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The Journal of Emergency Medicine, Vol. 31, No. 3, pp. 309–315, 2006Copyright © 2006 Elsevier Inc.

Printed in the USA. All rights reserved0736-4679/06 $–see front matter

doi:10.1016/j.jemermed.2005.09.020

Computersin Emergency Medicine

WIRELESS HANDHELD COMPUTERS AND VOLUNTARY UTILIZATION OFCOMPUTERIZED PRESCRIBING SYSTEMS IN THE EMERGENCY DEPARTMENT

Tony Shannon, MD*, Craig Feied, MD, FACEP, FAAEM*†, Mark Smith, MD, FACEP*†, Jonathan Handler, MD,

FACEP†‡, and Michael Gillam, MD, FACEP†‡

*Washington Hospital Center, Washington, DC, †National Center for Emergency Medicine Informatics, Washington, DC, and‡Northwestern University Feinberg School of Medicine, Chicago, Illinois

Corresponding Author’s Address: Craig Feied, MD, FACEP, FAAEM, National Institute for Medical Informatics, c/o Eliza Moody, 110 Irving

Street, NW #NA-1177, Washington, DC 20010

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Abstract—Illegible or invalid hand-written prescriptionsan result in avoidable medical errors. Computer-basedrescribing can mitigate the problem. An observationaltudy was performed to examine the effect of wireless hand-eld computers (handhelds) on voluntary utilization ofomputerized prescribing within an Emergency Depart-ent. Handhelds with prescription-writing software were

rovided to physicians and the numbers of hand-writtennd computer-generated prescriptions were compared be-ore and after the introduction of the handhelds. The re-ulting increase in computer-based prescribing was statis-ically significant and was observed largely amonghysicians who already used desktop computers for pre-cribing. The study concluded that handhelds increasedoluntary utilization of computerized prescribing, but thathe physicians most likely to use handhelds were those wholready used desktop-based prescribing. © 2006 Elseviernc.

Keywords—prescribing systems; wireless; computers,andheld; ED; utilization; technology

INTRODUCTION

edication errors are the most common cause of avoid-ble adverse events affecting hospital patients (1). Anstimated 1 million serious medication errors occur ev-

Computers in Emergency Medicine is coordinateMedical Center, San Diego, California

ECEIVED: 1 September 2004; FINAL SUBMISSION RECEIVED

CCEPTED: 15 September 2005

309

ry year in U.S. hospitals (2). Many medication errorstem from problems associated with the traditional prac-ice of writing orders and prescriptions by hand. Amongther problems, illegible handwriting and decimal pointonfusion account for a significant number of errors (3).omputer-based prescribing systems can help to mitigate

he problem in many ways. Even simple systems canuarantee a complete, legible, and pharmaceuticallyalid prescription, and more advanced systems can alsocreen for known allergies, pertinent medical conditions,nd drug-drug interactions. Some systems can even ap-ly rules to assess the likely correctness of prescriptionsor the particular problem of a specific patient. Adoptionnd utilization of computer-based prescribing systemsepends on many factors; ease of access and mobilityay be important in achieving a high rate of voluntary

tilization of computerized prescribing.A brief review of pharmacy records at Washington

ospital Center (WHC) revealed that the pharmacy re-eives approximately 3 million handwritten order sheetser year; of these, approximately 25,000 cannot be de-iphered or cannot be acted upon because they contain aonexistent medication, an invalid or toxic dose, annvalid form of the medication, an invalid route of ad-inistration, or some other patently obvious error. It is

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mpossible to know with what frequency less obviousrrors may slip through unrecognized.

The Emergency Department (ED) at WHC utilizes aomprehensive real-time clinical information system thatrovides sub-second access to more than 12,000 dataoints, offering instant access to all orders, results, andmages. The system has included electronic prescribingince 1999; with a few clicks, any patient can be selectednd any common medication can be prescribed with noyping. Medications can be selected from personal orroup lists of prescriptions that have been previouslyeviewed and validated by a designated member of theroup, and new “custom” medication orders can bedded as needed, although they do not become availableor general use until after validation.

The WHC emergency physician acceptance and vol-ntary utilization of the clinical information system forurposes of information retrieval has long been at 100%,et at the time of this study, utilization for purposes ofomputer-based prescribing was much less, even in areasuch as the ED, where many desktop computers werevailable no more than a few feet away.

