to one of the approved therapies on the list. The messages to and from the prescriber can be sent in any medium, but are preferably in the form of an electronic mail message, or displayed with a patient's laboratory results stored on a computer database, which is accessed by the physician to determine the results of laboratory tests (such as culture and sensitivity studies). Each departure from the approved therapies is recorded, and sorted by prescriber. A report can then be generated, for a given time period, of the number of departures from approved protocol therapies by each prescriber. This information can be used as an educational tool for the prescriber, or as an indicator of unwanted medical resource utilization patterns. Drug Protocol Development for Non-Infectious Diseases Although the example of Table III shows a list of treatments for an infectious disease (pneumonia), the computer system of the present invention can also be used to evaluate and recommend treatments for non-infectious diseases as well. A sample screen of some DRG descriptive listings is shown in Table V, followed by a disease condition code.
TABLE V
______________________________________
CRANIOTOMY- AGE GREATER THAN EXCEPT FOR TRUAMA 110
CRANIOTOMY- AGE GREATER THAN EXCEPT FOR TRUAMA 111
CRANIOTOMY- AGE GREATER THAN EXCEPT FOR TRUAMA 112
CRANIOTOMY- AGE GREATER THAN EXCEPT FOR TRUAMA 113
CRANIOTOMY- AGE GREATER THAN EXCEPT FOR TRUAMA 114
TREATMENT OF CHRONIC ANGINA 115
______________________________________
In the illustrated example, Treatment of Chronic Angina is associated with code 115. That code may then be entered to retrieve the record shown in Table VI, which lists the approved treatments for this disease condition. This retrieved record also displays the allowable expense permitted (under Medicare guidelines) for treatment of this condition. The allowable expense entry may be an indication of either the total charge permitted for treating the patient, or the total cost of drug treatment budgeted under the relevant DRG.
TABLE VI
______________________________________
DRG CODE: 115
DRG ALLOWABLE EXPENSE: $454.35
DRG DESCRIPTION: TREATMENT OF CHRONIC
ANGINA
DRG DRUGS
DILTIAZEM PROPANOLOL CARDIZEM
VERAPAMIL TIMOLOL
______________________________________
Protocol Development and Data Flow in Hospital Environment FIG. 2 is a flow chart that illustrates the overall function of the computer implemented system of the present invention. In this method, a physician or other health care provider (which for purposes of convenience will be collectively referred to as a physician) makes a diagnosis (as shown in step 10) by traditional means, such as physical examination and laboratory data. In step 12, this diagnosis is entered into the hospital record as an order, which is then transferred to a computerized medical record system. When the diagnosis is entered into the computer (either by the physician or a clerk), the diagnosis is matched with a DRG for hospital billing purposes. Assignment of the DRG can be made by a billing specialist, the physician, or by a computer program as described in U.S. Pat. No. 5,483,413 or U.S. Pat. No. 4,667,292. Once the DRG is established, either at the time the patient is admitted to the hospital or later, a DRG protocol 14 is presented on a computer screen for the physician to review at step 16. The DRG protocol lists the recommended treatments (or the treatments approved by a hospital or other committee) for the physician to review before writing an order for treatment. After reviewing the protocol, the physician writes an order (at step 18) to treat the patient. (Alternatively the order can be written immediately after the diagnosis is made, without first consulting the DRG protocol 14). The order often takes the form of a direction that a particular medication be given to the patient. That drug order is then communicated to the pharmacy at step 20 (for example via a hospital computer network), and the pharmacist reviews the drug order at step 22. The pharmacist also reviews the DRG protocol at step 24, and may also perform optional reviews at step 26, for example by consulting databases such as 28a (linked to patient records 29) containing patient laboratory data, clinical drug database 28b which contains drug information, drug inventory and cost database 28c, drug administration cost calculation program 28d, drug interaction database 28e (which also consults patient records 29 to detect any drug interactions with medications already prescribed to the patient which are listed in the patient record), and dosage calculation program 28f which calculates appropriate doses of medication based on patient information (such as weight and renal function retrieved from patient records 29). Dose calculations are often needed to determine the appropriate dosage of a drug according to patient weight or in view of comorbid conditions (such as renal failure). If this pharmacist review indicates that the physician order entered at step 18 varies from the DRG