Factors influencing quality of patient interaction at community pharmacy drive-through and walk-in counselling areas

Factors influencing quality of patient interaction atcommunity pharmacy drive-through and walk-incounselling areasOlufunmilola K. Odukoya, Michelle A. Chui and Jia Pu

Social and Administrative Sciences Division, School of Pharmacy, University of Wisconsin, Madison, WI, USA

KeywordsAndersen behavioural model of health servicesutilization; community pharmacy;drive-through counselling areas; patientencounters

CorrespondenceDr Olufunmilola K. Odukoya, Department ofPharmacy and Therapeutics, School ofPharmacy, University of Pittsburgh, 3501Terrace St, Pittsburgh, PA 15261, USA.E-mail: [email protected]

Received September 25, 2012Accepted August 5, 2013

doi: 10.1111/ijpp.12073

Abstract

Objective To examine factors influencing the amount of time and informationpharmacy personnel provide to patients at drive-through and walk-in counsellingareas.Methods On-site observational data collection in 22 community pharmacies bypharmacy students. Information included observable patient characteristics such asgender, age range, English proficiency and mobility impairment; encounter charac-teristics included type of prescription and whether the patient was acknowledged;and counselling characteristics included types of counselling information conveyedand length of time for each encounter.Key findings Patient–pharmacist encounters were documented at the drive-through and walk-in counselling areas 961 and 1098 times respectively. Pharmacistsspent less time, and technicians more time, with patients at the drive-through coun-selling area. The amount of information provided to patients was significantlyaffected by whether the patient was receiving new versus refill prescriptions. Patientswith a new prescription were twice as likely to receive more information from phar-macy personnel. There was a significant difference between the amount of counsel-ling provided to patients at the drive-through and walk-in counselling area (rateratio (RR) 0.92, 95% confidence interval (CI): 0.86–1.00). Patients at the drive-through received a lower amount of information relative to patients using the walk-in. Amount of information provided to patients was affected by the level ofpharmacy busyness (RR 0.96, 95% CI: 0.95–0.99).Conclusions Providing patient care at the drive-through counselling area maynegatively influence quality of patient care. To improve quality of pharmacy drive-through services, standardization of drive-through services in pharmacies may beneeded.

Introduction

Drive-through services are commonly used in many indus-tries such as fast food restaurants and banks to promote effi-ciency and render faster services. The use of drive-throughcommunity pharmacies began in the 1990s in the USA topromote faster dispensing of medications and improvepatient satisfaction. However, faster services do not alwaystranslate to safer and higher quality patient care. Despiteyears of experience with drive-through services in commu-nity pharmacies, little is known about pharmacy–patient

encounters at the drive-through counselling area. Thereis limited research on the use of drive-through servicesin community pharmacies. Studies exploring the dif-ferences between patient–pharmacist interaction at thedrive-through and traditional walk-in counselling areaof a pharmacy found that pharmacist interaction withpatients might be richer when the walk-in counsellingarea is used, particularly for patients with limited Englishproficiency.[1–3]

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International Journal of

Pharmacy PracticeInternational Journal of Pharmacy Practice 2014, 22, pp. 246–256

Research Paper

© 2013 Royal Pharmaceutical Society International Journal of Pharmacy Practice 2014, 22, pp. 246–256

Several studies have reported a positive link betweenpharmacist counselling and patients’ adherence tomedications.[4–7] Findings from these studies suggest that alack of patient counselling by pharmacists may result inreduced medication adherence, treatment failure and wasteof health resources.[8] Another important aspect of patient–pharmacy encounters is the amount of time spent withpatients by pharmacists and technicians. Although thesefindings may not be generalized to community pharmacies,Tarn et al. found that the amount of time a physician spent oncommunication with the patient, and the quality of that com-munication, was positively correlated with a more compre-hensive discussion of important counselling elements.[9]

Provision of poor counselling at the drive-through, andhurried patient care, may not afford patients the opportunityto obtain necessary information to appropriately use theirmedications. Inappropriate counselling could negativelyimpact patient care or even lead to adverse drugs events ordrug interactions.[10] Another study has suggested a possiblerelationship between time spent with patients at the drive-through in community pharmacies and the quality of patientcounselling.[1]

The aim of this study was to explore the factors that areassociated with the amount of information provided topatients and the amount of time pharmacists or techniciansspend with patients at the drive-through compared with thewalk-in counselling area. This study will provide insight onthe factors that are associated with the quality of patient inter-action in community pharmacies at the drive-through andwalk-in counselling area to improve pharmacy practice.

This study had two objectives. The first objective was todescribe the factors that might influence the time spent withpatients at the drive-through and walk-in counselling area.The second objective was to determine the factors that couldinfluence the amount of information patients received at thedrive-through and walk-in counselling area.

