THE WISN APPROACH TO DETERMINING

STAFFING REQUIREMENTS: TECHNICAL

INSIGHTS FROM DONKORKROM PILOT

JAMES AVOKA ASAMANI Nursing Officer

Staffing Norms Review Planning Meeting,

Venue: GHS Headquarters, Accra

Date: 4th October, 2013

The Gateway to Afram Plains

Donkorkrom Presby Hospital – Front view

New Maternity Complex

Outline

Introduction

Background

The WISN method and how it was applied

in DPH

Results

Challenges

Recommendations

Further work

INTRODUCTION A pilot workload analysis was done in the

Emergency unit using the manual technique of WISN

Result was presented during the hospital’s annual review meeting.

The method caught the attention of the DDHS and the General Manager of the Kwahu Presbytery Health Services who jointly called for a comprehensive analysis of the hospital.

Lack of resources limited the analysis to only clinical staff but now being expanded to include administration and support staff.

Steps of WISN method

1. Determine priorities for WISN application

2. Estimate Available Working Time

3. Define workload components

4. Set Activity Standards

5. Establish Standard Workloads

6. Calculate Allowance Factors

7. Determine WISN-based staff requirements

8. Analyse and interpret results

9. Use and share results

How was the method applied in

DPH? A six-member Technical Team was set up to

conduct the WISN study. The team

included

◦ Mr. James Avoka Asamani (Nurse) - Leader

◦ Mr. Eric Demegbe (Senior Biostatistician)

◦ Mr. Marcus Datsey (Accountant)

◦ Mr. Livingstone Adjetey (Pharmacy Technician)

◦ Ms. Cynthia Agyekum (Midwife)

◦ Mr. Alexander Gyimah (Nurse)

AVAILABLE WORKING TIME:

DETERMINING THE ABSENCES

Sick Leave: Records from the sick staff

register was used to calculate the average

sick leave spent by all staff in the hospital.

◦ On the average staff spent an average of 4.76

days in 2012 as excuse duty due to sickness. This

figure was rounded to 5 days for all categories of

staff irrespective of whether one person spent

more or less.

DETERMINING THE ABSENCES CONT’D

Public Holidays: In 2012, thirteen (13) statutory public holidays were declared by the Government of Ghana.

Training days per year: from the records, junior staff averagely benefited from four (4) days of training.

◦ However, all top level professionals or heads of departments on average got an additional two to three (2-3) days external training opportunities. This was standardized to 5 days of training per year for all senior personnel*

DETERMINING THE ABSENCES CONT’D

Special No Notice Leave: All forms of leave or requests for permission to travel for private assignments unrelated to personal ill-health was classified as special No Notice Leave.

The Admin. Manageress and the Nurse Manager were contacted for records of staff requests for permission to travel.

The average for each category of staff was calculated separately and later standardized to be 4 days per staff (of all categories).

Maternity leave was also standardized to 3 days per each staff

Total special no notice leave then came to 7 days per staff

Defining workload components

A questionnaire was designed and given to various workers to list ‘what they do on a typical day’

Only actual activities carried out by staff were used and not necessarily those on the job description which they do not practice.

The workload components were reviewed and categorized into health service, support and additional activities

The categorized workload components were peer reviewed by ‘experts’ for consistency and validity

Setting Activity Standards: The Steps

used in Donkorkrom Interviewed relevant staff

Consulted experts (within and/or outside the facility) for validation

Observed and timed staff (unobtrusive participant or non-participant observation was used)

Used a log and diary in some cases

Retrospective record review (esp. surgical cases)

