Cardiac Care Performance Report: Acute Coronary Care

This report is intended only for the use of the individual entity to which it is addressed and may contain information that is privileged, confidential, and exempt from disclosure.

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Disclaimer:

The content of this report is based on information mainly gathered from published secondary sources. Although best efforts have been made to ensure that the information and data contained here is reliable, no representations are made as to its completeness, timeliness or quality. Majority of data originated from the Ministry of Health institutions hence generalizability is limited to the population of which they represent. Anyone may reproduce, publish or otherwise use the content of this report as the concepts and information herein are already in the public domain. However, acknowledgement to Malaysian Healthcare Performance Unit, Ministry of Health Malaysia would be appreciated.

Suggested citation is: Malaysia Acute Coronary Care Performance Report 2016 (2017) Malaysian Healthcare Performance Unit, Ministry of Health Malaysia, Kuala Lumpur.

Acknowledgement of Publication:

We would like to thank the Director General of Health Malaysia, for his permission to publish this article.

Published by:

Malaysian Healthcare Performance Unit 1st Floor, MMA House, 124 Jalan Pahang, 53000 Kuala Lumpur, Malaysia. Tel : (603) 40443060 Fax : (603) 40443080 Email : [email protected]


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FOREWORD 1

Needless to say that Cardiovascular disease is one of our top priority in term of burden of disease as well as the impact it can have on both quality of life as well as economic impact on the family and the nation. Hence it is imperative for us as custodians of health for the nation to start performance assessment of our health services in this area.

This proof of concept is preliminary evidence that good team effort of clinicians, public health specialists, data holders and MHP can result in something meaningful for future improvement.

Although as a starter this report is limited to Acute Coronary care performance, I anticipate that eventually it will evolve to be more holistic in nature spanning the entire subsystem for Cardiovascular Disease Care, including both natural as well as clinical pathway where possible. This means that it should cover performance from health promotion, preventive, curative right up to rehabilitative care. The idea is not only must we go beyond average level of provision of care and the ensuing outcomes, but also to narrow the unfavourable variations and improve equity.

My advice is for all stakeholders to start using this and future reports for their policy and decision making with the common aim in mind for better care and better outcome for our rakyat!!

YBhg Datuk Dr Noor Hisham Abdullah


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FOREWORD 2

MHP is the DG’s aspiration – as a mean to have a governance tool for monitoring and evaluating performance of the health system or subsystems.

2016 was MHP third year and this report is their second attempt at assessing a selected subsystem (disease-specific) performance assessment, their first being the cardiovascular care performance report.

The attempt to introduce performance assessment using scorecards is rather new in the nation’s health arena – people need to adapt to it and soon when they find it useful the work will become less challenging.

I must acknowledge that MHP have been successful in engaging the various stakeholders and data holders in converting readily available data into actionable information.

However there will always be room for future improvement, building on lessons learnt from this first report. I urge all the pertinent players to make use of the report.

Again I would like to remind that this report belongs to us; it is our assessment of our system, and thus we welcome any constructive feedbacks or comments.

Lastly I would like to thank all those who have contributed in many ways to make our DG’s aspiration a reality.

YBhg Datuk Dr Shahnaz Murad

ACKNOWLEDGEMENTS


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We wish to thank YBhg. Datuk Dr Noor Hisham bin Abdullah, Director General of Health and Datuk Dr Shahnaz binti Murad, the Deputy Director General of Health (Research & Technical Support) for their guidance. We also sincerely thank the Director of National Clinical Research Centre, Dr Goh Pik Pin for her strong support. Acknowledgement of contribution goes to all state health directors and other stakeholders listed below:-

Y.Bhg. Datuk Dr Lokman Hakim b. Sulaiman Timbalan Ketua Pengarah Kesihatan (Kesihatan Awam) Kementerian Kesihatan Malaysia

Y.Bhg. Dato' Dr Hj Azman bin Abu Bakar Pengarah Bahagian Perkembangan Perubatan Kementerian Kesihatan Malaysia

Dr Md. Khadzir bin Sheikh Hj. Ahmad Timbalan Pengarah Pusat Informatik Kesihatan (PIK) Kementerian Kesihatan Malaysia

External reviewer

Professor Niek Klazinga

Health Care Quality Indicator Project Directorate for Employment, Label, and Social Affair (OECD)

Contributors

Dr. Jamilah Hashim Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Sarawak

Datuk Dr. Christina Rundi Pengarah Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Sabah