Methods

For this study, a walk-in counselling area was denoted aspharmacy interaction with patients inside the pharmacy,typically at the pharmacy counter or semi-private counsellingarea, as opposed to use of the drive-through counselling areawhere patients drive up in their cars and interact with phar-macy personnel via a microphone or a window.

Community pharmacists, with both walk-in access for atleast one individual and drive-through access for at least onecar at a time, and who were University of Wisconsin rotationsite preceptors, were invited via a telephone call andfollow-up mailed letter to take part in this study. Fourth yearstudents from the University of Wisconsin School of Phar-macy, USA, were invited to participate in the study if theywere assigned to a participating pharmacy between July

2009 and May 2010. The students were required to completea training course on how to work with human research par-ticipants, and one-to-one data collection, prior to participat-ing in the study.

This study was approved by the University of Wisconsin–Madison Institutional Review Board, Wisconsin, USA.

Observations

An observation form, pilot tested in a previous study,[1] wasrevised to include information that may be conveyed duringpatient counselling, and perceived pharmacy busyness.[8] (seeFigure 1).

Both the drive-through and walk-in counselling areas wereobserved for each pharmacy. Twenty-three student observersrecorded encounters on the standardized form and timedencounters using a stopwatch. The elements observedincluded patient, encounter and counselling characteristics.The variables for patient characteristics that were observedand recorded included gender, age range, mobility impair-ment, limited English proficiency, accompanying passengers,smoking status during the encounter and mobile-phone useduring the encounter. Encounter characteristics includedtype of prescription, level of pharmacy busyness, whether thepatient was acknowledged and by whom. Counselling char-acteristics included information items conveyed to patientsduring counselling, number of questions patients asked andtime. The amount of information provided to each patientduring counselling was aggregated as a composite score ofinformation items provided to the patient during eachpharmacy–patient interaction.

Student observers were each asked to collect 50 encountersat the walk-in counselling area, and 50 encounters at thedrive-through counselling area.While student observers wereasked to dedicate periods of time to collect data, the days ofthe week and the length of time were not prescribed. Duringdata-collection periods, data were recorded for every sequen-tial patient who approached the drive-through or walk-incounselling areas, and observers were dedicated exclusively todata collection (i.e., did not have dispensing or patient careresponsibilities).

Patients were observed when they arrived at the drive-through counselling area or came to the front of the line atthe walk-in counselling area. Students recorded whether thepatient was acknowledged upon approaching the counsel-ling area and by whom. A stopwatch was started when phar-macy personnel first made verbal contact with the patient. Ifa non-pharmacist first made verbal contact, the studentmade note of the time at which the patient began interactingwith the pharmacist. When the encounter was concluded,the observer stopped timing and recorded the start and stoptimes.

O. K. Odukoya et al. 247


DRIVE-THRU Date: _______________Patient Acknowledged? Yes No N/A By whom? RPh TechInteraction Time Tech start: _______________ RPh start: _______________ End time: _______________Patient Counselling Accepted RefusedRPh Verbal Interaction (check if RPh mentions these types of information – do not record actual information conveyed i.e., actual drug name)At least 1 new Rx All refills Type of Rx(s) unknownPatient Name (Y_/N_) Drug Name (Y_/N_) Drug Purpose (Y_/N_)Directions (Y_/N_) Any side effects (Y_/N_) Other Precautions (Y_/N_)When drug would begin to work (Y_/N_)Patient UnderstandingConfirmed (open ended) Confirmed (closed ended)Not ConfirmedWritten Info Provided Yes (not referred to) Yes (referred to) No# Questions asked by patient 0 1 2 3Level of busyness 0 1 2 3 4 5 6Gender Male FemaleApprox. age range <40 40–60 >60Is driver smoking Yes NoTalking on cell phone Yes NoMobility impaired Yes No UnknownLimited English proficiency Yes (able to counsel)Yes (needed interpreter) NoOther passengers None Children Adults PetsRequest non-Rx purchases Yes NoOther Comments:_______________WALK-IN Date: _______________Patient Acknowledged? Yes No N/A By whom? RPh TechInteraction Time Tech start: _______________ RPh start: _______________ End time: _______________Type of Rx Patient Counselling Accepted RefusedRPh Verbal Interaction (check if RPh mentions these types of information – do not record actual information conveyed i.e., actual drug name)At least 1 new Rx All refills Type of Rx(s) unknownPatient Name (Y_/N_) Drug Name (Y_/N_) Drug Purpose (Y_/N_)Directions (Y_/N_) Any side effects (Y_/N_) Other Precautions (Y_/N_)When drug would begin to work (Y_/N_)Patient UnderstandingConfirmed (open ended) Confirmed (closed ended)Not ConfirmedWritten Info Provided Yes (not referred to) Yes (referred to) No# Questions asked by patient 0 1 2 3Level of busyness 0 1 2 3 4 5 6Gender Male FemaleApprox. age range <40 40–60 >60Talking on cell phone Yes NoMobility impaired Yes No UnknownLimited English proficiency Yes (able to counsel)Yes (needed interpreter) NoOther shoppers with patient None Children Adults PetsRequest non-Rx purchases Yes NoOther Comments:_______________

