`
`birth weight infants: the absorption of calcium and fat. Pedi-
`atrics. 1976‘. 57:16—25.
`9. Rowe .10. Wood DH, Rowe DW at al. Nutritional hypophos—
`phatemic rickets in a premature infant fed breast—milk. N Engl‘
`J Med. 1979; 300:293—&
`10. Kulkarni PB, Hall RT. Rhodes PG et a]. Rickets in very low
`birth weight. infants. J Pediatr. 1989: 96:249-52.
`11. Day GM. Chance GW. Radde 10 et al. Growth and mineral
`metabolism in very low birth weight infants. II. Effects of cal-
`cium supplementation on growth and divalent cations. Pediatr
`Res. 1975; 91568—75.
`
`12. Knight PJ, Buchanan S. Clatworthy W J I'._Calcium and phos-
`phate requirements of preterm infants who require prolonged
`hyperalirnentation. JAMA. 1930; 243:1244—6.
`13. Schuetz DH, King JC. Compatibility and stability ofelectro-
`lytea. vitamins. and antibiotics in combination with 8% amino
`acid solution. Am J Hosp Pliorm. 1978; 35:33—44.
`14. Weast R, ed. Handbook of chemistry and physics. Cleveland:
`CRC Press; 1976:3100.
`15. Henry RS. Jurgens RW Jr.. Sturgeon R et a]. Compatibility of
`calcium chloride and calcium glueonato with sodium phosphate
`in a mixed 'l‘l‘N solution. Am J Hosp Pharm. 1980; 37:673—4.
`
`Review Article
`
`Am J Help Pharm. 1933: 39:53-39
`
`Review 01 computer applications in institutional pharmacy—1975-
`1981
`
`Ken W. Burleson
`
`A literature review of computer applications in institutional pharmacy. covering papers pub—
`lished from 1975 to 1931, is presented.
`Articles are categorized as computer concepts, applications to administrative functions. can-
`trollcd substances. drug distribution systems (including on—line and offline services. intrave-
`nous admixture services, and ambulatory services). drug information, clinical services (includ-
`ing drug-use review, drug interactions and therapeutic incompatibility surveillance. and phar—
`maookinetics). and pharmacy—related applications developed by nonpharmacists.
`Before 1975. computer applications in institutional pharmacy reported in the literature were
`largely single—use applications. After 1975. many reports described the integration of individu—
`al applications into sophisticated systems that supported many functions. There is still a need
`for good cost justification studies of computerisation in pharmacy.
`
`Index terms: Administration; Automation. data processing, computers; Controlled sub-
`stances; Drug distribution systems; Drug information; Drug interactions; incompatibilities;
`Pharmacy. institutional
`
`In the past 20 years electronic data processing (EDP) in
`hospital pharmacy has grown from applications that im—
`proved accounting procedures to sophisticated multifunc-
`tional. integrated systems for institutional drug control and
`clinical pharmacy support. Early innovators were hospital
`pharmacists who applied computers to accounting and
`billing functions. However, as pharmacists became aware
`of the benefits of automation and as they gained expertise
`in the field. applications of EDP became varied. Innovative
`approaches to pharmacy practice have been instituted that,
`
`
`lion W. Burleaon is Director, Phan-nacy Services. Catawba County Memorial
`Hospital. Hickory. NC 291391.
`The assistance of the librarians of the Area Health Education Center
`(AHECJ. Catawba County Memorial Hospital. in performing the literature
`searches; Ethel Hall for secretarial help} and Margery Adams. M.S.N.. for
`critical review is acknOWchgEd.
`
`Copyright © 1982. American Society of Hospital Pharmacists. inc. All rights
`reserved.
`
`without automation, would be too time-consuming, too
`costly. or too difficult to implement. Automated drug control
`systems, medication delivery systems, and support of clinical
`services are examples of these applications. Interest in au-
`tomation for pharmacy practice has stimulated vendors of
`commercial systems to develop hardware and software
`packages designed for pharmacy.