protocol recommendations, or if other problems are noted, then at step 28 a message 30 is sent to the physician to call attention to this variance or problem. If no such problem is noted, then the order is filled at step 32, and the prescribed treatment is given to the patient. It will be apparent from the foregoing description that a DRG protocol must be developed as part of the process shown in FIG. 2. As the name of the protocol indicates, the protocol is developed with reference to a DRG (or an ICD or other accepted disease category). The DRG is the preferred means of categorizing the protocols, because the DRG is also associated with reimbursement information. This reimbursement information helps provide financial information to the hospital (or health care provider) which may help assist in the selection of an appropriate treatment for a DRG condition. However, the drug protocol is also a starting point from which more effective and efficient protocols can be developed, because the present invention continues to gather information about the effectiveness, side-effects and cost of the drugs on the protocol, as applied to the particular population being served by the pharmacy or hospital. This continuing collection of information is then used to modify the protocol, for example by eliminating drugs that are poorly tolerated by the population served, or are found to have an inadequate clinical effect. The protocol development process is summarized at step 36 in FIG. 2. The protocol is developed by preparing a recommended list of drugs for each DRG condition, for example based on clinical experience and recommendations in the medical literature. Lab protocols are also devised, and set forth the laboratory tests that should be performed to effectively evaluate a patient presenting with a particular clinical condition without wasting clinical resources. A set of standards for evaluating the effectiveness of the protocol treatments and laboratory tests is also developed, and these standards help direct the collection of data that will be used in evaluating and modifying the protocols. A specific example of information considered for each of these steps, when developing a DRG protocol for essential hypertension, is shown in Tables VII-X. The protocol development will usually involve the identification of goals or objectives of treatment, and standards for diagnosis, including clinical findings and recommended laboratory investigations (Table VII); a general statement of treatment strategies (Table VIII); and a record of pharmaceutical agents that are possible treatments along with associated costs of administering those treatments (a exemplary partial listing of some of these treatments and associated costs is shown in Table IX). Based on the information in Tables VII-IX, guidelines are prepared for selecting initial therapy (Table X), based on the clinical setting (patient history, including comorbid conditions such as angina pectoris and renal disease) in which the drug is to be used. Although not shown in the Tables, selected drug interactions with antihypertensive therapy, and known adverse drug effects, would also be taken into account in developing the protocol.
TABLE VII
______________________________________
INDICATIONS, GOALS, OBJECTIVES OF THERAPY
1. Goal: Treatment of hypertension to prevent morbidity and mortality
associated with high blood pressure and to control blood pressure by
the least intrusive means possible.
2. Indications: Systolic blood pressure of 140 mm Hg or greater and/or
diastolic blood pressure of 90 mm Hg or greater.
3. Repeated blood pressure measurements will determine whether initial
elevations persist and require close observation or prompt
attention,
or whether they have returned to normal and need only periodic
remeasurement. Initial blood pressure readings that are markedly
elevated (ie, a DBP of .gtoreq. 120 mm Hg or an SBP of .ltoreq. 210
mm Hg)
or are associated with evidence of target-organ disease (heart,
kidney,
brain, and large arteries) may require immediate drug therapy. The
timing of subsequent readings should be based on the initial blood
pressure as well as previous diagnosis and treatment of
cardiovascular
disease and risk factors.
4. Recommendations for follow-up based on initial set of blood pressure
measurements for adults:
Initial screening BP, mm Hg
Systolic
Diastolic
Follow-up recommended
<130 <85 Recheck in 2 years
130-139
85-89 Recheck in 1 year
140-159
90-99 Confirm within 2 months
160-179
100-109 Evaluate or refer to source of care within 1 month
180-209
110-119 Evaluate or refer to source of care within 1 week
.gtoreq.210
.gtoreq.120
Evaluate or refer to source of care immediately
5. Laboratory tests and diagnostic procedures to be performed before
therapy is initiated include: urinalysis, complete blood cell count,
blood glucose (fasting, if possible), potassium, calcium,
creatinine,
uric acid, cholesterol (total and high-density lipoprotein) and
triglyceride levels; and electrocardiography.