Figure 1 Observation form used to obtain data on pharmacist–patient interactions in drive-though versus walk-in pharmacy premises. RPh indicatespharmacist, Rx is prescription and Tech indicates pharmacy technician.

248 Quality of community pharmacy–patient interaction


Measures

Conceptual framework

The Andersen behavioural model of health services utiliza-tion[11] was used as the guiding framework for this study. Asshown in Figure 2, this framework stipulates how use ofhealth care is explained by predisposing, enabling and needsfactors. We hypothesized that there are different factors asso-ciated with pharmacy–patient interactions at the drive-through and walk-in counselling area pharmacy services, andthat this relationship is explained by predisposing, enablingand needs factors.

Dependent variables

Our primary outcome variables include time (in seconds)spent by the pharmacist or technician with the patient and atotal count of the amount of information provided topatients. The amount of information was measured by thetotal number of counselling points for each patient, includingverification of patient name, medication name, indication ordrug purpose, drug directions for use, possible adverseeffects, onset of action and other precautions. These outcomevariables were the indicators for quality of pharmacy–patientinteractions at the drive-through or walk-in counselling areabased on the US Omnibus Budget Reconciliation Act of1990[12] and has been used in a previous study on drive-through pharmacies.[1]

Independent variables

The primary study independent variable was the location ofinteraction, which was coded as walk-in or drive-through.

Predisposing variables were patient characteristics thatmight affect the pharmacy–patient interaction at the drive-through or walk-in counselling area. This study includedobserved age range and gender, which are categorical vari-ables. Observed age range was coded into younger than 40years old, between 40 and 60, and older than 60. Gender wascoded as dummy variable (male = 1, female = 0).

Enabling variables were factors that either facilitate orimpede pharmacy–patient interaction at the drive-throughor walk-in counselling area, including talking on the mobilephone, presence of accompanying people with the patientand level of pharmacy busyness. The variable ‘level of phar-macy busyness’ was initially conceptualized in a study bySvarstad et al. in 2004[8] and was estimated in this study usinga scale ranging from 0–6 (where 1 is no patients are waiting,pharmacy is calm and workflow is slow or non-existent and 6is rush hour during a holiday and the pharmacy has manyoutstanding issues to address). In order to interpret level ofpharmacy busyness, the variable in the dataset was classifiedinto low (0–1), medium (2–3) and high (4–5). Other enablingvariables, including talking on the mobile phone and pres-ence of accompanying people with the patient, were coded asdummy variables (yes = 1, no = 0).

Need variables were variables that may necessitate morepharmacy–patient interaction at the drive-through or walk-incounselling area. The need variables were estimated by type ofprescription, mobility impaired and limited English profi-ciency. Type of prescription was categorized into having atleast one new prescription and refills only. If patients had atleast one new prescription this was coded as ‘1’ and if thepatients had all refills, the coding was ‘0’. Limited English pro-ficiency was coded as a dummy variable (yes = 1, no = 0).

Figure 2 Adaptation of the Andersen behavioural model of pharmacy services utilization.



The models discussed below were used to examine whichvariables may affect pharmacy–patient interactions at thedrive through or walk-in counselling area.

Model 1: pharmacist time = predisposing variables +enabling variables + need variables;

Model 2: technician time = predisposing variables +enabling variables + need variables;

Model 3: amount of information = predisposing vari-ables + enabling variables + need variables.

Data analysis

The software STATA 11.1 (STATA, College Station, Texas,USA) was used to conduct the descriptive statistics for allvariables and to conduct all multivariate models. Descriptiveanalysis was first conducted to compare the patient character-istics and pharmacy encounters between drive-through andwalk-in counselling areas. Bivariate and stepwise negativebinomial regression analysis were further used to identify therelationship between pharmacy services location andoutcome variables, and how this relationship was associatedwith predisposing, enabling and needs variables. A negativebinomial regression was used in this study due to over-dispersion, which indicates that the Poisson regressionassumption was violated[13,14].

To assess the different factors that are associated with phar-macy personnel time and amount of information provided topatients at the drive-through and walk-in counselling area,this analysis reports rate ratios (RR) as the exponentiatedvalues of the regression coefficients and the 95% confidenceintervals (CI) of the RR.

