Determining staffing standards for primary care services using workload indicators of staffing needs in the Philippines

Abstract

Background
Health services cannot be delivered without an adequate, competent health workforce. Evidence suggests a direct relationship between density of health workforce and health outcomes. The Philippines is faced with health workforce challenges including shortages, inequitable distribution and inadequate skill mix which hinder health service delivery. Evidence-based workforce planning is, therefore, critical to achieve universal health care.

Methods
The Philippines adopted the World Health Organization’s workload indicators of staffing need methodology. Using a multistage sampling method, nine regions with poor health indicators in tuberculosis, family planning, and maternal child health were identified. Physicians, nurses, midwives, and medical technologists were prioritized in the study from 89 primary care health facilities (barangay health stations, rural health units, and city health offices). Data was collected using in-depth interviews, document reviews, observations, and field visits. The workload indicators of staffing need software were used for data analysis to determine staffing requirements and analyse workforce pressure.

Results
The study showed varied results in terms of staffing requirements and workload pressure across cadres and facility types. Some health facilities exhibited staff shortages and high workload pressure. Out of the 40 rural health units and city health offices, only three had the required physicians needed and 22 facilities had a shortage of physicians working under high workload pressure. Other facilities had excess staff compared to the calculated requirements. Nurses at the rural health units showed high workload pressure. Ten rural health units had no medical technologists. Midwives at barangay health stations exhibited extremely low workload pressures.

Conclusion
The study identifies the need for the Philippine Health System, both through the Department of Health and the local governments to efficiently optimize the available health workers by revising the services offered at the primary health care facilities. The results provide evidence for staffing requirements at various levels of care based on workloads, scope of practice and time taken to undertake specific tasks at the barangay health stations, rural health units and city health offices to be integrated into the human resources for health management systems.

Full text

Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
https://doi.org/10.1186/s12960-021-00670-4
CASE STUDY
Determining stang standards forprimary
care services using workload indicators
ofstang needs inthePhilippines
Ma Graziella Aytona1* , Mary Ruth Politico1, Leah McManus2, Kenneth Ronquillo1 and Mollent Okech3
Abstract
Background: Health services cannot be delivered without an adequate, competent health workforce. Evidence
suggests a direct relationship between density of health workforce and health outcomes. The Philippines is faced
with health workforce challenges including shortages, inequitable distribution and inadequate skill mix which hinder
health service delivery. Evidence-based workforce planning is, therefore, critical to achieve universal health care.
Methods: The Philippines adopted the World Health Organization’s workload indicators of staffing need methodol-
ogy. Using a multistage sampling method, nine regions with poor health indicators in tuberculosis, family planning,
and maternal child health were identified. Physicians, nurses, midwives, and medical technologists were prioritized
in the study from 89 primary care health facilities (barangay health stations, rural health units, and city health offices).
Data was collected using in-depth interviews, document reviews, observations, and field visits. The workload indica-
tors of staffing need software were used for data analysis to determine staffing requirements and analyse workforce
pressure.
Results: The study showed varied results in terms of staffing requirements and workload pressure across cadres and
facility types. Some health facilities exhibited staff shortages and high workload pressure. Out of the 40 rural health
units and city health offices, only three had the required physicians needed and 22 facilities had a shortage of physi-
cians working under high workload pressure. Other facilities had excess staff compared to the calculated require-
ments. Nurses at the rural health units showed high workload pressure. Ten rural health units had no medical tech-
nologists. Midwives at barangay health stations exhibited extremely low workload pressures.
Conclusion: The study identifies the need for the Philippine Health System, both through the Department of Health
and the local governments to efficiently optimize the available health workers by revising the services offered at the
primary health care facilities. The results provide evidence for staffing requirements at various levels of care based on
workloads, scope of practice and time taken to undertake specific tasks at the barangay health stations, rural health
units and city health offices to be integrated into the human resources for health management systems.
Keywords: Primary health care, Universal health care, Workload indicators of staffing need, Health workforce, Health
workforce planning, Staffing requirements
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Background
e 1978 Declaration of Alma Ata on primary health
care (PHC) revolutionized the world’s interpretation
of health with the core principles of universal access to
care, equity, community participation, intersectoral col-
laboration and appropriate use of resources [1].Moving
Open Access
*Correspondence: gcaytona@doh.gov.ph
1 Department of Health, Health Human Resources and Development
Bureau, Manila, Philippines
Full list of author information is available at the end of the article
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
forward, reforms towards Universal Health Coverage are
hinged on strong primary care systems to provide essen-
tial health services to all.
e Philippines has a long history of PHC having
adopted the approach in 1981 as a national strategy. is
strategy relies heavily on the community through baran-
gay health stations (BHS) that serve a population of 5,000
and rural health units (RHUs)/city health offices (CHOs)
that serve a population of 20,000 [2]. e devolution of
health services in 1991 mandated the management of
primary care facilities at the barangay, city, or municipal
levels to local governments units (LGU) [3]. e DOH,
on the other hand, sets the standards for primary care
facilities, including their staffing. In addition to formal
cadres of health workers under the primary care facility
(e.g., physicians, nurses, and midwives), Barangay Health
Worker (BHW) complement health services at the com-
munity level, acting as the first point of contact between
the healthcare system and the rest of the community [4].
