Identification of Influence Factors on Waiting Time of

Prescription Services for Outpatient

Dorra Ribta Alam, Ermi Girsang*, Sri Lestari R. Nasution

Faculty of Medicine,Universitas Prima Indonesia, Indonesia

Keywords: Waiting time, prescription service, hospital pharmacy.

Abstract: Waiting time is one of the minimum standards for pharmaceutical services in a hospital. From many studies,

there are still many pharmaceutical services that do not meet the established time standards. The purpose of

this study was to identify the factors that influence the waiting time for prescription services in Outpatient

Pharmacy. Analytical research uses cross-sectional design. With a sample of 100 prescriptions both finished

drugs and concoctions taken by simple random sampling method. Data analysis used univariate analysis,

bivariate analysis with Chi-Square Test and multivariate analysis with multiple logistic regression at 95%

confidence level (α = 0.05). The involved variableswere Type of Drugs, Number of Drug Items, Work Shift,

and Patient Status.It appears that the factors that influence the waiting time for prescription services awere

the number of drug items (p = 0.013) and patient status (p = 0.000). The most dominant variable was the

patientstatus with Exp (B) / OR about 15,546, which means patients with collateral status have a 15.5 times

higher chance of experiencing an extended prescription service compared to patients who pay in cash.

1 INTRODUCTION

Patient waiting times for hospital services are

identified by the World Health Organization (WHO)

as one of the benchmarks of the health care system.

Patient satisfaction plays a significant role in

determining the health outcomes and in the quality

of health-care services provided by any health-care

organization.It is also directly associated with the

patient–provider relationship and with thec

ompliance of treatment plans of the patients. Patient

satisfaction is measured by using several indicators

that include services provided by the health-care

professionals, cleanliness, quietness, and wait times.

Prolongation of waiting time has long been

something that is complained of by the public and

seen as one of the things that has the potential to

cause dissatisfaction with patients (Alrasheedi, K.F,

et al, 2019, Odili et al., 2017). A patient’s

experience of waiting for long periods of time can

completely influence his/her perceptions of service

quality. A close relationship between patient

satisfaction and waiting time has been studied in

many studies (Xie et al., 2017; Sun, Jing. et all.,

2017, Luis Margusino-Framiñán et al.,2017,

Sengupta, Mitali, et al., 2019). The 2017 report from

the Institute of Medicine’s Report on the US

"Crossing The Quality Chasm" underlines a

framework of 6 principles that must be met in order

to remain competitive in the field of health. One of

these principles is the ability to provide timely

services and reduce delays that can harm patients.

Pharmacy unit provides product services and

services in the form of prescription services.

Prescription services as the frontline of

pharmaceutical services to patients must be managed

properly, because the quality of pharmaceutical

prescription services is generally associated with

speed in providing services.An increasing number of

patients visiting outpatient care units will increase

increasing challenges for the pharmacy unit to

continue to work effectively in providing excellent

service to patients (Amerine, et al, 2017). A slow

service will cause a long queue, causing an

extension of the waiting time for drug services.

Several studies have been carried out where

prescription services are still found that are not in

accordance with established standards (Himawan,

Vanji Budi, et al., 2018). The minimum service

standard set by the Kepmenkes is <30 minutes for

finished drugs and <60 minutes for compound drugs.

From these standards, we will get the level of

efficiency, effectiveness and sustainability of

Pharmacy services through prescription service

Alam, D., Girsang, E. and R. Nasution, S.

Identiﬁcation of Inﬂuence Factors on Waiting Time of Prescription Services for Outpatient.

DOI: 10.5220/0010286300230029

In Proceedings of the International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical (HIMBEP 2020), pages 23-29

ISBN: 978-989-758-500-5

waiting times, as well as the level of comfort and

perception of Pharmacy services through patient

satisfaction. The speed of service is target service

time can be completed within the time taken

determined by the organizer unit service.

Various methods have been carried out to

improve pharmaceutical services in terms of

reducing waiting times for prescription services

(Johann Daniels, et al., 2018, Alam et al., 2018 ,

2015; Loh et al., 2017, Lau, et al. 2018). In a study

conducted by Nanda, et al., 2017, one of the factors

that caused the lengthening of prescription service

waiting times was due to the long queues and the

way that could be done to fix the problems caused

by this long queue was to change the structure of the

queue model. The way to improve the waiting time

is to use a technology-based queuing system and

improve the quality and quantity of human resources

in the pharmaceutical department

(Ulfa et al, 2017;

Turnip et al, 2020; Wijaya et al, 2019). Suryana,

Danyel, 2018, made improvements by proposing the

replacement of a new hospital license and activating

the function of the Quality Control Team in the

Pharmacy Installation.

