- Email: [email protected]
A Computerized Prescription Recording System
by Joseph D. McEvilla
n 1963, under the sponsorship of a demonstration grant from the United States Public Health Service, we began a pilot study to determine if the information contained on dispensed prescription orders could be collected, recorded and retrieved easily and what multiple investigational technics were applicable to this research. Through the use of developed mechanisms and with the cooperation of physicians and pharmacists in our research area, we collected this information, stored it and retrieved it utilizing unique programs specifically designed for application of data processing equipment. We have developed a methodology that meets the desired criteria of simplicity, flexibility and economy. The system has demonstrated its ability to accept all ,fields of data written by practitioners without altering conventional medical or pharmaceutical practice. It can be maintained at a desirable level of performance without highly specialized professional personnel for coding or creating computer input. Within the past three and one-half years we have collected approximately 475,000 dispensed prescription medication orders from 14 cooperating pharmacies. The medications prescribed on these orders have been written by more than 2,000 practitioners and dispensed to more than 70000 patients . Before beginning our st~dy, we obtained the unconditional endorsement of the American Medical Association, American Pharmaceutical Association, American Public Health Association, Pennsylvania ,M edical Society, Pennsylvania Pharmaceutical Association, research area medical society and pharmaceutical association, Pennsylvania Department of Health and the health department in the study site. The system of collecting, recording and retrieving prescription order information is composed of five parts. The first pint is the collection process
I
636
in which identical bodies of source material, consisting of dispensed prescription medication orders, have been collected by various experimental means and studied in terms of applicability to the system designed. Technics used to assemble the material include1. 2. 3. 4. 5. 6.
microfilm eletrostatic photocopy slow-scan television flexowriter oral dictation direct telephone communication
Of these, microfilm and electrostatic photocopy represent the most feasible methods for capturing source documents. In the largest volume pharmacies, a single pass microstatic photocopy machine has been installed. Pharmacists photocopy all dispensed prescription medication orders and mail them to research headquarters on a daily basis. Redispensed medication orders are recorded on forms provided to the pharmacy. On these, the pharmacist records only the serial number of the original prescription order, if he dispenses the same quantity and charges the same as for the original source document. If, on redispensing, he changes quantity or cost, he m!lst also record this change. The redispensed prescription medication order forms are photocopied on a weekly basis and mailed to research headquarters. The source documents and redispensed prescription order forms from all other pharmacies are collected on microfilm using a Kodak model CP20 microfilm camera. To limit the collection time to one day, we divided the pharmacies into two groups on the basis of geographical location and collected source documents on weekly trips to the research area. Within each 12-month (52-week) time period, we collected source documents 26 times from each group of pharmacies. To view .the processed microfilm of photographed source documents, we
Journal of the AMERICAN PHARMACEUTICAL ASSOCIATION
use manually operated microfilm readers (Kodak model CV). The second part of the system is coding the collected information onto a specifically designed format consisting of 80 columns across and 27 lines down, permitting one record to a line. In our procedure we utilize alpha-numeric codes for recording information obtained from prescription medication orders. Numeric codes are assigned for manufacturers, prescribers, therapeutic class, dosage form, drug, pharmacy, prescription type, age and sex. The collected information is coded into 16 fields including1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.