In 2019, building upon successes in the past 30years
of health reforms, the Government of the Philippines
signed the Universal Health Care (UHC) Law (Republic
Act 11223) which provides a strong agenda for effective
health workforce management in the country [5]. e
UHC Law highlights the importance of the primary care
approach and provides for the formulation and imple-
mentation of human resources for health (HRH) poli-
cies and plans that generate, recruit, retrain, regulate,
retain, and reassess the health workforce based on popu-
lation health needs [5]. UHC ensures that everyone has
access to well-trained, culturally sensitive, and competent
health workers. e best strategy for achieving this is by
strengthening multidisciplinary teams at the primary
health care level [6–8]. Key in this endeavour is the avail-
ability of competent and well-motivated health workers
at the community level [9]. e Philippines, however,
faces several HRH challenges. ese challenges include
a shortage of health workers, maldistribution, and an
urban bias that causes most rural areas to be severely
understaffed. Some health workers are employed on a
contractual basis, either by the government or develop-
ment partners. is has negative consequences on reten-
tion and biases service provision towards specific disease
programs [10].
e HRH shortages and inequities in the Philippines
translate to disparities in the provision of quality of
health care services, impacting critical PHC services,
such as Tuberculosis (TB) and family planning (FP)
[11]. TB remains one of the leading causes of morbidity
and mortality despite sustained investments on the pre-
vention, control and management by the government
and partners. In 2016, the World Health Organization
(WHO) reported that there were 260,000 projected
cases in the country with 28,000 dying per year [11].
e report further highlighted the emergence of mul-
tidrug-resistant TB and extensively drug-resistant TB
across population groups have significantly increased.
In addition, the 2017 Philippines National Demo-
graphic and Health Survey indicated the low uptake of
FP services noting that one in every five married Filipi-
nas wishing to postpone their next birth or stop child-
bearing are not using contraceptive [12]. is is despite
provisions in the Responsible Parenthood and Repro-
ductive Health Law (Republic Act No. 10354) guaran-
teeing universal access to FP information in all public
health facilities with emphasis in the primary care level
facilities [13].
e UHC Law echoes the need for evidence-based
planning for HRH at all levels of care with an empha-
sis on primary care. Evidence-based HRH planning
provides the information necessary for mobilizing ade-
quate resources based on these needs. Furthermore, it
recognizes that having adequate staffing in health facili-
ties requires critical consideration for HRH planning
beyond the usual workforce to population ratios. [10,
14–16].
In response to this need to conduct evidence-based
planning, the Philippine Department of Health (DOH),
with support from the United States Agency for
International Development (USAID) funded Human
Resources for Health 2030 (HRH2030) Philippines Pro-
ject implemented by Chemonics International, in 2019
used the World Health Organization’s (WHO) Work-
load Indicators of Staffing Need (WISN) methodology
with a focus on the four most prevalent cadres, namely,
nurses, midwives, physicians and medical technolo-
gists in primary care health facilities in selected regions
of the country. While the DOH and other stakeholder
conducted workforce analysis studies in the past using
population and health worker densities, this study was
the first in the Philippines to adopt the WISN meth-
odology step by step to provide evidence for staffing
requirements for the country’s context. e WISN
methodology offers an objective and scientific method
to estimate health workforce requirements based on
actual workloads, looking at both the health service
and non-health service activities that are conducted by
health workers using actual service statistics from the
facility [17–21]. e WISN study allowed the DOH to
conduct a thorough analysis of the workload of physi-
cians, nurses, midwives, and medical technologists at
BHS, RHUs/CHOs. e study resulted in the identifica-
tion of staffing needs, as well as minimum and maxi-
mum staffing standards, for these cadres to carry out
PHC and ultimately contribute to achieving UHC.
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
Methods
Study design
e DOH and HRH2030 Philippines used a cross sec-
tional study design to adopt the WISN methodology.
e study included WISN variables, namely, the available
working time, workload components (health services,
support, and additional activities), service standards
and the standard workloads for health service activities.
Annual statistics for the year 2018 were used together
with the existing staff for the four main cadres of focus in
the selected health facilities.
Setting
e study was set in the Philippines in the Luzon, Visayas
and the Mindanao regions. Data collection was con-
ducted from October 2018 to April 2019, while data anal-
ysis and report development were completed from April
to July 2019. e study focused on services delivered by
physicians, nurses, midwives, and medical technologists
at BHS (49) and the RHUs/CHOs (40) that are managed
by LGUs.
Working groups
ree critical committees with specific roles to ensure
accurate implementation, oversight and acceptable work-
load components and activity standards were established.
e Steering Committee consisted of senior health
managers and policy makers, chaired by the Undersec-
retary providing overall oversight and supervision for
implementation. A national level technical task force
(TTF) and three regional TTFs from the regions of focus
were established. e national TTF consisted of repre-
sentatives from the Health Human Resources Develop-
ment Bureau (HHRDB) and other key offices within the
DOH, selected key health workers from the four cadres
and technical officers from the HRH2030 Philippines
team. e national TTF was trained to ensure that they
acquired skills and knowledge on how to use the WISN
tool manually and electronically. e national TTF sub-
sequently trained the regional TTFs. As the critical team
to logically ensure implementation of the WISN method-
ology was ingrained in the country, the members of the
TTF undertook an oath of commitment to ensure WISN
was implemented logically and successfully as per the
WHO guidelines. Finally, the last group formed was the
expert working groups (EWG). e four EWGs consisted
of experienced health workers from the four cadres of
priority at all levels of care from both public and private
health facilities. ey underwent 3-day training on the
WISN methodology. eir role was to establish realistic,
reliable, and acceptable comprehensive workload compo-
nents and activity standards based on actual and accept-
able professional standards. To validate the workload
components and activity standards developed by the
EWG, a separate group made of up of the four cadres
was formed to validate the workload components and it
included representatives from the regulatory councils,
professional associations and health training institutions.