`The expanded use of electronic data processing in phar—
`macy practice has been due to both the development of more
`sophisticated hardware and software during the past 20 years
`and the experiences of individual practitioners in applying
`EDP to various segments of practice. The literature has
`contributed substantially to the increased awareness of the
`individual pharmacist of the benefits of automation. In 1975,
`Knight and Conrad1 published an extensive review of
`pharmacy applications of electronic data processing made
`to that time. This article reviews those applications made
`from 1975 to the present.
`
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`Computer Concepts
`Data processing concepts and technology are areas in
`which few pharmacists have had formal training. They
`should become familiar with fundamentals of systems
`analysis, design, and computer technology prior to involve-
`ment with appiication development. A number of articles
`have described the basic concepts of data processing for the
`pharmacist.
`Nelson2 presented an introduction to computer hardware
`that could be used in a pharmacy system. He described the
`various hardware components, including the central pro—
`cessing unit {CPU}, input devices, and data storage devices.
`Advantages and disadvantages of different components were
`presented. Downtime, system security, and vendor systems
`evaluations were discussed. He also presented a dictionary
`of computer terminology. Mehl3 outlined the minimum re-
`quirements for a pharmacy data processing system. He
`compared advantages of centralized versus decentralized
`systems, and examined the methods of data entry and types
`of drug coding for developing a data base. He also empha-
`sized the need for order verification to prevent errors.
`Computer hardware configurations range from the large
`mainframe computer to the minicomputer to the most recent
`development in the field. the microprocessor. Given the
`premise that the pharmacist has a choice in the selection of
`hardware, an understanding of the advantages and disad-
`vantages of each can be essential to the development of a
`successful application. Knowles“ explained the differences
`between mainframe systems and minicomputers. Lauer at
`a].5 explained the apparent and subtle differences between
`a mainframe computer shared with other users {shared
`system) and a stand—alone dedicated minicomputer system
`for pharmacy, particularly in regard to ambulatory phar—
`macy practice. Advantages and disadvantages of each con;
`figuration were presented. Data storage was found to be the
`most serious drawback to a stand-alone system, a disad—
`Vantage that could be minimized with a properly designed
`system. The authors concluded that in most situations for
`pharmacy practice, either configuration could provide ad—
`equate support.
`Another configuration is a pharmacy application devel-
`oped as a part of a total hospital information system (HIS).
`Ball et a].'3 examined the past, present, and future develop
`ments in hospital data processing systems, from stand-alone
`pharmacy systems to large hospital information systems.
`The authors predicted that in the immediate future, many
`physicians would have terminals in their offices interfaced
`with hospital information systems. Mecklenburg1r described
`the expanding applications of hospital information systems.
`including pharmacy and other clinical applications.
`An important concept for the pharmacist to understand
`before developing an application is the methods used to
`justify the need for and cost of a computerized system._Al-
`though many articles have been written describing the varied
`applications of computerization, few articles have described
`controlled documented studies to justify the cost and eval—
`uate the effects of a computerised system. The fact that
`evaluation of systems and intensive cost-benefit studies have
`
`64 American JwrnalofHospiial Pharmacy Vol39 Jan1982
`
`not been accomplished may be a major reason why there has
`not been a greater acceptance of pharmacy systems by hos-
`pital administrators or pharmacists. In 1975, Gouveia8 re-
`viewed the few studies to date that had attempted to analyse
`the effects of computerization on hospital costs, medication
`errors, and patient care. He found that the few studies
`published actually raised more questions than they an-
`swered. He emphasized the need for research to establish
`adequate cost~benefit ratios to justify computerization to
`hospital administrators, patients, and third party payers.
`Since that time, other studies have been published de-
`scribing the steps involved with analyzing and justifying the
`need for and cost of computerization. Freibrun9 analysed a
`traditional pharmacy system in a 360-bed hospital. He
`identified procedures needing improvements and examined
`alternate manual and automated approaches for change;
`areas in which automation would offer potential savings;
`developed a rating scale for vendors; and described steps
`involved in successful operations analysis in a pharmacy.