pharmacy code date prescription was dispensed prescription charge prescription number patient name patient address zi p code of patient prescriber's identification including medical specialty age of patient sex of patient dosage form of medication name of medication pharmaceutical manufacturer therapeutic class of drug prescribed strength of drug prescribed quantity of drug prescribed
In the third part of the system the coded information is keypunched onto data-processing cards and subsequently verified. The equipment used is an IiBM 026 card punch and an IBM 056 card verifier. The coded forms, given daily to the keypunch operators, are separated by pharmacy and placed in date order. They are then separated further into regular pres·criptions, compounded prescriptions and redispensed prescriptions. The coding sheets are then keypunched by pharmacy and date order. Afterwards the data-processing cards are placed with the appropriate coding sheet for later veriHcation. After verification the data cards are filed by pharmacy. The
code sheets are then microfilmed and the originals destroyed. Upon completion of keypunching and verification the data-processing cards are merged onto the master tape. The fourth step involves placing the coded information onto magnetic tape for storage and later retrieval by an input program which will arrange the data in a suitable format and place the English name of the drug or pharmaceutical product at the end of each record. F or the fifth and final part of the devised system information is retrieved by means of interrogation and search procedures. The electronic data processing equipment used in this project is that available in the computation and data processing center of the University of Pittsburgh-an IBM 1401/7070 and all necessary periferal equipment. By using specifically developed programs for interrogation and search, we are able to retrieve the following information1. Specific patient information consisting of the sex of the patient, the name of the drug or drugs the patient has received, the quantities received, the date the medication order was dispensed, the pharmacy from which it was dispensed, the amount charged for each individual prescription medication order and the total amount charged within a given time pe,riod such as one year. In addition, we are also able to retrieve the name of the prescribing physician for each medication order, the number of physicians prescribing medication for each patient and the therapeutic classes of the drugs prescribed. 2. Specific prescriber information consisting of the names of the patients for whom each drug or pharmaceutical product was prescribed, the quantity prescribed, the strength of the drug or pharmaceutical product prescribed, the date the prescription medication order was written, the therapeutic class of the drug, the sex of the patient and the number of times the patient had the original prescription medication order redispensed. 3. Specific pharmacy information consisting of the total number of patients served, classified as regular pay patients or patients whose medicati'on ,is paid for ·by the Department of Public Assistance; the total amount spent per patient for a given time period; the number of regular prescription medication orders dispensed per pharmacy, the number of renewed prescription medication orders by pharmacy, the number of Department of Public Assistance prescriptions dispensed by pharmacy, the average charge for regular prescription medication orders .and the average charge for Department of
Public Assistance prescription medication orders. 4. Specific drug or pharmaceutical product information ,c onsisting of the identity of each patient for whom the drug has been prescribed, the total amount each ,patient has received and the name of the prescriber. 5. Specific therapeutic class and cross-class information consisting of all drugs and pharmaceutical products within the selected cla,ss, identity of each drug or pharmaceutical product with specific patients and each patient's drug profile from which the subjunctive therapeutic classes and the drugs involved may be ascertained.
The data obtainable by means of the total system procedures has manifold applications ranging from academic to commercial. Academically, the data has usefulness in teaching pharmacy, pharmaceutical or medical economics and pharmacology. Through the data, the pharmacy student becomes aware of the actual drugs being prescribed, the quantities in which they are prescribed and the medical specialties in which various drugs are most useful; he receives an indication of what drugs and pharmaceutical products are prescribed the most frequently within therapeutic classes; he learns how many times drugs from multiple therapeutic classes are prescribed for the treatment of concomitant disease entities; he examines, under true life circumstances, the frequency with which patients visit two, three, four or more physicians concurrently. From this background he can see the importance of maintaining patient records of prescribed medications to help prevent a patient's receiving therapeutically incompatible drugs or multiple quantities of dangerous drugs without knowledge of the prescribing physicians.