Previous studies examined prescription waiting

times from the queuing model structure, the quality

and quantity of Human Resources in the pharmacy

unit . This study was designed to observes the effect

of each factor from the pharmacy itself (type of

drug, number of drug items, work shifts) and patient

status (payment status) on the waiting time for

prescription services and to identify the most

dominant factor influencing the waiting time for

prescription services.

2 METHOD

The study was carried at Pharmacy Unit of the

Children's Outpatient Services at the Stella Maris

Hospital in Medan in November - December 2019.

The population in this study was the number of

prescriptions that were received from the pediatric

outpatient services. Determination of the population

is based on the average number of recipes per month

The data obtained by researchers researchers that the

number of outpatient prescriptions for children

served in the Pharmacy Outpatient Services for

Children during January - September 2019 is as

follows: In January 2019 : 3951 prescriptions,

February 2019 : 3350 prescriptions, March 2019 :

3728 prescriptions, April 2019 : 3743 recipes, May

2019 : 3671 recipes, June 2019 : 3717 recipes, July :

recipes, August 2019 : 4809 recipes and in

September : 5442 recipes. Thus the average number

of prescriptions served in the Outpatient Pharmacy

of the Children's Services Unit is 4012 prescriptions.

By using the Slovin formula based on the calculated

population, the number of samples used in this study

is 100 recipes. Samples were taken at random from

outpatients. Data is collected by filling out the

research sheet that has been provided. The

instruments used are digital clock, stationery,

calculator and form fields to write data obtained in

the research sheet.

Prescription service time will be calculated

from the time the recipe is received at the Pharmacy

Unit until the drug is received by the patient.

Through quasi observing prescriptions received in

the Pharmacy Unit for outpatient cases of Child

Services in the Children's Services Outpatient Unit,

second floor of Stella Maris Hospital. Some factors

related to the time of outpatient prescription service

are: Types of prescriptions, number of drug items,

shift workers and patient status. In this study, the

dependent variable (Dependent) is the prescription

service time for outpatients in the Pharmacy

Installation, while the Independent Variable

(Independent) is the type of prescription, the number

of drug items, shift workers and patient status.

The data processing is carried out by carrying

out various stages, as follows:

1. Coding is to group the samples obtained in

accordance with the existing conceptual

framework. The sample is coded to facilitate

identification and input process to the

computer. The author categorizes the data

manually based on the group, namely the type

of prescription, the number of drug items, staff

shifts and the status of the patient into a

working paper including equating units of

time to minutes

2. Editing is to re-examine the completeness and

accuracy of data categorization manually

3. Data Entry is entering data into the computer,

in this study using SPSS

4. Cleaning is checking the data that has been re-

entered to ensure that the data is free from

errors.

Data analysis was carried out univariately to

analyze existing variables descriptively by

calculating the frequency distribution and the

proportions of each dependent and independent

variable. Bivariate analysis is continued using Chi-

Square to determine the relationship between the

dependent variable and independent variables and

multivariate analysis using multiple logistic

regression tests with a confidence level of 95% (α =

HIMBEP 2020 - International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical

0.05), to find out which variable most significantly

influences the waiting time for prescription services.

Overall the research is shown in Figure 1.

Figure. 1 The Scheme of Research Procedure

3 RESULT AND DISCUSSIONS

From the observations in the field, the flow of the

outpatient service process (figure 2) can be

explained as follows:

1. Patients registered at the Front Office.

2. Medical staff will conduct an assessment

(body weight, body temperature, patient’s

chief complains, history of allergic)

3. Patient will be served by doctor’s on duty.

4. If the patient needs medicine, the doctor will

give a prescription

5. Prescription is sent through the hospital

system (e-prescription).

6. After prescription are sent to the pharmacy

unit, patients will be asked to complete

payment at the hospital chasier. Patients can

take medicine after completed the payment

7. The pharmacist will open the patient’s

medical record to see the doctor’s prescription

and conduct the prescription assesment.

Prescription review has to accordance with

administrative requirements, pharmaceutical

requirements and clinical requirements.