Results

Data on patient–pharmacist encounters were collected from23 community pharmacies from July 2009 through to May2010. However, one data collection binder with recordedinformation was lost in the post, resulting in a total of 22community pharmacies for study. Of the 22 communitypharmacies, 12 (55%) were part of chains and 10 (45%) wereindependently owned.

The data collected consisted of 2059 patient–pharmacyencounters, where encounter is the unit of analysis. Of theanticipated 1100 drive-through and 1100 walk-in counsellingarea encounters, a total of 961 (87%) and 1098 (99%)encounters were documented for the drive-through andwalk-in counselling areas respectively. Table 1 presents basiccharacteristics of patients using both counselling areas.According to the descriptive statistics, there were significantdifferences in pharmacy personnel interactions withpatients at the drive-through compared with the walk-incounselling area. Patients using the drive-through andwalk-in counselling areas were similar in terms of gender, but

patients older than 60 years were more likely to use thewalk-in than drive-through counselling areas (28% versus15.7%). There were more encounters at the drive-throughwith patients with other companions, such as children oradults, than at the walk-in counselling area (27.9% versus13.7%). Patients using their mobile phone during the interac-tions were more likely to use the drive-through counsellingarea (3.5% versus 1.2%). On average, pharmacist interactionwith patients was 32s longer at the walk-in counsellingarea (97.2 ± 114.1s) than at the drive-through counsellingarea (P < 0.001). Technicians spent an average of 36s longerwith patients at the drive-through counselling area(84.4 ± 108.7s) than at the walk-in counselling area (P <0.001). The average amount of drug information provided to

the patient by pharmacy personnel was higher at the walk-incounselling area.

Table 2 reports the results for the stepwise regressionanalysis of the predisposing, enabling and need factorshypothesized to be associated with the amount of time phar-macists spent with patients at the drive-through and walk-incounselling area. As shown in Table 2, after controlling for allthe variables in the model, age as a predisposing variable had asignificant effect on the amount of time pharmacists spendwith patients at drive-through or walk-in counselling areas.The key enabling variables affecting amount of time pharma-cists spent with patients were location of interaction (drive-through or walk-in) and level of pharmacy busyness.Pharmacists spent less time with patients at the drive-through compared to the walk-in counselling area (RR: 0.70,95% CI: 0.62–0.78). The results also suggest that as the level ofpharmacy busyness increased, pharmacists spent less timewith the patient (RR: 0.80, 95% CI: 0.77–0.84). After control-ling for other variables in the model, the need variable, havinga new prescription was significantly associated with theamount of time pharmacists spent with patients (RR 1.72,95% CI: 1.51–1.95). This suggests that pharmacists spendmore time with patients who have new prescriptions thanthose who have refill prescriptions.

Table 3 reports the results for the stepwise regressionanalysis for the predisposing, enabling and need factorshypothesized to be associated with the amount of time tech-nicians spent with patients at the drive-through or walk-incounselling areas. The unadjusted bivariate analysis of eachvariable in the model suggests that the significant variablesaffecting amount of time technicians spent with the patientwere interaction at the drive-through, having other passen-gers with the patient, level of pharmacy busyness and having anew prescription. When accounting for the predisposing,enabling and need factors the only significant enabling vari-ables were drive-through interaction (RR 1.54, 95% CI: 1.18–2.00) and level of pharmacy busyness (RR 1.13, 95% CI:1.02–1.24); the only significant need variable is having a newprescription (RR 1.43, 95% CI: 1.07–1.91). Introducing the



need variables resulted in a greater reduction of the RR for thedrive-through interaction than the addition of the enablingvariables. According to the multivariate analysis, there was asignificant difference in the time technicians spent withpatients at the drive-through after controlling for confound-

ing factors in the model. Technicians spent more time withpatients at the drive-through compared to the walk-in coun-selling area.

Table 4 shows the results for the multivariate analysis offactors associated with amount of information provided to

Table 1 Differences in patient encounters at the drive-through and walk-in pharmacy windows

Drive-throughwindow (n = 961)

Walk-in window(n = 1098)

P% %

Gender 0.083Women 62.9 59.2Men 37.1 40.8

Observed age range (years) <0.001<40 37.4 27.140–60 46.9 44.7>60 15.7 28.2

Mobility impaired* <0.001Yes (required assistance) 0.9 1.4No (ambulatory without assistance) 81.1 97.2Unknown 18 1.5

Individual accompanying patient (in the store or in the car) <0.001Children or adults 27.9 13.7Patient was alone 72.1 86.3

Limited English proficiency 0.024Yes (able to counsel) 0.6 1.8Yes (needed interpreter) 0 0.2No 99.4 98

