Management in Health, Vol 17, No 1 (2013)

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REDUCING WAITING TIME IN OUTPATIENT SERVICES OF LARGE UNIVERSITY TEACHING HOSPITAL - A SIX SIGMA APPROACH

 

REDUCING WAITING TIME IN OUTPATIENT SERVICES OF LARGE UNIVERSITY TEACHING HOSPITAL - A SIX SIGMA APPROACH

 

 

Prof. Dinesh T.A1 , MHA, Ph.D

Prof. Dr. Sanjeev SINGH1 , DCH, M.Phil

Prem NAIR1 , MBBS, MD

Remya T R1 , MHA

 

1 Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham (Amrita University), Cochin, Kerala, India

 

 

ABSTRACT: This papar presents the results of a project of improving the quality of services provided in an outpatient department of an university hospital in India. The project was conducted on the basis of the six sigma methodology and aimed to reduce waiting times in outpatient cardiology office.

Significant reduction in waiting time was achieved in the outpatient services of the Cardiology department by using the six sigma approach. In addition to the overall reduction in waiting time for cardiac medical consultation significant reduction in waiting time for getting the lab results was also achieved.

As an off shoot of the study nine registration counters were started, registration forms were modified, usherers were appointed to guide patients, additional staff were appointed to handle the telephones in the Cardiology OPD and they were also taught basic telephone etiquette, dedicated biochemistry analyser was provided for the cardiology department and an alert system was put in place for patients waiting for more than one hour.

Further data collection through VOC will help to monitor and control any variance.

 

Keywords: quality, health services, waiting time, India

 

 

INTRODUCTION

Patients' waiting time has been defined as "the length of time from when the patient entered the outpatient clinic to the time the patient actually leaves the OPD".

Whether it's a time used for registration of patient, routine doctor's appointment, emergency room treatment, laboratory/diagnostic test, procedures, receiving the results of various tests, waiting happens to just about everyone seeking medical care.

It's often one of the most frustrating parts about healthcare delivery system.

Waiting times for elective care have been considered a serious problem in many health care systems since it acts as a barriers to efficient patient flows.

OPDs is considered as the window to hospital services and a patient's impression of the hospital begins at the OPD. This impression often influences the patient's sensitivity to the hospital and therefore it is essential to ensure that OPD services provide an excellent experience for customers. It is also well-established that 8-10 per cent of OPD patients need hospitalization.

 

LITERATURE REVIEW

Six Sigma is a business management strategy originally developed by Motorola, USA in 1986 [1,2] and was associated with statistical modeling of manufacturing processes. A six sigma process is one in which 99.99966% of the products manufactured are statistically expected to be free of defects (3.4 defects per million).

The term "six sigma process" comes from the notion that if one has six standard deviations between the process mean and the nearest specification limit, as shown in the chart 1, practically no items will fail to meet specifications [3]. This is based on the calculation method employed in process capability studies (Chart 1).

Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in the work process [4].

Data and statistical analysis are used to identify defects in processes and reduce variation. DPMO (defects per million of oportunities) and sigma level are described in the Table 1.

 

Chart 1. Process capability.

 

Table 1. DPMO and sigma levels [5,6]

 


Sigma level

DPMO

Percent defective

Percentage yield

1.

691.462

69%

31%

2.

308.538

31%

69%

3.

66.807

6.7%

93.3%

4.

6.210

0.62%

99.38%

5.

233

0.023%

99.977%

6.

3.4

0.00034%

99.99966%

 

METHODOLOGY

 

The DMAIC method under Six Sigma which consists of the following five steps was used to achieve the objectives of this study.

Step 1 - Define

Step 2 - Measure

Step 3 - Analysis

Step 4 - Improve

Step 5 - Control

 

Study was carried out in the department of Cardiology of a large University Teaching Hospital with an average annual Cardiac OP of 40000.

 

Period of Study - January 2012 to April 2012.

 

a. Measurables

1.      Total waiting time for a cardiac consult.

2.      Time taken for laboratory result.

3.      Time taken for laboratory and ECG result.

 

b. Sample Size

Respondents of this study included selected patients, staffs and doctors in the department of Cardiology at the Heart Institute.

1.      Retrospective data of 640 patients was analysed for waiting time during the period Jan - Dec 2011.

2.      Voice Of Customers was obtained from 320 patients during the Define phase in April 2012.

3.      Waiting time of 640 patients was obtained during the Analyze phase in February 2012.

4.      Waiting time of 640 patients was obtained during the Control phase in March 2012.

 

Simple Random sampling was followed.