8. Preparation consists of several stages:

Compounding, an activity of preparing,

weighing, mixing, packaging and giving

etiquette to the container. Etiquette. Drug

packaging. Submission of drugs. Before the

drug is delivered to the patient, a final check

must be made of the suitability of the drug

with the prescription and drug information.

9. After the medicine is finished prepare, the

pharmacy officer will deliver the drug to the

patient by showing proof of payment (if the

patient pays in cash) or there is confirmation

from the guarantor (if the patient is

guaranteed).

10. Patients have to be informed about the

medicine information that at least includes:

how to use the drug, how to store the drug, the

duration of treatment, activities and food and

drinks that must be avoided during therapy.

From the flow described, Waiting time for

prescription services in this research is defined the

time needed from the prescription received by the

pharmacy unit until the medicine is delivered to the

patient / family.

The flow for the prescription waiting time can be

seen in figure 2.

Figure. 2 The Flowchart of Outpatient Department Service

Identiﬁcation of Inﬂuence Factors on Waiting Time of Prescription Services for Outpatient

Figure. 3 Pictures of research process

The study was conducted by direct observation

in the field of prescriptions that entered the

children's outpatient services. Based on data from

100 samples taken, the frequency distribution of

each variable is 50% of finished drugs and 50% of

concoctions. The number of drug items in the

majority is large (55%), minority is small (45%).

The majority of work shifts are morning (59%), the

afternoon minority (41%) and the majority are cash

patients (87%), the minority is guaranteed (13%).

Shown Table 1.

Table 1: Frequency Distribution of Each Independent

Variable

No Independen Variables f %

1 Type Of

Drug

Fixed

Concoction

2 Items Few

Many

Shift Morning

Noon

4 Patient’s

status

Cash

Guarantee

Data taken from prescription are independent

variables (Table 1) patient status (A), work shift (B),

type of drug (C), number of drug items (D) and

Dependent variable was waiting time (E). Each

variable was given 2 categories: patient cash status

with code 1 and guarantee with code 2; morning

shift work with code 1 and afternoon with code 2;

Type of fixed drug with code 1 and concoction drug

with code 2; The number of drug items was few with

code 1 and many with code 2; Standard waiting time

to code 1 and not standard to code 2. The waiting

time periodwas from the time the prescription

received at the pharmacy to the medicine being

delivered to the patient. The standard time is <30

minutes for finished drugs and <60 minutes for

compound drugs. The measured data is given in

Table 2.

Table 2: The measured data for each variables of

evaluated prescription.