Accepted patient counselling when offered† 0.005Yes 86.7 90.9No 13.3 9.1

Talking on mobile phone during encounter 0.001Yes 3.5 1.2No 96.5 98.8

Type of prescription 0.323At least one new prescription 21.9 24.5All refill prescriptions 69.9 66.6Unknown 8.2 8.9

Level of pharmacy busyness 0.001Low 52 54.1Medium 38.7 41High 9.3 4.9

Technician time with patient (in seconds) <0.001Mean 84.4 47.5Standard deviation 108.7 90.5Confidence interval 77.3–91.4 41.9–52.9

Pharmacist time with patient (in seconds) <0.001Mean 65.4 97.2Standard deviation 78.7 114.1Confidence interval 60.3–70.5 90.2–104.1

Amount of information provided to patient <0.001Mean 1.9 2.2Standard deviation 1.8 1.8Confidence interval 1.8−2.1 2.1–2.4

*100% of patients were offered counselling by pharmacy personnel.



the patient at the drive-through or walk-in counselling area.After controlling for all variables, there was a significant dif-ference between amount of counselling provided to patientsat the drive-through and walk-in counselling area (RR 0.92,95% CI: 0.86–1.00). Patients at the drive-through counsellingarea may have received less information relative to patientsusing the walk-in counselling area. Also, the amount of infor-

mation provided to patients is affected by level of pharmacybusyness (RR 0.96, 95% CI: 0.95–0.99). The results suggestthat the need variable having the most significant effect onthe amount of information provided to a patient was having anew prescription (RR 2.74, 95% CI: 2.56–2.94). Patients whohad a new prescription were given twice the amount of infor-mation from pharmacy personnel.

Table 2 Factors associated with pharmacist interaction time with patients at the drive-through and walk-in window

Variable Unadjusted P P/E P/E/N

Predisposing variablesObserved age range 1.07 (1.00–1.16) 1.09* (1.01–1.17) 1.07 (0.99–1.16) 1.11 (1.02–1.20)Male 0.88* (0.79–0.99) 0.90* (0.78–0.97) 0.83* (0.75–0.93) 0.91 (0.81–1.02)Female – 1 1

Enabling variables –Drive-through interaction 0.67* (0.61–0.75) 0.70* (0.62–0.78) 0.75* (0.67–0.84)Walk-in interaction – 1 1Talking on the cell phone 0.83 (0.58–1.19) 0.94 (0.65–1.34) 0.88 (0.60–1.30)Not talking on the cell phone – 1 1Passengers with the patient 0.88 (0.77–1.00) 0.95 (0.82–1.09) 0.97 (0.83–1.12)No passengers with the patient – 1 1Level of pharmacy busyness 0.82* (0.78–0.86) 0.82* (0.78–0.85) 0.80* (0.77–0.84)

Need variables – –New prescription 1.66* (1.47–1.87) 1.72* (1.51–1.95)Refill prescription – 1Mobility impaired 1.36 (0.82–2.25) 1.12 (0.66–1.85)Non-mobility impaired – 1Limited English proficiency 1.21 (0.76–1.94) 0.63 (0.38–1.05)English proficient – 1

Rate ratios reported; *P < 0.05; P is the model with only predisposing variables; P/E, the model with both predisposing and enabling variables only; P/E/N,the model with the predisposing, enabling, and need variables; numbers in parentheses indicate 95% confidence interval.

Table 3 Factors associated with technician interaction time with patients at the drive-through and walk-in window


Predisposing variablesObserved age range 0.91 (0.80–1.04) 0.92 (0.80–1.05) 1.02 (0.88–1.16) 1.07 (0.90–1.27)Male 0.88 (0.72–1.08) 0.90 (0.73–1.10) 0.84 (0.68–1.03) 0.83 (0.64–1.00)Female – 1 1 1Enabling variables –Drive-through interaction 1.78* (1.46–2.16) 1.70* (1.38–2.08) 1.54* (1.18–2.00)Walk-in interaction – 1 1Talking on mobile phone 1.25 (0.65–2.41) 1.09 (0.56–2.12) 1.30 (0.54–3.08)Not talking on the mobile phone – 1 1Passengers with the patient 1.43* (1.12–1.83) 1.21 (0.94–1.56) 1.22 (0.88–1.69)No passengers with the patient – 1 1Level of pharmacy busyness 1.13* (1.04–1.21) 1.09* (1.03–1.21) 1.13* (1.02–1.24)

Need variables – – 1New prescription 1.36* (1.05–1.76) 1.43* (1.07–1.91)Refill prescription – 1Mobility impaired 1.30 (0.51–3.36) 1.10 (0.36–3.37)Non-mobility impaired – 1Limited English proficiency 0.81 (0.34–1.92) 0.94 (0.31–2.89)English proficient – 1

Rate ratios reported; *P < 0.05; P is the model with only predisposing variables; P/E, the model with both predisposing and enabling variables only; P/E/N,the model with the predisposing, enabling, and need variables; numbers in parentheses indicate 95% confidence interval.



