Page 45 - MOH Supply and Needs-Based Requirement Hyperlink 02032021

37 EXTENDED EXECUTIVE SUMMARY

Table 13 and Table 14 show data source by model parameter and profession after a thorough
data validation process. The data validation process is vital to sift through various data obtained
from multiple sources as mentioned. During this process, stakeholder was consulted to
assist in identifying the most suitable data to be used in the supply and requirement model.

If data is unavailable, inputs from expert opinions were used where Delphi method was applied
in this study to obtain experts’ opinion and consensus on the unavailable data. Following the
Delphi method, engagement with clinical specialists, consultants, experienced health care
professionals from relevant disciplines and sub-specialities was carried out in one-to-one
sessions to obtain relevant data e.g. levels of service, including time and frequency for services
offered. The one-to-one sessions with clinical specialists and consultants also facilitated
improvements in the data collection template. For example, the pathology service data
collection template was improved by input gained from the initial two sessions with pathologists
from Hospital Kuala Lumpur. The improvised template enabled data collection for relevant
diagnostic tests and tests for differential diagnosis, which may have been missed otherwise.

Subsequently, head of services, who were mostly consultants with sub-speciality training,
convened to vet through the initial input data obtained through one-on-one engagement.
This enabled discussions among consultants from various disciplines or sub-speciality to verify
concerns where necessary and ultimately achieved consensus on the data that should be used.

Table 13: Main Data Source by Parameter and Profession in Supply Model

Supply Main Data Source
Models
Parameter Doctors Dentists Pharmacists Nurses AMOs
Student Number of Newly Employed HRH: Human Number Number
Intake Resource Division MOH of Newly of Newly
(Local) Registered: Regis-tered:
Malaysian Medical
Nursing Board Assistant
Board (MAB)
Student Expert Opinion from Boards / Councils and local university representative
Dropout
Rate
Foreign- Number of newly employed foreign trained Number of
trained graduate: Human Resource Division MOH newly registered
Graduates nurses overseas
graduate:
Malaysian
Nursing Board
Existing Number of HRH (total): Health Informatics Centre (2008-2017)
Stock Number of HRH (by age, gender): Councils / Boards
Attrition Resignation Rate: Human Resource Division MOH Resignation Death Rate:
Rate Death Rate: DOSM Rate: Malaysian DOSM
Retirement Rate: Expert Opinion Nursing Board Retirement
Death Rate: Rate: Expert
DOSM Opinion
Retirement
Rate: Expert
Opinion
Percentage Number of HRH in direct patient care: Staffing and distribution of staffs by facilities,
of Direct state (MOH Human Resource Division, 2014)
Patient
Care HRH
Pregnancy Number of HRH on study leave: Training Management Division MOH
of HRH on
study leave

SUPPLY AND NEEDS-BASED REQUIREMENT PROJECTIONS OF MALAYSIAN HUMAN
RESOURCES FOR HEALTH USING SYSTEM DYNAMICS APPROACH 2016 - 2030