Analysis of Discrepancies Between Manual and Automated ROL of Drugs1

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Summer PlacementIn

SIR GANGA RAM HOSPITAL

(April 4 - May 30, 2011)

Analyses of discrepancies between manual and automatedRE-ORDER LEVEL / RE -ORDER QUANTITY of drugs

Dr. SHUCHI VASHISHTHA

Post-graduate Programme in Hospital & HealthManagement,New Delhi

2010-12

International Institute of Health Management Research, NewDelhi

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2011

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ACKNOWLEDGEMENT

I hereby take this opportunity to thank, Dr R. K. Ganjoo, Director Medical for giving me the

opportunity to do my Summer Training at Sir Ganga Ram Hospital. He was very kind

enough to give his valuable guidance and advice. He inspired me greatly to work in this

project. His willingness to motivate me contributed tremendously to my project.

My special thanks to Dr. Karanveer Singh, Consultant Surgeon and Head of Medical

Informatics

And Head IT, Sir Ganga Ram Hospital for his guidance, support, interest, involvement and

encouragement. He has left no stone unturned in updating me regarding the subject.

I wish to express my deep sense of gratitude to Dr. Gurvinder Kaur, Deputy MedicalSuperintendent, Sir Ganga Ram Hospital for her guidance and support throughout. She was

very kind enough to spare her valuable time and provided several important suggestions at

every stage of my study.

Besides, I would also like to thank the entire Healthcare IT team and the Hospital Staff for

their encouragement and cooperation in carrying out the project work.

My sincere acknowledgement goes to Professor Indrajit Bhattacharya and Professor

Aanandhi Ramachandran for their kind assistance and support throughout my dissertation.

Finally, an honorable mention goes to my family and friends for their understanding and

support on me in completing this project.

Thank You

Dr. Shuchi Vashishtha

PGDHHM,

IIHMR, New Delhi

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FEEDBACK FORM

Name of the Student:

Summer Training Institution:

Area of Summer Internship:

Attendance:

Objectives met:

Deliverables:

Strengths:

Suggestions for Improvement:

Signature of the Officer-in-Charge

(Training)

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DatePlace

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Table of contents

1. Acronyms / Abbreviations

5

2. Hospital/organization profile

63. Introduction

8

Hospital information system

8

Objectives of HIS

9

Advantages of HIS

9

Workflow of pharmacy

14 Re-order Level

17

Re-order quantity 18

Maximum stock level

18

Minimum stock level

18

Lead time

19

Buffer quantity19

Area of engagement

21

1. Method and Data

24

2. General Findings

31

3. Conclusion

38

4. Case study Introduction

41

Methodology

45

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Observation

47

Recommendation

65

Conclusion

66

1. References

68

2. Annexure 70

Acronyms / Abbreviations

HIS Hospital information system

ROL Re order level

ROQ Re order quantity

PO Purchase order

IP In patient

CSSD Central sterilization and supply department

GRN Goods received note

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Hospital/organization profile

Sir Ganga Ram Hospital (India)

Sir Ganga Ram Hospital is a 650-bed multi-specialty state-of-the-art hospital in Delhi. It

provides comprehensive health care services, and has acquired the status of a premier

medical institution. It is one of the hospitals in the private sector that has maintained nearly

100% bed occupancy due to its reputation of providing the highest level of medical services

to patients from Delhi and all over India.

History / Location / Area

The hospital was founded initially in 1921 at Lahore by Sir Ganga Ram (1851-1927), a civil

engineer and leading philanthropist of his times. After the partition in 1947, the present

hospital was established in Rajindra Nagar in New Delhi on a plot of land approximately

11 acres (45,000 m2). The foundation was laid in April 1951 by the then Prime Minister of

India Shri Jawaharlal Nehru and inaugurated by him on 13 April 1954.

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Departments

Critical Care and Emergency Medicine

Institute for Child Health (with state of the art neonatology services)

Institute of Renal Sciences (nephrology, urology and kidney transplantation)

Institute of Minimal Access, Metabolic and Bariatric Surgery

Gastroenterology

Surgical Gastroenterology & Liver Transplantation

Neurosciences (medical, surgical and spinal surgery) Cardiology & Cardiac Surgery

Cosmetic and Plastic Surgery

Clinical Hematology & Bone Marrow Transplantation

Joint Replacement

ENT and Cochlear Implantation

Ophthalmology

Peripheral Vascular and Endo vascular Surgery

Medical Genetics

In-vitro Fertilization

Medical and Surgical Oncology

Blood Transfusion Services

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Introduction

Hospital information system:

According to U.S. National Library of Medicine HIS is an integrated, computer-assisted

system designed to store, manipulate and retrieve information concerned with the

administrative and clinical aspects.

As an area of medical informatics the aim of HIS is to achieve the best possible support of

patient care and administration by electronic data processing. It helps to integrate all the

departments through the electronic records.

Hospital Information system (HIS) is a computerized software that helps in various

activities of the Hospital. HIS is expected to perform following activities:

Patient Registration . Admission

Emergency Nursing Activities

Laboratory Investigations Radiology Tests

Pharmacy Management Medical Consumables

Operations CSSD

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Diet Management Discharges

Billing Purchase

Finance HR etc.

Objectives of HIS

1. To increase the operational efficiency of the hospital.

2. To increase the operational effectiveness of the hospital.3. To reduce human error.

4. To reduce operational cost.

Advantages of HIS in a hospital

Provides continuous medical record for each patient.

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Helps in billing for medication

Result of a test can be compared

.

History of diagnosis, operations and medicines can be obtained.

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Computerized Physician Order Entry (CPOE) can be done

Interaction alerts are provided.

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Allergy alerts are provided

.

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Drug monographs are given.

Drug substitution can be done.

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Helps in inventory control, etc.

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Sir Gangaram hospital is using Intersystems TrakCare as its HIS and Cache as the

database. Earlier it was using Fox Pro system for 20 years. The implementation of

Intersystems TrakCare started in 2005 in phases. It was implemented in pharmacy in

2007.

Various Modules of HIS at SGRH

Pharmacy management is a crucial part of HIS functions. The pharmacy management deals

with the maintenance of drugs and consumables in the hospital. The functions of this

module include, online drug prescription, inventory management of drugs and consumables.

This module optionally handles the billing of drugs and consumables, if required. The

Pharmacy module ensures that there is a round the clock availability of a sufficient quantity

of drugs and consumable material for the patients in a mode that neither hinders efficient

clinical work, nor it becomes a threat to the survival of the Pharmacy.

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Workflow of pharmacy:

Indent is transferred from ward to pharmacy.

Then it is further transferred to main pharmacy (godown).

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Then a purchase requisition (ROL/ROQ) is made to purchase

department.

Purchase department makes purchase order (PO).

PO goes to vender.

Vender supplies goods receiving notes (GRN) to the receiving department

Stock gets replenished.

Re order level

Stock consumption

(packing )

Purchase order

Stock increaseDelivery and GRN

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But before raising the request pharmacy has to calculate a re-order quantity. In order to

estimate the minimum quantity of goods required the pharmacy manager should know the

following

How much in hand. At what point to re order?

How much to order.

(Desselle S. P. and Zgarrick D P,):

ROQ is calculated by taking into consideration certain factors like: lead time, re-order level,

minimum quantity, maximum quantity and buffer quantity.

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Re-order Level:

This is the minimum stock level of an item at which a new order for supply of stock is to be

placed. In other words, at this level a purchase requisition is made out.

The reorder point for replenishment of stock occurs when the level ofinventory drops down

to zero. In view of instantaneous replenishment of stock the level of inventory jumps to the

original level from zero level. (Khan, M.Y.; & Jain, P.K.)

In real life situations one never encounters a zero lead time. There is always a time lag from

the date of placing an order for material and the date on which materials are received. As a

result the reorder point is always higher than zero, and if the firm places the order when the

inventory reaches the reorder point, the new goods will arrive before the firm runs out of

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goods to sell. The decision on how much stock to hold is generally referred to as the order

point problem, that is, how low should the inventory be depleted before it is reordered.