We hypothesized that the inconvenience of leavinghe bedside and returning to a desktop personal computerPC) to write a prescription was a significant factorimiting the voluntary use of computerized prescribing inhe ED, and that spontaneous physician utilization ofomputerized prescribing would increase when comput-rized prescribing became available via wireless hand-eld computers. We also hypothesized that physiciansho used the desktop PC less often to write prescriptionsould be more likely to use a mobile handheld solu-

ion—and that those who had preferred hand-writtenrescribing would also prefer handheld computerizedrescribing.

METHODS

tudy Design

his was a controlled, prospective, observational cohorttudy.

tudy Setting

his study was conducted in the urban ED of Washing-on Hospital Center (WHC), the largest hospital in Wash-ngton, DC. The ED sees 68,000 adult patients per year;n average, 36% of patients seen in the major ED aredmitted to the hospital.

The clinical information system at Washington Hos-

ital Center is a multi-terabyte real-time data repository t

ontaining all the elements of an electronic patientecord. The primary user interface is a full-featured desk-op PC program providing sub-second access to approx-mately 12,000 data elements for a typically complexatient, and allowing point-and-click computerized pre-cribing within the context of all pre-existing patientnformation. For this project, a new web-based usernterface was designed to fit into the limited screen spacend processing power of currently available handheldomputers. This web-based handheld computer system isonnected to central data servers via a wireless network.

The handheld system provides real-time access touch of the same clinical information found in the

esktop system, and includes a web-based prescription-riting interface. To write prescriptions, the physician

hooses the patient from a list of current patients, scrollshrough a list of medication regimens, and marks a checkox beside each drug to be prescribed. Prescriptions foredications or regimens not previously defined within

he system can be added at the bedside, although thisequires entering characters into the handheld device.inks to external reference material are also provided forach medication, making additional data about the drugvailable at the bedside.

The handheld devices used in this study were Win-ows CE-based systems with wireless PCMCIA Type IIireless network cards. Data were transmitted over an02.11 wireless network operating at 2 Mbps. Prescrip-ions selected using a handheld device are printed within0 seconds by the same printer used to print prescriptionsrom a desktop PC.

tudy Population

he study population included all discharged patientsreated by any of nine participating emergency physi-ians working on the “major” side of the ED during thetudy period. All physicians were board certified inmergency Medicine, with a range of practice experi-nce from 3 to 25 years. Physicians were aware thatlectronic handheld computers were being tested, butere unaware that usage patterns were the focus of the

tudy.

tudy Design

e introduced wireless handheld computers that permitomputerized prescribing using an interface very similaro that of a pre-existing desktop PC system. We studiedhe rate of computerized prescribing before and after thentroduction of the wireless handheld solution. Each par-

icipant received a brief demonstration of the handheld

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Wireless, Handheld Computers 311

ystem and demonstrated the ability to create a prescrip-ion using the system.

Nine participating emergency physicians worked oner more shifts during each phase of the study, duringhich the clinical information system automatically col-

ected computerized prescribing utilization data for allD patient encounters. The intervention phase consistedf the 1-week period immediately after the introductionf the wireless handheld prescribing system. The controlhase consisted of the 3-month period immediately be-ore the introduction of the handheld devices. Becausee were interested solely in the behavior of the ninehysicians during the two phases of the study, we madeo attempt to match cases and controls according to anyatient attributes; however, we did ensure that the controleriod and intervention period contained a similar num-er of patient encounters for each physician.

A research ethics committee at WHC approved thetudy.

ata Collection

e analyzed the change in electronic prescribing afterhe introduction of wireless handheld computers as andditional method for creating computer-based prescrip-ions. We also assessed whether a prior physician pref-rence for hand-written paper prescriptions predictsdoption of handheld computers for electronic prescrib-ng.

Data points collected for each physician included theumber of admitted and discharged patients seen, theotal number of prescriptions written, and the number ofrescriptions written using computer-based prescribing.omputer-based prescriptions were further characterizeds having been generated from a desktop PC or from aandheld wireless device.

