PROJECT TITLE

REDUCTION OF KISWA HCIII NEW OPD ATTENDANTS’ WAITING TIME IN

NAKAWA DIVISION KAMPALA DISTRICT

FELLOWS:

JEROME MPAATA AJUNA ALBERT

Medicines and Health Service Delivery Monitoring Unit (MHSDMU)

Plot 21 Naguru Hill Drive

P.O Box 25497

KampalaTel: 0414‐288442, 0414‐288445, 0800100447 (Toll free)

1 Table of Contents 1.0 Introduction ...... 7 2.0 Literature review ...... 8 3.0 Problem statement...... 11 4.0 Objectives...... 12 5.0 Methodology...... 13 5.1 Brainstorming ...... 13 5.2 Motivating...... 13 5.3 Theme selection...... 14 5.4 Fishbone Analysis...... 16 5.5 Countermeasure matrix ...... 16 6.0 Baseline survey...... 18 7.0 Project Output……………………………………………………………………………….15

7.1 Challenges that led to long waiting before CQI intervention……………………………1.5

7.2 CQI interventions that led helped to reduce patients waiting time……………………..16

7.3 Comparison of current and previous patients waiting time………………………….…16

7.4 Graph showing current and previous patients waiting time………………………….…17

8.0 Lessons learnt …………………………………………………………………………….…17

9.0 Challenges faced ………………………………………………………………………….…18

9.1 How challenges were resolved………………………………………………………….…22

10.0 References...... ………...23

2 Declaration We, Jerome MpaataOwagage and Albert Ajuna, do hereby declare that this endofproject Entitled:REDUCTION OF KISWA HCIII NEW OPD ATTENDANTS WAITING TIME IN NAKAWA DIVISION KAMPALA DISTRICT has been prepared and submitted in fulfillment of the requirements of theMediumtermHIV/AIDS Fellowship Program at Makerere University Schoolof Public Health, and has not been submitted for any academic or nonacademicqualifications.

Signed………………………………………………….Date………………… …………………… Jerome MpaataOwagage, Medium –term Fellow Signed………………………………………………….Date………………… & Albert Ajuna, Medium –term Fellow Signed………………………………………………….Date…………………

…………………… Dr. Diana Atwine – Institutional Supervisor Signed………………………………………………….Date………………… …………………… Dr. Ibrahim Kirunda Academic Supervisor

3 Acknowledgement

Special thanks go to, our supervisors Dr. I brahimKirunda and Dr. Diana Atwine for their positive criticism and guidance. We also wish to appreciate the entire CQI team at Kiswa HC III and staff for their commitment to the project.

We owe a lot to Mak‐SPH for availing us the opportunity to participate in the medium term fellowship program.

We cannot forget the entire staff of MHSDMU and our fellow Fellows who have been a source of inspiration.

4 Acronyms

MHSDMU‐ Medicines and health Service Delivery Monitoring Unit

KCCA‐ Kampala City Council Authority

MakSPH – Makerere University School of Public Health

CDC – Centers for Diseases Control and Prevention

5 Operational definitions

For purposes of this intervention, the following definitions were adopted.

Waiting time‐ is the time spent by the client from arrival at the site up to exit after receiving treatment.

Quality improvement – Applying appropriate methods to close the gap between current and expected level of quality/performance as defined by standards.

6 1.0 Introduction The Medicines and Health Service Delivery Monitoring Unit (MHSDMU) was set up in October 2009 as a strategic response to existing challenges to service delivery in the health sector. MHSDMU is an independent unit under the President’s Office whose broad remit is to improve health services for the population by monitoring the management of essential medicines and service delivery. MHSDMU’s Mission is to monitor, support and sustain a national health care system that is efficient in operation; which provides affordable, high quality healthcare at all times and is cognizant of the right to health and dignity of the people of Uganda.

Kiswa Health center is a government unit in Nakawa division under Kampala Capital City Authority (KCCA). The facility is currently the only functional unit in the division but is yet to be relieved by Naguru hospital which was originally a health center IV but was demolished two years ago to construct a government hospital. Kiswa has a catchment population of 333,840 people and serves all the suburbs in Nakawa division. The CQI fellows together with MHSDMU agreed to do a CQI project at this health center because of its patients load, and it was intended to improve service delivery at the unit so as to avoid patients from Nakawa division referring themselves to Mulago hospital which is already overwhelmed by patients.