Table 5 reports a summary of the significant predictors ofamount of time spent and amount of information providedwhen analysing the drive-through and walk-in models sepa-rately, controlling for all variables in the model. At the drive-through counselling area, the amount of time the pharmacistspent with a patient was influenced mainly by two factors:level of pharmacy busyness (RR 0.75, 95% CI, 0.70–0.81) andhaving a new prescription (RR 1.68, 95% CI, 1.35–2.09). At

the walk-in counselling area, time spent by pharmacist wasinfluenced by three factors only: level of pharmacy busyness(RR 0.84, 95% CI, 0.79–0.89), having a new prescription (RR1.74, 95% CI, 1.48–2.05) and observed age of the patient (RR1.13, 95% CI, 1.02–1.25). The pharmacist possibly spent lesstime with the patient at the drive-through and walk-in coun-selling area as level of pharmacy busyness increased. Thepharmacist also spent more time with patients who had atleast one new prescription. There were no significant predic-tors of amount of time the technician spent with the patientat the walk-in counselling area. However, technicians spentsignificantly more time with patients at the drive-throughcounselling area as the level of pharmacy busyness increased(RR 1.16, 95% CI, 1.04–1.31). At both the drive-through andwalk-in counselling areas, the variable‘having a new prescrip-tion’ (patients receiving one or more of their medications forthe very first time) significantly increased the amount ofinformation that pharmacy personnel provided to patients.When a patient had a new prescription, the pharmacist wasmore likely to spend more time counselling the patient onhow to use their medication by providing information such asthe purpose of the drug, the name of the drug, possible sideeffects and information on how and when to use the drug.

Discussion

Main findings

Results from this study indicate that there are differentfactors that might influence pharmacy encounters with

Table 4 Factors associated with amount of information received by patients at the drive-through and walk-in window


Predisposing variablesObserved age range 0.97 (0.93–1.03) 0.97 (0.91–1.02) 0.98 (0.93–1.04) 1.05 (0.99–1.10)Male 0.87* (0.81–0.95) 0.92* (0.85–0.99) 0.87* (0.80–0.94) 0.95 (0.88–1.02)Female – 1 1 1

Enabling variables –Drive-through interaction 0.86* (0.80–0.93) 0.86* (0.93–1.03) 0.92* (0.86–1.00)Walk-in interaction – 1 1Talking on the mobile phone 0.89 (0.69–1.16) 0.91 (0.70–1.20) 1.02 (0.77–1.34)Not talking on the mobile phone – 1 1Passengers with the patient 1.03 (0.93–1.13) 1.06 (0.97–1.17) 0.96 (0.88–1.06)No passengers with the patient – 1 1Level of pharmacy busyness 0.96* (0.93–0.99) 0.96* (0.93–0.00) 0.96* (0.94–0.99)

Need variables – – 1New prescription 2.68* (2.51–2.86) 2.74* (2.56–2.94)Refill prescription – 1Mobility impaired 1.30 (0.94–1.81) 1.09 (0.81–1.46)Non-mobility impaired – 1Limited English proficiency 0.84 (0.60–1.19) 0.85 (0.61–1.20)English proficient – 1

Rate ratios reported; *is P < 0.05; P is the model with only predisposing variables; P/E is the model with both predisposing and enabling variables only;P/E/N is the model with the predisposing, enabling, and need variables; numbers in parentheses indicate the 95% confidence interval.

Table 5 Significant predictors for time spent and amount of informa-tion at the drive-through only and walk in window only when controllingfor all variables in the models

Drive-through model only Walk-in model only

Pharmacisttime

Level of pharmacybusyness

Level of pharmacybusyness

0.75* (0.70–0.81) 0.84* (0.79–0.89)New prescription New prescription1.68* (1.35–2.09) 1.74* (1.48–2.05)Not significant Observed age range

1.13* (1.02–1.25)Technician

timeLevel of pharmacy busyness Not significant1.16* (1.04–1.31)

Amount ofinformation

Level of pharmacy busyness Not significant0.93* (0.90–0.98)New prescription New prescription2.78* (2.47–3.11) 2.73* (2.50–2.98)Not significant Observed age range

1.08* (1.02–1.15)

Rate ratios reported; *P < 0.05; numbers in parentheses indicate the95% confidence interval.



patients at the drive-through and walk-in counselling areas.Some of the variables in the model were consistently signifi-cantly associated with the amount of time pharmacists andtechnicians spent with patients (having a new prescription,level of pharmacy busyness and using the drive-throughcounselling area). The predisposing factor included inthe model (observed age) appears to significantly impactthe time pharmacists spent with patients and the amountof information they received, particularly at the walk-incounselling area. The enabling variable, drive-throughinteraction, was a significant factor in all of the modelsanalysed.