All electronic and handwritten aspects of the patientedical records were reviewed for all cases and controls.he counts of electronic prescriptions were automati-ally tracked and recorded by the computer system. Todentify all cases in which a prescription was handwrit-en, we reviewed all physicians’ notes, nurses’ notes,ischarge forms, and patient instruction sheets. A specialeview was performed whenever the diagnosis suggestedhat a prescription would likely have been written, andhenever electronic records showed that a patient had

eceived an initial dose of a medication that would likelyave been continued as a prescription after discharge.or both the control period and the intervention period,e tallied the number of prescriptions that were writteny hand, the number that were generated using a desktopC, and the number that were generated using a wireless

andheld device. i

The study was carried out in the major side of theHC ED, where approximately 65% of patients are

ischarged to home, and the remainder are admitted,ransferred, or expire in the ED. All cases were reviewed,ut patients who were not discharged from the ED weremplicitly excluded from this study because such patientso not receive written prescriptions in the ED.

tatistical Analysis

he paired t-test measure was used to compare the observedate of computer-based prescribing exhibited by each phy-ician before and after the introduction of handheld mobileomputers. Prior usage data within the computer systemhowed that the fraction of discharged patients receiving anlectronic prescription during each of the 6 weeks immedi-tely before the study was stable, with mean � 0.105 (SD.013, 95% confidence interval [CI] 0.090 to 0.119). Theignificance of observed differences was assessed using ane-tailed p value because the base rate of electronic pre-cribing was stable and because the introduction of andditional means of utilizing electronic prescribing (leavingntouched all pre-existing methods for electronic prescrib-ng) could only result in an increase (or no change) in therue rate of utilization. A simple correlation coefficient wassed to assess whether handheld computers had strongerffect on the prescribing habits of those who previouslyere more likely to use hand-written prescriptions. A con-entional 95% CI was used to assess significance, thus palues � 0.05 were considered to be statistically significant.

RESULTS

total of 475 clinical encounters were reviewed for thetudy: 236 in the intervention group (144 ED dischargesnd 92 excluded admissions) and 239 in the controlroup (158 ED discharges and 81 excluded admissions).

total of 167 outpatient prescriptions were written byhe nine physicians during the course of the study: 89uring the intervention period and 78 during the controleriod. Tables 1 and 2 show details of prescribing prac-ices before and after the introduction of handheld com-uters.

We found a high degree of variability from physiciano physician in the rate of computer-based prescribing inoth groups. For the entire control group (n � 239), 59%f all prescriptions were computer-generated (SD 0.29,5% CI 48% to 69%). For the entire intervention groupn � 236), 73% of all prescriptions were computer-enerated (SD 0.29, 95% CI 63% to 82%).

Of the 65 prescriptions generated by computer in the

ntervention phase, 32 (50%) were generated using a desk-

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op PC and 33 (50%) were generated using the mobileireless device. For individual physicians during the inter-ention phase, the fraction of computer-based prescriptionshat were generated using the wireless handheld deviceanged from 0% (0 of 8) to 100% (11 of 11).

The addition of wireless handheld computers resultedn a statistically significant increase in electronic pre-cription-writing by physicians. The observed rate ofomputer-based prescribing exhibited by each physicianefore and after the introduction of handheld mobileomputers is shown in Table 3. The mean of the ob-erved rates of electronic prescribing was 52% during theontrol period and 64% during the intervention period, a2.5% increase (SE 0.057, p � 0.03).

We examined the strength of any association betweenhe rates of hand-written prescribing during the controleriod and the rates of electronic prescribing using mobileandheld computers during the intervention period (Table). For this comparison, the correlation coefficient was r �0.653 (95% CI �0.919 to 0.020) and the two-tailed p

alue was 0.057, indicating that a prior preference forandwritten prescribing was not a positive predictor fordoption of mobile handheld computers for prescribing.

DISCUSSION

rrors in medication dosing occur at a significant rate,ith significant morbidity and mortality (4–6). Besides

rrors due to illegibility, drug interactions, and failure to

able 1. Computer-Generated and Handwritten Prescription

hysician ID 1 2 3Paper prescriptions 1 3 4Desktop PC prescriptions 3 14 8Total prescriptions 4 17 12ate of all prescriptions .44 .44 .55ate of paper prescriptions .25 .176 .333ate of electronic prescriptions .75 .824 .667Outpatients 9 39 22

HF � congestive heart failure; ETOH � ethanol; HTN � hyper

able 2. Computer-Generated and Handwritten Prescription

hysician ID 1 2 3Paper prescriptions 2 3 3Desktop PC prescriptions 0 9 1Handheld PC prescriptions 11 14 4All PC prescriptions 11 23 5Total prescriptions 13 26 8ate of all prescriptions .87 .60 .50ate of paper prescriptions .13 .07 .19ate of all electronic prescriptions .846 .885 .62ate of handheld electronicprescriptions

.846 .538 .5

Outpatients 15 43 16

ecognize contraindications to the use of a drug, clini-ians sometimes have difficulty in accurately calculatingrug dosages (7). The use of computers to assist clini-ians in prescribing medications quickly and safely haseen proposed as one approach to reduce error andmprove efficiency.