In reality, demand during any time period is uncertain. When demand is uncertain, a natural

question is "How low one should let ones inventory level goes before placing an order?" We

call the inventory level at which an order should be placed the reorder level. Clearly, a high

reorder level will lower shortage costs and increase holding costs. Similarly, a low reorder

level will increase shortage costs and lower holding costs. At some intermediate value for

the reorder level, the sum of shortage and holding costs will be minimized. (Winston W. L.)

The re-order level can be calculated by using the following formula:-

Re-order level = Average daily consumption *(Lead

time + Minimum inventory days)

Re-order quantity:

It is the quantities to be ordered once the re order level is reached.

According to Accounting Terms Dictionary Inventory level of an item which signals the

need for placement of a replenishment order, taking into account the consumption of the

item during order lead time and the quantity required for the safety stock.

The reorder quantity can be calculated by using the following formula:-

Re-order quantity = Maximum stock level (Stock in

hand +Quantity already in

purchase / delivery pipeline)

Maximum stock level:

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Maximum stock level is the maximum amount of stock you should maintain to avoid

wastage of drugs due to expiration.

The maximum stock level can be calculated by using the following formula:-

Maximum stock level = Reorder level + (Average daily

consumption * Optimum stock holding days)

Minimum stock level:

The minimum level or minimum stock is that level of stock below which stock should not

be allowed to fall. Stock replenishment should occur before this.

The minimum stock level can be calculated by using the following formula:-

Minimum stock level = (Average daily consumption *

Minimum inventory days) + Buffer stock.

Lead time:

A time gap from the date of submission of purchase request to the purchase department for

an item to the date on which that item is received.

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Buffer quantity:

A supply of inputs held as a reserve to safeguardagainstunforeseen shortages ordemands.

This is done for life saving drugs.

Objective of the study

The pharmacy in a hospital is an area where the medical and non-medical components of a

hospital information system (HIS) meet. Alongside inventory control are components

relating to drug allergy warnings, drug-drug interaction alerts and intelligent pharmaceutical

substitution of prescribed drugs from within current inventory stock. Sir Ganga Ram

Hospital, New Delhi, went in for enterprise wide computerization of its hospital, including

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its pharmacy in June 2007. The hospital has an in-house pharmacy with a daily turnover of

over Rs 13 lakhs. Now the pharmacy is totally computerized except for the process of

making purchase requisition, which is in process of being automated.

The main features of pharmacy module are:

Computerized Physician Order Entry (CPOE)

The care providers are able to place medication orders in the system at the ward

level itself. This allows the hospital to also limit the number of medicines they can

order. The list of medicines visible to care providers can also be limited initially to

only those that are listed in the hospital formulary. Since formulary drugs are

available at a much lower price than non-formulary drugs, their purchase price

having been negotiated with the vendor, it adds up to a substantial cost saving. In

case the care provider does not find the medication in the formulary list, he has the

option to uncheck the 'Limit to Formulary' box and see all medicines.

Interaction alerts

The HIS system warns of drug-drug interactions and gives details of each interaction

type. However to be really useful, all medication prescription entries need to done in

the system by the doctor who is more likely to attend to the alert than if the same

entry is being done by a nurse on the behest of a doctor.

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Allergy alerts

Allergy alerts are also provided by the system. In case the patient has been flagged to

be allergic to a particular medication, even during a previous visit to the hospital,

such alert information is carried forward during the lifetime of the patient, unless

manually cancelled by a care provider. The system does not stop the prescription

from going through; it simply warns the doctor.

Drug monographs

Drug details (monographs) are available in the system. A doctor can click on a drug

he is planning to prescribe and read up details on the indications, dosage, side

effects, interactions, etc. This data had been provided to the hospital as part of the

drug database that was purchased prior to starting the system.

Drug substitution

Intelligent drug substitution works by substituting another drug only if the generic

drug, strength, drug form, route and unit of packing are the same for both the drugs.

Thus, tablet Crocin does not substitute with injection Calpol. Nor does tablet Crocin

250 mg substitute with tablet Calpol 500 mg. It also will not substitute Tetanus

Toxoid vial with Tetanus Toxoid ampoule, since the packing unit is not the same.

Inventory control

At any time it is possible to know the medicine stock lying at various sub stores.

This also allows moving stocks from a location where they are in excess to areas

where they are urgently needed. It also allows to recall a batch from circulation

should it be required, since we can trace movements of each batch to various sub

stores as well as patients to whom they had been dispensed.

Billing for medication

Each batch of a drug has a price attached to it at the time of receiving the drug in the

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hospital's receiving section. This is what gets billed to each patient without any

additional user intervention.

Indent :

The indent is raised by the nursing station and other departments to the main store (like IP

pharmacy). It can be defined as the request for the items intended to be used on a patient or

for internal consumption of the department.

Types of indent

Emergency:

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Emergency medicines are urgent or immediate medicines. This means they are

required RIGHT NOW. If the ward nurses send indent as emergency medicines then

nurses go to collect the medicine from IP pharmacy within 30 min.

Stat:

Stat medicine is a medicine whose ideal time for receiving is within 1hr.it is also an

urgent medicine. If a patient needs stat medicine then nurses send the indent as stat.

Normal:

Normal medicines are those medicines which are required on daily basis and they

are not so urgent. Time for receiving normal medicine is within 24 hrs.

In Sir Gangaram Hospital the formation of pharmacy indent is a manual process whichrequires at least 4 days. Now the hospital is trying to make the whole process automated by

using HIS in pharmacy. The process of making indent automatic is in its pre implementation

phase. This is a base line study based on which complete re order quantity will be

automated.

A pilot run of the automated indent was done. The project allotted to me is to analyze

discrepancies between the existing manual and the pilot run of automated RE-ORDER

QUANTITY of drugs, to find out the accuracy of automated technique and if there are any

discrepancies and suggest interventions to improve it.

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METHODOLOGY

Method and Data

The study is analytical in nature. It is based on secondary data collection.

The formation of indent happens in both TrakCare and prodigious modules of HIS. In

TrakCare the transfer of indent from ward to pharmacy and then to godown is done. The

purchase requisition, purchase order and GRN are made in prodigious. The change in stock

level happens simultaneously in both.

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TrakCareoduct

mission, Ordering, Nursing, Stock Issue, Radiology etc.

TrakCareoduct

mission, Ordering, Nursing, Stock Issue, Radiology etc.

ProdigiousIndian Product

For Back office

Modules: Purchase, Stock Receiving, Finance, HRD, As

ProdigiousIndian Product

For Back office

Modules: Purchase, Stock Receiving, Finance, HRD, As


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The nursing station and other departments raise the indent to the main stores (like IP

pharmacy) Nursing station/wards/ ICUs/ emergency raise Patient indents on HIS based on

IPID (for items charged to patients) and Day care nursing station (dialysis, procedure room,

day care OT) raise Day care patient indents based on UHID (for items charged to patients)

and then main store IP pharmacy acknowledges patient indent on HIS.

The pharmacy in Gangaram hospital is totally computerized except the process of making

pharmacy purchase requisition. The indent formation is a manual process in Gangaram.

Now the hospital is trying to make it a computerized process. In order to check the accuracy

of computerized process a pilot run of automated ROQ was done.

MANUAL PROCESS OF RAISING INDENT

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Manual indent

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In the main pharmacy stock movement report for 2 months is generated. Out ofwhich average for one month is extracted.

[(Stock in hand) (Average for 1 month)] = Purchase request

This request is then sent to purchase department for creation of purchaseorder.

Problems with the manual process of raising indent

It is a Time consuming process.

Most of the time the drugs already in pipeline are not considered.

The risks of human errors are high.

Drugs are left from being added in the indent

Some generic drugs are added more than once.

These problems are addressed in computerized process

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COMPUTERISED PROCESS OF RAISING THE PILOT RUN

The data for the ROL report was extracted from the prodigious module of

HIS.