Sampling design, size, andprocedure
Using a multistage sampling method, nine regions of the
Philippines were identified with poor health indicators
in maternal child health, FP and TB as reported by 2017
health statistics. e regions cut across the urban, rural,
and geographically isolated and disadvantaged areas
(GIDA) with a proportional representation from the
three major island groups of Luzon, Visayas, and Mind-
anao. In the second phase of selection, DOH regional
offices provided a list of facilities, where 49 BHSs and 40
RHUs/CHOs were randomly selected from to form part
of the study.
Data collection andanalysis
Considering that the existing health information system
did not gather all the data as established by the EWG
during the development of the workload components,
there was a deliberate need to collect specific data from
the health facilities. A team of trained data collectors
which included some members of the EWG and national
and regional TTF visited the facilities and collected data
using pre-developed Excel sheets to gather monthly
health services statistics for the year 2018. Before data
collection, the data collection team paid courtesy calls
to the Provincial Health Offices. e offices served as the
entry points to the health facilities and provided prelimi-
nary information on the health sector and staff records
in the province. e Human Resources Officers provided
information on the staff establishments, authorized and
unauthorized leaves and actual hours worked per day
and days taken for training or other reasons. ey also
shared other health systems issues that were relevant to
the WISN process. Data for all the three workload groups
were collected for the specific cadres in the various ser-
vice areas in the health facility. e raw data was entered
in the master Excel sheet, validated by team leaders, and
finally uploaded into the WISN software to produce
reports per facility and by cadre in web archive transfor-
mation files for further analysis.
Limitations
ere were some limitations to the study which included
the sample size selection considering the overall number
of facilities in the country and funding restrictions that
prescribed the scope. In addition, there were gaps in data
availability in the health facilities, while some data were
aggregated for annual service statistics conducted by
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Table 1 Available working time for four cadres in a Rural Health Unit
Cadre Working Days
per Week Working
Hours per Day Annual
Leave Public
Holidays Sick Leave Special/No
Notice Leave Training Days AWT in Weeks AWT in Days AWT in Hours
Physicians 5 8 8 13 3 0 3 46.6 233 1864
Nurse 5 8 8 13 4 0 17 43.6 218 1744
Midwives 5 8 2 13 0 0 1 48.8 244 1952
Medical Technologist 5 8 8 13 5 0 2 46.4 232 1856
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
different cadres. ese were mitigated by triangulating
data sources, further interviews, and expert opinion.
Results
Trends inavailable working time
e study first calculated the available working time
(AWT) for each of the cadres in the various facilities.
AWT can differ from one facility to the other. Table1
shows an example of an RHU AWT for four cadres. e
nurse has 1744h in a year, 1856h for a medical tech-
nologist, 1864 for a physician and 1952h for the midwife
being the highest. In this facility, the nurse was out of the
workplace for training for 17days, while the other cadres
took less than 5 days out of work due to training.
Workload group andactivity standards percadre
e study provides results based on the three workloads
groups for physicians, nurses, midwives and medical
technologists providing PHC services at the BHSs and
RHUs/CHOs in the Philippines context. Tables 2, 3, 4
and 5 annexed provide the workload components for
health services, support and additional activities. In addi-
tion, included in the tables are the activity standards and
allowance factors for each of the cadres. For example, a
workflow in an RHU/CHO is provided. A patient visits
an RHU/CHO with symptoms of dengue fever; the nurse
spends 13min assessing the patient by welcoming, regis-
tering, taking vital signs and taking history before send-
ing the patient over to the physician for examination. e
physician in turn examines the patient during consulta-
tion that takes 16min before ordering a confirmatory test
to be conducted by a medical technologist in the labora-
tory. In the laboratory, the medical technologist spends
10min conducting a dengue rapid test and interprets the
results before sending the patient back to the doctor for
prescription which is finally administered by the nurse.
is is an indication of how the skill mix supports the
health interventions.
Stang requirements calculated
e 2018 annual service statistics were collected from the
BHSs and RHUs/CHOs uploaded and analysed using the
WISN software to determine staffing requirements for
the specific facilities. e results were provided as dif-
ferences and ratios. Table6 provides a summary of com-
puted required staffing per cadre in each of the BHS with
midwives. e differences show shortages, excesses, and
balances, while the ratios show the levels of workload
pressure whether high or low.
At the BHSs, results on staffing differed across the
cadres. Some facilities exhibited shortages, others bal-
ance between existing staff and calculated needs, while
some facilities exhibited surpluses. e midwives did not
perform the full range of services for the level of care as
provided for in the BHS package of services. Out of the
49 BHS, eight (16%) recorded shortages, 24 (49%) oper-
ated normally with enough staff, while 17 (34%) of the
Barangays Health Stations registered staff surpluses.
Further results on staffing requirements for the RHUs/
CHOs are provided in the annex in Table 7 annexed.
Six (15%) of the RHUs/CHOs registered staffing short-
ages, none operated at normal levels with sufficient staff
and 34 (85%) health facilities recorded staff surpluses.
A total of 10 RHUs/CHOs in the study had no medical
technologists.
Workload pressure
e workload pressure for each of the cadres was exam-
ined (see Fig. 1). Using the WISN difference and ratio,
a staff difference 0 and ratio of 1.00 was rated as having
normal workload pressure. In circumstances, where staff
required showed a difference of -1 and ratio of 0.50, the
workload pressure was rated as high and where the staff
difference was less by 2 and above with a WISN ratio
of -2.00, the workload pressure was rated as very high.