Properly designed computerized prescribing and de-ision support systems decrease medication errors andllow clinicians to calculate medication dosages moreccurately and more quickly, but hospitals and EDs haveeen slow to adopt new technologies (8–14). This studynvestigated the effect of mobile wireless handheld com-uters on voluntary utilization of computer-based pre-cribing systems in the Emergency Department setting.

Medline literature search did not identify any priortudies examining this issue in a prospective, controlledashion (e.g., using PubMed search strategy: “[emer-ency department OR emergency room] AND computerND medication AND prospective AND wireless” onctober 17, 2003).In our facility, the introduction of wireless hand-

eld computers into an environment where desktopomputers were already used by all physicians for allnformation retrieval (but only by a subset of physiciansor a subset of their prescription writing) was associatedith a significant overall increase in the rate of com-uter-generated prescriptions, though the change wasnfluenced strongly by the usage patterns of individualhysicians.

re Introduction of Wireless Handheld Computer

5 6 7 8 9 Total4 4 2 1 11 328 2 7 0 2 4612 6 9 1 13 78.52 .86 .53 .25 .59.333 .667 .222 1.0 .846.667 .333 .778 0.0 .154 0.5923 7 17 4 22 158

; OTC � over the counter; UTI � urinary tract infection.

r Introduction of Wireless Handheld Computer

4 5 6 7 8 9 Total4 1 5 0 1 5 245 5 2 8 1 1 321 3 0 0 0 0 336 8 2 8 1 1 6510 9 7 8 2 6 89.77 .47 .88 .53 .67 .50.31 .05 .63 0.0 .33 .42.60 .889 .286 1.00 .50 .167 .73.1 .333 .0 .0 .0 .0

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Wireless, Handheld Computers 313

One of our central hypotheses was that the reasonaper prescriptions were preferred by some physiciansas related to the convenience and mobility of paperrescription pads. We believed that the inconveniencessociated with walking to a desktop computer was anmportant reason why some physicians did not voluntar-ly adopt electronic prescribing. For this reason, we hadxpected that physicians who had preferred handwrittenaper prescribing would also prefer handheld computer-zed prescribing. Contrary to our expectations, a prefer-nce for handwritten prescriptions was negatively corre-ated with subsequent use of the handheld computer,hereas prior preference for electronic prescribing using

he desktop PC was positively correlated with subse-uent use of the handheld devices. This study found thathose who had preferred to handwrite prescriptions con-inued to do so, whereas those who were already morenterested in technology sought to expand their experi-nce.

Our data demonstrate that lack of mobility is anmportant factor limiting adoption of electronic prescrib-ng in the ED, but that other factors are also important.

ith respect to adoption of electronic prescribing in theD, technophilia seems to be a more important factor

han mobility: those who like desktop PCs also likeandheld PCs, whereas those who prefer not to use theesktop computer for writing prescriptions also preferot to use mobile handheld devices.

During both the control period and the interventioneriod, we observed a large variability in the rate of

able 3. Comparison between the Rate of ElectronicPrescribing during the Control Period and theRate during the Study Period

Controls Cases

9 9ean 0.519 0.644D 0.295 0.288ifference of means 0.125tandard error of the difference 0.057ne-tailed p value 0.03

able 4. Correlation between the Rate of Paper-BasedPrescriptions during the Control Period and theRate of Handheld Computer-Based Prescriptionsduring the Study Period

Controls Cases

9 9ean 0.481 0.257ariance 0.077 0.087orrelation (r) �0.653

dwo-tailed p value 0.057

tilization of PC-based prescribing from physician tohysician. After handheld computers became available,ne physician abandoned the desktop PC completely androte all prescriptions using the handheld device,hereas four other physicians did not use the handheldevice at all. Overall, physicians who previously usedhe desktop PC heavily for prescribing were more likelyo use the handheld computer than were those who wroteost of their prescriptions by hand. Yet, among physi-

ians who did engage in a high rate of computer-basedrescribing, some continued to walk to the desktop PC inreference to using the wireless handheld device at theedside.

The overall rate of ED prescription-writing during thistudy was seemingly low, at 167 prescriptions for a studyopulation of 302 discharged patients. This is consistentith our historically observed rate, and is also consistentith the rate of prescribing in other affiliated EDs wheree have examined this issue. Table 5 helps explain this

ate of prescribing by showing details for 20 sequentialischarged ED patients, with a prescription rate of 30%or the sample group shown.