______________________________________
This information is then used to recommend laboratory protocols (which are laboratory tests that should be performed before initiating treatment for each condition), and a recommended list of drugs will then be prepared for each DRG condition. Such a list is shown in Table VI. Each medication can be ranked based on a review of the medical literature, a consideration of the adverse effects of the medication, and an analysis of the cost of treating a DRG condition with that medication. The recommended medications can be ranked, for example, on the basis of a formula that takes into account the following factors: A=cost of medication per unit (e.g. cost of package divided by number of pills per unit) B=Average times drug administered per day C=Cost of administration by nursing personnel (averaged monthly) D=Cost of dispensing by pharmacist (average time per pill/unit) E=A+B+C+D The medications may be ranked in order by E result, with medication regimens having lower E rankings being ranked as more preferable. Adverse effects of drugs Q may also be taken into consideration by considering such factors as: a=number of adverse effects reported for this medication b=pharmacy interventions required to correct medication errors c=medication errors reported Q is then calculated by Q=a+b+c. Other additional factors that are considered important to determining the adverse effects of the drug may of course be added to the E or Q calculations. The ranking of the medications may be determined by calculating the sum R=E+Q, with the drugs being ranked from lowest score to highest score. Medications having the lowest score are considered the preferred treatments that are at least initially recommended in the DRG protocol. It is a particular advantage of the present invention that information used to calculate the numerical medication score R is continually collected and used to update the rankings. For example, changing costs of the medication will be entered into the cost equation E, which will ultimately change the ranking score R. Similarly, an increase in adverse effects detected by the data collection aspect of this program will change the Q score, which can also affect the R score. An example of a changing pattern of adverse effects could be that the racial composition of the population being treated changes, and that new racial group has a poor biochemical tolerance for the medication that is ranked first. This demographic change in the population served by the hospital (or other health care delivery organization) will be reflected in the rankings, which will change to better serve the new population. Many DRG categories will have several protocol treatments for the DRG condition, with the treatments ranked in order of preference (usually by the R score). However, the R score alone will not always control the treatment selected. Some treatments, for example, will be inappropriate for certain racial minorities within the population served, or patients older than a certain age, or patients who suffer from a comorbid condition such as unilateral renal artery stenosis. At other times, the highest ranked treatment will fail in a particular patient. These situations can be addressed by IF statements in the ranking program. For example, if the DRG condition is essential hypertension and the top ranked treatments (by R score) are: 1. ACE (angiotensin converting enzyme) inhibitor 2. Diuretic 3. Beta Blocker then demographic and clinical information entered into a patient record 29 will be consulted before a final recommendation for the patient is made. As shown in FIG. 3, a IF statement would contain a series of statements that would fig establish contraindications for the use of an ACE inhibitor. Hence if the patient was black, at least 65 years of age, or diagnosed with renal failure (or renal artery stenosis), then the second ranked drug in the protocol is automatically established as the top ranked drug. A reason for this change in the ranking is then displayed to the physician or pharmacist (e.g. "ACE inhibitors should not be used in patient with renal artery stenosis"). Each subsequent drug that is then ranked first is similarly evaluated by the program for clinical contraindications. For example, if the patient with renal artery stenosis also suffers from reactive airway disease or heart block, then the beta blocker may be removed from the list (with the appropriate reason displayed). An automatic re-ranking of the protocol treatments can also occur if the individual patient has not responded to the top ranked therapy. For example as shown in FIG. 4, if the drug in Class A fails to meet the goals established in the protocol in a preselected period of x days, then the next preferred class is automatically ranked over the previously preferred class. Hence if the patient is treated with an ACE inhibitor, and after 5 days of treatment the systolic blood pressure (SBP) is greater than 140 or the diastolic blood pressure (DBP) is greater than 90, then the rankings are reordered to rank the second preferred class of treatment (diuretic) as the top ranked therapy. The percentage of such treatment failures is also calculated, and may be used as a factor in re-ranking the therapies. An example of a record prepared by this process is shown in Table XI, which is indexed by the DRG Heading Code 133 for Treatment of Essential Hypertension. Table XI illustrates that the DRG Total Allocation (total allowed expenditure for the hospital treatment of the condition) is displayed as part of this record to help inform the selection of drugs and other treatments that are within the allowed expenditures.
TABLE XI
______________________________________
DRG PROTOCOL
______________________________________
DRG HEADING CODE: 133 DRG TOTAL ALLOCATION: 1456.54
DRG NAME CODE: 102.44
DRG MAIN DESCRIPTION: Treatment of Essential Hypertension
DRG SUB GROUP CODE: 1113.45
DRG SUB GROUP DESCRIPTION: Treatment of Essential Hypertension
DRG MEDICATIONS
Captopril (1) Hydrochlorothiazide(2) Propanolol(3)
Nifedipine (4) Guanabenz(5) hydralazine(6)
DRG MEDICAL REVIEW
To Prevent Morbidity and mortality. Use repeated blood pressure
measurements. Initial BP DBP>120 or SBP>120 evidence of end
organ disease require immediate therapy. See chart for
screening recommendations. Treat with life style modifications,
drugs classes includes diazides, ACE inhibitors, beta blockers,
alpha adrenergic inhibitors.