Where staff calculated was more than the required by 1,
2 3 and above, workload pressures ranged between low,
very low and extremely low, respectively. In all the 49
Barangay health stations, 57% of the midwives functioned
at extremely low workload pressures. On the other hand,
20% exhibited low and very low workload pressures, 18%
experienced high and very high workload pressures,
while only 4% of the midwives operated at normal work-
load pressures.
At the RHUs, the situation was similar with midwives
recording extremely low workload pressure at 44%, fol-
lowed by nurses at 48% and medical technologists at
67% Physicians registered 8% extremely low workload
pressures.
Workload analysis acrossall workload groups
e study also looked at how the health workers spent
their AWT across health service activities, support and
additional activities (see Fig. 2). e findings show that
RHU medical technologists, midwives and nurses spend
about 20% of time in support activities, with physicians
spending 18% of their time on individual activities. Mid-
wives at BHS also spent nearly 38% of their time on sup-
port and individual activities, leaving only 62% for health
services, in contrast to the Nurses 86% of time spent on
health services.
Results demonstrated many trends in provision of ser-
vices which impacted workload. ere were differences
in services offered at the same levels of care, or PHC ser-
vices being referred to level one hospital, despite the Phil-
ippines having a prescribed package of health services for
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
Table 2 Workload components and activity standards for medical technologists
Workload Group 1: Health Service Activities Activity standard
Complete blood count—automated 9 min/sample
Complete blood count—manual 25 min/sample
ABO and Rh blood typing 10 min/sample
Fasting blood sugar 33 min/sample
Oral glucose tolerance test (OGTT) 123 min/sample
Cholesterol 9 min/sample
Creatinine (serum/urine) 9 min/sample
Lipid profile 9 min/sample
Triglycerides 9 min/sample
Dengue rapid 10 min/sample
Hepatitis B antigen rapid 10 min/sample
Hepatitis B (AHBS)—automated 9 min/sample
Hepatitis BHBc—automated 9 min/sample
Hepatitis B IgG 9 min/sample
HIV—automated 29 min/sample
HIV rapid 31 min/sample
Rapid syphilis 10 min/sample
Pap smear staining 33 min/sample
Acid fast bacilli 29 min/sample
Urinalysis—automated 4 min/sample
Urinalysis—manual 8 min/sample
Faecalysis 23 min/sample
Workload Group 2: Support Activities Activity Standard
Internal quality control (IQC) 30 min/day
Calibration of laboratory equipment 20 min/day
Inventory management 1 h/month
Technical Evaluation of New Equipment 3 h/year
Validation of test parameters 8 h/year
Advocacy lecture 2 h/week
Mobile blood collection 6 h/year
External quality control 1 h/month
Departmental meetings 2 h/month
Continuous professional development 5 days/year
Workload Group 3: Additional Activities Activity standard
Number of sta per additional activity varied
per facility
Registration of health certificates 1 h/day
Management meetings and review 4 h/month
Supervision of staff 30 min/day
Orientation new staff 2 h/year
Documentary requirements for License to Operate 30 min/year
Monthly reports 1 h/month
Billing forms 30 min/month
Quality manual review 2 h/year
Research 2 h/month
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
each level of care. e study also found that some health
workers were regularly undertaking tasks that were not a
part of their scopes of practice. In addition, overlapping
and shifting of tasks among the health workers was seen.
For example, FP services and immunizations were offered
by the nurses, midwives or even the physicians. BHWs
are also involved in offering selected FP services an indi-
cation of tasks being shared and shifted. In addition,
results revealed that cadres, such as medical technolo-
gists hired by partners for TB programs only conducted
TB diagnosis related activities.
Discussion
Findings from this WISN study highlight the health
workforce situation at the primary care facilities. e
study results show that the health workers AWT differed
for each of the cadres at the various facilities. For exam-
ple, midwives spent more time in BHSs due to fewer days
taken for leave, training, or other absences. It emerged
that there were inequitable days for training for each
of the cadres with the physicians having more days for
training compared to their other colleagues. e lack of
a coordinated approach and weak supervision and man-
agement of health worker training at the LGUs is likely
to exacerbate HRH absences thus affecting access to ser-
vices. While continuous training to update health worker
skills is critical for both motivation and improving
effectiveness it should be well distributed within the cad-
res to enhance productivity [22]. is finding supports
rationale for ongoing efforts to apply innovative training
approaches, such as use of eLearning to enhance com-
petency of staff with less disruption in health service
delivery.
e differences in services offered at the various BHSs
and RHUs demonstrate that facilities are not offering
the prescribed standard package of services. Midwives
mainly provided services, such as consultations for minor
illnesses, selected maternal and child health services,
such as FP, antenatal, postnatal care, and immunizations.
Midwives have the clinical skills and scope of practice to
undertake more services, but it was found they do not
offer all services described by the BHS package of health
services. Similarly, the medical technologists offered very
minimal services, focusing mainly on acid-fast bacilli
testing, urinalysis and faecalysis, from a wide range of
services they can offer. is finding provides evidence
for the revision of the existing standard packages of ser-
vices for health facilities to match the needs of commu-
nities. In other countries, WISN studies have been used
to revise the services offered at various levels of care in
other countries [23, 24]. As such, the WISN study rec-
ommended to the Steering Committee that an update of
the standard package of services for PHC was needed. By
2020, during the drafting of this manuscript, the DOH
Table 3 Workload components and activity for physicians
Workload Group 1: Health Service Activities Activity standard
Consultations 16 min/patient
Minor surgical procedures 30 min/patient
Referrals 9 min/patient
Family planning—bilateral tubal ligation (BTL) 30 min/patient
Family planning—vasectomy 30 min/patient
Workload Group 2: Support Activities Activity standard
Workload Group 2: Support Activities Activity standard
Health education 2 h/month
Departmental meetings 2 h/month
Continuing professional development 8 days/year
Outreach program (medical mission) 8 h/month
Issuance of documents and medicolegal management 8 h/month
Workload Group 3: Additional Activities Activity standard
Number of sta per additional activity varied
per facility
Staff supervision 30 min/day
Trainee supervision 2 h/week
Administrative functions 1 h/week
Interpretation and action on surveillance 2 h/week
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
used the study results to inform development of the
essential package of services for primary care facilities
including staffing norms considering the WISN results.