NO A B C D E NO A B C D E

1 1 1 1 2 2 51 1 1 2 2 1

2 1 1 1 2 2 52 1 1 2 1 1

3 1 1 1 1 1 53 1 1 2 1 1

4 1 1 2 2 1 54 1 1 1 1 1

5 1 1 2 1 1 55 1 1 1 1 1

6 2 1 2 2 2 56 1 1 2 1 1

7 2 1 2 2 2 57 1 1 2 2 1

8 1 1 1 2 2 58 1 1 2 2 1

9 1 1 1 2 1 59 1 1 1 1 1

10 1 1 1 1 1 60 1 1 1 2 1

11 1 1 2 2 1 61 2 1 1 1 1

12 1 1 2 2 1 62 1 1 1 2 1

13 1 1 2 1 1 63 1 1 2 2 1

14 1 1 1 2 1 64 1 1 1 2 2

15 1 1 2 2 1 65 1 1 1 2 1

16 1 1 1 1 1 66 1 1 1 1 1

17 1 2 2 1 1 67 1 1 2 2 1

18 1 2 1 1 1 68 1 1 1 1 1

19 1 2 1 1 1 69 1 1 2 2 1

20 1 2 2 1 1 70 2 1 2 2 1

21 1 2 1 1 1 71 2 1 1 2 2

22 1 2 1 2 1 72 1 1 1 2 2

23 1 2 2 2 1 73 1 1 1 2 2

24 1 2 2 1 1 74 1 1 1 2 2

25 1 2 1 2 1 75 1 2 1 1 1

26 1 2 2 1 1 76 2 2 2 2 2

27 1 2 2 1 1 77 1 2 1 1 1

28 1 2 2 1 1 78 1 2 1 2 2

29 1 2 1 1 1 79 1 2 2 1 2

30 1 2 1 1 2 80 1 2 2 2 1

31 1 2 2 2 2 81 1 2 1 1 1

32 1 2 2 2 1 82 1 2 1 2 1

33 1 2 1 1 1 83 1 2 1 1 1

34 2 2 1 2 2 84 2 2 1 1 1

35 1 2 1 2 1 85 1 2 2 1 1

36 1 2 1 1 2 86 1 2 2 2 1

37 1 2 1 1 1 87 2 2 1 2 2

38 1 2 1 1 1 88 1 2 2 2 1

39 1 2 2 2 1 89 1 1 2 2 1

40 2 2 1 2 2 90 1 1 2 1 1

41 1 2 2 2 1 91 1 1 2 2 1

42 1 2 2 1 1 92 1 1 1 2 1

43 1 2 1 2 1 93 1 1 2 2 1

44 1 1 2 1 1 94 1 1 1 1 1

45 2 1 1 1 2 95 1 1 2 2 1

46 1 1 1 1 1 96 1 1 1 2 2

47 1 1 2 2 1 97 2 1 2 2 2

48 1 1 2 2 1 98 2 1 2 2 2

49 1 1 2 1 1 99 1 1 1 1 2

50 1 1 2 2 1 100 1 1 2 1 1

HIMBEP 2020 - International Conference on Health Informatics, Medical, Biological Engineering, and Pharmaceutical

Data management was done by testing the

characteristics of each variable (Columns A, B, C, D

and E), then a bivariate test (Chi-square) was used to

determine the effect of the independent variables

(Columns A, B, C, D) on the dependent variable

(Column E). After finding a variable with a p-value

<0.05, it was continued with the Multiple Logistic

Regression test to find the most dominant factor

influencing the waiting time for prescription service.

From the data that has been processed, it appears

that the variable Drug Type (C): from 100

prescription samples, found 68% (34 prescriptions)

of finished drugs and 84% (42 prescriptions) of

concoction drugs that are in accordance with the

standards. Whereas 32% (16 prescriptions) of

finished drugs and 16% (8 prescriptions) of

concoction drugs did not meet the established time

standard. This means that for each drug category>

50% was still in accordance with the expected time

standard. It was in line with the chi-square

calculation where a p-value of 0.101 was obtained,

by mean that there was no effect of the type of drug

with prescription service waiting times (Table 3).

The number of drug items (D) prescribed by

doctors varies from 1-6 types of drugs. The mean

number of drugs prescribed was 2.77. For

prescriptions prescribed drugs <2.77 (small

category), those that were in accordance with the

standard are 88.9% and those that do not meet the

standard of 11.1%. For those who are prescribed>

2.77 (many categories), those that comply with the

standard are 65.5% and those that do not meet the

standard 34.5%. It appears that the more the number

of drugs prescribed, the higher the percentage of the

number of prescriptions whose waiting time does not

meet the established standards. These results were in

line with the Chi-Square test between types of drugs

to the waiting time for prescription services that get

p-value of 0.013, by mean that there was an

influence of the number of drug items to the waiting

time for prescription services (Table 3).

For the Work Shift variable (B), a total of 59

samples were taken on the work shift morning and

41 samples at the afternoon shift. Of the 59 recipes

in the morning shift that were in accordance with the

standards as many as 44 recipes (74.6%) and those

that did not comply with the standard were 15

recipes (25.4%). For 41 recipes in the afternoon

work shift that were in accordance with the standard

as many as 32 recipes (78%) and those that were not

in accordance with the standard were 9 recipes

(22%). Comparison of the percentage obtained in the

morning shift and the afternoon shift is almost the

same between those in accordance with the

standards and those that do not comply with the

standards. Statistical test results were in line with

using the Chi-Square test obtained p-value of 0.825

meaning that there was no effect of work shifts on

prescription service waiting times (Table 3).

Of the 100 samples obtained data for patient

status variables, 87 samples are private patients who

pay in cash and 13 samples are patients with

payments guaranteed by partner companies and

insurance. It appears that there were more patients

with cash payments than patients with collateral. Of

the 87 prescriptions for patients using the cash

payment method, 73 prescriptions (83.9%) were in

accordance with the standard and those that did not

comply with the standard were 14 prescriptions

(16.1%). For 13 recipes with a guarantee payment

method, 10 recipes (76.9%) were not in accordance

with the standard while 3 recipes (23.1%) were in

accordance with the standard. These results were in

accordance with the results of statistical tests using

the Chi-Square test obtained p-value of 0.000

meaning that there was an influence of patient status

on the waiting time for prescription services (Table

2).Based on the results of bivariate analysis obtained

independent variables significantly related to waiting

time for prescription services which the number of

drug items (p = 0.013) and patient status (p = 0.000).