 

Data Collection

1.      The following collection methods were used in this study.

2.      Voice of Customers (VOC) was obtained using standardized questionnaire.

3.      Data was also collected through direct observation.

4.      Management staff and doctors were interviewed to obtain information on the working process in the hospital.

 

Statistical Tools

1.      Process Map-Flow Chart that shows description and sequence of the process done.

2.      Cause and Effect Diagram - Diagram that shows the relationship of a cause that gives rise to a certain problem.

3.      Affinity Diagram.

4.      Descriptive statistics.

5.      SPSS analysis.

RESULTS AND DISCUSSION

DEFINE

This is the first step that refers to defining the goals of the project. Process improvement goals may be aimed at increasing market share, the output of a particular department, bringing about improved employee satisfaction as well as customer satisfaction and so on.

The goal has to align the customer demands and the strategic goals of the organization. Data mining methods can be used to find prospective ideas for project implementation.

In other words, businesses are designing a road map for achieving the targets and goals of the organization.

 

Problem Statement:

Three months retrospective data from the department indicates that in October 2011 only 49.27% of patients were seen within 60 minutes by the physician. In November 2011 this increased marginally to 51.11% and in December this was fond to be 53.31%.

 

OPD WAITING TIME - PERCEPTION OF CUSTOMERS

For understanding perception of customers on OPD waiting time, VOC was collected from 320 patients in the cardiology OP.

 

Questionnaire for OP Patients (Cardiology)

1.      Did you take an appointment for OPD visit?

2.      How did you get the appointment? Through telephone or direct?

3.      Are you satisfied with the way your phone call was handled?

4.      What instruction was given by the counter staff at the time of appointment/arrival?

5.      How do you feel is the reception staff?

6.      How much time it took at the reception, to attend you?

7.      At what time you were asked to report at the counter and when did you reach the OPD reception?

8.      Did any staff brief you regarding the workflow in OPD

9.      How long you have been waiting in OPD?

10.   Did any information regarding waiting time in OPD was given to you, at the time of appointment?

11.   How much time it took for you to interact with doctor after your arrival?

12.   Are you aware of the existing appointment system in AIMS?

13.   What is your perception on waiting time in the hospital?

14.   What would you suggest to reduce waiting time in OPD

15.   Any other suggestions?

 

How long have you been waiting in the OPD (Chart 2)

As is evident from the above diagram, 64% of the patients had to wait for more than 3 hours for a Cardiac consultation with 24% of patients waiting anywhere between 2 hours to three hours.

Only 6% of patients could have their consultation within one hour. This clearly indicates that majority of patients are not satisfied with the present waiting time.

VOC reflects customer expectation to see doctor within 60 minutes of Registration/Encounter.

It was found that routine lab test and ECG results are critical information for a cardiac medical consultation. Patients were waiting for either the lab test or both lab test and ECG.

To assess this measurable the time taken for the blood test results and ECG results were collected separately in the measure phase:

 

1.      Time to complete the Blood Test.

2.      Time to complete the Blood Test and ECG.

 

 

MEASURE

This phase refers to the analysis of the existing system with various measurement techniques for the defects and levels of perfection that exist. In this step, accurate metrics have to be used to define a baseline for further improvements.

This helps in understanding whether any progress has been achieved when process improvements are implemented.

To identify High level process map the SIPOC (Table 2) has been done.

 

The various processes involved in the particular project has been described in detail in flow chart (Chart 3)

 

Value Analysis: A value analysis was done based on the flow chart and the processes were categorized into Value added, Operational Value Added Activity and Non Value Added Activities as given in Table 3.

 

 

ANALYZE

The analyze phase was undertaken to determine any disparity that may exist in the goals set and the current performance levels achieved. The understanding of the relationship between cause and effect is necessary to bring about any improvements, if needed.

Brainstorming session was carried out and all the causes were listed in the affinity diagram. The Fish Bone Diagram was prepared.

 

The causes which got from the brain storming session has been segregated into non controllable causes, direct improvement causes and controllable and likely causes (Table 4); its fish bone diagram for controllable causes only is shown in the Chart 4.

Causes were then ranked on the basis of severity and occurrence as per criteria given Table 5

A modified Failure Mode and Effects Analysis (FMEA) was carried out for Occurrence and Severity only. The top Risk Priority Number were considered for further analysis, using 5WHY.

         Single Registration counter

         Time taken to process blood test only

         Time taken to process blood test and ECG

 

 

DATA ANALYSIS

Null Hypothesis

Based on the data from the measure phase the following Null hypotheses were formulated:

1.      H0 = There is no reduction in waiting time before and after starting new registration.

2.      H0 = There is no reduction in waiting time for getting lab result for the patients having Blood Test only.

3.      H0 = There is no reduction in waiting time for getting lab result in old & new data for the patients having Blood Test + ECG.

 

1.    H0 = There is no reduction in waiting time before and after starting new registration counters

Analysis of waiting time after and before starting new registration counters Table 7.