High and extremely high workloads and pressure
recorded in some facilities indicate staff shortages that
may compromise quality of services provided. Other
WISN studies have equally reported high pressure at var-
ious levels and cadres and recommended staff redistribu-
tion of health workers to facilities with high workloads
[25]. Recognizing that maximizing the potential of the
health workforce is one of the policy orientations speci-
fied in the UHC law, the WISN results provided evidence
that resulted in defining staffing minimum and maxi-
mum requirements at primary care facilities as shown in
Table8. e study found that a BHS requires a minimum
of one midwife and maximum of two midwives as well
as a minimum of two nurses and a maximum of three
nurses to offer the wide range of services at these units.
Similarly, RHUs/CHOs require a minimum of one and a
maximum of two laboratory technologists. e RHUs/
CHOs also require two nurses and two midwives at the
minimum and a maximum four nurses and midwives,
respectively. Finally, RHUs/CHOs require a minimum of
one and two maximumphysicians.
Such results have been reported in WISN studies con-
ducted in other countries that have expanded services
in the community units as part of primary care [26–28].
Globally, countries are increasingly turning to com-
munity health workers, or BHWs in the Philippines, to
extend health services to underserved areas [29]. During
the study interviews, the researchers found that BHWs
contributed to most of the workloads on PHC services
captured in BHSs and some RHUs. Supporting and
Table 4 Workload components and standards for midwives
Workload Group 1: Health Service Activities Activity standard
Antenatal visits 39 min/client
Family planning—male condoms 24 min/client
Family planning—injectables 23 min/client
Family planning—intrauterine device (IUD) 53 min/client
Family planning—natural 33 min/client
Family planning—implants 44 min/client
Family planning—pills 12 min/client
Normal spontaneous delivery 99 min/patient
Newborn care 120 min/patient
Labor management 168 min/patient
Post-natal care 35 min/patient
Childcare/well baby clinic 18 min/patient
Integrated management of childhood illness 22 min/patient
Visual inspection with acetic acid (VIA) 25 min/patient
Pap smear 20 min/patient
Rehabilitation of malnourished children 20 min/patient
Caesarean section (pre-operative care) 14 min/patient
Workload Group 2: Support Activities Activity standard
Health education 30 min/day
Home visits 8 h/month
Staff meetings 2 h/month
Continuous professional development 48 h/year
Medical missions 16 h/month
Housekeeping (5S) practice 40 min/day
Mentoring of students 12 h/week
Workload Group 3: Additional Activities Activity standard
Number of sta per
additional activity
varied per facility
Supervision of BHWs I hour/day
Management meetings I hour/month
Mass circumcision 8 h/year
Table 5 Workload components and standards for nurses
Workload Group 1: Health Service Activities Activity standard
Patient assessment 13 min/patient
Nursing diagnosis and management 34 min/patient
Minor surgical procedures 37 min/patient
Wound care 30 min/patient
Administration of medication 20 min/patient
Immunization 12 min/patient
External referral with escort 142 min/patient
Internal referral/external referral without escoW-
orkload Group 1: Health Service Activities
rt
12 min/patient
Workload Group 2: Support Activities Activity standard
Health teachings 30 min/day
Home visits 8 h/week
Reporting patient census 30 min/day
Staffing meetings 1 h/month
Community outreach programs 8 h/month
Group counselling 2 h/month
Continuing education program 2 h/month
Workload Group 3: Additional Activities Activity standard
Number of sta per
additional activity
varied per facility
Disease Surveillance 1 h/month
Supervision of staff 1 h/day
Staff scheduling 1 h/week
Mentoring of students 1 h/week
Management meetings 2 h/month
Supervisor’s monthly reports 1 h/month
Performance evaluation 2 h/year
Nursing audit 2 h/month
Committee work 3 h/month
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
recognizing the importance of BHWs, through relevant
short training, supervision, and provision of equipment,
is a critical opportunity to achieve UHC [30].
Key policy changes recommended bythestudy
Based on the results, the following recommendations
were proposed:
1. Review of service packages at the primary care
levels. e results recorded different services at the
same levels of facilities despite the existence of a pre-
scribed service delivery model with key services to be
offered. In addition, some facilities rated themselves
differently compared to the rating in the master facil-
ity list of the country. ere is a need to reclassify
facilities according to their capacities at various levels
of the health system. Finally, to guide the catchment
population, lists of services under the mandate of the
facility to provide should be published publicly.
2. Redistribution of stang based on the workloads
for particular facilities. ere were instances, where
some facilities had more staff with less workload,
while others had high workloads with less staff within
the province, LGU and facility levels. Staff redistri-
bution using population health trends from highly
staffed facilities within the LGUs and provinces
under the same jurisdiction or health care provider
network can be a rational approach to balance work-
loads.
