4. determining and implementing correc- 0195 ...

RULE-BASED DRUG PRESCRIBING REVIEW INCORPORATING PATIENT CHARACTERISTICS

Stuart M.Speedie,Ph.D.; David A. Knapp,Ph.D.; Francis B. Palumbo,Ph.D.; Robert Beardsley,Ph.D.

University of Maryland School of Pharmacy

Baltimore, MD 21201 Abstract This paper describes a rule-based software system for Drug Prescribing Review (DPR) which considers patient characteristics as well as concomitant therapy and prescription parameters. Its purpose is to screen drug orders to determine if potential problems exist. This DPR system evaluates the drug order's parameters in terms of the patient's diagnoses, age, sex, laboratory test values and concurrent drug therapy. The DPR criteria are formulated as a rule-based inference system. The system is a three level hierarchy of testable assertions,rules and screens. Each screen corresponds to a misjudgment that can occur in the process of prescribing drug therapy. This DPR system is currently implemented in a 3 year study of drug use in long term care facilities as one of several factors intended to influence physician prescribing. A principle outcome of this study in 1983 will be an evaluation of the effectiveness of rule-based, computerized DPR in influencing the physician's prescribing behavior in long term care facilities.

2. provide

high quality therapy nomically as possible.3

DUR is a feedback process which involves several steps: 1. determining "optimal" drug use, 2. measuring actual drug use, 3. making comparisons between "optimal" drug use and actual use, 4. determining and implementing corrective action for discrepancies, and 5. remeasuring actual drug use. The steps are the same regardless of the setting of the review. It can be a statewide Medicare program, a neighborhood health center, a regional professional standards review organization or an in-hospital system. Drug Prescribing Review(DPR) is currently a major area of activity within the larger area of drug use review. DPR focuses only on the quality of physician's decision in prescribing drug therapy. Ideally, DPR evaluates the appropriateness of the drug, the dose, the regimen and other prescription parameters in terms of the individual patient and their total drug therapy. The goal of DPR as with DUR is to improve the quality of the physician's decision making through examination of prescribing patterns and the development and implementation of suitable corrective actions. There are two major types of drug prescribing reviews. The first is best described as an indepth review, in which individual drug orders are exhaustively reviewed. This review takes into account the characteristics of the drug therapy in order to arrive at a clinical judgment as to the appropriateness or inappropriateness of the specific drug order. As such, it is an individualized, expert clinical review of each drug order. In-depth review in DPR is a comprehensive, time consuming process which results in a definitive decision for a given drug order for a given patient. The second type of DPR is best described as a screening review. In contrast to in-depth review, a screening review is not intended to arrive at a definitive judgment about a particular drug order. Rather, it attempts to identify drug orders which are potentially inappropriate. Screening review is a "gross" measure of prescribing quality which relies on general guidelines for appropriate prescribing rather than on a final decision using professional clinical judgment. Obviously, screening is a simpler and less exhaustive process than in-depth review. However,

Introduction The drug use process encompasses physician prescribing, pharmacist dispensing and patient use of drugs. The importance of the drug use process in health care is evidenced by the fact that two of every three outpatient physician visits result in at least one prescription order and that the average American obtains over 5 prescription orders a year.1 Thus drug utilization review, the methodology which evaluates the quality of the drug use process, is an important component of any health program's quality assurance effort. In its broadest sense, drug utilization review(DUR) is defined as the review of physician prescribing, Sharmacist dispensing and patient use of drugs. The purpose of DUR is primarily education; the more we know about how specific drugs are used, the easier it is to determine how such use may be optimized. In addition to the improvement of the quality of the drug use process, DUR also may lead to cost savings for a health program by uncovering situations in which less expensive therapy may be used with equal or better results. Thus the twin goals of DUR are to:

1. encourage optimal drug use, and *Work supported by NCHSR Research Grant No. 1 R18-