`Kay et al.” described the method used to analyse a hospital
`pharmacy’s need for automation and identify the various
`areas where automation would benefit both pharmacy and
`the hospital. The impact of the proposed system upon other
`areas of the hospital were also listed. Cost justification for
`a dedicated mini-computer was developed. The authors were
`successful in justifying automation of the pharmacy de-
`partment, based upon a potential cost savings and an im-
`proved. medication delivery system.
`Neal” developed an in~depth cost proposal to justify to
`hospital administration the computerization of a hospital
`pharmacy. He identified seven areas of tangible cost savings
`(reduction in costs, elimination of salaries paid, increased
`revenues} and two areas of intangible savings (reduced
`overhead, labor reallocation}. He was able to project tangible
`dollar savings to each of these areas. He found that auto~
`mation of the department would result in a substantial cost
`savings. He also described the various steps in developing
`and presenting the analysis to hospital administration.
`Gray12 evaluated the cost of computerization of an i.v. ad—
`mixture service in a hospital pharmacy. Staffing analysis and
`life cycle cost projection were determined. Workloads and
`staffing patterns both with and without the computer Were
`calculated. The basis of the study was to determine the
`amount of money that could be invested in a computer sys-
`tem as justified by staffing reductions and other savings. The
`author’s conclusion was that the computer was cost effective
`and, therefore, should be purchased.
`Lsuer13 gave an overview of the need for automation in
`pharmacy practice and the benefits to be realized from
`computerization. Three areas of savings as a result of auto-
`mation—time, space, and personnel costs—justified the cost
`of computerization.
`Two authors have described the methods of dealing with
`vendors of computer systems. Olsen et al.” described the
`method used to select an upgraded computer system that
`would=support an automated clinical department in the
`hospital. Although the article dealt specifically with an au-
`tomated laboratory system, the authors presented a general
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`discussion of vendors, vendor selection, systems require—
`ments, terminal requirements, and hardware and software
`that could be used by the pharmacist in selecting a pharmacy
`system. Cutely15 presented an extensive list of questions a
`pharmacist should ask a hardware or software vendor of a
`commercial system when considering the purchase of such
`a system.
`Before beginning development of any automated appli—
`cations, the pharmacist must develop a data base, or drug
`file, listing all the drugs to be found in the pharmacy, along
`with any information pertinent to the description of each
`drug. The method in which a data base is developed can
`mean the difference between a flexible system with the
`ability for expanded applications and a rigidI single appli—
`cation system. Hanson et al.16 have described the develop—
`ment of a master drug file that was developed by examining
`an existing computerised drug data file to determine which
`existing fields of information should be retained for the new
`data base. The new data base was developed to support in-
`creasingly sophisticated pharmacy applications. Twenty-
`seven data fields for the master drug file were identified.
`Programs were written to permit entry and maintenance of
`the file by using punched cards input to an offline computer.
`The authors envisioned using online entry of data through
`a cathode ray tube (CRT) in the future. Programs were
`written that permitted machine verification of data ac—
`cording to predefined specifications. Any errors detected
`were rejected for correction. This editing feature resulted
`in a high degree of accuracy of the stored data. Strand et a1.”
`developed a master drug file after comparing commercially
`available data bases which they found to be deficient.
`Twenty-seven different data fields were identified and in—
`formation for each drug entered to a coding form which was
`used for data entry. Entry was online via a cathode ray tube.
`The data base was used to support certain administrative
`and drug distribution programs for both inpatient and
`outpatient services. The authors also examined the cost of
`the development of the file. They found that more than 900
`hours were involved with the development, ata total salary
`cost of $8451. This calculated to $7.43 per line item in the
`data base. Although this cost was twice that of a commer~
`cially available data base, the authors thought that the ad~
`ditionsl data fields that were available to them justified the
`cost.