We are confident that all electronic prescriptions wereroperly identified, because all interactions with theomputer system are recorded. A substantial effort wasade to identify all hand-written prescriptions through a

able 5. Details of Subscribing for 20 Sequential PatientsDischarged during the Study Period, with aPrescription Rate of 30% for this Sample

No prescription given Prescription given

brasion Nonenkle sprain Pain medsronchitis Antibiotics,

antitussiveonjunctivitis Antibiotic ophth

qttsmergency dialysis for CHF NoneTOH intoxication NoneTN, patient already has medications Noneypoglycemia, feels better after a meal Noneaceration, OTC meds recommended Noneeds given to go, no prescription Noneuscle sprain, recommend OTC meds Noneheezing, needs inhaler refill Inhalerneumonia Antibiotics,

antitussiveregnant with vaginal bleeding Nonesychiatric complaint Noneo labor and delivery for evaluation Nonenexplained chest pain, resolved NoneTI Antibiotics,

antispasmodicaginal foreign body, removed Noneiral syndrome, needed hydration None

HF � congestive heart failure; ETOH � ethanol; HTN � hyper-ension; OTC � over-the-counter; UTI � urinary tract infection.

etailed review of all electronic and handwritten mate-

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ials, including physicians’ notes, nurses’ notes, dis-harge forms, patient instruction sheets, medications dis-ensed, and complaints or diagnoses that should haveriggered a prescription. We believe this effort was suc-essful in identifying virtually all ordinary prescriptionselated to a patient’s presenting problem, although it isossible that occasional “impulse” prescriptions couldave been handwritten and given to patients without anyhart notation or other evidence that we could detect.

If we unknowingly missed handwritten prescriptionsn the same proportions during the two study phases, thisould artificially increase the absolute magnitude of thebserved difference in electronic prescribing before andfter the introduction of handheld computers, but itould not affect the true p value for the difference. If weissed handwritten prescriptions in the control phaseore than in the intervention phase, the absolute mag-

itude of the observed difference would be larger thane calculated, and the difference would have been sta-

istically significant at a higher confidence level than wealculated. Because the number of total prescriptions andhe number of electronic prescriptions went up in thentervention group compared with the control group, weelieve it is unlikely that we missed more handwrittenrescriptions in the study group than in the control group.

LIMITATIONS AND FUTURE DIRECTIONS

his study had limited power because it involved onlyine physicians at a single hospital during brief intervalsefore and after the introduction of a new device forlectronic prescribing. The study took advantage of anlready planned introduction of handheld devices at aingle hospital, thus, we had little control over the timingf the study or the number of physicians who met theriteria for participation. We carried out the study despitehese known limitations because we were unable to findther published articles describing changes in the rate ofoluntary electronic prescribing when mobile handheldomputers were added to a comprehensive clinical infor-ation system that already offered electronic prescrip-

ion writing capabilities using desktop PCs. A multi-nstitutional study involving large numbers of cliniciansver longer periods of time would have more power toonfirm our findings.

This study involved physicians who treat a primarilydult population. Its applicability to clinicians working inpediatric population is unknown. A more frequent need

or weight-based dosing might cause wireless handheldrescribing to be more readily adopted in an ED with aignificant pediatric population, but such an effect re-

ains to be demonstrated.

The scope of this study was limited; there was noffort made to investigate the reasons some physiciansreferred not to utilize desktop or handheld computersor electronic prescribing, and we did not perform anyong-term review after the initial period of introduction.he study may have measured artificially high or artifi-ially low utilization due to the effects of early novelty orarly unfamiliarity with the new devices. In other words,t is possible that either over- or under-use of the hand-eld device occurred because the device was newly in-roduced. Nonetheless, the results we observed weretriking: although overall utilization of electronic pre-cribing went up after the introduction of wireless mobileandheld computers, the handheld devices seemed toave little appeal for those physicians who least oftensed the desktop PC for electronic prescribing.

CONCLUSION

he introduction of wireless handheld computers foromputer-based prescribing was associated with a statis-ically significant overall increase in the rate of comput-r-based prescribing, but there was a great deal of vari-bility between physicians in the rate of utilization.roviding access to wireless handheld computers was notufficient to ensure a uniformly high rate of utilization ofomputer-based prescribing. Wireless handheld comput-rs did not strongly attract those physicians who hadeast often used a desktop system for electronic prescrib-ng.

As newer mobile handheld computers become smallernd more powerful, we believe they will play an increas-ngly important role in the Emergency Department, butur experience suggests they will be adopted mosteadily by those who have already adopted the use ofesktop PCs for the same or similar functions.

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