HS03305-1

0195-4210/80/0000-0957$00.75

a 1980 IEEE

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screening review has demonstrated its usefulness for evaluating programs which focus on prescribing patterns of physicians.4*5 The development of "optimal" drug prescribing guidelines or criteria is a critical activity in screening type DPR. Criteria development is a multi-stage process involving a thorough literature search, and multiple draft-review-revision cycles. Ideally, these criteria should specify: a) appropriate indications, b) acceptable dosage ranges, c) acceptable quantity ranges, d) appropriate regimens, e) required and contraindicated concomitant therapy, f) required m'onitoring, and g) the impact of relevant patient variables.6 Unfortunately, the automated DPR systems such as that described by Helling7 most often have not incorporated all the desirable components of criteria. Judgment concerning patient characteristics as it relates to appropriate indications and other relevant patient variables is either left to "professional judgment" or not included at all. The exception to this statement is the work reported by Maronde in which some diagnostic information was included in their automated DPR system.8 Even that system, however, did not take advantage of the full range of information available in the patient record. The challenge, then, is to develop a computerbased DPR system which incorporates these patient factors into the criteria, in order to more closely approach the ideal DPR system. It should be evident from this discussion that the criteria are the core of any DPR system. Their formulation and implementation are the key to system quality. Thus any computer-based system must develop procedures which are capable of evaluating all the components of ideal criteria. DPR Screening Criteria and Rule-Based Systems In the process of examining and working with DPR it became evident that the evaluation process in DPR was an instance of a pattern directed inference system as described by Waterman and HayesB.oLb.. 9 Patterns in the data (prescriptions and patient records) trigger the use of particular sets of criteria for judging the quality of the physicians' drug therapy decision making. Furthermore, the criteria themselves are components of a rule-based system; a pattern directed inference system where the system consists of rules or antecedent-consequent pairs. DPR criteria are generally stated in the form "for digoxin to be appropriate there should be an indication of chronic heart failure". This is easily recast into the antecedent-consequent form by restating it as "if there is an indication of chronic heart failure and the prescribed drug is digoxin, then the prescription is appropriate with respect to indication". This latter statement also indicates another characteristic of DPR criteria in that they can be formulated in complex patterns of antecedent-consequent pairs much in the same manner as one constructs logical statements in symbolic logic. In fact, almost all DPR criteria can be stated in terms of the "if A,then prescription is appropriate", where A is a logical statement involving the symbolic logic operators "AND, "OR" and "NOT".

This latter fact also leads into the area of artificial intelligence and the work done by Shortliffe with MYCIN.lU This is a program which is used to arrive at decisions by the operation of a rule-based system in response to data patterns. MYCIN evaluates a system of antecedent-consequent rules in order to reccmend decisions in antibiotic therapy. It appears that a DPR has much in common with the MYCIN approach to medical decision making, with the exception that diagnoses are assumed to be correct at the starting point. Examining DPR in this light indicate that it is essentially a post hoc evaluation of medical decision where the physician's decision is compared to a decision reached by using "optimal" criteria. Therefore, it appears reasonable to the authors that one should be able to apply the techniques used in the MYCIN system to the DPR process. It should be possible to design a computer-based system for DPR which employs a rule-based criteria system to search for patterns within drug orders and the patient's medical record in order to arrive at a decision about the potential inappropriateness of a given drug order. This conceptualization of DPR results in an important advantage for the computer system - the rule-based inference system is separate from the programs used to process it. Thus the criteria are independent of the rule-processing programs. This greatly enhances the generalizability of the system, since any criteria which can be formulated in terms of a rule-based inference system can then be evaluated without modifying the processing system. Methodology The current implementation of this DPR system consists of three major components: the patient data base, the criteria, and the processing system. The patient data base is derived from a larger project which is based in long term care facilities. The data base is structured to correspond to the types of medical records which occur in those institutions. Figure 1 outlines the information contained in the data base. The patient demographic data consists of the age and sex of the patient. The patient condition data essentially contains all available medical information about the patient. The drug therapy data and the other therapy data describe all the therapeutic measures which are being undertaken for the individual patient. Since the project will be in operation for over two years, all data is time sequenced within the data base. It is important to note that in this first version of the DPR system all data is coded according to a scheme developed for this project, and currently does not correspond to any of the standard schemes for coding diagnosis or drug information. It is anticipated that in future versions of the system standard coding schemes will be employed. The second component of the system, the criteria were developed for each generic drug entity under consideration in the project. The criteria for each drug entity consist of a set of screens, each of which focuses on one type of problem which can occur in the prescribing of that drug. Figure 2 describes the types of screens which exist for each drug.