3. Review of implications of donor funded programs
on stang. It was noted that the medical technolo-
gists hired by partners for TB programmes only
conducted TB related activities. Because of this, cli-
ents who needed tests for various conditions were
referred to other facilities. is is not a sustainable
practice given funding cycles of projects, results in
underutilization of trained health professionals, and
limits accessibility to key health services. is prac-
tice should be examined, and WISN results should
be used to guide decision making regarding all staff
deployed in the facilities regardless of the employer.
4. Revision of scopes of practice and job descriptions.
It was found that most cadres informally undertake
tasks that originally are not part of their training or
tasks that have been shifted from another cadre. is
calls for revision of scopes of practice and creation
of new cadres, such as those at the assistant level.
In addition, a task shifting and task sharing policy
should be developed to formalize the shifting and
Table 6 WISN calculated staffing requirements for midwives in
barangay health stations
Facility Existing sta WISN
calculated
sta
Dierence WISN ratio
BHS11 2 − 1 0.50
BHS22 1 1 2.00
BHS 31 1 0 1.00
BHS 41 1 0 1.00
BHS 51 2 − 1 0.50
BHS 61 2 − 1 0.50
BHS 72 1 1 2.00
BHS 81 1 0 1.00
BHS 92 2 0 1.00
BHS 10 2 2 0 1.00
BHS 11 1 1 0 1.00
BHS 12 3 3 0 1.00
BHS 13 1 1 0 1.00
BHS 14 1 1 0 1.00
BHS15 1 1 0 1.00
BHS16 1 2 − 1 0.50
BHS17 1 2 − 1 0.50
BHS18 1 2 − 1 0.50
BHS19 2 2 0 1.00
BHS20 2 2 0 1.00
BHS21 2 1 1 2.00
BHS 22 2 1 1 2.00
BHS 23 2 2 0 1.00
BHS 24 2 2 0 1.00
BHS25 5 2 3 2.50
BHS26 2 1 1 2.00
BHS27 2 1 1 2.00
BHS28 2 1 1 2.00
BHS29 2 1 1 2.00
BHS30 2 1 1 2.00
BHS31 2 1 1 2.00
BHS32 1 1 0 1.00
BHS33 1 1 0 1.00
BHS34 1 1 0 1.00
BHS35 1 1 0 1.00
BHS36 1 1 0 1.00
BHS37 1 1 0 1.00
BHS38 2 1 1 2.00
BHS39 1 2 − 1 0.50
BHS40 1 1 0 1.00
BHS41 1 1 0 1.00
BHS42 2 2 0 1.00
BHS43 1 1 0 1.00
BHS44 2 1 1 2.00
BHS45 1 1 0 1.00
BHS46 1 1 0 1.00
BHS47 2 1 1 2.00
BHS48 1 1 0 1.00
BHS49 1 2 − 1 0.50
Table 6 (continued)
Most BHS have only midwives supervising BHWs who are not part of the
professionalized workforce
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
Table 7 WISN Results for the Four Cadres in RHUs/CHOs
Facility Cadre Existing
sta WISN
calculated
sta
Dierence WISN ratio
RHU1Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Nurse(OP) 1 1 0 1.00
RHU2Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Nurse(OP) 1 2 − 1 0.50
Midwife 1 1 0 1.00
RHU3Med. Tech 2 1 1 2.00
Physician 1 2 − 1 0.50
Nurse(OP) 3 4 − 1 0.75
RHU4Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Nurse(OP) 3 1 2 3.00
RHU5Med. Tech 3 2 1 1.50
Physician 2 8 − 6 0.25
Midwife 5 3 2 1.67
Nurse(OP) 5 8 − 3 0.63
RHU6Med. Tech 1 1 0 1.00
Physician 1 2 − 1 0.50
Midwife 3 2 1 1.50
Nurse(OP) 4 1 3 4.00
RHU7Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Midwife 12 3 9 4.00
Nurse(OP) 8 2 6 4.00
RHU8Med. Tech 1 1 0 1.00
Physician 1 2 − 1 0.50
Midwife 2 2 0 1.00
Nurse(OP) 2 3 − 1 0.67
RHU9Med. Tech 3 2 1 1.50
Physician 4 2 2 2.00
Midwife 7 3 4 2.33
Nurse(OP) 6 7 − 1 0.86
RHU10 Med. Tech 1 1 0 1.00
Physician 1 5 − 4 0.20
Midwife 1 1 0 1.00
Nurse(OP) 3 6 − 3 0.50
RHU11 Med. Tech 1 1 0 1.00
Physician 3 4 − 1 0.75
Midwife 8 5 3 1.60
Nurse(OP) 5 8 − 3 0.63
RHU12 Med. Tech 2 1 1 2.00
Physician 2 2 0 1.00
Midwife 14 4 10 3.50
RHU13 Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Midwife 8 1 7 8.00
Nurse(OP) 2 2 0 1.00
Table 7 (continued)
Facility Cadre Existing
sta WISN
calculated
sta
Dierence WISN ratio
RHU14 Med. Tech 2 3 − 1 0.67
Nurse(OP) 14 3 11 4.67
RHU15 Med. Tech 1 1 0 1.00
Physician 1 3 − 2 0.33
Midwife 8 5 3 1.60
Nurse(OP) 7 1 6 7.00
RHU16 Physician 1 1 0 1.00
Midwife 3 2 1 1.50
Nurse(OP) 13 2 11 6.50
RHU17 Midwife 4 2 2 2.00
RHU18 Nurse(OP) 2 2 0 1.00
RHU19 Med. Tech 3 1 2 3.00
Physician 1 1 0 1.00
Midwife 3 2 1 1.50
Nurse(OP) 1 1 0 1.00
RHU20 Physician 1 1 0 1.00
Midwife 4 1 3 4.00
Nurse(OP) 9 2 7 4.50
RHU21 Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Midwife 7 6 1 1.17
Nurse(OP) 8 4 4 2.00
RHU22 Med. Tech 1 1 0 1.00
Physician 1 2 − 1 0.50
Midwife 6 4 2 1.50
Nurse(OP) 5 2 3 2.50
RHU23 Midwife 1 1 0 1.00
Nurse(OP) 1 1 0 1.00
RHU24 Physician 1 2 − 1 0.50
Midwife 1 3 − 2 0.33
Nurse(OP) 1 4 − 3 0.25
RHU25 Physician 1 2 − 1 0.50
Midwife 8 5 3 1.60
Nurse(OP) 1 4 − 3 0.25
RHU26 Physician 1 2 − 1 0.50
Midwife 1 5 − 4 0.20
Nurse(OP) 1 5 − 4 0.20
RHU27 Med. Tech 2 2 0 1.00
Physician 1 2 − 1 0.50
Midwife 16 12 4 1.33
Nurse(OP) 13 4 9 3.25
RHU28 Med. Tech 3 6 − 3 0.50
Physician 3 4 − 1 0.75
Nurse(OP) 6 5 1 1.20
RHU29 Med. Tech 3 1 2 3.00
Physician 1 4 − 3 0.25
Nurse(OP) 3 4 − 1 0.75
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
sharing practices already being undertaken, ensuring
adequate training and supervision are emphasised.