`
`The American Society of Hospital Pharmacists provides
`a computer-generated, machine—readable data base called
`Drug Products Information File (DPlli‘)fl for use by phar-
`macists in computerised systems. Frankenfeldla examined
`the problems associated with the National Drug Code (NDC)
`system as a pharmacy data base and the potential for in-
`terfacing it to DPIF. He explained the advantages of cross-
`referencing the information in the two files.
`
`Administrative Applications
`
`Because of the computer’s inherent ability to quickly
`tabulate numerical data, and to store, retrieve, and compile
`statistical information, certain administrative functions are
`
`Computer sppllcatlcms
`
`ideally suited to automation. Among these functions are
`patient billing and accounting, drug use review. and inven-
`tory control. A number of articles have described applica-
`tions of EDP in these areas.
`Silverman19 described the administrative functions that
`
`could be automated using a dedicated minicomputer.
`Among these applications were personnel management,
`patient billing and accounting, and inventory control.
`Wuest and Schaengoldzo described an automated ac-
`counting system shared by two hospital pharmacies, using
`a time-shared computer system. Data were entered from
`dispensing records showing all transactions for each phar-
`macy. The system generated a monthly report of expenses
`for chargeable patient drugs and nonchargeable floor stock.
`Drug use statistics from this report were used for purchasing
`and inventory control. The system also printed a formulary
`for each hospital.
`in a hospital without data processing capability, Elliott”
`contracted to use the computer services of a local drug
`wholesaler to develop an inventory and purchasing system.
`The wholesaler’s programs for
`inventory control were
`modified to adapt to the special needs of the hospital. All
`drug issues to stock from inventory were manually recorded
`on an inventory master list by a clerk and this was sent to the
`wholesaler for keypunching into the system. A weekly
`computergenerated report summarized the use of each item.
`and this list served as a stock status report and purchase list.
`Each item that had reached a predetermined order point was
`flagged. Items supplied by the wholesaler were automatically
`shipped and entered into the computerised inventory. 0r—
`ders to direct. vendors were completed by the pharmacist,
`working from the report. The system also generated a hos-
`pital formulary by use of therapeutic category coding. Both
`an alphabetical listing and a listing by therapeutic categories
`were available.
`
`Pickup et al.2'2 utilized the Massachusetts General Hos-
`pital Utility Mold-Programming System (MUMPS) to de—
`velop programs to control ward stock levels and contribute
`to workload analysis in a quality control section of a hospital
`pharmacy. The system was programmed to determine each
`hospital ward’s minimum stock levels, based upon historical
`demand and the ability of the pharmacy to respond to the
`needs of the various wards. Results showed that the system
`could reduce the inventory of drugs on the nursing units,
`thereby effecting a cost savings, without any deterioration
`of service or inconvenience to the nursing units. The system
`also handled data concerning raw materials in the quality
`control section. It was determined that a time savings could
`be realized by automating some of the reports in this area.
`Automated patient billing has been a feature of hospital
`computer systems for many years. This is one of the earlier
`applications to which EDP was applied in pharmacy. Tru-
`deau23 modified an existing time-shared payroll and ac—
`counting system to provide drug use review and patient drug
`billing. The time saved from these applications was used to
`permit the pharmacy to complete a hospital-wide traditional
`unit dose system. The author did notuse the computer di~
`rectly to support the unit dose system. Priest24 used com—
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`puter-printed gummed labels to be attached to intravenous
`fluids and other pharmacy patient charge items that were
`kept as floor stuck on the nursing units. These gummed
`stickers functioned as a charge voucher as well as a stock
`replenishment mechanism. The author concluded that the
`system aided in the capture of more charges, while simul-
`taneously saving personnel time.