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I. II.

III.

-

IV.

level are simple assertions about the patient or the drug entity.

Patient Demographic Data - Age - Sex Patient Conditions - Diagnosis - Other symptoms/conditions - Allergies - Dietary restrictions - Sensitivities (drug and other) - Laboratory values Patient Drug Therapy (for each drug) - Product name - Generic drug - Start date - Stop date

Digoxin Criteria: The dosage should be less than or equal to .5mg unless patient suffers from renal failure, in which case dosage should be less than or equal to .25mg.

DRUG:

DOSAGE SCREEN: If Rl OR R2,then drug order passes screen RULES: Rl: Al AND (NOT A3) A2 AND A3 R2:

Dose

Regimen Monitoring Instructions Prescribing Physician Other Therapy - Nursing Procedures - Special Therapy Figure 1.

ASSERTIONS:

Al. A2.

Patient Data Base

A3. Name I. Indication

II. Dosage III. Regimen

IV. Contraindications V. Required Concurrent Therapy

VI. Unacceptable Concurrent Therapy

Explanation Acceptable disgnosis or symptom present. Dose is within range of acceptable doses for drug. Instruction for drug use are acceptable in terms of frequency, timing and daily quantity. Diseases or conditions which contraindicate use of this drug are not present. Required supportive or concurrent therapy is ordered or already in patient's record. Drug or other supportive therapy contraindicated with this drug is not present and

Figure 3.

Monitoring Figure 2.

Simplified Drug Screen

Each assertion can be evaluated against the patient data base to determine its truth value. The second level consists of rules. Rules are logical combinations of assertions. These rules are constructed as symbolic logic statements using the "AND", "OR", and "NOT" operators. Finally, screens are logical combinations of rules using the same logical operators as rules. The reason why there is a differentiation between rules and screens is that rules may be employed in more than one screen. Thus each screen is a complex antecedent-consequent statement which can be rigorously evaluated to determine if a particular drug order is potentially inappropriate. The third component of the DPR system is the processing software. The system operates essentially in a batch mode after all current data is entered into the data base which applies to the patient under consideration. This includes all active drug orders for that patient. The software then indexes through each of the active drug orders in order to apply the DPR screens. The generic drug entity in each drug order is identified and the applicable screens, rules, and assertions are retrieved for that drug entity. The location of information in the data base as referenced by the assertions is facilitated by a "dictionary" which contains associations between the assertions references and the specific data entries in the data base. The system begins the screening process by evaluating each assertion for the generic drug entity. Then it uses the truth value of these assertions to

not ordered.

VII. Required

Dosage is less than or equal to .5mg Dosage is less than or equal to .25mg A diagnosis is renal failure

Monitoring required with this drug is ordered or part of routine monitoring. Types of DPR Screens

There are seven types of screens which are applied to each drug order. Criteria (sets of screens) for 25 drug entities have been developed as a part of the larger project. These criteria focus on digoxin, laxatives, diuretics, and internal

analgesics. Each screen is a three level hierarchy of logical statements. Figure 3 is a simplified illustration of such a screen. At the lowest

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evaluate the rules and then in turn the individual screens for that drug. The results are recorded in the data base for later use in generating DPR reports for physicians and other project uses. The system proceeds in a similar manner for each active drug order for each patient in the data base. This DPR system plays an important role in the larger project which is examining the use of drugs in long term care facilities. The system currently has two major roles. The system is used to generate DPR feedback reports for physicians on a quarterly basis. This report summarizes the prescribing habits of each physician and indicates those orders which passed the criteria and those which did not. Furthermore, the reports provide the reasons when a drug order does not pass the criteria. The second purpose of the DPR system is to accumulate evidence for the evaluation of the overall success of the project. The criterion measure is the appropriateness of prescribing by physicians. The same data which is used to generate the DPR reports is also used to evaluate the project because it is hypothesized that as a result of educational efforts the number of potentially inappropriate orders will significantly decrease.