The amount of time a patient spends at a health facility has often been used as a measure of patient satisfaction with the service being provided. A patient’s experience of waiting can radically influence his/her perceptions of service quality (Afolabi&Erhun, 2003). The other implications of long waiting time leads to unnecessary delays in assessment leading to worsening conditions and death In a study carried out at the University of Southern California, Los Angeles, USA, it was shown that the overall satisfaction of patients with medical services is closely related to their satisfaction with waiting time (Trop J Pharm Res, June 2003).

It was against the above introduction that MHSDMU proposed to implement a continuous quality improvement project at Kiswa Health Centre III to reduce patients waiting time at the facility as a way of improving health service delivery. The project ran from December 2011 to August 2012.

7 2.0 Literature review

2.1 Need for short waiting time to OPD clients

The health facility system, but almost invariably, a high percentage of these patients arrive and leave the hospital at various times. The amount of time a patient waits to be seen is one factor which affects the utilization of health care services (Fernandes et al., 1994; dos Santos et al., 1994) and patients perceive long waiting times as barriers to actually obtaining services (Kurata et al., 1992). In a competitively managed health care environment, patient waiting time play an increasingly important role in a clinic’s ability to attract new business. It is difficult to sell services if individuals are dissatisfied with waiting time which is the length of time from when the patient entered the waiting room or the consulting room to the time the patient actually left the hospital (Mackey and Cole, 1997).

Additionally, waiting time becomes a factor in retaining current users of the services. Patient satisfaction has Healthcare systems throughout the world face long and increasing wait times for medical services (Willcox et al. 2007; Siciliani and Hurst 2004; Hurst and Siciliani 2003; Blendon 2002 ). Sometimes these waits may have little medical impact, but excessive delays may be detrimental to patients' health (CIHR 2007). As a result, there is growing public and patient pressure on political leaders to reduce wait times to acceptable levels of quality of health care; hence, healthcare assessment.

Facility performance can be best assessed by measuring the level of patient’s satisfaction. A completely satisfied patient believes that the organization has potential in understanding patient needs and demands related to health care (Net et al., 2007). A study in the United Kingdom concluded that, patient satisfaction is directly correlated with waiting times to see a doctor (Maitra and Chikhani, 1992) while another study found that, because of prolonged waiting times, a substantial number of patients left outpatient departments (Fernandes et al., 1994).

A study of this nature is critical to public appreciation of the quality of health care operating environment; hence, this study was aimed at assessing patients’ waiting time and factors affecting waiting in the outpatients’ departments. Data generated from the study could be used by hospital administrators to address gaps in human resources, logistics, infrastructures and other internal procedures towards ensuring an effective health care delivery system.

Long wait times for access to certain health care procedures are a concern in the Ugandan health care system. As governments in Uganda struggle to reduce health care wait times, most

8 government institutions are publishing the data on the wait times for specific procedures in their institutions.

Wait times for health services arise because

• capacity does not match demand,

• capacity or demand is not well managed and

• There is significant variability over time in the demand for healthcare services.

By capacity, we mean the maximum rate at which a resource can deliver a service when operating at peak efficiency (Anupindi et al. 2005). Capacity is controlled through investment in and scheduling the use of people, physical plant and equipment. Setting capacity levels entails an unavoidable trade‐off between wait times and resource utilization.

In most healthcare settings, patient scheduling is carried out by schedulers who must make complex trade‐offs in the absence of intelligent software and precise decision rules to support their decisions. This activity becomes especially challenging and complex when

• patients are categorized into priority classes with different service time targets,

• there are multiple types of equipment with different capabilities on which a patient can be scheduled,

• patients must be booked for a course of treatment requiring several days or weeks or

• Resources are spread across a wide geographic region.