Strengths and limitations of the study

This study is the first to reveal the key factors, such as phar-macy busyness, that are associated with the time pharmacypersonnel spend with patients at the drive-through, and theamount of information patients receive about their medica-tions using the Andersen behavioural model of healthservices utilization.[11] However, this study includes onlyencounters with patients and pharmacy personnel in phar-macies in one US state. Also, the time or days when the datawere collected, which were not recorded, could have impactedthe results. As a result, the generalizability of findings may belimited.

The design and methods chosen for this study had severaladvantages. First, by documenting patient encountersat both the drive-through and walk-in counselling areasof each pharmacy, we attempted to hold constant the per-sonnel that would interact with patients as well as anyorganizational structure or policy that might externallyinfluence the patient interaction. Second, unlike previousstudies that surveyed pharmacists regarding their percep-tions of advantages and disadvantages of having a drive-through counselling area, this study sought to collectempirical data on characteristics of pharmacy–patient inter-action, recognizing that pharmacists’ perceptions may notbe consistent with actual practice. However, one limitationof this design is a Hawthorne effect, whereby pharmacy staffmay have changed their behaviour as a result of beingobserved. A second limitation to this design is the potentialvariability between scorers. These effects were not measured.Lastly, given the amount of time that student observerswere provided to collect data, we were unable to record50 encounters per pharmacy at the drive-throughcounselling area. This was because of some lower-volumepharmacies having significantly less patients presentingat the drive-through counselling area (one observer indi-cated that only three patients on average received their pre-scriptions at the drive-through counselling area at hispharmacy).

Implications of time spent at walk-inand drive-through

This study showed that pharmacists spent more time withpatients at walk-in counselling areas, while technicians spentmore time with patients at drive-through counselling areas.Our findings are consistent with previous research that foundthat pharmacists interacted with patients for the majority ofthe total encounter at walk-in counselling areas, whereas theyspent only a small proportion of total encounter time withpatients at drive-through counselling areas (an average of41s of a 187s total encounter).[1] These findings support thehypothesis that pharmacists might perceive the drive-through counselling area to be an inefficient means ofproviding adequate patient counselling and suggest that tech-nicians specifically attend more to the needs of patients at thedrive-through. This has important implications, as patientswho use the drive-through may be less likely to receiveadequate counselling by the pharmacist. This could result inlower quality of care provided to patients at a drive-throughcounselling area. Future research should confirm this findingin a larger, more generalizable study.

This study also helps to identify the key factors that areassociated with pharmacy personnel’s interaction withpatients at a drive-through or walk-in counselling area. Twoimportant factors that are significantly associated with thelevel of pharmacy personnel interaction with patients, are thetype of prescription and level of pharmacy busyness. Afinding not anticipated in this study was that as the level ofpharmacy busyness increased, the amount of time pharma-cists spent with patients reduced while the amount of timetechnicians’ spent with patients increased. Pharmacists mightperceive the walk-in counselling area to be a more efficientuse of their time and frequently delegate drive-through ser-vices to technicians. Another key finding of this study wasthat patients were more likely to be provided less informationat the drive-through than at the walk-in counselling area.Pharmacists and technicians spent significantly less time withpatients who had refill prescriptions and more time withpatients who had at least one new prescription. The differ-ences in time spent with each patient could be influenced bythe pharmacy personnel’s perceived patient need. It might benecessary to standardize or regulate quality of care at thedrive-through counselling area to ensure patient needs areadequately met. Many other factors could influence timespent with patients at the drive-through and walk-in counsel-ling area, such as weather conditions or time of data collec-tion.[1] Future research is needed to determine other factorsthat influence the use of a drive-through counselling area,possibly examining patients’ reasons for selecting a drive-through rather than a walk-in counselling area.