The other steps

Using the 2012 service utilization

statistics, the rest of the WISN steps was

completed using the software

RESULTS STAFF CATEGORY EXISTING CALCULAT

ED

GAP WISN

RATIO

% GAP

Community Oral Health

Officer 1 1 0 1 0

Dental Assistant 1 1 0 1 0

Dental Surgeon Assistant 1 1 0 1 0

Laboratory Technologist 1 6 -5 0.17 500%

Understaffed

Laboratory Assistant 9 8 1 1.12 11%

Overstaffed

General Practitioner 3 4 -1 0.75 33%

Understaffed

Physician Assistant-

Medical 2 2 0 1 0

Registered Midwives 8 10 -2 0.8 25%

Understaffed

Results cont’d STAFF CATEGORY EXISTING CALCULATED GAP WISN

RATIO

% GAP

General nurses 26 42 -16 0.62 61%

Understaffed

Health Assistants 21 18 3 1.17 14%

Overstaffed

Psychiatric Nurses 2 1 1 2 50

Overstaffed

Surgical Nurses 3 3 0 1 0

CHNs 3 3 0 1 0

Enrolled Nurses 10 18 -8 0.56 80%

Understaffed

Pharmacist 1 2 -1 0.5 100%

Understaffed

Results cont’d STAFF CATEGORY EXISTING CALCULAT

ED

GAP WISN

RATIO

% GAP

Pharmacy

Technician 2 4 -2 0.5

100%

Understaffed

Dispensary

Assistant 7 4 3 1.75

43%

Overstaffed

X-ray Technician 2 1 1 2 50%

Overstaffed

Ophthalmic Nurse 1 1 0 1 0

Physician Assistant

Anesthesia 3 2 1 1.5

33%

Overstaffed

TOTAL 107 132 -25 18.9%

understaffed

COMMUNITY ORAL

HEALTH OFFICER

1%

DENTAL

ASSISTANT

1%

DENTAL

SURGEON

ASSISTANT

1%

LABORATORY

TECHNOLOGIST

1%

LABORATORY ASSISTANT

8% GENERAL

PRACTITIONER

3% PHYSICIAN

ASSISTANT-MEDICAL

2%

REGISTRED MIDWIVES

7%

GENERAL NURSES

24%

HEALTH ASSISTANTS

20% PSYCHIATRIC NURSES

2%

SURGICAL NURSES

3%

CHNS

3%

ENROLLED NURSES

9%

PHARMARCIST

1%

PHARMARCY TECHNICIAN

2%

DISPENSARY

ASSISTANT

7%

X-RAY

TECHNICIAN

2%

OPHTHALMIC NURSE

1%

PHYSICIAN ASSISTANT

ANAESTHESIA

3%

Existing Staff Composition

community oral health officer

1% Dental Assistant

1%

Dental Surgeon Assistant

1%

Laboratory Technologist 5%

Laboratory Assistant 6%

General Practitioner 3%

Physician Assistant-Medical

2%

Registred Midwives 8%

General nurses 32%

Health Assistants 14%

Psychiatric Nurses

1%

Surgical Nurses

2%

CHNs 2%

Enrolled Nurses 14%

Pharmarcist 2%

Pharmarcy Technician 3%

Dispensary Assistant

3%

X-ray Technician

1% Ophthalmic Nurse

1% Physician Assistant Anaesthesia

2%

Calculated Clinical Staff Composition

com

munity…

Denta

l…

Denta

l…

Lab

ora

tory

…

Lab

ora

tory

…

Genera

l…

Phys

icia

n…

Regi

stre

d…

Genera

l nurs

es

Heal

th…

Psy

chia

tric

…

Surg

ical

Nurs

es

CH

Ns

Enro

lled…

Phar

mar

cist

Phar

mar

cy…

Dis

pensa

ry…

X-r

ay…

Ophth

alm

ic…

Phys

icia

n…

TO

TA

L

1 1 1 1 9

3 2 8

26 21

2 3 3 10

1 2 7

2 1 3

107

1 1 1 6 8

4 2 10

42

18

1 3 3

18

2 4 4 1 1 2

132

Existing Staff Vs Required Staff

EXISTING CALCULATED REQUIRED STAFF

Challenges

Training

Records keeping issues; data

separation

Mistaken for market premium

determination

Skepticism

Funding

CONCLUSIONS 1. Despite its limitations, the WISN tool is a useful, more

objective and empirical method of determining staff requirements based on service utilization and workload.

2. The Donkorkrom pilot suggests a critical shortage of key professionals such as Doctors, Biomedical scientists, Dispensing Technicians, Midwives and Nurses among others

i. This has given way for auxiliaries to take up responsibilities that are above their level of training. This poses a real threat to quality health care and increases the risk of medico-legal suits against the hospital.

ii. Whilst some professionals are in short supply, many categories of auxiliary staff are overstaffed, a situation that is more than the 60% professionals to 40% auxiliaries norm used in Ghana.

3. Documentation and record keeping is far below expectations (a study on documentation is complete and is due to be published)

RECOMMENDATIONS/POLICY IMPLICATIONS

DONKORKROM PRESBYTERIAN

HOSPITAL

Train or recruit the core clinical

professionals to fill the gaps identified in

this study to enhance quality of health

care delivery

Streamline the additional employment of

auxiliary staff and make deliberate efforts

to train some of the existing auxiliaries to

become professionals

DONKORKROM PRESBYTERIAN HOSPITAL

Integrate WISN into the organizational

processes as the basis of Management’s

human resource policy decisions.

Special motivational package for staff

who are clearly overburdened with

work but to be removed when the

indicators no longer warrants it.

Recommendations – MoH/GHS/CHAG

As a matter of policy, adopt and promote

the use of the WISN method as the

standard tool of determining the staffing

needs in health facilities across the country

to partly resolve the issue of mal-

distribution of health staff

Organize in-service training for health

facilities across the country on the use of

WISN as a human resource planning tool.

Recommendations – MoH/GHS/CHAG

Designate National/Regional workload

analysis focal persons to support, train

and coordinate the integration of WISN

into the organizational processes of

GHS/CHAG (Avoid WISN being a one-

off event)

Advocate for the inclusion of the WISN

methods as a subject or topic in the

training of health care professionals

Utilization of results

Intra-hospital analysis led to internal

redistribution of some staff especially

nurses

In line with GHAG directive, a WISN-

based human resource plan is being

developed

WISN analysis of our health centres is

also in progress

A laundry in need of help

and so far,

if you have been,

thanks for listening!

12/23/2013 avokaj@yahoo.com

Contributions

Clarifications

Questions