`Fish25 describeda computerized patient billing system
`that was based on a combination of a percentage markup of
`drug costs plus a dose fee. Seven different dose fees {factors}
`were used, depending upon the type .of drug product ad-
`ministered to the patient; e.g., oral unit dose, injectable unit
`dose, and i.v. additives. Manual patient profiles were used
`for a unit dose medication system, and cumulative charges
`for each patient were maintained on these profiles. At the
`time of patient discharge, the profile for the patient was
`inactivated and all drug charges were added. A pharmacy
`technician also entered the patient number, computer drug
`code, and dose factor for all drugs. The profile was then sent
`to the pharmacy pricing area, where the charges were entered
`into the computer via a cathode ray tube. A final patient bill
`was produced as a result of data entry. The system offered
`advantages of an accurate, itemized statement: charges ware
`equitable, based upon the type of drug administered: and
`the system produced useful statistical reports. The time
`required to enter charges manually into the system was a
`drawback, and the author proposed an automated unit dose
`system that would eliminate much of the manual data
`entry.
`Gurtel el. al.26 projected drug use review statistics for a
`pharmacy and therapeutics committee to use in determining
`the benefit of adding a new drug to the formulaty of an am-
`bulatory patient care clinic. A computer-supported ambu—
`latory pharmacy system was used to determine if a new drug,
`ticrynafen, a diuretic with uricosuric properties, would
`benefit patients in the clinic. The computerized patient
`profile was used to determine the number of patients taking
`'a diuretic who were also taking a uricosuric agent, to deter-
`mine how many patients could benefit from the new drug
`which offered both therapeutic actions. Computer analysis
`revealed that only 8% of the patients on a diuretic were si—
`multaneously receiving a uricoeuric agent. In view of the cost
`of the new drug and the limited application. as shown by
`computer analysis, the pharmacy and therapeutics com-
`mittee chose to add the drug only on a restricted formulary
`status. The drug was eventually prescribed for four patients.
`Later, the drug was recalled from the market because of its
`adverse reactions. The computer was used to search the
`patient profiles for those patients receiving the drug at the
`time of recall, so that their physicians could contact them
`and make appropriate changes in therapy. The authors
`concluded that the use of the computerized patient infor—
`mation system enabled the pharmacy and therapeutics
`committee to prevent the potential exposure of more than
`160 patients to the adverse effects of the drug.
`Not all administrative applications of data processing
`must be developed on a computer. Word processing equip-
`ment is similar to a computer, with the exception that word
`
`58 American Journal of Hospiial Pharmacy Vol 39
`
`Jan ‘932
`
`processing equipment ordinarily has no built-in logic. The
`system is used for storage of small amounts of data and re—
`trieval and printing of this information on a repetitive basis.
`Letcher” compared three different commercial brands of
`word processing equipment to various applications in hos—
`pital pharmacy. The applications studied were label pro—
`duction; storage of personnel information; scheduling of
`repetitive tasks; and composition of narrative information,
`such as drug bulletins and procedure manuals. The evalua—
`tion included keyboard design, disk storage capabilities,
`software, print format, and security of data. One of the three
`systems was clearly superior to the other two because of its
`flexibility of applications. The author summarised the re—
`sults of the evaluations of each machine.
`
`Controlled Substances Applications
`
`Controlled substances are defined as those drugs which
`have the potential and liability for abuse; i.e., narcotics and
`barbiturates. Federal and state laws require that practi-
`tioners who dispense these medications maintain records of
`disposition for all drugs under this regulation. Because of the
`large number of drugs in this category, proper recordkeeping
`has been time-consuming for both the pharmacist and
`nursing personnel. Automation of this segment of practice
`can reduce time involvement for both the pharmacist and
`nurse, while maintaining accurate control and accountability
`records as required by law.
`Pstoletti23 used an off—line system in an outpatient clinic
`to monitor for potential abuse of controlleddrugs by pa-
`tients. Dispensing data were entered on a source document
`for each prescription dispensed. These data were key-
`punched weekly, and reports were generated that notified
`the pharmacist of those patients receiving excessive supplies
`of controlled drugs.