______________________________________
The DRG medications that are part of the protocol are then displayed in ranked order, with the rank displayed after the drug name. Captopril (an ACE inhibitor) is listed first, with the designation (1) indicating that it is the first choice according to the protocol ranking result R. Hydrochlorothiazide (a diuretic) is listed second, with the designation (2) indicating that it is the second ranked drug according to the protocol ranking R. Propranolol (a beta blocker) is listed third, with the designation (3) indicating that it is the third choice according to the ranking R. Nifedipine (a calcium channel antagonist) is similarly ranked fourth, guanabenz (a sympatholytic agent) is ranked fifth, and hydralazine (a direct vasodilator) is ranked sixth. According to the DRG Protocol for essential hypertension, captopril would be selected as the drug of choice for this condition. If a physician orders a drug that is not listed on the protocol (such as the alpha adrenergic blocker Prazocin), or does not enter the top ranked drug, a message is sent to the physician stating that a non-protocol drug has been selected, and a justification for this variance is requested. Absent appropriate justification, the variance is not allowed, and the order is changed to the appropriate protocol drug. If the patient is black, the protocol drugs will be automatically reranked, so that captopril (an ACE inhibitor) will be automatically eliminated from the listing (FIG. 3), because a diuretic remains the first choice therapy in these patients, and an ACE inhibitor is less likely to be cost effective. Similarly, if the patient has unilateral renal artery stenosis, which is an absolute contraindication to administration of an ACE inhibitor, then the ACE inhibitor is also automatically eliminated from the rankings. Blood pressure readings of the patient are taken in the hospital, for example three times a day or more, to monitor response to anti-hypertensive therapy. If the protocol requires that a response to the first ranked therapy be demonstrated in three days, then the patient's blood pressure (both systolic (SBP) and diastolic (DBP) is entered in response to a prompt automatically displayed on a computer screen on the third day of hospitalization. If the SBP or DBP are above the desired levels at that time (e.g. SBP 140 or DBP 90) then the protocol drugs are reranked by eliminating the top ranked drug (captopril), and now showing the diuretic (such as hydrochlorothiazide) as the top ranked drug. A message can be sent to the prescriber noting that the protocol now has changed the rankings of the drugs, and asking if a drug change will be made. The prescriber is then given an opportunity to justify not following the protocol, and if the justification is not forthcoming, the drug will be changed to the new top ranked drug (the diuretic). Automatic Collection of Adverse Drug Reactions Another of the advantages of the present invention is that it can monitor adverse drug reactions to drugs as treatment progresses, and use that information to modify the DRG protocol treatments. An Adverse Drug Reaction Form can be accessed through a menu, and the menu prompts the user to identify the drug to which the adverse reaction has occurred, the class of drug to which the medication belongs, select the type of reaction that has been observed (from a list of choices), and quantify the clinical seriousness of the reaction. An example of the Adverse Drug Reaction Form is shown in Table XII.
TABLE XII
__________________________________________________________________________
ADVERSE DRUG REACTION REVIEW FORM
__________________________________________________________________________
PATIENT ID#: 6893
6893 LEET RUSTY
PRESCRIBING PHYSICIAN: Weston, Mark
DISCHARGE DATE:
1. TYPE OF REACTION:
SKIN/DERMATITIS
NAUSEA/VOMITING
ANAPHYLAXIS
CARDIAC DYSRHYTHMIA
DROWINESS
OTHER-PLEASE DESCRIBE
ANSWER: SKIN/DERMATITIS
2. NAME AND CATEGORY OF DRUG CAUSING ADVERSE DRUG REACTION
ANALGESIC AGENT ANTI-SEIZURE AGENT
OTHER-PLEASE SPECIFY
CARDIOVASCULAR AGENT
CNS AGENT
ANTIMICROBIAL AGENT
HYPNOTIC AGENT
CHEMOTHERAPY AGENT
ANTI-INFLAMMATORY
DRUG NAME: PENICILLIN 500 MG VK PO DRUG CLASS:
PRESS F2 TYPE IN GENERIC DRUG NAME THEN HIT ENTER
__________________________________________________________________________
The generic name of the drug (for example penicillin) is then entered, which causes a menu of possible penicillin preparations to be displayed. The specific drug that has caused the reaction (for example Penicillin 500 mg VK PO) is then selected from the menu (Table XIII).
TABLE XIII
______________________________________
PENICILLIN 2 MU IV/IM PENICILLIN
PENICILLIN 500 MG VK PO UD PENICILLIN
PENICILLIN 5 MU IV/IM PENICILLIN
PENICILLIN G BENZATHINE/PROCAINE 900/300 INJ PENICILLIN
CHEMOTHERAPY AGENT ANTI-INFLAMMATORY
DRUG NAME: PENICILLIN 500 MG VK PO DRUG CLASS:
______________________________________
The class of drugs (penicillin) is then either automatically retrieved, or is entered from a walk through menu by the user. A list of categories of reaction severities is then displayed, as shown in Table XII, and a category of reaction is selected by number. The menu selections vary from category 1 (reaction only anticipated but not clinically evinced) to category 4 (injury severe, not resolved prior to discharge). An example of a category 4 injury would be an anaphylactic reaction with respiratory compromise and a permanent neurological insult.