Dr. Sakinah Alwi Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Perlis

Dato’ Dr. Norhizan Ismail Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Kedah

Dato’ Dr. Hj. Ahmad Razin Dato’ Hj. Ahmad Mahir Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Kelantan

Dr. Saifur Rahman Muhammad Wakil Pengarah Kesihatan Negeri Jabatan Kesihatan Negeri Terengganu

Dr Julian Tey Hock Chuan Wakil Pengarah Kesihatan Negeri

Jabatan Kesihatan Negeri Melaka

Dr. Nur Zulaiha Wakil Pengarah Kesihatan Negeri Jabatan Kesihatan Pulau Pinang

Dato' Dr Omar bin Ismail Pakar Perunding Kanan Kardiologi & Ketua Jabatan Kardiologi, Hospital Pulau Pinang

Dato' Dr. Mohd Hamzah bin Kamarulzaman Pakar Perunding Kanan Kardiotorasik Hospital Serdang

Dr. Abdul Kahar Bin Abdul Ghapar Pakar Perunding Kanan Kardiologi & Ketua Jabatan Kardiologi, Hospital Serdang

Dr G. R. Letchuman Ramanathan Pakar Perunding Kanan Perubatan & Ketua Jabatan Perubatan,


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Hospital Raja Permaisuri Bainun, Ipoh

Dr. Rozlan B Ishak Timbalan Pengarah, Cawangan Penyakit Tidak Berjangkit Bahagian Kawalan Penyakit

Dr. Fatanah Binti Ismail Ketua Penolong Pengarah Kanan, Cawangan Kesihatan Primer Bahagian Pembangunan Kesihatan Keluarga

Dr Paa Mohamed Nazir Bin Abdul Rahman Pakar Perubatan Kesihatan Awam, Cawangan Kualiti Penjagaan Perubatan Bahagian Perkembangan Perubatan

Dr. Muhammad Fadhli Bin MohdYusoff Pakar Perubatan Kesihatan Awam, Pusat Penyelidikan Penyakit Tidak Berjangkit, Institut Kesihatan Umum

Dr. Rotina Binti Abu Bakar Ketua Penolong Pengarah Kanan, Bahagian Kawalan Penyakit

Datin Dr. Siti Haniza Mahmud Pegawai Penyelidik,

Institut Penyelidikan Sistem Kesihatan

Dr Nur Athirah Imran Penolong Pengarah Kanan Pusat Informatik Kesihatan

Dr Foo Chee Yong Pegawai Perubatan, Healthcare Statistics Unit, Pusat Penyelidikan Klinikal Kebangsaan

Dr Chin May Chien Pegawai Perubatan, Healthcare Statistics Unit, Pusat Penyelidikan Klinikal Kebangsaan

Matron Pn Jalalah Mohamad Penolong Pengarah Bahagian Kejururawatan

Puan Viola Michael Pegawai Dietetik, Unit NCD/CVS Diabetes, Bahagian Kawalan Penyakit

Ms. Gunavathy Selvaraj NCVD Registry National Heart Association Malaysia

Malaysian Healthcare Performance Unit

Team lead:

Dr. Jamaiyah Haniff

Project lead:

Dr Mohd Kamarulariffin Kamarudin

Members:

Dr Nor Aini Abdullah Dr Theyveeka Selvy Rajoo Dr Ariza Zakaria Cik Nuramalina Abdullah

Contents


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List of tables ..........................................................................................................................................................................i

List of figures ...................................................................................................................................................................... ii

List of abbreviations ........................................................................................................................................................ ii

EXECUTIVE SUMMARY ................................................................................................................................................. iv

ACUTE CORONARY CARE PERFORMANCE SCORECARD ................................................................................. v

Chapter 1 Introduction ................................................................................................................................................... 1

Background .................................................................................................................................................................... 2

Report Objectives ........................................................................................................................................................ 2

Methodology & Analysis ........................................................................................................................................... 3

Chapter 2 Malaysian Coronary Heart Disease Profiling ................................................................................... 8

Disease Demographics ............................................................................................................................................... 9

Coronary Heart Disease Risk Factors Prevalence ....................................................................................... 11

Chapter 3 Cardiac Care Performance Indicators .............................................................................................. 14

Where we stand ......................................................................................................................................................... 15

Human Resources & Facility ................................................................................................................................ 16

Process of Care ........................................................................................................................................................... 19

Health Outcome ......................................................................................................................................................... 22

Admission Rate ..................................................................................................................................................... 22

