workload indicators of staffing needs: technical insights from ghanaian pilot study
DESCRIPTION
This presentation was delivered in a staffing norm planning meeting held at the Director General's conference room of Ghana Health Service. Accra. It gives technical details of how the WISN method was used (in a pilot) to determine the staffing requirements of a district hospital in Ghana. This formed part of the process leading to the establishment of evidence based staffing norms for the health sector in Ghana. The project is championed by the Ministry of Health, Ghana Health Services and the Christian Association of Ghana (CHAG)TRANSCRIPT
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
Contributions
Clarifications
Questions