5. Development of referral guidelines. ere were
instances, where referrals were made to a cadre of the
same competency at a higher level of care. e study
found that often services meant to be conducted at
the BHSs or RHUs were referred to level one hospi-
tals. To curb unnecessary referrals to the next level of
care, referral guidelines should be developed.
6. Improvement in data collection and investing in
health information systems. e need for improved
data collection and record keeping was emphasised.
Although many of the facilities used the same tools,
the modes of reporting differed and data on some
key indicators were missing in the final reporting
tool. e DOH and health facilities should invest
in strengthening collection and storage systems
for health services and HRH data, as well as linking
these systems through an interoperable health man-
agement information system to ensure availability of
quality data in real time.
7. Strengthening supervision and management
of resources. e study found there was a need to
strengthen the leadership capacities of the health
workers who had additional activities related super-
vision of resources. Without these skills, it is difficult
for the health workers tasked with the roles to super-
vise and manage the resources (staff, financial, equip-
ment and infrastructure) effectively. Use of non-face-
to-face modalities for training may be optimized to
increase available working time and lessen disruption
in health services. Supportive supervision of staff can
also promote efficiency gains by minimizing time
allotted for repetitive training.
Best practices forcountries wanting toimplement
andintegrate WISN intoHRH management practices
In the Philippines, WISN was not implemented as a
one-time activity, but implemented with the intention of
long-term integration into HRH management. Several
best practices were identified to facilitate this integration:
1. Development of a governance structure that includes
representation of the high-level officials and mem-
bers of the DOH both for a regular standing commit-
tee and for the steering committee,
2. Having a dedicated core team from the HRH depart-
ment, who conduct all planning, lead implementa-
tion of WISN, analysis of results, and work closely
with the Regional Health Offices.
3. Development of a sustainability strategy and plan
to guide needed policy modifications to reflect the
needs and outputs of WISN, promote domestic
resource mobilization to carry out the approach and
overall planning for application of results.
4. Creating a culture of continuous learning. For exam-
ple, the Philippines developed an online WISN ori-
entation course for all HR management officers and
members of WISN committees, new and old, as part
of continuous professional development through an
eLearning platform.
Table 7 (continued)
Facility Cadre Existing
sta WISN
calculated
sta
Dierence WISN ratio
RHU30 Med. Tech 3 3 0 1.00
Physician 1 5 − 4 0.20
Nurse(OP) 5 2 3 2.50
RHU31 Med. Tech 2 3 − 1 0.67
Physician 2 4 − 2 0.50
Nurse(OP) 3 2 1 1.50
RHU32 Med. Tech 1 2 − 1 0.50
Physician 5 6 − 1 0.83
Nurse(OP) 3 5 − 2 0.60
RHU33 Med. Tech 1 1 0 1.00
Physician 1 2 − 1 0.50
Midwife 18 5 13 3.60
Nurse(OP) 1 1 0 1.00
RHU34 Midwife 24 4 20.06 6.09
RHU35 Med. Tech 2 3 − 1 0.67
Physician 1 2 − 1 0.50
Midwife 5 1 4 5.00
Nurse(OP) 3 3 0 1.00
RHU36 Med. Tech 1 1 0 1.00
Physician 2 3 − 1 0.67
Midwife 5 7 − 2 0.71
Nurse(OP) 2 2 0 1.00
RHU37 Physician 1 3 − 2 0.33
Nurse(OP) 3 2 1 1.50
RHU38 Physician 1 1 0 1.00
Nurse(OP) 2 1 1 2.00
RHU39 Med. Tech 1 3 − 2 0.33
Physician 1 2 − 1 0.50
Midwife 8 5 3 1.60
Nurse(OP) 2 2 0 1.00
RHU40 Med. Tech 1 1 0 1.00
Physician 1 1 0 1.00
Nurse(OP) 5 2 3 2.50
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
7%
19%
10% 7% 6%
10%
42%
20%
4%
12%
0%
8%
5%
4%
4%
13%
17%
8%
26%
18%
3%
6%
10% 15%
2%
67%
8%
48% 44%
57%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
RHU MED TECH RHU PHYSICIANRHU NURSERHU MIDWIFEBHS MIDWIFE
Extremely low
Very low
Low
Normal
High
Very high
Fig. 1 Summary of workload pressure by cadre and facility
Fig. 2 Summary of workload analysis by cadre and facility
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
5. Development of a basic toolkit for training, carrying
out WISN and analysing results, relevant and unique
to the country.