30-day Case Fatality after Acute Myocardial Infarction ...................................................................... 24

Conclusion ................................................................................................................................................................... 27

Recommendations .................................................................................................................................................... 28

Bibliography .................................................................................................................................................................... 29

GLOSSARY ......................................................................................................................................................................... 30

APPENDIX ......................................................................................................................................................................... 32

LIST OF TABLES


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Table 1: Data availability, coverage, and levels of disaggregation of selected performance indicators ............................................................................................................................................................................. 5 Table 2: Cardiovascular disease (CVD) risk factor prevalence, 2015. .................................................... 12 Table 3: State variation of CVD risk factor prevalence, 2015. .................................................................... 12 Table 4: Number & density of cardiologist, cardiothoracic surgeon and cardiac catheterization laboratory, 2013. ........................................................................................................................................................... 16 Table 5: State variation of number & density (per 1 000 000 population) of cardiologist, cardiothoracic surgeon and cardiac catheterization laboratory, 2013. .................................................. 18 Table 6: Percentage of STEMI patients who received timely fibrinolysis therapy and the median time-to-intervention, 2013. ....................................................................................................................................... 20 Table 7: Hospital admission rate (per 100 000 population) for acute coronary syndrome (ACS), 2013. ................................................................................................................................................................................... 23 Table 8: State variation of hospital admission rate for ACS (per 100 000 population), 2013. ...... 23 Table 9: 30-day case fatality rate for ACS patients, 2013 ............................................................................ 26

LIST OF FIGURES

Figure 1: Breakdown of cases by age groups, 2013 .......................................................................................... 9 Figure 2: Breakdown of cases by ethnicity, 2013 .............................................................................................. 9 Figure 3: Age-specific prevalence of ACS, 2010-2013 .................................................................................. 10 Figure 4: National hypertension prevalence progression 18+, 2006-2015 ......................................... 11 Figure 5: National hypercholesterolemia prevalence progression 18+, 2006-2015 ....................... 11 Figure 6: National diabetes prevalence progression 18+, 2006-2015 ................................................... 11 Figure 7: National daily smoker prevalence progression by gender 15+, 2006-2015 .................... 11 Figure 8: Malaysian rankings of selected performance indicators .......................................................... 15 Figure 9: Proportion of cardiologist (public vs private) and the total cardiologist density by state, 2013 ........................................................................................................................................................................ 17 Figure 10: Proportion of cardiothoracic surgeon (public vs private) and the total cardiothoracic surgeon by state, 2013 ................................................................................................................................................ 17 Figure 11: Median DTN time 2006-2013 ............................................................................................................ 19 Figure 12: Median DTB time 2006-2013 ............................................................................................................ 19 Figure 13: Rate of fibrinolysis, 2006-2013 ........................................................................................................ 20 Figure 14: Rate of primary PCI, 2006-2013 ...................................................................................................... 20 Figure 15: State variation of door-to-needle time achievement ............................................................... 21 Figure 16: Hospital admission rate for STEMI ................................................................................................. 22 Figure 17: Hospital admission rate for NSTEMI .............................................................................................. 22 Figure 18: Hospital admission rate for unstable angina .............................................................................. 22 Figure 19: 30-day case fatality rate after STEMI, 2006-2013 .................................................................... 24 Figure 20: 30-day case fatality rate after AMI, 2006-2013 ......................................................................... 24 Figure 21: State variation of in-hospital NSTEMI/UA case fatality rate, 2013 vs 2014 .................. 25 Figure 22: State variation of in-hospital STEMI case fatality rate, 2013 vs 2014 .............................. 25

LIST OF ABBREVIATIONS


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AAR Average Annual Rate of Change

ACS Acute Coronary Syndrome

AMI Acute Myocardial Infarction

BMI Body Mass Index

BP Blood Pressure

CHD Coronary Heart Disease

CHF Congestive Heart Failure

CPG Clinical Practice Guideline

CKPP Clinical Performance Surveillance Unit

CVD Cardiovascular Disease

DTB Door-to-balloon Time

DM Diabetes Mellitus

DTN Door-to-needle Time

ECG Electrocardiogram

ED Emergency Department

GP General Practitioner

KOSPEN Komuniti Perkasa Negara

LDL Low Density Lipoprotein

NCD Non-communicable Disease

NCVD National Cardiovascular Database

NDR National Diabetes Registry

NHEWS National Health Care Establishment and Workforce Statistics

NHMS National Health and Morbidity Survey

NSTEMI Non-ST-elevation Myocardial Infarction

OECD Organization for Economic Cooperation and Development

PCI Percutaneous Coronary Intervention

SMRP Sistem Maklumat Rawatan Perubatan

STEMI ST-elevation Myocardial Infarction

UA Unstable Angina

WHO World Health Organization


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EXECUTIVE SUMMARY

Malaysian cardiovascular scenarios

National health and Morbidity Survey (NHMS) shows significant increase in the prevalence of

diabetes and hypercholesterolemia over the last 10 years period, with high proportion are made up

of undiagnosed cases. This phenomenon will likely contribute to the increasing burden of NCDs in

Malaysia.