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The data for the ROL report was extracted from the prodigious module of HIS.The data for the ROL report was extracted from the prodigious module of HIS.

Ported in Microsoft access database.Ported in Microsoft access database.


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In the manual process the data is collected by using the brand names but in the automated

process the data is collected by using generic names. Using generic names avoids chances of

repetition of drug thus avoids ordering of extra quantity of drugs.

During manual process most of the times pipeline is not considered but in automated

technique it is considered every time.

The collection of data in manual technique requires 4 days minimum but it takes just 5 to 10

minutes in automated technique to generate the report. And further 2-3 hrs are required for

further processing.

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Thus the report was generated after further processing.Thus the report was generated after further processing.


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General Findings

The raising of purchase requisition is a manual process in sir Gangaram hospital, now the

hospital is trying to make it a computerized process. In order to reach the desired goal the

information and technology department generated formulae to calculate ROL, ROQ etc. A

pilot run was done in order to check the accuracy of the computerized process.

The purpose of my study was to analyze the discrepancies between the existing manual and

the pilot run of automated RE-ORDER QUANTITY of drugs and to find out the accuracy of

automated technique.

In order to fulfill the purpose of the study the two reports were collected. The two reports

were ported in the Microsoft excel format for further analysis. The analysis was done on the

basis of any differences found between the amount indented in both manual indent and the

computerized ROL report.

The automated ROL report was taken as the basis of the study and it was further compared

with the manual report and thus the differences found were named as discrepancies. The

analysis was done by comparing both the dataes and finding the differences between them.

The answers were then plotted as graphs.

The data used for analysis was as follows:

A total of 740 drugs were reported in Manually Prepared Indent

based on 2 month consumption.

A total of631 drugs were reported in automaticROL Reportbased on

3 month consumption.

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One of the main draw backs of raising an indent manually is that it is a time consuming

process. And also there is a significant amount of labor lost. This labor and time can be

utilized in doing something more productive. The manual process requires a time period of

at least 4 days to raise the purchase requisition whereas in automatic process report was

generated in just 5 min. and further 3 hrs more are required for further processing.

The total numbers of drugs indented in computerized ROL report are 601 out of which 203

drugs were found to have different values in both the reports. Thus on analysis around 32%

discrepancies was found between the manual and automated ROL report. This means that

due to some reason either manual report was showing some mistakes or automated ROL

report had done some mistake.

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Purchase requisition is made by the main pharmacy store to the purchase department

and then purchase department sends a purchase order to the vendor. Some times

when drugs are ordered in a particular amount and are supplied in lesser amount by

the vendor the drugs left are said to be in pipeline and sometimes the drug has

already been ordered but not supplied then again it is said to be in pipeline. It is very

important to keep in mind the status of drugs in pipeline because if not considered it

may lead to crossing of maximum stock level.

Out of total discrepancy in ROL report 54% were due to items being already in

pipeline which had not been considered in the manual indent.ie out of 203 drugs

with discrepancies 110 drugs were already in pipeline and were ordered again.

One of the main defects of a manual indent is the high risk of human errors.

Sometimes few generic drugs are ordered more than once because of the

dissimilarities in the brand names and cost. This factor is again very important

because if a generic drug is being ordered more than once then there is a high risk of

its crossing the maximum stock value and can be overstocked and thus get wasted

due to multiple reasons like expiration, breaking etc.

Out of total discrepancy in ROL report 5% were found to be the items had

accidentally been included multiple times in the manual ROL report. This

means that out of 203 discrepancies found between manual indent and automated

ROL report 13 cases had been accidentally ordered multiple times.

.

Some drugs have an average daily consumption much higher than other drugs these

drugs are called as fast moving drugs. The importance of these drugs is that the

consumption rate of such drugs is very high thus if these drugs are ordered either in

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higher amounts or in lower amounts the drugs might cross the maximum or

minimum stock level.

The total discrepancy in fast moving drugs was found to be aprox. 19%. Thus this

means that out of total 203 discrepancies found between manual indent and

automated ROL report 39 drugs were found to be fast moving.

The raising of indent being a manual process the risk of human errors is very high.

Sometimes it happens that some of the drugs are missed in indent. Thus might result

in crossing the minimum stock level. And during urgent need of the drug the drug

may not be present in the stores. Thus it is again a serious drawback of manualprocess.

The total discrepancy in costly drugs was found to be approx. 11% of total

discrepancies in ROL report.ie out of total 203 drugs with discrepancies 23 drugs

were costly. The importance of costly drugs is that if these drugs are ordered in high

amounts and thus are over stocked hospital loses its money due to wastage and if

these are ordered in lees amount than desired the drug may not be available in case

of emergency.

Conclusion

The purpose of the study was to find out the discrepancies between manual indent and the

automated ROL pilot run report and to find out the accuracy of the automated process. The

following advantages and disadvantages were observed in the pilot run during the study.

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A dvantages:

The time consumption in raising the indent reduces from 4 days to 5 min.

Reduces human errors.

The drugs in pipeline are always considered.

No drug is left from including in indent.

No generic drug is ordered more than once.

Reduces the risk of reaching minimum inventory level.

Reduces the risk of crossing maximum inventory level.

DISADVANTAGES OF AUTOMATED ROL REPORT

* Although it studies dynamic usage patterns, these are based on past trends. It cannot

predict future trends, for instance the onset of the flu season, requiring advance stocking of

antipyretics.

* The computerized ROL report is an advisory report and some further manual

processing is still required, for instance rounding off of the request quantity to match the

nearest packaging available. However this process adds only a couple of hours to the

exercise, effectively reducing the time from 4 days (manual) to 3 hours (automated).

* There are still some technical problems in the computerized process like correction

of master drug data, few drugs were not ordered in the computerized process etc these

problems have to be delt with before implementation.

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Thus this can be concluded that though there is some manual activity still required, but

the advantages of using the automatic process is far more than the manual process.

It is suggested that this report should only be implemented after the corrections have

been done because it involves inventory (monetary) considerations. Thus the

implementation of automatic indent is recommended after some more analysis has been

done.

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CASE STUDY

ANALYSIS OF REVENUE & EXPENDITURE

OF DAYCARE GYNAECOLOGY PACKAGES

USING SPEEDMINER

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Introduction

Hospitals using a hospital information system (HIS) accumulate a huge amount of

transactional data during their daily activities. Extracting these data in an analyzable form to

maximize the benefits of the HIS is rarely given importance. If the hospital wants to extract

data using ad hoc criteria, e.g. elderly female patients being admitted under the cardiology

services with acute myocardial infarction with a length of stay of more than one month, it is

impossible to use readymade MIS reports. This is where a data mining software tool comes

in handy.

Data mining is the process in which there is analysis of data from different angle and

perspectives and summarizing the same data into the relevant information. This kind of

information could be utilized to increase the revenue, cutting the costs or both. (Malick Md)

Data mining software is mainly used for analyzing data and also assists in accumulation of

data for the different sources and categorizes and summarizes the given data into some

useful form

The data mining gives a chance or opportunity to enhance the future performance of the

business organization. There is a common philosophical phrase that, he who does not learnfrom the history is destined to repeat the same. Therefore, if these predictions are done with

the help and assistance of the historical information (data), then you can get sufficient data

for improvising the products of the business organization.

Data mining tools allow on-the-fly data analysis. One simply selects the criteria to be

studied and the data are updated immediately. One can add more criteria and the data are

updated each time. Sir Gangaram is using speed miner as the data mining tool. Speedminer

DW and BPM is one the most comprehensive and fully integrated sets of data warehouse,business intelligence and business performance management solution available. Speedminer

not only assists in uncovering the wealth of information in the corporation to build the best

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Business Intelligence platform, but also to manage the performance of the business so that

the business will always stay ahead of competition and excel.

Modern day hospitals provide a variety of services to patients under one roof. It is akin to a

large service organization considering the number of personnel involved and the capital-

intensive nature of the business be it the civil structures, operation theaters & equipment,

diagnostic and therapeutic equipment, resuscitation equipment, gas lines, surgical

instruments, consumables, etc. Moreover, it is 24 x 7 operations with people playing a vital

role in the well being of the patients in the hospital.