In the area of pharmacology the data provides a list of drugs currently prescribed by physicians. The study of the pharmacological action of these drugs would lend a contemporary touch to the course. The available information also indicates the drugs used in primary and secondary therapy. A study of the action of these drugs and the rationale of multiple drug therapy would be of interest to all students of pharmacology. The areas of medical or pharmaceutical economics may use the data in a variety of ways to provide additional knowledge about drug utilization and expenditures. The system permits retrieval of data relative to the quantities of drugs used within therapeutic classes and the average expenditures for these classes. It is possible to obtain average expenditures by sex and age. This type of data may also be segmented into public assistance patients and pay patients in terms of average prescription cost, age, sex and specialty of prescribing physician. The procedure developed permits the recording of drugs by either trade name or generic name, depending on the prescriber's written order. This record allows data to be retrieved relative to the frequency of generic prescribing by therapeutic class, medical specialty and by actual drug prescribed. Because patient identification, either by name or assigned number, is an integral part of the system, complete drug profiles are possible. The drug profile will provide the following data on individual patients1. pharmacy from which prescribed drug was obtained 2. pay patient or public assistance patient 3. prescription number 4. prescription charge 5. date medication was ,received 6. new prescription or renewal prescription
The University of Pittsburgh has been the hub of Joseph D. M cEvilla's academic activity. Professor of pharmaceutical economics in the school of pharmacy, M cEvilla earned his BS, MS and PhD at the school and began his teaching career there as a teaching fellow in 1950. He is an assistant editor of Remington's Practice of Pharmacy and has published articles in state and national journals, including this Journal. Costs of pharmaceutical service and prepaid prescription service are two of M cEvilla's research interests. H is memberships include APhA, AMA, AACP, the American Economic Association and American Public Health Association.
Vol. NS7, No. 12, December 1967
637
IT'S .
A MATTER OF LIFE
AN BREAI
~ USE
~H~l§1
" SEAL
FIGHT TUBERCULOSIS ... EMPHYSEMA, .. AIR POLLUTIQ~, ...
638
computerized ij; system ( continued from page 637)
7. number of times original prescription was renewed 8. sex 9. age 10. identification of prescriber 11. location of prescriber 12. name of drug prescribed 13. therapeutic class of drug prescribed 14. strength of drug prescribed 15. quantity of drug prescribed 16. expenditures for any selected time period
Because data from the total universe of prescriptions dispensed from the participating pharmacies is captured and stored, it is possible to retrieve information covering the prescribing habits of not only physicians but also dentists, osteopaths, veterinarians and podiatrists. The data obtained has proved to be of interest to a variety of health research personnel. Initial use of the information available has been made by research personnel interested in the general area of health economics. Requested data has related to drug utilization and expenditures by sex, age and therapeutic class. Retrieval of similar data can be obtained by location of the patient's home, thus permitting generalizations to be made concerning utilization expenditures and therapeutic classes relating to economic environment. This type of data has been requested most frequently for patients either over 65 years of age or under 18 years of age. It is of particular interest in projecting drug expenditures by age groups and by therapeutic classes and in determining the relationship between these two variables. This data may then be used in predicting the cost of providing prescribed drug coverage through health service plans employing either government or private funds. Because all obtainable data can be separated as to pay patient and public assistance patient, it is useful not only to health economics personnel working in an academic environment but also to similar personnel working in state welfare agencies. Comparisons may be made of the types of drugs and the quantities being prescribed within therapeutic classes for each type of patient. Cost comparisons may be made between types of patients receiving drugs within therapeutic classes. Additional research data may be obtained by personal interview with patients selected at random. Inquiries may be made as to age, income, education and family size. These facts may then be correlated with drug expenditures to determine what portion
Journal of the AMERICAN PHARMACEUTICAL ASSOCIATION