It is never advisable to book patients beyond their wait time targets. Doing so does not avoid the need for overtime; instead, it just delays when it is needed. For lower‐priority patients, scheduling them as late as possible without exceeding the wait time target for their priority class gives the scheduler maximum flexibility to account for future demand variability.

Waiting time is one of the most noticeable signs of good health care service and is often used as a key performance indicator of health performance especially for outpatients’ clinics.

Out Patient Departments (OPD) act as a 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. When well organised and professionally run, not only can OPDs help avoid confusion, frustration and overspending by fearful patients but can also regulate the flow of

9 inpatients to the hospitals. Having observed the importance of OPD, hospitals today are making changes on various fronts to streamline this area.(SonalShukla 2007)

Long waiting time by OPD patients at Kiswa Health Centre was a big challenge at the facility. This sometimes turned visible when the patient would get agitated and shouts at the staff for the delay in the OPD procedures. Some patients arrived with pain and grief and ended up being delayed which often led to worsening conditions of the patients.

10 3.0 Problem statement The MHSDMU MakSPH‐CDC CQI fellows did a Time and Motion study In Kiswa HCIII on new patients waiting time and found out that a patient took an average of 95 minutes at the facility. This had created patients dissatisfaction and led to some patients going back home not attended to. This problem had also led to patients conditions worsening sometimes leading to death.

11 4.0 Objectives 4.1 General objectives

Overall objective:

• To provide quality health care by increasing efficiency and patient satisfaction through reduction in waiting time from about two hours to less than half an hour.

4.2 Specific objectives

• 1. To create a smooth patient flow enabling all OPD attendants to navigate through all the relevant points of care within 30 minutes by July 2012.

• 2. To increase Kiswa HC III clinical staff levels from 55% to above 70% by July 2012

• 3. To create an efficient staff duty allocation and support system thereby ensuring maximum output from all staff by July 2012.

12 5.0 Methodology

5.1 Brainstorming The MHSDMU team together with the MakSPH‐CDC fellowship coordinator had an orientation session with staff of Kiswa HCIII where the concept of CQI was well brought up to the staff. This was followed by a brain storming session. At a brainstorming session, Kiswa HC III staff suggested the following process related problems affecting service delivery at the unit. The problems were assigned letter codes as below:

AAccumulation and Duplication of data resulting from traditional methods of capturing data

B Poor organization of the unit leading to long waiting time.

C Lack of health education, health talks and shows leads poor adherence and lower than expected OPD attendance

D Lack of triage equipment e.g weighing scale, thermometers, height scales

E Lack of utilities in the facility

F Staff refreshments/ stress relievers/motivators

G Staff arrival time is too late

H Staff roles not clearly defined

5.2 Motivating The above problems were subjected to multivoting as below:

13 Item letter 1 st vote 2 nd vote 3 rd vote 4 th vote A 6 8 10 B 6 6 8 C 5 6 7 D 8 7 7 E 5 3 F 1 G 4 5 7 H 6 6 9

5.3 Theme selection Problems A, B, and H were selected for theme selection as below:

14 A,B and H were subjected to theme selection as below

Themes Customer(s) Impact on Need to Overall external improve customer(s)

A Patients & staff 4 5 20

B Patients & staff 5 5 25

H Patients & staff 4 5 20

Voting results

“Reducing Patients waiting Time for new patients at the HC in OPD” (B) was hence voted as the problem to be handled

15 5.4 Fishbone Analysis Staff Infrastructure

One staff attends many depts

Few staff &rosta not followed

Long pt‐clinician time Multiple breaks for tea, nature calls

Equipment shared e.g BP No tea at station, one toilet (queues)

Multiple returns of pts to prevstatns Under staffing Poor organization of unit

Long waiting time

Recording process too long Disorganised/Poor patient flow Recording process too long Disorganised/Poor patient flow Archaic recording methods used Lack of guidance/no flow chart

High OPD attendance

Lack of appointment system

Patients not utilizing peripheral units

Records Patients

16 5.5 Countermeasure matrix

Problem Root causes Counter measures Practical methods Effectiveness Feasibility Overall Action