TABLE XIV
__________________________________________________________________________
ACUITY/SEVERITY OF REACTION (PLACE A NUMBER IN THE `ANSWER` BOX)
1. CATEGORY 1:
INJURY/EFFECT OF REACTION ANTICIPATED
2. CATEGORY 2:
INJURY/EFFECT MILD/TRANSIENT, RESOLVED RAPIDLY
3. CATEGORY 3:
INJURY MODERATE, RESOLVED PRIOR TO DISCHARGE BUT
REQUIRED SIGNIFICANT INTERVENTION OR PATIENT WAS
GIVEN A DRUG TO WHICH THE PATIENT WAS KNOWN TO BE
ALLERGIC
4. CATEGORY 4:
INJURY SEVERE, NOT RESOLVED PRIOR TO DISCHARGE
ANSWER: 3
CATEGORY 3: INJURY MODERATE, RESOLVED PRIOR TO
DISCHARGE BUT REQUIRED SIGNIFICANT INTERVENTION OR
PATIENT WAS GIVEN A DRUG TO TREAT REACTION
COMPLEXITY OF CASE: SELECT ONE:
1. HIGH 3. LOW
2. MODERATE
ANSWER:
__________________________________________________________________________
As shown in Table XIV, a menu entry is also prompted for the complexity of the case, i.e. high, moderate or low. The information gathered in this part of the program is then used to modify the ranking of the protocol drugs. In addition to actual adverse reaction information, data is also collected on clinical interventions that are required when an order contains a medication error. Clinical interventions refer to an action, usually taken by a pharmacist when reviewing an order that has been entered into the hospital record, to correct a medication error. Table XV shows a clinical intervention form displayed in accordance with the present invention, which categorizes types of medication errors that require intervention:
TABLE XV
__________________________________________________________________________
CLINICAL INVERVENTION FORM
__________________________________________________________________________
PATIENT ID #: 6893 6893 LEET RUSTY
DATE: 7/14/97 TIME: 1400 NURSING UNIT: 2N M.D.: Weston, Mark
TYPE OF INTERVENTION: (PLEASE WRITE IN AS MANY AS APPLY)
A.
INCORRECT PATIENT K.
DUPLICATE THERAPY
T.
IV/PO CONV
B.
INCORRECT ADMINISTRATION SCHEDULE
L.
TPN U.
NO D/C QTY
C.
ADMINISTRATION SCHEDULE CHANGE
M.
INCORRECT ROUTE
V.
DIRECTION
D.
FAILURE TO DISCONTINUE A MEDICATION
N.
NO ROUTE CHANGE
E.
ADVERSE DRUG REACTION O.
ILLEGIBLE ORDERS
W.
OTHER
F.
INCORRECT FREQUENCY P.
PCA
G.
INCORRECT DOSE Q.
ALLERGY
H.
MUE (SPECIFY) R.
NO DRUG STRENGTH
I.
NONFORMULARY (FREQUENCY, DOSE ROUTE)
S.
CONSULT
J.
ROUNDS (SERVICE)
ANSWERS:
1. G INCORRECT DOSE
2. .sub.-- --
3. .sub.-- --
PRESS F2 AND SELECT INTERVENTION THEN PRESS ENTER
__________________________________________________________________________
In the example shown in Table XV, "G" is entered to indicate that an incorrect dose was prescribed. The user is prompted to select another screen (Table XVI), which displays a menu of interventions from which the user selects the intervention that was performed.
TABLE XVI
______________________________________
OUTCOME DUE TO INTERVENTION
A. MORE APPROPRIATE DOSING REGIMEN
C. FINANCIAL
B. PREVENTION OF ALLERGIC REACTION
D. OTHER
ANSWERS:
1. A MORE APPROPRIATE DOSING REGIMEN
2. .sub.-- --
3. .sub.-- --
RECOMMENDATION
CHANGE IN DOSE RECOMMENDED
RECOMMENDATION WAS (ACCEPTED) (REJECTED): ACCEPTED
COMMENTS
TIME INVOLVED: COST SAVINGS: $0.00 PHARMACIST:
______________________________________
The next screen asks for the suspected outcome without intervention, and prompts to enter one of the categories of suspected outcome, as shown in Table XVII.