of total income medical specialties utilized and to learn how far prescriber and pharmacy were from the patient's home. The data has proved useful in conducting prospective studies regarding adverse reactions to all drugs or to a selected drug or group of drugs within any therapeutic class. The procedure we have developed is predicated upon the collection of all prescriptions dispensed from participating pharmacies. Investigations into health care and drug utilization are best done by a complete and continuous study of the population in selected areas. Such studies permit a 365-day-a-year basis for determining what is being prescribed and received by patients as well as who is prescribing what. Our experience has shown that sampling technics tend to contain built in bias when only prescriptions selected from various parts of a month or a quarter year are used. Only by using the total volume of dispensed prescriptions is it possible to develop drug profiles of patients and follow the prescribing habits of practitioners . We are continuing our research in this area and hope that the developed procedures utilizing information obtained directly from the prescription order form will provide better data on the various aspects surrounding the use and misuse of drugs and pharm al ceuticals and their importance in health care. •
n 1963, under the sponsorship of a demonstration grant from the United States Public Health Service, we began a pilot study to determine if the information contained on dispensed prescription orders could be collected, recorded and retrieved easily and what multiple investigational technics were applicable to this research. Through the use of developed mechanisms and with the cooperation of physicians and pharmacists in our research area, we collected this information, stored it and retrieved it utilizing unique programs specifically designed for application of data processing equipment. We have developed a methodology that meets the desired criteria of simplicity, flexibility and economy. The system has demonstrated its ability to accept all ,fields of data written by practitioners without altering conventional medical or pharmaceutical practice. It can be maintained at a desirable level of performance without highly specialized professional personnel for coding or creating computer input. Within the past three and one-half years we have collected approximately 475,000 dispensed prescription medication orders from 14 cooperating pharmacies. The medications prescribed on these orders have been written by more than 2,000 practitioners and dispensed to more than 70000 patients . Before beginning our st~dy, we obtained the unconditional endorsement of the American Medical Association, American Pharmaceutical Association, American Public Health Association, Pennsylvania ,M edical Society, Pennsylvania Pharmaceutical Association, research area medical society and pharmaceutical association, Pennsylvania Department of Health and the health department in the study site. The system of collecting, recording and retrieving prescription order information is composed of five parts. The first pint is the collection process
I
636
in which identical bodies of source material, consisting of dispensed prescription medication orders, have been collected by various experimental means and studied in terms of applicability to the system designed. Technics used to assemble the material include1. 2. 3. 4. 5. 6.
microfilm eletrostatic photocopy slow-scan television flexowriter oral dictation direct telephone communication
Of these, microfilm and electrostatic photocopy represent the most feasible methods for capturing source documents. In the largest volume pharmacies, a single pass microstatic photocopy machine has been installed. Pharmacists photocopy all dispensed prescription medication orders and mail them to research headquarters on a daily basis. Redispensed medication orders are recorded on forms provided to the pharmacy. On these, the pharmacist records only the serial number of the original prescription order, if he dispenses the same quantity and charges the same as for the original source document. If, on redispensing, he changes quantity or cost, he m!lst also record this change. The redispensed prescription medication order forms are photocopied on a weekly basis and mailed to research headquarters. The source documents and redispensed prescription order forms from all other pharmacies are collected on microfilm using a Kodak model CP20 microfilm camera. To limit the collection time to one day, we divided the pharmacies into two groups on the basis of geographical location and collected source documents on weekly trips to the research area. Within each 12-month (52-week) time period, we collected source documents 26 times from each group of pharmacies. To view .the processed microfilm of photographed source documents, we
Journal of the AMERICAN PHARMACEUTICAL ASSOCIATION
use manually operated microfilm readers (Kodak model CV). The second part of the system is coding the collected information onto a specifically designed format consisting of 80 columns across and 27 lines down, permitting one record to a line. In our procedure we utilize alpha-numeric codes for recording information obtained from prescription medication orders. Numeric codes are assigned for manufacturers, prescribers, therapeutic class, dosage form, drug, pharmacy, prescription type, age and sex. The collected information is coded into 16 fields including1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.