`McDanielzg modified an existing patient accounting sys-
`tem to develop an automated recordkeeping system. All
`controlled drugs were assigned specific service codes within
`a designated group of service numbers. A separate file was
`set up in the computer for this group designation. As charges
`were posted to the patient's account, records of controlled
`drugs dispensed were created. Daily and cumulative monthly
`reports were printed, which showed distribution of con-
`trolled drugs. Nazaaroi’o developed a program on an off-line
`computer to provide accurate records for controlled sub
`stances accountability, while reducing manual transcriptions
`involved with record maintenance. The system was used for
`both inpatient ward stock and outpatient prescriptions in
`a military hospital. All prescription transactions were re-
`corded manually on punched cards, and included patient
`number or hospital ward code, physician's identification
`code, drug code, and quantity of drug dispensed. All data
`were later keypunched and entered into the computer.
`Various records were generated by the system. including
`perpetual records of each drug by patient or ward, monthly
`inventory of all controlled substances, and ward monitoring
`lists of excess stock of controlled substances. The system
`could also search for prescriptions by patient or prescriber.
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`Shaver et al.31 described a system for an inpatient and out—
`patient military hospital pharmacy which used limited
`computer hardware. The system was run on a remote
`mainframe computer through a telephone hookup. A phar-
`macist or technician entered all transactions daily via a
`cathode ray tube. After data entry was complete, all trans—
`actions were verified before the update program was run. to
`ensure accuracy of information. The system generated a
`number of reports. including transactions by drug and cur-
`rent inventory balances. It also permitted patient drug use
`screening and physician prescribing screening to monitor
`for potential drug abuse. The system was capable of tying
`in terminals at other military hospitals.
`Finally, Dickinson-1'2 reported how the Drug Enforcement
`Agency used computers to map entire states to show drug
`distribution. to pinpoint areas of potential drug abuse. Data
`are obtained from two sources—the Automated Reporting
`and Consolidated Order System (ARCOS), which shows
`drug distribution from manufacturers and wholesalers to
`pharmacies; and the Drug Abuse Warning Network
`(DAWN), which tracks drugs from selected hospital emer~
`gency rooms. All data Were entered into the computer and
`analyzed. The resultant output was distributed to DEA field
`offices and other local and state law enforcement officials
`for follow-up.
`
`Drug Dislrlbullon System Appllcailons
`
`Traditional manual drug distribution systems are time
`consuming, involve much clerical work for both pharmacist
`and nurse, and tend to be error-prone. Automation of the
`medication cycle can provide substantial benefits to the
`pharmacist, nurse. and patient by reducing the amount of
`clerical work involved with maintaining a medication system,
`reducing errorsI
`improving administrative control, and
`freeing the pharmacist for more clinical involvement. Much
`work has been done in automating various segments of the
`medication cycle. Many pharmacists have automated one
`or more procedures involved in medication delivery. How-
`ever, prior to 1975, only a few systems had integrated the
`various components of the cycle into a completely automated
`medication delivery system. Since that time, several articles
`have described the development and application of total
`systems for automated medication delivery. This increased
`development has been due, in part, to the reduced cost of
`hardware necessary to support an automated medication
`delivery system and to the entry of vendors that provide
`hardware and software packages. Yet, the use of EDP in the
`medication cycle is not extensively employed by hospitals.
`Stolar,33 in a 1978 national survey of hospital pharmacies,
`found that of the 738 reporting hospitals, only 13% of the
`large hospitals and 5% of the small hospitals used computer
`systems in the drug dispensing process.
`The importance of EDP in hospital drug delivery systems
`and the role of the pharmacist in implementing its use has
`been recognized by the American Society of Hospital
`Pharmacists {ASHP). The ASHP Statement on Hospital
`Drug Control Systems“ states, “The pharmacist should
`utilize EDP to decrease the many traditional paper-handling
`
`Compulor appllc alluns
`
`chores so that his clinical role may be effectively expanded
`and his talents utilized properly." This position statement
`also outlined the many applications of EDP to pharmacy
`practice and the role of the pharmacist in systems develop—
`ment.