In order to improve quality of pharmacy drive-throughservices, there may be a need for standardization of



drive-through services in pharmacies. This study has impor-tant implications because patients who use the drive-throughare likely to be provided less counselling by the pharmacist,and thus lower quality of care. Although the drive-throughcounselling area provides faster access to healthcare servicesfor patients, the quality of medication communicationbetween the pharmacist and the patient might also be lower.Our findings indicate that pharmacies may need to take stepsto ensure pharmacists provide more adequate counselling topatients at the drive-through to improve quality of care espe-cially when the pharmacy is busy. These steps could include arethinking of the physical layout of the pharmacy as well asadditional technician training to provide services at the drive-through location. This could help to ensure that patients at adrive-through counselling area are not attended by techni-cians only. Drive-through encounters should entail morepharmacist–patient interactions to increase the exchange ofinformation and overall patient care. This is importantbecause drive-through services can serve as a valuableresource for particular patient populations such as the dis-abled and the elderly, who have difficulty ambulating,and parents who do not want to bring sick children into thepharmacy.

Conclusion

Despite years of experience with drive-through services incommunity pharmacies, little is known about pharmacy–patient encounters at a drive-through counselling area. Thisstudy found that multiple factors are associated with thelength of time pharmacists and technicians interact withpatients in pharmacies, and raises concerns that pharmacistsmay be delegating care to technicians for patients at the drive-through counselling area and thereby affect the quality of

their care. This study also suggests that the amount of timepharmacists and technicians spend with patients is greatlyaffected by how busy the pharmacy is, and the type of pre-scription being dispensed.

Declarations

Conflict of interest

The Author(s) declare(s) that they have no conflicts of inter-est to disclose.

Funding

This research received no specific grant from any fundingagency in the public, commercial or not-for-profit sectors.Michelle A. Chui was supported by the Clinical and Transla-tional Science Award (CTSA) program, through the NIHNational Center for Advancing Translational Sciences(NCATS), grant UL1TR000427. The content is solely theresponsibility of the authors and does not necessarily repre-sent the official views of the NIH.

Authors’ contributions

All Authors participated in writing the manuscript. The cor-responding Author, Olufunmilola K. Odukoya, was respon-sible for conceptualizing the research questions, conceptualframework, data analysis, and facilitating revisions of themanuscripts. Michelle A. Chui, was responsible for conceptu-alizing data collection methods used and writing and revisingparts of the manuscript. Jia Pu took active part in data analysisand writing and revising parts of the manuscript. All Authorshad complete access to the study data that support the publi-cation of this manuscript.

References

1. Chui MA et al. Exploring patient-pharmacist interaction differencesbetween the drive-through and walk-inwindows. J Am Pharm Assoc 2009; 49:427–431.

2. Quinlan C. ‘Drive-thru window adver-tising system.’ U.S. Patent Application10/436,840, filed May 13, 2003. Alexan-dria, VA: The United States Patentand Trademark Office, February 12,2004.

3. Lee TA, Larson LN. Evaluating the useand quality of pharmacy drive-up ser-

vices. J Am Pharm Assoc 1999; 39: 338–345.

4. Schnipper JL et al. Role of pharmacistcounselling in preventing adverse drugevents after hospitalization. Arch InternMed 2006; 166: 565–571.

5. Lee JK et al. Effect of a pharmacy careprogram on medication adherence andpersistence, blood pressure, and low-density lipoprotein cholesterol: arandomized controlled trial. JAMA2006; 296: 2563–2571.

6. Simpson RJ Jr. Challenges for improv-ing medication adherence. JAMA 2006;296: 2614–2616.

7. Haynes RB et al. Interventions toenhance medication adherence.Cochrane Database Syst Rev 2008; (2):CD000011.

8. Svarstad BL et al. Patient counsellingprovided in community pharmacies:effects of state regulation, pharmacistage, and busyness. J Am Pharm Assoc2004; 44: 22–29.

9. Tarn DM et al. How much time does ittake to prescribe a new medication?Patient Educ Couns 2008; 72: 311–319.

10. Puspitasari HP et al. A review of coun-selling practices on prescription medi-



cines in community pharmacies. ResSoc Admin Pharm 2009; 5: 197–210.

11. Andersen RM, Davidson PL. Improv-ing access to care in America: individ-ual and contextual indicators. In:Andersen R et al, ed. Changing the U.S.Health Care System: Key Issues in HealthServices, Policy and Management. SanFrancisco, CA: Jossey-Bass, 2001: 3–30.

12. U.S. Senate Special Committee onAging. Implementation of the Drug UseReview Provisions of the MedicaidPrudent Pharmaceutical Provisions ofthe Omnibus Budget Reconciliation Actof 1990. Washington, DC: U.S. SenateSpecial Committee on Aging, 1991:1–6.

13. Wang J et al. Utilizing new prescriptiondrugs: disparities among non-Hispanicwhites, non-Hispanic blacks, and His-panic whites. Health Serv Res 2007; 42:1499–1519.

14. Greene WH. Econometric Analysis, Ethedn. Upper Saddle River, NJ: PrenticeHall, 2000.



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Factors influencing quality of patient interaction at community pharmacy drive-through and walk-in counselling areas