pharmacy code date prescription was dispensed prescription charge prescription number patient name patient address zi p code of patient prescriber's identification including medical specialty age of patient sex of patient dosage form of medication name of medication pharmaceutical manufacturer therapeutic class of drug prescribed strength of drug prescribed quantity of drug prescribed
In the third part of the system the coded information is keypunched onto data-processing cards and subsequently verified. The equipment used is an IiBM 026 card punch and an IBM 056 card verifier. The coded forms, given daily to the keypunch operators, are separated by pharmacy and placed in date order. They are then separated further into regular pres·criptions, compounded prescriptions and redispensed prescriptions. The coding sheets are then keypunched by pharmacy and date order. Afterwards the data-processing cards are placed with the appropriate coding sheet for later veriHcation. After verification the data cards are filed by pharmacy. The
code sheets are then microfilmed and the originals destroyed. Upon completion of keypunching and verification the data-processing cards are merged onto the master tape. The fourth step involves placing the coded information onto magnetic tape for storage and later retrieval by an input program which will arrange the data in a suitable format and place the English name of the drug or pharmaceutical product at the end of each record. F or the fifth and final part of the devised system information is retrieved by means of interrogation and search procedures. The electronic data processing equipment used in this project is that available in the computation and data processing center of the University of Pittsburgh-an IBM 1401/7070 and all necessary periferal equipment. By using specifically developed programs for interrogation and search, we are able to retrieve the following information1. Specific patient information consisting of the sex of the patient, the name of the drug or drugs the patient has received, the quantities received, the date the medication order was dispensed, the pharmacy from which it was dispensed, the amount charged for each individual prescription medication order and the total amount charged within a given time pe,riod such as one year. In addition, we are also able to retrieve the name of the prescribing physician for each medication order, the number of physicians prescribing medication for each patient and the therapeutic classes of the drugs prescribed. 2. Specific prescriber information consisting of the names of the patients for whom each drug or pharmaceutical product was prescribed, the quantity prescribed, the strength of the drug or pharmaceutical product prescribed, the date the prescription medication order was written, the therapeutic class of the drug, the sex of the patient and the number of times the patient had the original prescription medication order redispensed. 3. Specific pharmacy information consisting of the total number of patients served, classified as regular pay patients or patients whose medicati'on ,is paid for ·by the Department of Public Assistance; the total amount spent per patient for a given time period; the number of regular prescription medication orders dispensed per pharmacy, the number of renewed prescription medication orders by pharmacy, the number of Department of Public Assistance prescriptions dispensed by pharmacy, the average charge for regular prescription medication orders .and the average charge for Department of
Public Assistance prescription medication orders. 4. Specific drug or pharmaceutical product information ,c onsisting of the identity of each patient for whom the drug has been prescribed, the total amount each ,patient has received and the name of the prescriber. 5. Specific therapeutic class and cross-class information consisting of all drugs and pharmaceutical products within the selected cla,ss, identity of each drug or pharmaceutical product with specific patients and each patient's drug profile from which the subjunctive therapeutic classes and the drugs involved may be ascertained.
The data obtainable by means of the total system procedures has manifold applications ranging from academic to commercial. Academically, the data has usefulness in teaching pharmacy, pharmaceutical or medical economics and pharmacology. Through the data, the pharmacy student becomes aware of the actual drugs being prescribed, the quantities in which they are prescribed and the medical specialties in which various drugs are most useful; he receives an indication of what drugs and pharmaceutical products are prescribed the most frequently within therapeutic classes; he learns how many times drugs from multiple therapeutic classes are prescribed for the treatment of concomitant disease entities; he examines, under true life circumstances, the frequency with which patients visit two, three, four or more physicians concurrently. From this background he can see the importance of maintaining patient records of prescribed medications to help prevent a patient's receiving therapeutically incompatible drugs or multiple quantities of dangerous drugs without knowledge of the prescribing physicians.