The complete Chi-Square statistical test results can

be seen in Table 3.

Table 3: Effects of Each Dependent and Independent

Variables

Varia-

bles

Standard Out of

Standard

Qty

value

f % f % F %

Type of

Drug :

Fixed

Concoc-

tion

100

0.1

Items:

Few

Many

88.9

65.5

11.1

34.5

100

0.0

Shift:

Mor-

ning

After-

noon

74.6

25.4

100

0.8

Patients

Status:

Cash

Guaran-

tee

83.9

23.1

16.1

76.9

100

0.0

After bivariate testing, it was continued with

multivariate testing with multiple logistic regression

to obtain the results as listed in Table 3.

Identiﬁcation of Inﬂuence Factors on Waiting Time of Prescription Services for Outpatient

Table 4: Significant Multiple Logistic Regression Test

Results

Variables B Sig Exp(B) 95%CIfor

Exp(B)

Typeof

Drug

1.301 .033 3.672 1.113‐12.114

Patient

status

2.744 .000 15.546 3.606‐ 67.030

Constant ‐6.509 



The most influential variable in this study is the

patient status variable which has an Exp (B) / OR

value = 15,546, which means patients with collateral

status have a 15.5 times higher chance of

experiencing extended prescription service time

compared to patients with cash status (without

guarantee).

Independent patients (without guarantee) can

make payments directly to the cashier. As for

patients with guarantees, the hospital billing

department must inform the guarantor in advance.

The billing process is considered complete when the

hospital billing staff has received confirmation from

the guarantor about the approval of the guarantee for

the services, procedures or drugs given to the

patient. Therefore, the difference in prescription

service time between independent and guaranteed

patients is the time needed to receive confirmation

from the guarantor of the cost of patient services. At

this time the hospital is doing all the confirmation

processes manually. To make improvements,

communication should be made with stakeholders so

that it can speed up the assessment and clarification

process related to the patient's condition. The

process that is carried out manually takes longer.

With the rapid development of technology, this

process should also be done using applications or e-

claims, so as to accelerate the process of hospital

services, especially in prescription services. Because

outpatients cannot receive drugs before the

clarification process is completed.

The variable number of drug items that have the

value Exp (B) / OR = 3.672 means that patients with

many drug items have a 3.6 times higher chance of

experiencing an extended prescription service time

compared to patients with a small number of drug

items.

The average number of prescriptions provided is

2.77, meaning that if the number of drugs prescribed

by a doctor is greater than 2.77, it will affect the

time required by the pharmaceutical staff to prepare

the prescription. The large number of items will

affect the addition of time in the numbering phase,

the stage of prescription entry, the stage of taking

fixed drugs and the stage of making concoction

drugs into capsules, packs, and liquids so that it

takes a longer time than those with fewer items.

The number of drug items related to the waiting

time for prescription services is caused by several

things, among others, outpatient pharmaceutical

facilities that are too narrow, thus limiting the space

for officers. The more the number of drugs

prescribed, the more time is needed to input the use

of drugs into the system. Therefore, it is need to

improve the pharmaceutical facilities in accordance

with established standards. Urge doctors through the

medical committee to prescribe drugs rationally and

reduce polypharmacy.

4 CONCLUSIONS

In this study, the infuence of six-variable on the

waiting time for prescription services was identified.

Patient status was the most dominant influence on

waiting time for prescription service (p-value =

0.000) and Exp (B) / OR = 15,546. Prescription

types about 68% of drugs and 84% of concoction

drugs are in accordance with the standard service

time (p-value = 0.101, no effect on the waiting time

for prescription services). The number of drug items

was 34.5% prescription with the category of the

number of drugs was still not according to the

standard (p-value = 0.013, there was an effect of the

number of drug items on the waiting time for

prescription services with Exp (B) / OR = 3,672).

Morning work shift, 74.6% prescription and

afternoon shift 78% are in accordance with the

standard (p-value = 0.82, there was no affect the

waiting time for prescription service).

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Identiﬁcation of Inﬂuence Factors on Waiting Time of Prescription Services for Outpatient