Earlier the hospitals were the place where a patient used to come to get good care. The

scenario in the past few years has changed dramatically within the healthcare industry.

Established names in the industry are facing tremendous competition from the newcomers.

Thus, each hospital has to be competitive both in terms of the quality of services as well as

cost management.

Until a few years ago, it was practically absurd to think of a Marketing function within a

hospital. That situation is pass with almost every hospital worth its salt employing

marketing professionals to attract new corporate. Hospitals also employ Loyalty Cards,

Discount Health cards to attract and retain customers.

46

SpeedminerMalaysian Product

Web Based

Data mining tool

Allows to create queries and reports on the fly

SpeedminerMalaysian Product

Web Based

Data mining tool

Allows to create queries and reports on the fly


47/172

One of the few ways of attracting and retaining customers is to offer different types of

packages like cardiac health care packages. Diabetes healthcare packages, gynecological

packages etc. These packages have few tests attached with them. The charge for these tests

as a package is less than the sum of the cost of all the tests if opted without a package.

Sir Ganga Ram Hospital is a 650-bed multi-specialty state-of-the-art hospital in Delhi. It

provides comprehensive health care services, and has acquired the status of a premier

medical institution. It is one of the hospitals in the private sector that has maintained nearly

100% bed occupancy due to its reputation of providing the highest level of medical services

to patients from Delhi and all over India.

In order to serve its patients well Sir Gangaram Hospital has also offered many packages.

These packages are available for many cases with different features and varying costs. Thepatients choose the package according to the need and the affordability.

Gynecology department is one of the very important departments in a hospital. It is one of

the high revenue earning part of a hospital. Thus the hospital has offered six gynecological

packages in order to attract and retain its customers. These packages are of different cost

and different features:

Colposcopy, Hysteroscopy and D&C package

Colposcopy, Hysteroscopy and LEEP package

Colposcopy & Cautery package

Colposcopy & LEEP package

Diagnostic hysteroscopy with D&C package

MTP package

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Sir Ganga Ram Hospital (SGRH), a pioneer in health informatics, has been using data

mining with Speed Miner, a data mining software product by Hesper. Speed Miner was

installed as an adjunct to HIS at SGRH in 2008 and has proved to be an effective business

intelligence tool which helps in data analytics and real time monitoring of the Key

Performance Indicators (KPI), query handling, and serves as a quality dashboard through

the various data collated over a period of time under specific heads.

Data analytics focuses on inference, the process of deriving a conclusion based solely on

scientific knowledge and facts. At a time when health organizations are operating in a

competitive environment and want to wring value for every penny spent, data analytics will

provide them with the strong foundation and confidence they need to excel with minimized

risk. Recently, the health care organizations are using data as a part of Business Intelligence,to make strategic decisions and choices, and to gain competitive edge in global markets.

Today, analytic strategy is viewed as a key engine of a dynamic capability of an

organization.

Sir Gangaram hospital started using Speedminer as their data mining tool in 2008. It was

used to analyze the various packages available at the hospital. The data that was extracted

revealed that the hospital was having loss in its gynecological packages. On analysis it was

found that the cost of the packages was much less than the amount hospital was spending on

its patient. By fine-tuning of the packages hospital was able to cut the losses and at the same

time make them more competitive and attractive to patients.

Objective of the study

The objective of the study is to:

Do profitability analysis of gynecological packages using Speedminer.

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Suggest recommendations to improve he scenario.

Methodology

The speed miner is used as data mining tool in Sir Gangaram Hospital. In sir Gangaram

hospital various gynecological packages are there. These packages are of different cost and

different features:

Colposcopy, Hysteroscopy and D&C package

Colposcopy, Hysteroscopy and LEEP package

Colposcopy & Cautery package

Colposcopy & LEEP package

Diagnostic hysteroscopy with D&C package

MTP package

In order to extract the data a query has to be put in the speed minor and the data can

be extracted. For example in order to find the data for Colposcopy, Hysteroscopy

and D&C package charges the query was put in the speed miner and thus the data

was extracted. The data was collected in the similar manner for all the six packages.

It was then ported into Microsoft excel format and then further analysis was done.

It is an analytical type of study. The data is secondary. Total data used for all the

packages are (i.e. no. of patients who opted for it)

Colposcopy, Hysteroscopy and D&C package 43 patients

Colposcopy, Hysteroscopy and LEEP package 155 patients

Colposcopy & Cautery package 8 patients

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Colposcopy & LEEP package 87 patients

Diagnostic hysteroscopy with D&C package 845 patients

MTP package 835 patients

50

Extracting the data via customized query through


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Observation

The data collected via Speedminer were then ported in the Microsoft excel

format. Then the data was further analyzed. The payer bill amount was

compared with the package rate. The payer bill amount is the amount that the

patient was expected to pay if he had not opted to take the package thus this is

the cost that is borne by the hospital). The analysis was done for four financial

years. For the first two years it was found that the payer bill amount is much

higher than the package rate thus the hospital was suffering a big amount of

loss. In the subsequent years it was found that the amount difference has been

significantly reduced but hospital is still suffering some loss.

Analysis for Colposcopy, Hysteroscopy and D&C package

Profitability analysis for all the patients

The analysis of all the patients who opted for Colposcopy, Hysteroscopy and

D&C package for the time period between 11/06/07 to 31/03/11 was done and

it was found that for the time period between 11/06/07 to 31/03/09 the package

rate was Rs6000 and the minimum payer bill amount was Rs8785 and

maximum was Rs15841 and for the time period between 01/04/09 to 31/03/11

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the package rate was Rs8000. And the minimum payer bill amount was

Rs2558 and maximum was Rs8575. The graph clearly shows the difference

between the package rate and cost to the hospital (payer bill amount) for both

time periods.

For two financial year s between 11/06/07 to 31/03/09

The package rate for this duration was Rs6000 and out of 16 patients the

average cost to hospital per patient for this duration was Rs12963.56.

Thus the hospital had to borne RS 6963.56 more i.e. the lost suffered byhospital was Rs6963.56.



average cost to hospital per patient for this duration was Rs8115.5. Thus

the hospital had to borne RS115.5more i.e. the lost suffered by hospitalwas Rs115.5

Profitability analysis of the financial years.

By plotting a graph loss borne by the hospital for the two durations it can

be clearly understood that the hospital has reduced the loss by significant

amount but still the loss is there.

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Analysis for Colposcopy, Hysteroscopy and LEEP package


The analysis of all the patients who opted for Colposcopy, Hysteroscopy and

LEEP package for the time period between 19/06/07 to 31/03/11 was done and

it was found that for the time period between 19/06/07 to 31/03/09 the package

rate was Rs7000 and the minimum payer bill amount was Rs8870 and

maximum was Rs16826 and for the time period between 01/04/09 to 31/03/11

the package rate was Rs9000. And the minimum payer bill amount wasRs5613 and maximum was Rs11592. The graph clearly shows the difference

between the package rate and cost to the hospital (payer bill amount) for both

time periods.


The package rate for this duration was Rs7000 and out of 62 patients theaverage cost to hospital per patient for this duration was Rs14163.62.

Thus the hospital had to borne RS 7163.62 more i.e. the lost suffered by

hospital was Rs7163.62.

For the two financial year s between 01/04/09 to 31/03/11

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hospital was Rs331.45

P rofitability analysis of the financial years.

By plotting a graph loss borne by the hospital for the two durations it

can be clearly understood that the hospital has reduced the loss by

significant amount but still the loss is there.

Analysis for Colposcopy & Cautery package


The analysis of all the patients who opted for Colposcopy, & Cautery package

for the time period between 19/06/07 to 31/03/11 was done and it was found

that for the time period between 19/06/07 to 31/03/09 the package rate was

Rs1200 and the minimum payer bill amount was Rs2655 and maximum was

Rs13178 and for the time period between 01/04/09 to 31/03/11 the package

rate was Rs2600. And the minimum payer bill amount was Rs2718 and

maximum was Rs2768. The graph clearly shows the difference between the

package rate and cost to the hospital (payer bill amount) for both time periods.