In the area of pharmacology the data provides a list of drugs currently prescribed by physicians. The study of the pharmacological action of these drugs would lend a contemporary touch to the course. The available information also indicates the drugs used in primary and secondary therapy. A study of the action of these drugs and the rationale of multiple drug therapy would be of interest to all students of pharmacology. The areas of medical or pharmaceutical economics may use the data in a variety of ways to provide additional knowledge about drug utilization and expenditures. The system permits retrieval of data relative to the quantities of drugs used within therapeutic classes and the average expenditures for these classes. It is possible to obtain average expenditures by sex and age. This type of data may also be segmented into public assistance patients and pay patients in terms of average prescription cost, age, sex and specialty of prescribing physician. The procedure developed permits the recording of drugs by either trade name or generic name, depending on the prescriber's written order. This record allows data to be retrieved relative to the frequency of generic prescribing by therapeutic class, medical specialty and by actual drug prescribed. Because patient identification, either by name or assigned number, is an integral part of the system, complete drug profiles are possible. The drug profile will provide the following data on individual patients1. pharmacy from which prescribed drug was obtained 2. pay patient or public assistance patient 3. prescription number 4. prescription charge 5. date medication was ,received 6. new prescription or renewal prescription
The University of Pittsburgh has been the hub of Joseph D. M cEvilla's academic activity. Professor of pharmaceutical economics in the school of pharmacy, M cEvilla earned his BS, MS and PhD at the school and began his teaching career there as a teaching fellow in 1950. He is an assistant editor of Remington's Practice of Pharmacy and has published articles in state and national journals, including this Journal. Costs of pharmaceutical service and prepaid prescription service are two of M cEvilla's research interests. H is memberships include APhA, AMA, AACP, the American Economic Association and American Public Health Association.
Vol. NS7, No. 12, December 1967
637
IT'S .
A MATTER OF LIFE
AN BREAI
~ USE
~H~l§1
" SEAL
FIGHT TUBERCULOSIS ... EMPHYSEMA, .. AIR POLLUTIQ~, ...
638
computerized ij; system ( continued from page 637)
7. number of times original prescription was renewed 8. sex 9. age 10. identification of prescriber 11. location of prescriber 12. name of drug prescribed 13. therapeutic class of drug prescribed 14. strength of drug prescribed 15. quantity of drug prescribed 16. expenditures for any selected time period
Because data from the total universe of prescriptions dispensed from the participating pharmacies is captured and stored, it is possible to retrieve information covering the prescribing habits of not only physicians but also dentists, osteopaths, veterinarians and podiatrists. The data obtained has proved to be of interest to a variety of health research personnel. Initial use of the information available has been made by research personnel interested in the general area of health economics. Requested data has related to drug utilization and expenditures by sex, age and therapeutic class. Retrieval of similar data can be obtained by location of the patient's home, thus permitting generalizations to be made concerning utilization expenditures and therapeutic classes relating to economic environment. This type of data has been requested most frequently for patients either over 65 years of age or under 18 years of age. It is of particular interest in projecting drug expenditures by age groups and by therapeutic classes and in determining the relationship between these two variables. This data may then be used in predicting the cost of providing prescribed drug coverage through health service plans employing either government or private funds. Because all obtainable data can be separated as to pay patient and public assistance patient, it is useful not only to health economics personnel working in an academic environment but also to similar personnel working in state welfare agencies. Comparisons may be made of the types of drugs and the quantities being prescribed within therapeutic classes for each type of patient. Cost comparisons may be made between types of patients receiving drugs within therapeutic classes. Additional research data may be obtained by personal interview with patients selected at random. Inquiries may be made as to age, income, education and family size. These facts may then be correlated with drug expenditures to determine what portion
Journal of the AMERICAN PHARMACEUTICAL ASSOCIATION
of total income medical specialties utilized and to learn how far prescriber and pharmacy were from the patient's home. The data has proved useful in conducting prospective studies regarding adverse reactions to all drugs or to a selected drug or group of drugs within any therapeutic class. The procedure we have developed is predicated upon the collection of all prescriptions dispensed from participating pharmacies. Investigations into health care and drug utilization are best done by a complete and continuous study of the population in selected areas. Such studies permit a 365-day-a-year basis for determining what is being prescribed and received by patients as well as who is prescribing what. Our experience has shown that sampling technics tend to contain built in bias when only prescriptions selected from various parts of a month or a quarter year are used. Only by using the total volume of dispensed prescriptions is it possible to develop drug profiles of patients and follow the prescribing habits of practitioners . We are continuing our research in this area and hope that the developed procedures utilizing information obtained directly from the prescription order form will provide better data on the various aspects surrounding the use and misuse of drugs and pharm al ceuticals and their importance in health care. •