TABLE XVII
______________________________________
SUSPECTED OUTCOME WITHOUT INTERVENTION
A. CRITICAL/LIFE THREATENING
E. ALLERGIC REACTION
B. DELAY IN THERAPY
F. OVERDOSE
C. FINANCIAL G. SUBTHERAPEUTIC DOSE
D. NONE G. OTHER
ANSWERS:
1. F OVERDOSE
2. .sub.-- --
3. .sub.-- --
DESCRIPTION OF SITUATION
______________________________________
The clinical interventions in each category are summed for each drug in the protocol, as shown in Table XVIII.
TABLE XVIII
______________________________________
Viewer
______________________________________
ADMINISTRATION SCHEDULE CHANGED
1
ADVERSE DRUG REACTION 2
ALLERGY 15
CONSULT 6
DUPLICATE THERAPY 11
FAILURE TO DISCONTINUE A MEDICATION
9
ILLEGIBLE 2
ILLEGIBLE ORDERS 7
INCORRECT ADMINISTRATION SCHEDULE
7
INCORRECT DOSE 16
INCORRECT FREQUENCY 12
INCORRECT PATIENT 3
IV/PO CONVERSION 1
NO DISCONTINUED QUANTITY 1
NO DRUG STRENGTH 13
NO ROUTE 3
______________________________________
The number of interventions required for each drug are an indication of the potential problems that can arise in the use of the drug. The user is also prompted to categorize the reaction as avoidable, unavoidable, or possibly avoidable, as shown in Table XIX. An avoidable reaction is one that could have been avoided based on available clinical information (drug given to patient in spite of known allergy). An example of an unavoidable reaction is an unanticipated anaphylactic reaction to a drug in a patient who had received the drug before without an adverse reaction. A example of a possibly avoidable reaction is a drug reaction in a patient who had not received the drug before, but had previously exhibited an allergy to a similar drug in the same pharmaceutical class.
TABLE XIX
______________________________________
MORBIDITY/MORTALITY CATEGORY: SELECT ONE
1. AVOIDABLE REACTION
2. UNAVOIDABLE REACTION
3. POSSIBLY AVOIDABLE REACTION
ANSWER: 1 AVOIDABLE REACTION
______________________________________
The distribution of severity levels of the medication errors can also be displayed to further quantify the problems encountered with clinical use of the drug (Table XIX). This information is automatically collected by the computer system of the present invention, and used to change the drugs recommended in the protocol. For example, the two cardiac glycosides digitoxin and digoxin may be available in a protocol for treating heart failure. Digoxin requires glomerular (renal) filtration as its major mode of elimination from the body, while digitoxin uses hepatic metabolism as its major mode of elimination. Hence the dose of digoxin must be reduced in patients having a creatinine clearance of 10-50, while the dose of digitoxin need not be reduced. The incidence of dosing errors may be found to be much greater with digoxin, particularly in an environment with a high percentage of patients in renal failure (such as a kidney transplant center). Hence an unacceptably high number of digoxin dosage errors may be identified in this center, which information may be used to rank digitoxin higher than digoxin. This is an example of the ability of the computer system to identify particular drug problems in a local population being served, and use that information to modify protocols to fit the particular needs of the special population. Departure from Protocol Treatment An example of the ability of the program to detect departures from the protocol drugs, and warn the prescriber of this departure, is illustrated in the example of treating the DRG condition "Chronic Angina." Prior to entering any drug data, the DRG code for Chronic Angina is entered, which points to the approved protocol for treating this condition, and displays it as shown in Table XX.
TABLE XX
__________________________________________________________________________
TREATMENT OF CHRONIC ANGINA ADMINISTRATION RECORD
PNEUMONIA (>40 YRS W/UNDERLYING ALC.,DIA., CHF)
IDENTIFICATION#: 6893
N ROOM#: 104-1
PHYSICIAN:
Weston, Mark
LAST NAME: LEET
FIRST NAME: RUSTY WT: 75
DIET: 22:53:58
ALLERGIES: furosemide
DIAGNOSIS: REPORT:
DISCHARGE DATE:
ACTIVE: y NOTES: n PLEASE REVIEW DRUG TH
##STR1##
__________________________________________________________________________
The user is then prompted to enter the therapy selected for treating this condition, which in Table XXI (Medical Administration Record) is shown to be the ACE inhibitor captopril.