It was suspected that there is no reduction in waiting time before and after starting new registration counters. 2 t Test was conducted to ascertain this.

Null hypothesis was rejected as the p-Value was found to be below 0.05 at 95% confidence level.

It was suspected that there is no reduction in waiting time for new patients as well as revisit patients in getting the results of the Blood Tests before and after implementation of six sigma. A t Test was conducted to ascertain this.

t-Test to analyse reduction in waiting time for patients having Blood Test only Table 8.

Summary of Statistics Table 9.

Sigma Levels Table 10.

 

As is evident from the above table, there is significant reduction in waiting time with p-Value of <.05 at 95% confidence level. The sigma levels have also shown a significant increase from 2 before the study, 2.6 during the study and 3.4 during the control phase. Hence the hypothesis is rejected.

 

 

2.    H0 = There is no reduction in waiting time for getting lab result in old & new data for patients having Blood Test and ECG

 

It was suspected that there is no reduction in waiting time for patients in getting the results of the Blood Test and ECG. A 2 t Test was conducted to ascertain this. It has been described in Table 11, 12 and 13.

Sigma Levels Table14. As is evident from the above tables, there is significant reduction in waiting time with p-Value of <.05 at 95% confidence level. The sigma levels have also shown a significant increase from 2 before the study, 2.9 during the study and 3.3 during the control phase. Hence the hypothesis is rejected. Hence the hypothesis is rejected.

No of patients waiting for cardiac consultation for less than one hour has gone up from 6% before the study to 49% during the study which further increased to 53% during the control phase. Similarly patients waiting for more than two hours has come down from 24% to 6% and 4% respectively. Similarly patients waiting for more than three hours has come down significantly from 64%, 13% and 8% respectively.

 

 

3.    H0 = There is no reduction in waiting time for getting lab result for patients having Blood Test only

 

IMPROVE

Improvements in existing systems are necessary to bring the organization towards achievement of the organization goals. Creative development of processes and tools brings about a new lease on life for the organization's processes and takes them nearer to organizational objectives.

Various project management and planning tools can be used to implement these new techniques and processes. Appropriate usage of statistical tools is important to measure the data, which is necessary to understand improvements done and any shortcomings that may exist.

The solutions with their respective Causes are listed in the Table 6.

 

CONTROL
Control phase is the last step in the DMAIC method. VOC was conducted to find out if there is any significant variation.

Waiting Time for Consultation by using VOC (Table 15, 16)

Waiting Time for Consultation by using VOC

It was suspected that there is no reduction in waiting time for consultation in VOC of old and new data. A t Test was conducted to ascertain this.

It was found that the p-Value was below 0.05 at 95% confidence level; the null hypothesis was rejected.

 

 

Table 2

SUPPLIER (S)

INPUTS

(I)

PROCESS

(P)

OUTPUT

(O)

CUSTOMER

(C)

Registration staff

Registration form

Patient registering

MRD No

Patient

Reception staff

MRD Card

Encountering

Token No. & Instructions for billing

 

Billing Clerk

Cash

Billing

Receipt

 

Nursing / Technician

Order

Preliminary Examinations/ investigations

Instructions to wait / have breakfast

 

Jr. Doctor

 

 

 

Work up by junior doctor

Advise / refer to senior physician

 

Jr. Doctor

Order

Additional Tests

Advise

 

Doctor

 

 

Consultation by Sr. Doctor

Advise

 

 

 

Table 3

Value Activity

Nos

Value Added Activity

35

Operational Value Added Activity

13

Non Value Added Activity

27

 

Table 4

Sl. No.

Nature of Cause

Numbers Identified

1.

Non Controllable Causes

32

2.

Direct Improvement Causes

11

3.

Controllable and Likely Causes

67

TOTAL

110

 

Table 5

Occurrence

Rank

Severity

Rank

Once a Month

1

Mild

1

Once a Week

5

Moderate

5

Every Day

9

Severe

9

 

Table 6

Causes

Solutions

Single Registration Counter

Start multiple Registration Counters

Registration form is lengthy & difficult to fill

Simplify Registration Form

Lack of proper communication

Provide adequate training

Time taken to barcode & process the samples in lab/ blood reports takes more time

Provide a dedicated machine for biochemistry test for Cardiology OPD

AHD asking patients to report at the same time at OPD

Segregated appointment to be given based on the fasting blood sugar need and the appointments available into forenoon and afternoon

Delay in starting OPD

To start work up for New visit OPD at 8.30 am and Sr doctor consultation at 10.00am every OP days

Delay due to entry in to EMR

Provide training to doctors

 

Chart 2 - Proportion of Patients Waiting - Before Study

Table 7

t-Test: Two-Sample Assuming Unequal Variances

 

April

July

Mean

23.2

17.7

Variance

127

96.5

Observations

382

331

Hypothesized Mean Difference

0

 

df

711

 

t Stat

6.97

 