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The package rate for this duration was Rs1200and out of 6 patients the






average cost to hospital per patient for this duration was Rs2743. Thus

the hospital had to borne RS 143 more i.e. the lost suffered by hospital

was Rs143.


By plotting a graph loss borne by the hospital for the two durations it can beclearly understood that the hospital has reduced the loss by significant amount

but still the loss is there.

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Analysis for Colposcopy & LEEP package


The analysis of all the patients who opted for Colposcopy and LEEP package

for the time period between 19/06/07 to 31/03/11 was done and it was found

that for the time period between 19/06/07 to 31/03/09 the package rate was

Rs2900 and the minimum payer bill amount was Rs4838 and maximum was

Rs8336 and for the time period between 01/04/09 to 31/03/11 the package rate

was Rs4500. And the minimum payer bill amount was Rs3460 and maximum

was Rs9108. The graph clearly shows the difference between the package rate

and cost to the hospital (payer bill amount) for both time periods.




56


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By plotting a graph loss borne by the hospital for the two durations it can be

clearly understood that the hospital has reduced the loss by significant amount


Analysis for Diagnostic hysteroscopy with D&C package


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The analysis of all the patients who opted for, Hysteroscopy and D&C

package for the time period between 19/06/07 to 31/03/11 was done and

it was found that for the time period between 19/06/07 to 31/03/09 the package rate was Rs5200 and the minimum payer bill amount was

Rs5801 and maximum was Rs9897 and for the time period between

01/04/09 to 31/03/11 the package rate was Rs7200. And the minimum

payer bill amount was Rs2404 and maximum was Rs9318. The graph

clearly shows the difference between the package rate and cost to the

hospital (payer bill amount) for both time periods.







The package rate for this duration was Rs7200 and out of 753 patients

the average cost to hospital per patient for this duration was Rs7332.33.

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Analysis for MTP package


The analysis of all the patients who opted for MTP package for the time

period between 19/06/07 to 31/03/11 was done and it was found that for

the time period between 19/06/07 to 31/03/09 the package rate was

Rs7000 and the minimum payer bill amount was Rs8870 and maximum

was Rs16826 and for the time period between 01/04/09 to 31/03/11 the

package rate was Rs9000. And the minimum payer bill amount was

Rs5613 and maximum was Rs11592. The graph clearly shows the

difference between the package rate and cost to the hospital (payer bill

amount) for both time periods.

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For the two financial year s between 18 /06/07 to 31/03/09


the average cost to hospital per patient for this duration was Rs8759.33.





the average cost to hospital per patient for this duration was Rs6107.77.Thus the hospital had to borne Rs 307.77 more i.e. the lost suffered by






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Recommendations

On analyzing the data the following recommendations can be given

Though the amount of loss has been significantly reduced still the package cost is

less than the cost borne by the hospital. Thus the cost of the packages can be

increased by comparing the cost of such packages with other hospitals.

There is a fixed cost up to which the use of medical consumables is allowed to be

used in a package. But in order to provide better care sometimes this limit is crossed,

thus increasing the cost born by the hospital. Thus this limit should be made

mandatory to be followed.

Timely monitoring of market is very important so that the charges of these packages

can be mapped up with the inflation. Specially those packages which are frequently

consumed

Timely monitoring should be done so that such loses are not missed again.

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Conclusion

Sir Gangaram hospital has various gynecological packages for its patients available at

various fixed charges. These charges were fixed after consultation with surgeons and thefinance department. Over the period of time the market price of the medical consumables

and medicines kept on increasing but charges of the packages were not changed

accordingly. When speed miner was introduced and data mining was done to analyze the

gynecological packages it was found that the hospital was suffering a great amount of loss.

With the help of speed miner for the first time, hospital was able to see clearly what its

actual expenditure within each package was, where it was losing money. By fine-tuning the

packages hospital was able to cut its losses and at the same time hospital was able to make

them more competitive and attractive to patients.

The purpose of this study was to do a profitability analysis of the gynecological packages

using Speedminer and then providing recommendations to improve the scenario. The

extraction of data becomes very easy by using a data mining tool. Data mining tools allow

on-the-fly data analysis. One simply selects the criteria to be studied and the data are

updated immediately. One can add more criteria and the data are updated each time. The

data mining gives a chance or opportunity to enhance the future performance of the business

organization. If these predictions are done with the help and assistance of the historical

information (data), then one can get sufficient data for improvising the products of the

business organization.

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Thus in order to improvise the gynecological packages Speedminer was used. The data

extracted using Speedminer shows a considerable amount of loss in the first two financial

years and a reduction in loss in the subsequent years. Though significantly reduced, loss is

still there, thus a few recommendations have been given. The implementation of any of the

above recommendation would ensure profit in gynecological packages, a disciplined

monitoring of the market and a better use of data mining tools.

References

Microsoft Excel Data Analysis and Business Modeling by Wayne L.

Winston

Facilities planning and management by G. D. KUNDERS.

Implementing an Advanced Hospital Pharmacy Information System

by Dr. Karanvir Singh.

Pharmacy management: essentials for all practice settings By Shane

P. Desselle, David P. Zgarrick.

Data mining and business intelligence in a hospital setting by DrKaranvir Singh.

Counting on Data - Dr Sanjeev Sood.

U.S. National Library of Medicine.

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http://www.google.co.in/url?sa=t&source=web&cd=6&ved=0CDsQFjAF&url=http://www.ehealthonline.org/articles/article-details.asp?Title=Counting%20on%20Data&ArticalID=2433&Type=APPLICATIONS&ei=-QniTYQIjdSAB_G02MIG&usg=AFQjCNEDr1gqDzruyds8212sqHRzAgtdQghttp://www.google.co.in/url?sa=t&source=web&cd=6&ved=0CDsQFjAF&url=http://www.ehealthonline.org/articles/article-details.asp?Title=Counting%20on%20Data&ArticalID=2433&Type=APPLICATIONS&ei=-QniTYQIjdSAB_G02MIG&usg=AFQjCNEDr1gqDzruyds8212sqHRzAgtdQghttp://www.google.co.in/url?sa=t&source=web&cd=6&ved=0CDsQFjAF&url=http://www.ehealthonline.org/articles/article-details.asp?Title=Counting%20on%20Data&ArticalID=2433&Type=APPLICATIONS&ei=-QniTYQIjdSAB_G02MIG&usg=AFQjCNEDr1gqDzruyds8212sqHRzAgtdQg


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Accounting Terms Dictionary.

Khan, M.Y.; & Jain, P.K.; Theory and Problems in FinancialManagement.

Accounting Tools by Steven Bragg.

Charles Atkinson by Safety Stock.

White paper on re-order level by Richard D Henshell.

Oracle Reorder Point and Min-max Planning: Based on Outdated

Concepts? Dr. Volker Thormhlen

Simulation-Optimization for Business Decision

Support in a Global Specialty Chemicals

Enterprise by Jia Hui Tana, AriefAdhityab,

Rajagopalan Srinivasana,b, b.

Designing and managing the supply chain: by

David Simchi-Levi, Philip Kaminsky, Edith

Simchi-Levi

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http://www.businesstermsdictionary.com/accounting/http://www.accountingtools.com/about-accountingtools/http://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22David+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CBsQ9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Philip+Kaminsky%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CBwQ9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Edith+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CB0Q9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Edith+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CB0Q9Ag4Cghttp://www.businesstermsdictionary.com/accounting/http://www.accountingtools.com/about-accountingtools/http://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22David+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CBsQ9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Philip+Kaminsky%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CBwQ9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Edith+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CB0Q9Ag4Cghttp://www.google.co.in/search?hl=en&sa=N&biw=1345&bih=592&q=inauthor:%22Edith+Simchi-Levi%22&ei=Zf3tTZ3eM4fh0QGK-YyGCA&ved=0CB0Q9Ag4Cg


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Barron's Accounting Dictionary.