Conclusion
ere is a need for the Philippine health system, both
through the DOH and the local government to effi-
ciently optimize the available health workers for PHC.
e results provide evidence for staffing requirements
in the primary care facilities by defining the minimum
and maximum numbers based on workloads, scope of
practice and time taken to undertake specific tasks at
the barangay health stations, rural health units and city
health offices. WISN results can be integrated into the
human resources for health management systems.
Abbreviations
AWT : Available Working Time; BHS: Barangay Health Station; BHW: Barangay
Health Worker; CHO: City Health Office; DOH: Department of Health; EWG:
Expert Working Group; HHRDB: Health Human Resources Development
Bureau; HRH: Human Resources for Health; HRH2030: Human Resources for
Health in 2030 Program; HRO: Human Resource Officer; IRR: Implementing
Rules and Regulations; LGU: Local Government Units; OP: Outpatient; RHU:
Rural Health Unit; TTF: Technical Task Force; UHC: Universal Health Care; USAID:
United States Agency for International Development; WISN: Workload Indica-
tors of Staffing Need; WHO: World Health Organization.
Acknowledgements
The development of this report is the result of concerted efforts from various
individuals and institutions. The process involved an inclusive and consulta-
tive process with several stakeholders in the health sector at the national,
regional, and local government levels. We thank the Department of the Health
of the Philippines Undersecretary Dr Mario Villaverde and the Health Human
Resources Development Bureau for their commitment and leadership to this
process, namely: Charisse Esperanza, Grace Obedoza, Maria Yzlette Lising,
April Delos Santos, Madelyne Mabini, Grace Fernando, Angeli Loren Caguioa,
Lily Marlyn Briones, Kaycee Manuel and Dr Christine Joan Co. Special thanks
goes to the United States Agency for International Development Philippines,
specifically Dr Yolanda Oliveros, for inputs, technical guidance and over-
sight throughout the process; as well as the HRH2030 Program/Chemonics
International, Wanda Jaskiewicz, Dr Fely Marilyn Lorenzo, Dr Annabelle
Borromeo, Matthew Kuehl, and Mark Darren Cacanindin, for the technical
and logistical support during all the phases of implementation. In addition,
acknowledgement and appreciation must be made to those that participated
throughout the process: the regional health offices and local government
units and staff of the nine regions, especially the health facilities and health
workers visited for their cooperation; members of the Steering Committee for
their guidance and valuable inputs throughout the WISN process; members
of the technical task force committees from DOH central and regional offices;
members of the expert working group committees for their professionalism,
tireless efforts and commitment in determining workload components and
service activities that guided the data collection process; all data coordinators,
collectors and compilers from the Alliance for Improving Health Outcomes,
Inc; and the World Health Organization’s Khassoum Diallo, Teena Kunjumen,
Indrajit Hazarika, and Florante Trinidad for their collaboration, support and
feedback throughout the process. Finally, we thank HRH2030/Chemonics
technical reviewers Dr Grace Namaganda and Rachel Deussom.
About this supplement
This article has been published as part of Human Resources for Health Volume
19, Supplement 1 2021: Countries’ experiences on implementing WISN meth-
odology for health workforce planning and estimation. The full contents of the
supplement are available at https:// human- resou rces- health. biome dcent ral.
com/ artic les/ suppl ements/ volume- 19- suppl ement-1.
Authors’ contributions
MO and LM conceptualized the idea and discussed it with KR and MRP who
approved the concept. MRP, MGA, MO and LM conducted the field visits and
supervised the data collection. MO participated in all the phases of the WISN
study. MO, LM, KR, MRP and MGA analyzed the data and provided a draft
report that was reviewed by LM and KR. MGA, MRP, KR, MO, LM all reviewed,
revised and produced this final manuscript. All authors read and approved the
final manuscript.
Funding
The funding was provided by the United States Agency for International
Development (USAID) through the Human Resources for Health 2030 Philip-
pines Program implemented by Chemonics International.
Availability of data and materials
Data is available upon request to the Health Human Resources Development
Bureau at psd.hhrdb@doh.gov.ph.
Declarations
Ethics approval and consent to participate
DOH endorsed the WISN methodology for pilot implementation in the coun-
try. DOH provided elaborate explanation on the need for the study to all the
Table 8 Proposed staffing levels as defined by WISN method for primary care facilities
BHS
Health worker type Average of minimum stang requirement Average of maximum
stang requirement
Midwife 1 2
Nurse 2 3
RHU
Health worker type Average of minimum stang requirement Average of maximum
stang requirement
Physician 1 2
Nurse 2 4
Midwife 2 4
Med Tech 1 2
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Aytonaetal. Hum Resour Health 2022, 19(Suppl 1):129
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participating health facilities and the health workers. All participants signed
letters of consent after the explanations and were assured of their confidenti-
ality and anonymity during data collection and reporting.
Consent for publication
DOH and Chemonics International authorized the publication of this
manuscript.
Competing interests
All authors declare no competing interests.
Author details
1 Department of Health, Health Human Resources and Development Bureau,
Manila, Philippines. 2 Chemonics International, Washington, DC, United States
of America. 3 World Health Organization, Port Moresby, Papua New Guinea.
Received: 2 October 2021 Accepted: 8 October 2021
Published: 28 January 2022
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