P(T<=t) one-tail

3.58

 

t Critical one-tail

1.65

 

P(T<=t) two-tail

7.16

 

t Critical two-tail

1.96

 

 

Table 8

 

BT (Before)

BT (Control)

Mean

89.82

70.63

Variance

230.07

9.99

Observations

640

640

Hypothesized Mean Difference

5

 

df

694

 

t Stat

23.17

 

P(T<=t) one-tail

0.00

 

t Critical one-tail

1.64

 

P(T<=t) two-tail

0.00

 

t Critical two-tail

1.96

 

 

Table 9

 

BT (Before)

BT (Improve)

BT (Control)

Mean

89.82

76.17

70.63

Median

88

77

71

Standard Deviation

15.16

6.43

3.16

Range

84

24

13

Minimum

65

65

63

Maximum

149

89

76

Count

640

640

640

Confidence Level (95.0%)

1.17

0.49

0.24

 

Table 10

BT (Before)

BT (After)

BT (Control)

2

2.6

3.4

 

Table 11

t-Test: Two-Sample Assuming Unequal Variances

 

BTE (Before)

BTE (After)

Mean

91.67

77.55

Variance

197.71

37.14

Observations

640

640

Hypothesized Mean Difference

5

 

df

871

 

t Stat

15.04

 

P(T<=t) one-tail

0.00

 

t Critical one-tail

1.64

 

P(T<=t) two-tail

0.00

 

t Critical two-tail

1.96

 

 

Table 12

t-Test: Two-Sample Assuming Unequal Variances

 

BTE (Before)

BTE (Control)

Mean

91.67

70.75

Variance

197.71

10.64

Observations

640

640

Hypothesized Mean Difference

5

 

df

708

 

t Stat

27.90

 

P(T<=t) one-tail

0.00

 

t Critical one-tail

1.64

 

P(T<=t) two-tail

0.00

 

t Critical two-tail

1.96

 

 

Table 13

 

BTE (Before)

BTE (After)

BTE (Control)

Mean

91.67

77.55

70.75

Median

88

78

71

Standard Deviation

14.06

6.09

3.26

Range

83

24

14

Minimum

66

66

63

Maximum

149

90

77

Count

640

640

640

Confidence Level (95.0%)

1.09

0.47

0.25

 

Table 14

BTE (Before)

BTE (After)

BTE

(Control)

2

2.9

3.3

 

Table 15

t-Test: Two-Sample Assuming Equal Variances

 

VOC Before

VOC After

Mean

164.85

79.54

Variance

2710.56

3045.32

Observations

320

320

P(T<=t) one-tail

0.00

 

t Critical one-tail

1.64

 

P(T<=t) two-tail

0.00

 

t Critical two-tail

1.96

 

 

Table 16

t-Test: Two-Sample Assuming Unequal Variances

 

VOC Before

VOC Control

Mean

164.85

71.61

Variance

2710.56

2069.27

Observations

320

639

P(T<=t) one-tail

0.00

 

t Critical one-tail

1.64

 

P(T<=t) two-tail

0.00

 

t Critical two-tail

1.96

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Chart 3 - Process Map

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Chart 4 - Cause-effect diagram

 


Conclusion: Significant reduction in waiting time was achieved in the outpatient services of the Cardiology department by using the six sigma approach. In addition to the overall reduction in waiting time for cardiac medical consultation significant reduction in waiting time for getting the lab results was also achieved.

As an off shoot of the study nine registration counters were started, registration forms were modified, usherers were appointed to guide patients, additional staff were appointed to handle the telephones in the Cardiology OPD and they were also taught basic telephone etiquette, dedicated biochemistry analyser was provided for the cardiology department and an alert system was put in place for patients waiting for more than one hour.

Further data collection through VOC will help to monitor and control any variance.

 

Acknowledgement

Authors are grateful to Mata Amritanandamayi Math for providing the resources for carrying out the study and two anonymous referees for their comments and suggestions.

 

 

 

References:

1.       TENNANT, Geoff -SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. p. 6., 2000, 

2.       SCHROEDER, Richard, MIKEL, Harry, Phd -Six Sigma: The Breakthrough Management Strategy Revolutionizing the World's Top, 2006.

3.       The Inventors of Six Sigma". www.motorola.com/content/0,,3079,00.html  

4.       JIJU, Antony, "Pros and cons of Six Sigma: an academic perspective". www.onesixsigma.com/node/7630, 

5.       "Institute of Industrial Engineers Six Sigma certifications". http://www.iienet2.org/Seminars/SeminarGroup.aspx, 

6.       "Certification - ASQ". Milwaukee, Wisconsin: American Society for Quality http://www.asq.org/certification/index.html. Retrieved 2010-01-05.

 

 

 



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