Explicit formulas for the order size and reorder

point in certain inventory problems by

Chandrasekhar Das.

Clifton, Christopher (2010). "Encyclopedia

Britannica: Definition of Data Mining.

Annexure A

Generic Form UOM

Daily

qtyRO

LPipeline

ROQ

Indent

AceclofenacCapsule

100mg

40.12

1,003 0

816 100

Capsule

200mg

11.11

256 0

222 100

AcenocoumarolCapsule 1 mg

10.56

285 0

344 200

Capsule 2 mg

15.56

420 0

554 300

Capsule 3 mg

5.56

150 0

134

-200

Caps

ule 4 mg

5.6

7

15

3 0

23

8 200Acyclovir

Ampoules

250mg

7.77

179 200 95 200

Capsule

200mg

3.33 63 0 -37 0

65
http://www.answers.com/library/Accounting%20Dictionary-cid-10087960http://www.britannica.com/EBchecked/topic/1056150/data-mininghttp://www.britannica.com/EBchecked/topic/1056150/data-mininghttp://www.answers.com/library/Accounting%20Dictionary-cid-10087960http://www.britannica.com/EBchecked/topic/1056150/data-mininghttp://www.britannica.com/EBchecked/topic/1056150/data-mining


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Capsule

400mg

6.11

165 0

207 100

Capsule

800mg

8.62

181 300

-440 0

Tube 5%0.3

7 9 0 -37 0

Albendazole

Bottle

200mg/5ml

1.72 46 50 -63

Capsule

400mg

20.55

514 400

-128 300

Alendronate SodiumCapsule

150mg

0.22 5 0 -7

Capsule 35 mg

3.55 96 0

149 80

Capsule 70 mg

1.33 36 0 56 40

Alfacalcidol

Capsule

698.92

13,279

13000

10,763

8000

Capsule

0.25mcg

56.52

1,526 0

944 400

Capsule 1 mcg

2.22 60 0 93 100

AlfuzosinCapsule 10 mg

23.89

549 10

708 400

AllopurinolCaps

ule

100

mg

62.

22

1,6

80

100

0

1,6

13

200

0Aminophylline + Theophylline+

Ampoules 2 ml

19.45

525 0

717 500

Capsule

2.22 60 0

-307

Capsule

150mg

118.89

3,210 0

4,993

3500

Capsule

300mg

27.78

750 0

1,167

1000

Amiodarone

Ampoules

150

mg/3ml

24.53

613 400 -79 100

Capsule

100mg

19.22

519 400

207 400

Capsule

200mg

41.11

946

1000

362

1200

66


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AmlodipineCapsule 10 mg 20

540 0

240

Capsule

2.5000mg

32.56

879

1100

268

1200

Capsule 5 mg

222.06

5,996 10

2,927 600

Amlodipine + Atenolol CombinationsCapsule 50 mg

159.89

4,317 0

4,255

2000

Amoxycillin

Bottle

125mg/5ml

0.17 5 0 7 10

Bottle 60 ml 0.5 12 0 -26

Capsule

250mg 11

282 0

-243

Caps

ule

500

mg

17.

94

48

4 0

31

8 500

50

0

Amoxycillin + Clavulanic AcidAmpoules 1.2 g

32.25

716 0

452 300

Bottle200mg

0.22 5 0 8 0

Bottle

200mg+28.5mg

3.97

107 0

107 0

Capsule

1000mg

83.68

1,813 0

820 500

Capsule

375mg

10.18

224 44

155 200

Capsule

625mg

175.35

3,858 84

1,735 700

Syrup

200mg+28.5mg

0.66 18 0 -25 30

Amoxycillin + Cloxacillin

Capsule 2.3 62 400

-303 60

Amphotericin-B( Conventional )

Ampoules 50 mg

2.67 54 0 -86 10

Ampicillin + CloxacillinCapsule

500mg

1.78 48 0 75 100

Ampicillin + SulbactamSodium

Ampo 1.50 g 1.5 42 0 66 50

67


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ules 6

Capsule

375mg

2.89 78 0

-129

Antacid Preparations

BottleCOMMON

10.94

295 500

-

101 300

Tube 200 ml0.9

4 25 0 39 40Anti-haemorrhoidPreparations

Tube0.9

4 25 25 -31 10

Antioxidants

Bottle 100 ml0.0

3 1 0 -5

Capsule NA

11.67

315 300

-140 300

Antitussives

Bottle 100 ml0.2

2 5 0 8 10

Bottle

30mg/5ml

0.44 12 0 -20 0

Drops 15 ml 0.5 14 0 -54 0

Syrup 60 ml4.6

1106 0

145 10

ArtesunateAmpoules 60 mg

1.88 51 46 29 70

Aspirin (Low Dose)

Capsule

150mg

132.48

3,577 0

5,225

3100

Capsule

325mg

1.87 50 0

-5,115

Capsule 75 mg

191.39

5,168 0

7,181

4600

AtorvastatinCapsule 10 mg

139.55

2,651

4000

245

Capsule 20 mg

118.89

2,259

4100 -58

Capsule 40 mg

63.33

1,372

1500

822

2200

Capsule 5 mg

34.34

790 0

770

1000

Atorvastatin + EzetimibeCapsule 10 mg 35

805 0

730 100

Caps 20 mg 7.3 19 0 -

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ule 3 8432

AtracuriumAmpoules 25 mg

54.22

1,030 0

1,493

Ampoules 50 mg

1.11 21 0 -10

Vial

100mg/10ml

1.29 35 0 19

1300

AzithromycinAmpoules

500mg

0.27 6 6 4 15

Bottle

100mg/5ml

0.17 5 0 -13 0

Bottle

200mg/5ml

0.53 14 0 22 10

Capsule

250mg

0.69 16 0 -12 0

Capsule

500mg

36.13

831 180

905 500

AztreonamAmpoules 0.5 g

0.83 16 0 28 60

Ampoules 1 g

0.98 19 0 25 0

Ampoules

500mg

0.63 13 0 -7 0

Vial 1 g0.6

1 12 25 -19 50

Vial 2 g0.1

3 2 0 -2 0

Baclofen Capsule 25 mg

6.67

180 0

280 200

BetamethasoneCapsule 0.5 mg

2.44 66 0 22 100

Tube 0.05%1.1

8 32 0 44

Tube 5 g1.6

1 43 0 -62

Betamethasone Combinations

Tube1.8

9 51 30 25 40

Tube 10 g

0.0

3 1 0 -6Bleomycin

Ampoules 15 mg

0.17 4 0 6 10

Blood set

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PieceCOMMON

39.44

1,065

1300

356

1300

BortezomibAmpoules

0.01 0 0 0

Vial 1 mg0.3

9 9 0 4 20

Budesonide InhalersAmpoules 0.5 mg

178.34

4,459

1000

4,214

2000

Piece9.5

6258 0

248 200

Piece100mcg

0.06 2 0 -13 0

Piece200mcg

0.13 4 0 -26 0

BupivacaineAmpoules 0.25% 3.4 92 200 -57 200Ampo

ules 0.50%

13.