TABLE XXI
__________________________________________________________________________
##STR2##
IDENTIFICATION#: 6893
N ROOM#: 104-1
PHYSICIAN:
Weston, Mark
LAST NAME: LEET
FIRST NAME: RUSTY WT:75
22:53:58
CAPTOPRIL
12.5 MG
PO UD
E
CAPOTPRIL
25 MG
PO UD REPORT:
CAPTOPRIL
50 MG
PO AVTIVE: y NOTES: N PLEASE REVIEW DRUG
__________________________________________________________________________
THER
In this example, captopril is not on the approved protocol, which causes a message (Table XXII) to be printed on the screen (or on a print out) which warns that captopril is not in the current drug listing. Current drug cost information for captopril is also displayed, as is a list of the drugs that are in the protocol for the treatment of this DRG condition (Diltiazem, Propranolol, Cardizem, Verapamil, Timolol).
TABLE XXII
__________________________________________________________________________
##STR3##
IDENTIFICATION#: 6893
N ROOM#: 104-1
PHYSICIAN:
Weston, Mark
LAST NAME: LEET
FIRST NAME: RUSTY WT:75
DIET: 22:53:58
ALLERGIES: furosemide
WARNING- NOT IN THE CURRENT DRUG LISTING
PLEASE REVIEW DRG BEFORE ENTERING DRUG!!
DIAGNOSIS: PLEASE ENTER TO CONTINUE REPORT:
DISCHARGE DATE: ACTIVE: y NOTES: N PLEASE REVIEW DRUG THER
__________________________________________________________________________
The DRG protocol can be directly accessed, for example through a pop-up menu, such as that shown in Table XXIII, by highlighting and selecting the appropriate diagnosis which is categorized by the appropriate DRG code.
TABLE XXIII
______________________________________
CARDIOVASCULAR -A ANGINA - UNSTABLE (CRESCENDO
ANGINA)
CARDIOVASCULAR a TIMOLOL
CARDIOVASCULAR a ESMOLOL
CARDIOVASCULAR a AORTIC ARCH SYNDROME (TAKAYASU
SYNDROME; PULSELESS DISEASE)
CARDIOVASCULAR a AMIODARONE HCL
CARDIOVASCULAR a AMITRIPTYLINE AND PERPHENAZINE
CARDIOVASCULAR a SOTALOL
CARDIOVASCULAR a METOPROLOL
CARDIOVASCULAR a ANGINA PECTORIS STABLE #6
CARDIOVASCULAR a DISSECTING ANEURYSM OF AORTA
CARDIOVASCULAR a LABETALOL
CARDIOVASCULAR a ANGINA PECTORIS STABLE #5 -
CHRONIC ANGINA TMT#2
______________________________________
A general statement about the treatment of angina pectoris (stable) will then be displayed, followed by a diagnosis statement, which for example can state that either a beta blocker or calcium channel blocker is recommended initially for monotherapy. If symptoms are not adequately controlled then a combination of the 2 or 3 classes of antianginal agents is recommended. An exception would be made for clinical presentations that suggest coronary vasospasm (e.g. angina at rest), which would be treated with a calcium channel blocker. The physician or pharmacist would then be able to view current information on the best therapy for the DRG, and the drug regimens that would be followed with therapy for each of the classes of drugs. Information about each individual drug (including cost information) available from a database, can also be viewed on line in association with this information. Another significant advantage of the computer system of the present invention is that it can display comparative drug costs for the class of drugs which the physician is considering prescribing. If an ACE inhibitor such as captopril is under consideration, for example, other drugs of the same class (angiotensin converting enzyme inhibitors) are displayed together and with their costs, so that an informed decision can be made about the best and most economical treatment. An example of a display of the comparative cost information is displayed in Table XXIV.