`
`Off-line Medics tion Systems. Prior to 1975, many
`automated medication distribution systems were developed
`utilizing off-line systems, usually by modifying an existing
`batch process accounting system to provide pharmacy ap—
`plications. In recent years, more and more pharmacists have
`had access to on-line computer systems. and only a few au-
`thors have described the development of systems using
`off-line computer hardware.
`Swift“- described a semi-automated approach to a unit
`dose system, in which punched cards were used to provide
`information for medication cart filling. Each drug order was
`transferred in writing by a pharmacy technician to a
`punched card, called the master dose card. After verification
`of the transcription by a pharmacist, the data were key~
`punched onto cards. The cards for each patient’s medica—
`tions were then placed in the proper medication cart drawer.
`These cards were color—coded by drug type and alphabetical
`name to simplify cart filling. The technicians filled a 24-hour
`supply of medication from the information on the cards. The
`daily charge data were then entered manually on each card
`for the amount of drug dispensed. After the pharmacist
`checked the medications in the cart, using the master dose
`cards, the cards were sent to the data processing center for
`daily charging. The cards were then returned to pharmacy
`for subsequent use in the medication system. The system was
`cumbersome. since the cards were often misplaced and daily
`maintenance of the patient records involved a substantial
`amount of paper handling. The cards were not used to gen-
`erate a patient profile; therefore, monitoring of patient
`medication records was not possible.
`Gilbert et al.35 described a batch mode order entry pro-
`cedure on an off-line computer. The pharmacist reduced all
`drug orders to numeric codes on punched cards. Once each
`eight hours, the coded orders were batch keypunched. The
`computer printed a drug distribution log for unit dose cart
`filling, a cumulative patient profile, and a daily medication
`charting document for nursing. Automated patient charging
`and census control were features of the system. The author
`overcame the lapse between profile printings by sending
`doses of medications for new orders to cover the interim until
`the next cart exchange.
`Orr-line Medication Systems. On—line systems allow the
`operator to interact directly with the computer, allowing
`immediate access to data stored, thus overcoming the time
`lapse in information processing which occurs with off-line
`systems. Thus, on-line systems lend themselves to more
`flexible programming. For this reason, on-line medication
`systems have usually involved more sophisticated applica—
`tions. A number of such systems have been successfully
`implemented, both as dedicated pharmacy modules and as
`subsystems of larger hospital information systems.
`A series of articles has described the medication distri-
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`bution system at The Johns Hopkins HOSpital. Two gener-
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`Volas
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`Jan1932 Americandournel of HosoliaIPharmacy
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`Compular appllcatlnna
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`ations of the system. the first of which was implemented in
`1970, have been developed using a large computer. Derewicz
`and Simborg, in two separate communicatiorisfr‘r-33 described
`the second generation of this system. which used cathode ray
`tubes with light—pen entry capability. Each decentralized
`satellite pharmacy had a computer terminal. Medication
`orders were entered into the CRTs. Drug orders were auto—
`matically checked against patient allergies and diagnosis for
`incompatibility-For each hour that medications were due,
`the computer generated a single unit dose envelope. Phar—
`macy technicians placed the medications in the envelopes
`and these were delivered to the nursing units. The envelopes
`were used by the nurse to verify drug administration. The
`computer also generated medication profiles and medication
`histories. Advantages of the system included reduction of
`medication errors, reduction of time spent by nurses in
`medication administration tasks, and reduction of costs as—
`sociated with drug administration. The second communi—
`cation in this series was important in that it was the first
`description of a computerized unit dose system to appear in
`a publication oriented primarily toward physicians.
`Later articles in this series examined comparative costs
`and occurrence of drug errors in the automated system
`versus traditional manual methods, using well-controlled
`studies. Arrington ct ala‘J compared the cost for a com—
`puter—supported unit dose system for both adult and pedi-
`atric medicine. They found that the cost p