89

37

5 0

58

3 400Ampoules 20 ml

13.43

363 300

244 300

CalcitoninAmpoules 100 IU

3.56 68 50 21 100

Bottle0.1

7 3 0 1 5

Calcium

Ampoules 10%

50.85

1,237 0

-1,428

Bottle0.1

7 5 0 -3

Bottle250mg

2.42 65 0 50 30

Capsule

30.39

821 0

1,276

Capsule

1000mg

93.56

2,526 0

3,430

2500

Capsule

250mg 78

1,950 0

-2,080

Capsule

500mg

951.78

24,429

20000

18,706

25000

Capsule

625mg

46.67

1,073 0

-127

Capsule

COMMON

3.33 77 0

-1,273

Capsule NA

2.78 64 0

-1,474

70


71/172

Syrup 200 ml0.1

7 4 0 6 10

CarbamazepineCapsule

100mg

8.89

240 0 73

Capsule

200mg

20.21

530 0

833 400

100

Cardioplegia

Bottle0.5

6 15 25 -1 30

CarvedilolCapsule

12.500mg

6.67

180 200 80 300

Capsule

3.125mg

16.11

435 0

-223 0

Capsule

6.250mg

5.56

150 0

-216 0

Cefixime

Bottle

100mg/5ml

0.11 3 0 -5

Bottle 50 mg0.1

1 3 0 4Capsule

100mg

7.38

180 0 54

Capsule

200mg

54.24

1,356

3780

-2,630

1300

Capsule

400mg

1.22 33 0 -39

Cefpodoxime

Bottle

100mg/5ml 0.4 8 0 14 10

Capsule

100mg

-0.6

7 -18 0 -28 10

Capsule

200mg

37.85

901

1360

-771 300

Ceftazidime

Ampoules 1 g

14.22

270 590

-207 350

Ampo

ules 2 g

1.8

3 35 40 -10Ceftriaxone

Ampoules 1 g

40.95

1,024 600

218 500

Ampoules 2 g

15.39

385 0

366 800

71


72/172

Vial13.84

318 450 72

Ceftriaxone + TazobactamAmpoules 1 g 0.6 14 0 23 50

Vial1.0

1 25 0 40

Cefuroxime + Clavulanic acid

Capsule

250mg 1 23 210

-172 100

Capsule

500mg

13.67

314 90

399 600

Cetirizine

Bottle

5mg/5ml

2.19 56 0 -41 0

Capsule 10 mg

148.33

4,005 0

5,130

3500

Chlordiazepoxide

Capsule 10 mg

16.67

450 600

100 400

CinnarizineCapsule 25 mg

5.55

139 0

222

Capsule 75 mg

1.11 30 0 37 200

Ciprofloxacin

Bottle200mg

3.87

104 81 82 130

Capsule

500mg

58.55

1,347 0

1,585

1000

Ciprofloxacin (Eye/Ear Drops)

Bottle 0.30%7.4

8202 200 49 200

CisplatinAmpoules 10 mg

0.89 19 0 22 10

Ampoules

10mg/10ml

0.22 6 0 9

Ampoules 50 mg

0.33 7 0 7 5

CiticolineAmpoules 4 ml

17.31

398 0 98

Capsule

500mg 30

630 0

680 500

2

00

ClarithromycinAmpoules

500mg

1.88 36 0 -41 0

Caps 250 5.6 10 12 13 200

72


73/172

ule mg 6 8Capsule

500mg

12.06

229 0

270 500

ClindamycinAmpoules

150mg/ml

169.22

3,215

4600

663

Ampoules

600mg 2 50 0 10

Capsule

150mg

8.89

169 0

202

Capsule

300mg

83.22

1,581 0

2,229

50000

ClonazepamCapsule

0.25mg

32.89

888

1400 -19

1000

Capsule 0.5 mg

12.22

330 0

-787

Capsule 1 mg

1.11 30 0 -53

ClotrimazoleCapsule

100mg

58.34

1,575 0

2,330 300

Piece 1%1.8

2 49 50 11 50

Tube 0.8 22 0 -27

Tube10mg/g

6.51

176 0

103 100

TubeCOMMON

3.56 96 120 30 70

CycloserineCapsule

250mg

2.16 58 0 -59

1000

Cyproheptadine

Bottle

2mg/5ml

0.17 5 10 -3 10

DacarbazineAmpoules

200mg

0.33 7 0 12 5

DanazolCapsule

100mg

1.11 21 0 8 30

Dexamethasone

Ampo

ules

4

mg/ml

46.

64

1,2

59

210

0

-29

1

100

0

Capsule 0.5 mg

12.22

330 0

-287

DiaperPacket of

Adult 4 92 120 -6 110

73


74/172

10Packet of 5 Paed

19.92

458 200

557 600

Piece3.1

1 84 0131

Diazepam

Ampoules

10mg/2ml

0.02 1 0 1 0

Capsule 2 mg

0.11 3 0 -85 0

Capsule 5 mg

4.44

120 200 -14 200

Diclofenac SodiumAmpoules

25mg/ml

198.5

5,360 0

2,437 500

Capsule

100mg

36.22

978 0

1,176 375

Capsule 50 mg

69.55

1,739 100

2,567

2000

Capsule 75 mg 50.22 1,356 0 2,009 1500

TubeCOMMON

39.48

1,066 0

1,082

Diclofenac Topical

BottleCOMMON

5.92

148 0

191

Piece100mg

4.16 96 124 34

Tube0.5

6 15 50 -26 500

DigoxinAmpoules 0.5 mg

0.56 15 0 -56

Capsule

0.25mg

24.44

660 0

1,026 700

DiltiazemAmpoules

5mg/ml

0.07 2 0 3

Capsule

120mg

11.11

300 0

367 200

Capsule

180mg

2.22 60 0 -7

Capsule 30 mg

58.33

1,575 0

350 500

Capsule 60 mg

11.11

300 0

167

Caps

ule 90 mg

21.

67

58

5 0

41

0Disodium Hydrogen Citrate

Bottle1.53g/5ml

0.88 24 0 27 20

Sachets 4 g

5.02

136 0 -21 0

74


75/172

DobutamineAmpoules

250mg

3.28 62 0 42 60

DoxophyllineAmpoules 10 ml

0.22 5 0 -42

Capsule

400mg

99.61

2,689 10

2,344

1200

DoxycyclineCapsule

100mg

82.11

2,217 0

849 600

DrotaverineAmpoules 20 mg 10

230 0

182 200

Ampoules

20mg/ml

4.33

117 0

182

Capsule 40 mg

5.55

139 0

222 200

Capsule 80 mg

7.11

182 0

289 200

DutasterideCapsule 0.5 mg

3.33 90 120 20 100

DydrogesteroneCapsule 10 mg

26.67

720 700

420

1000

Enalapril

Ampoules

1.250mg

-0.0

6 -1 0 -2Capsule

1.11 30 0 47 100

Caps

ule 10 mg 6.5

17

6 0

27

3 150

Capsule

2.5000mg

7.67

207 500

-763

Capsule 5 mg

29.72

802 10

553 800

EntecavirCapsule 0.5 mg

5.33

101 0

151 120

EpirubicinAmpoules 10 mg

0.56 13 20 1 20

Ampoules 50 mg

1.06 29 20 25 30

ErlotinibCapsule

100mg

1.33 25 0 45 60

Capsule

150mg 1 23 0 38 30

Ertapenem

75


76/172

Ampoules 1 g

2.81 53 12 26 40

Erythromycin

Capsule

250mg

0.67 18 0

-162

Capsule

500mg

1.56 42 0 36 100

ErythropoietinAmpoules 0.3 6 0 8Ampoules

2000IU/ml

0.13 2 0 -2

Ampoules

3000IU

0.53 10 0 6

Ampoules

4000IU/ml

3.05 70 46 60 36

Esomeprazole

Ampoules 40 mg 12.28 332 0

-16,

904 300Capsule 20 mg

10.11

273 25 95

Capsule 40 mg

24.48

661 944 84 700

Esomeprazole + DomperidoneCapsule 40 mg

11.11

300 300

167 400

EthambutolCapsule 1 g

35.56

960

1000

494

1200

Capsule

200mg

8.89

240 200

173 400

Generic UOM

Dailyqty

ROL

Pipeline

ROQ

Capsule

400mg

15.56

420 300

354 400

Capsule

600mg

20.67

558 600

268 600

Capsule

800mg

67.89

1,833

2200

651

2300

EtoricoxibCapsule

120mg

8.89

240 0

373 300

Capsule 60 mg

18.89

510 0

793 400

Capsule 90 mg

21.55

582 0

845 700

Expectorant Preparations

Bottle 0.5 14 0 -94 0

76


77/172

BottleCOMMON 3.2 86 50 52 70

FenofibrateCapsule

4.44

120 0 -14

Capsule

160mg

4.44

120 100 86 100

Capsule

200mg 10

270 400 20 300

Flavoxate

Capsule

200mg

2.22 60 200

-107 100

Foley

Piece1.7

7 48 0 16

PieceCOMMON

30.39

821 110

1,116

FollitrophinAmpo

ules 150 IU

1.5

6 36 50 9 50Ampoules

300mg

0.38 7 0 4 10

Ampoules

600mg

0.28 5 0 1 10

Ampoules 75 IU

1.39 32 50 3 50

FrusemideAmpoules 20 mg

103.89

2,805 0

4,363

3000

Capsule 40 mg

46.44

1,254

1040 -50 500

GabapentinCapsule

100mg

71.11

1,920 0

1,387 500

Capsule

300mg

21.38

577 0

698 700

Capsule

400mg

2.22 60 0 -67

GefitinibCapsule

250mg 1 23 0 -22 25

Gentamicin

Ampoules 20 mg

-0.3

8 -10 0

-555

Ampo

ules 80 mg

25.