TABLE XXIV
__________________________________________________________________________
IDENTIFICATION#: 6893
N ROOM#: 104-1 PHYSICIAN: Weston, Mark
LASTNAME: LEET
FIRST NAME: RUSTY WT:75
DIET: 22:53:58
ALLERGIES: furosemide
DIAGNOSIS: REPORT:
DISCHARGE DATE:
ACTIVE: y NOTES: N PLEASE REVIEW DRUG THER
CATAPRIL 12. N
HYPOTENSIVE QUINAPRIL
5MG ACE INHIBITOR $0.00
.sub.-- BENAZEPRIL
10MG
PO ACE INHIBITOR Y $0.97 BID
COMMENTS: GIVE 1HR A
CAPTOPRIL
12.5MG
PO UD ACE INHIBITOR Y $1.02 BID
START DATE: 07/14/97
CAPTOPRIL
25MG
PO UD ACE INHIBITOR Y $1.11 BID
START TIME: 8:00:00
LISINOPRIL
5MG PO UD ACE INHIBITOR Y $1.16 BID
T2: 8:00:00 T3: 8:0
LISINOPRIL
10MG
PO UD ACE INHIBITOR Y $1.33 BID
T7: 8:00:00 T8: 8:0
ENALAPRIL
5MG PO UD ACE INHIBITOR Y $1.44 BID
DRUG UTILIZATION REVIE
DIAGNOSIS: CAPTOPRIL
N #DISP: 0 #INV: 0 N
__________________________________________________________________________
By comparing the cost information displayed, the prescriber will be able to determine that captopril is not the least expensive ACE inhibitor, but that it is less expensive than lisinopril or enalapril. Another feature of the computer system is that it can automatically provide information needed for adjusting drug dosages, for example reducing the doses of renally eliminated drugs in patients who have impaired renal function. A specific example of such a calculation is determining creatinine clearance, by the equation: ##EQU1## Laboratory data about the patient (such as serum creatinine level) is retrieved from the patient record, as is the patient age and ideal body weight. As creatinine clearance declines in renal failure, the fraction of the usual dose of a drug that can be administered also declines. The dose fraction of the drug can be calculated by the equation: ##EQU2## where F is the fraction of the drug normally excreted unchanged in the urine. When F is not known, the ratio of normal half-life of the drug to half-life in renal failure can instead be used. Using these or other equations the maximum dosage for the drug of interest can be computed and displayed, as shown in Table XXV.
TABLE XXV
______________________________________
This patient's BSA (m2) is: 1.89692734672803
This patient's IBW is 68.4 This patient's ACTUAL WEIGHT is: 75
This patient's Creatinine Clearance is: 34.87319 Age: 63
THE MAXIMUM DOSAGE FOR THIS MEDICATION IS: 450
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Alternatively, dosage adjustments for varying levels of creatinine clearance for each drug can be available in a database, from which the recommended dosage can be determined. For example, dosing of acetaminophen would be altered by increasing the interval between normal doses as renal function declines. In a patient who has a creatinine clearance of greater than 50, the normal dose is given each four hours. For a patient in whom creatinine clearance is 10-50, dosing is increased to every six hours. If creatinine clearance is less than 10, then the dosing interval is increased to every eight hours. Similar tables can be stored for reducing the percentage of the maximum dose, for given ranges of creatinine clearance. Hence the dose of captopril may be listed as 100% if the creatinine clearance is 10 or greater, but only 50% of the dose will be calculated if the creatinine clearance is less than 10. Outcome Analysis One of the objectives of the present invention is to provide an evolving treatment strategy that takes into account information gathered by the program to modify treatment of a patient, or modification of the protocol for treatment of future patients. At its most basic level, outcome analysis can be provided on a case-by-case basis. For example, the pharmacy staff may review a physician's orders for treatment of a particular patient, and provide recommendations for changing the therapy. A sample form for this purpose (which may be displayed on a screen or printed out) is shown in Table XXVI.
TABLE XXVI
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OUTCOMES ANALYSIS FORM
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6893 6893 LEET RUSTY
PHYSICIAN: Weston, Mark ROOM#: 104-1
DEAR DR: REQUEST
The pharmacy staff at BMH has reviewed your orders on this patient and
would like to
make the following recommendations for your consideration.. -
MEDICATION/DIAGNOSIS REVIEW
OUTCOMES SUMMARY
DO YOU WISH TO PRINT
OR FAX THIS REQUEST
(ENTRY Y OR N)
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However, in a more comprehensive sense, the data collected about treatment outcomes (e.g. was blood pressure controlled within three days? did empirical treatment for pneumonia successfully treat the infection?), side-effects (e.g. anaphylaxis, hypotension, respiratory compromise), and required interventions (dosing problems, transcription errors of similarly named drugs) are used to continually evaluate and update the drugs on the protocol, and the rankings of the drugs within the protocols. It will be appreciated from the foregoing description that the present computer system provides many advantages that have not previously been available. For the first time it gives individual hospitals or geographic localities the ability to provide rational protocols for treatment of disease in its community, and a mechanism to enforce the use of those protocols. The computer system also enables data to be collected, in the community where it is used, to assess the usefulness of that protocol in that subpopulation. This departure from standards set on an average basis, at the national level, over an average period of time, permits the best medical care to be delivered to the individual patient. The pharmacologic idiosyncracies of the population being served are identified and treatment is modified to address those particular needs. The disclosed computer system can also be used to identify emerging patterns of microbial resistance, and change antibiotic prescribing patterns before the microbial resistance becomes well established. In view of the many possible embodiments to which the principles of this invention may be applied, it should be recognized that the illustrated embodiment is only a preferred example of the invention and does not limit the scope of the invention, which is more appropriately understood in view of the following claims:
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