Streamlin Draw & Poor display flow e patient chart patients’ flow Create 5 4 9 Y flow Triage centre Multiple Reduce Staff tea on 5 5 10 Y Reducing staff staff site Long breaks breaks Waiting Lobby for time recruitment 4 4 8 Y Recruit of C/O Understaf critical 5 5 10 Y fing Recruit staff Volunteers

Decentralize Lab services 5 4 9 Y Streamlin Staff roles e staff not clear roles Make staff duty rosters 5 5 10 Y Lack of Start an Appointmen 3 4 7 N appointm appointm ts computer ent ent Allocate time for system system returning 4 3 7 N patients

17 6.0 Baseline survey Graph showing previous waiting time for new patients at OPD

Average time spent in each department by patients

18 7.0 Project Outcomes

How waiting time was reduced

ROOT CAUSES EMPLOYED COUNTER MEASURES

Absenteeism of clinical staff • Weekly duty rostas introduced (3)

• Info sharing with KCCA leading to warning & transfer of habitual offenders (3)

Long tea breaks by staff • Tea and refreshments introduced on site (3)

Lack of functional places of convenience forcing • Sewerage system unblocked, toilets now staff to go to opposite petrol station for nature functional (3) calls

Lack of power due to disconnection from • Lobbying KCCA led to all power bills being outstanding bills causing delays in lab results paid, all lab tests performed on time (1)

Understaffing (clinical staff) • Lobbying led to recruitment of two extra clinical. (2)

Lack of staff uniform (Patients take long to • Staff supplied with uniform by MoH after identify staff) lobbying (1)

No signs or direction for patients causing poor • Signage being printed and to be installed patient flow when renovations are complete (1)

19 7.3 Comparison of Current and Previous new OPD patients waiting time:

• The table below compares the previous new OPD patients waiting time and the current patients waiting time after the CQI intervention.

Before the CQI intervention, patients were spending approximately 2 hours at the facility for treatment. However after the CQI intervention, patients are now spending 1 hour and 6 minutes at the facility.

Graph showing average waiting time at baseline vs average waiting time

After intervention for the various duty

stations

Average time spent in each department by patients

20 8.0 Lessons learnt:

• Through cordial partnerships with the In‐charge, IDI, MOH and KCCA, we realized that most of challenges could be addressed in partnership, and we therefore agreed to work as a team. As result of this partnership, only 60% of the CQI budget was used, and the other expenses were met by our partners.

9.0 Challenges faced:

Challenge solution matrix

CHALLENGE SOLUTION

Initial resistance from Kiswa HC III staff • Orientation of staff in CQI concepts and motives

• Participatory approach

Transfer of CQI team members mid‐ • Co‐opting other HC staff to replace intervention transferred members

Some planned activities not implemented • Activities budgeted and to proceed post due to ongoing unit expansion fellowship.

21 Poor cash flow from KCCA could affect • Continuous lobbying intervention sustainability

9.1 How challenges were resolved:

• In mitigating project resistance from Kiswa HCIII staff, the Coordinator of MakSPH – CDC fellowship Program was invited to the facility and he ably informed the staff on the motives of the CQI program. • Transfer of most of CQI team members by KCCA was a big challenge. However the project’s continuity was helped by the in‐charge’s commitment and the other partners that were already on board. • Signage for guiding patients at the facility will be pinned after major renovations. • KCCA’s failure to release imprest, we are planning to meet its management over the matter.

22 10.0 References 1. Ronald M. Kasyaba, Ida K. Ndyabanawe. Reducing waiting time for clients attending the ART clinic at Kabale Regional Hospital, Uganda. Final Project Report, Medium‐term Fellowship Program, Makerere University School of Public Health. 2009.

2. Rosemary Nabadda. Reducing the turnaround time for voluntary counseling and testing clients at Kyambogo University Medical centre. Final Project Report, Medium‐term Fellowship Program, Makerere University School of Public Health. 2010.

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13. Steindel SJ, Howanitz PJ. Physician satisfaction and emergency department laboratory test turnaround time. Observations based on college of American pathologists q‐probes studies. Arch Pathol Lab Me

23 14. Hospital emergency department without being seen by a physician: Causes and consequences’, JAMA, 266: 1085–1090.

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