8

69

7 0

66

4 800

Vial17.52

473 9

118

Gonadotrophin F.S.HAmpoules 300 IU

1.83 35 0 57 50

77


78/172

Ampoules 75 IU

0.22 6 0 9 25

Ampoules 900 IU

1.42 27 0 43 30

Kit 150 IU3.8

9 74 0 -43

Kit 75 IU

0.8

3 16 0 28 10

HeparinAmpoules

10IU/ml

190.05

5,131 0

4,532 0

Ampoules

25000IU

18.9

510 120

525 600

Ampoules

5000IU

105.6

2,640 0

3,024

2000

Hydrocortisone SuccinateAmpoules

100mg

66.22

1,656 0

1,369 800

Hydroxypropyl MethylCellulose

Ampoules 16

432 0

672 540

Bottle14.81

400 0

487

Bottle 0.30%0.8

9 24 0 -5

Bottle 0.50%0.0

4 1 0 2 30

Hyoscine Butyl BromideAmpoules

20mg/ml

33.33

900 600

800 800

Capsule 10 mg

8.89

240 0

353 200

Suppositor

y

12.

61

34

0 0

36

0 200

Ibuprofen + Paracetamol

Bottle 100 ml3.1

7 86 0 -13

Capsule

400mg

555.95

15,011 0

16,960

11000

Insulin aspart + protamineAmpoules

100IU/ml

0.22 4 0 2 5

Insulin BiphasicAmpoules

8.76

166 0

184

Ampoules

100IU/ml

0.36 10 0 7 10

Ampoules

40IU/ml

2.67 51 0 41 40

Cartridge

100IU/ml

3.02 57 0 45 10

78


79/172

Insulin GlargineAmpoules

100IU/ml

0.41 8 0 1

Ampoules 3 ml

3.23 61 100 9 100

Cartridge 300 IU

0.22 5 0 8 10

INSULIN GLULISINEAmpoules 300 IU

0.54 10 10 3 10

Insulin NeutralAmpoules

40IU/ml

10.67

203 0

243 150

Cartridge

100IU/ml

0.44 8 0 10 20

IrinotecanAmpoules

100mg 0.3 7 5 4 6

Iron Formulations

Bottle COMMON 3.22 87 70 55 100

Capsule

14.33

387 600

-148

Capsule

100mg

37.22

856 0

1,414

1000

Capsule

COMMON

260.72

7,039

2100

8,750

1000

Isosorbide-5-Mononitrate

Capsule 10 mg

11.39

308 0

-1,237

Capsule 20 mg

25.88

699 0

687 300

Capsule 30 mg

1.78 48 0 75

Lactulose

Bottle10g/15ml

22.45

606 0

923 700

LansoprazoleCapsule 15 mg

11.12

278 300

145 200

Capsule 30 mg 5.5

127 0 -1 100

LercanidipineCapsule 10 mg

29.44

795 0

536 300

Capsule 20 mg 16

432 0

272

Letrozole

Capsule

2.67 51 0

-239

79


80/172

LeucovorinAmpoules 15 mg

2.11 49 0 -70 0

Ampoules 50 mg

3.56 82 40 85 120

Capsule 15 mg

0.67 13 0

-117 0

Leuprolide

Ampoules

-0.0

1 0 0 -3Ampoules

3.7500mg

0.04 1 0 -2

Ampoules 4 mg

0.94 18 0 2 10

LevamisoleCapsule

400mg

1.11 21 100 -62 100

Caps

ule

800

mg

0.8

9 17 100 -90 100Levetiracetam

Ampoules

100mg

9.47

180 390 -68 300

Capsule

1000mg

0.67 15 0 -15

Capsule

250mg

16.66

383 0

143 200

Capsule

500mg

37.78

768 0

935 200

500

LevocetirizineCapsule 5 mg

195.55

5,019 0

3,952

3000

Levofloxacin

Ampoules

500mg/100ml

1.56 30 0 8

Bottle 10190 0 15

Capsule

500mg

52.33

994 100

-176

Capsule

750mg

21.34

448 5

443 600

Levosalbutamol (Inhalers)

Piece0.31mg

7.33

198 0 48

Piece0.63mg

16.44

444 0

430 200

Piece1.250mg

7.11

192 0

299 300

Piece50mcg

0.09 2 0 -18

80


81/172

LignocaineAmpoules

12.44

336 0

422

Ampoules 2%

27.92

754 0

726 700

Ampoules 30 mg

14.11

381 0

583

Ampoules 4%

2.28 62 0 96 200

Ampoules

COMMON

2.57 69 0 40

Bottle

10%,10%,10%

0.74 20 0 18 30

Bottle 100 ml0.6

9 16 20 6

Tube 2% 541,458 0

608 200

LoratadineCapsule 10 mg

28.67

736 900

266 800

Losartan PotassiumCapsule 25 mg

28.56

771 0

1,000 600

Capsule 50 mg 57

1,539 0

2,154

1200

Losartan PotassiumCombinations

Capsule 50 mg

29.22

789 0

1,027 500

Low Molecular Weight Heparins(LMWHs)

Ampoules

10000IU

0.01 0 0 0 1

Ampo

ules 20 mg

1.5

6 30 50 -3 40Ampoules

2500IU

17.33

329 500 59

Ampoules 40 mg

19.6

372 0

480 350

Ampoules

5000IU

23.89

454 0

562 450

Ampoules 60 mg

8.87

169 0

192 150

Ampoules

7500IU

0.33 6 0 6

Ampoules 80 mg

0.07 1 0 2 4

Mebeverine

Capsule

135mg

7.77

210 200

-174

Capsule

200mg

1.67 38 0 33 100

Medroxyprogesterone

81


82/172

Ampoules

150mg

0.06 1 0 -2

Capsule 10 mg 10

270 0

320 400

MephentermineAmpoules

30mg/ml

2.33 63 60 38 60

MeropenemAmpoules 1 g

44.22

840 540

963

1080

Ampoules

250mg

1.63 31 14 -26

Ampoules

500mg

45.89

872 540

896

3000

MetforminCapsule

1000mg

124.44

2,862

3000

1,729

3500

Caps

ule

500

mg

187

.34

4,4

96

600

0

1,1

16

300

0

240

0Metformin + Gliclazide

Capsule

5.56

150 0

234 300

Capsule

500mg

5.56

128 0

211 300

Capsule 80 mg

77.33

2,088

3300

-112

2000

Metformin + GlimepirideCapsule 1 mg

12.56

289 0

207 200

Capsule 2 mg

36.56

841 0

1,179

1000

Metformin + PioglitazoneCapsule 15 mg

5.22

141 50 -21

Capsule 30 mg

3.33 90 100 40 100

Metformin + Pioglitazone + GlimeprideCapsule 1 mg

8.23

222 0

246 300

Capsule 2 m

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Analysis of Discrepancies Between Manual and Automated ROL of Drugs1

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