infeasible in small scale applications. However, it is encouraging that a number of long term care facilities are now moving toward computerized record keeping systems. As these automated systems become more structured, the use of this DPR system for a number of purposes besides the evaluation of large scale experimental studies will become more feasible. A third problem encountered in developing this DPR system centers on the time required to develop criteria. The process of reviewing literature, drafting criteria, obtaining expert feedback, redrafting, and finalizing for the four classes of drugs used in this study required approximately one man-year of efforts to complete. On such a time scale the development of a set of criteria to cover the most frequently used classes of drug entities would be a task which would be momentus in nature. Thus the utility of the DPR system is also limited by the time and effort required to develop the screens necessary to evaluate drug orders. A final problem with the current DPR system itself concerns its transportability. As the system stands, the patient condition coding and drug therapy coding do not correspond to any of the currently used standard coding schemes. Thus it would be difficult to envision any widespread use of the current system. However, the project staff is aware of this problem and is working on future versions of the system which will take a more standard approach to the coding of this data. Once standard coding schemes are implemented, it should make possible the more generalized use of this DPR system. In spite of the several problems cited above, this DPR system appears to be a significant step forward in the development of computer-based DPR systems. It is also evident, however, that much additional work is required in order to bring forth a DPR system which yields consistently accurate results and is economically feasible. The primary utility of the current program lies in its ability to perform large scale DPR on selected drugs in a screening type review. In this manner it can be used to guide educational efforts toward improving drug therapy decision making and also as a tool for examining and evaluating prescribing patterns.

Discussion A number of problems have been encountered in the process of developing and implementing this DPR system. Though none are intrinsic to the rule-based inference system approach to DPR, they all have an impact on the ultimate utility of the system. Perhaps the most difficult problem arises from the fact that the quality of output from the system is dependent on the accuracy and completeness of the long term care facility's medical records. This project has had to make the working assumption that records which are available are accurate and complete in the data that they contain. However, there is some evidence to indicate that this is not always the case. Particularly in long term care facilities, record keeping can become haphazard. Though new rules and regulations promulgated by the federal government may make some headway in improving the situation, it is still important to recognise that the decisions made by the DPR system are valid only to the extent that accurate information was obtained from the medical records. A second problem which also arises from medical records concerns the effort involved in obtaining the data required forthe DPR system. The project is currently studying approximately 1,000 patients in 30 different long term care facilitiees. The criteria for drug prescribing require a great deal of information from the medical record. Most long term care facility records are currently manual systems so that a great deal of time is involved in obtaining records and sifting information from those records. The collection of this information is an expensive task in terms of personnel time. The time required to obtain the data necessary to operate this DPR system might make its use

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References Stolley, P.D. and Lasagna, L., "Prescribing Patterns of Physicians," J. Chronic Dis., 22, 395 (1969) Brodie, D.C., "Drug Utilization Review/Planning", Hospitals, 46, 103 (June 1, 1972). Knapp, D.A., Brandon, B.M., West, S. and Leavitt, D.E., "Drug Use Review - A Manual System", J. Am. Pharm. Assoc. NS13, 417 (Aug. 1973) Knapp, D.A., Brandon, B.M., Knapp, D.E., Klein, L.S., Palumbo, F.B. and Shah, Rohit, "Incorporating Diagnosis Information into a Manual Drug Use Review System"', Am. J. Pharm. Assoc., NS17, 103 (February 1977)

Brandon, B.M., Knapp, D.A., Klein, L.S., and Gregory, J. "Drug Usage Screening Criteria", Am. J. Hosp. Pharm., 34(2), (February 1977) 6. Knapp, D.A., Brandon, B.M., and West, S. "Development and application of Criteria in Drug Use Review Programs", Am. J. Hosp. Pharm. 31(7), 648 (July 1974) 7. Helling, D.K., Hepler, C.D. and Herman, R.A. "Comparison of Computer-Assisted Medical Record Audit with Other Drug Use Review Methods" , Am. J. Hosp. Pharm., 36, 1665 5.

(Dec 1979) 8.

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Maronde, R. Drug Utilization Review with Online Computer Capability , Social Security Administration, Washington, D.C., 1973. Waterman, D.A. & Hayes-Roth, F. PatternDirected Inference Systems, New York: American Elsivier, 1976. Shortliffe, E.H. Computer Based Medical Consultations: MYCIN. New York: American

Elsivier, 1976.

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