Cigarette smoking among the male population is a concern. The prevalence of Malaysian male

smokers is almost 2-fold of the prevalence reported in most OECD countries. The high prevalence of

smoking seems to correlate with high mortality secondary to cardiovascular disease.

In addition, for every 100 cases of AMI admitted to our hospitals, close to 10% succumbed to death

within 30-days, a rate that is higher than an average OECD country.

Resources and facilities

We observed a positive growth in human resources related to cardiology and cardiothoracic services

from 2009 to 2013. The number of cardiologist and cardiothoracic surgeon are increasing at a rate of

9% and 5.4% respectively.

However, there is evidence of uneven distribution of cardiologists and cardiothoracic surgeons

reported between sectors and states with majority based in private sector.

More cardiac catheterization laboratories are available in private sector compared to public sector.

Some states like Melaka, Negeri Sembilan and Perlis have no such facility in public hospitals at all.

Process of care

More than half of eligible patients did not receive timely PCI.

Recent data shows about 94% of cases achieved fibrinolysis therapy initiation within 30 minutes of

arrival to Emergency Department.

Outcome

Overall increase in acute coronary syndrome hospital admission reflects the growing burden of

disease attributable to cardiovascular diseases.


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ACUTE CORONARY CARE PERFORMANCE SCORECARD

Year Achievement AAR (%)

AAR

period Standard

Input

4.3. Cardiologist per 1 000 000 populationPP

2013 8 - - -

4.4. Cardio-thoracic surgeon per 1 000 000 populationPP

2013 3 - - -

4.5. Cardiologist public : private ratio 2013 1 : 4 - - -

4.6. Cardiothoracic surgeon public : private ratio

2013 1 : 2 - - -

4.7. Ratio of public : private with cardiac catheterization laboratory

2014 1 : 4 - - -

Process of care

6.1. % of fibrinolysis with door-to-needle time < 30 minutesP

2014 94% ↓0.3 2013-2014 >85%1

6.2. Median door-to-needle-time (minute)PP

2013 49 - - <302

6.3. Median door-to-balloon time (minute)PP

2013 104 - - <902

6.4. % of STEMI not given fibrinolytic therapy due to missed thrombolysis timePP

2013 11% ↓2.4 2006-2013 -

6.5. Rate of fibrinolytic therapyPP 2013 74% ↑0.8 2006-2013 -

6.6. Rate of primary PCIPP 2013 10% ↑3.5 2006-2010 -

Outcome (Admission)

7.1. Admission rate for UA (per 100 000)PP

2013 112 ↓4.8 2010-2013 -

7.2. Admission rate for STEMI (per 100 000)PP

2013 20 ↑12 2010-2013 -

7.3. Admission rate for NSTEMI (per 100 000)PP

2013 20 ↑36 2010-2013 -

P Public sector only

PP Public and private sector

1 Cawangan Kualiti Penjagaan Perubatan 2 Clinical Practice Guidelines, Management of Acute ST Segment Elevation Myocardial Infarction 2014


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Year Achievement AAR

(%) AAR period Standard

Outcome (Mortality)

9.1. 30-day case fatality after STEMIPP 2013 11.4% ↓8.5 2006-2013 -

9.2. 30-day case fatality after AMI

(STEMI & NSTEMI)PP 2013 10.9% ↓11 2006-2013

9.3. In-hospital STEMI case fatality

ratePP 2013 5.9% ↓8.7 2008-2013 ≤15%

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9.4. In-hospital UA/NSTEMI case fatality

ratePP 2013 3.3% ↓16 2008-2013 ≤10%

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Impact

2.1. Prevalence of hypertension 2015 30.3% ↓0.7 2006-2015 -

2.2. Prevalence of hypercholesterolemia 2015 47.7% ↑9.7 2006-2015 -

2.3. Prevalence of diabetes 2015 17.5% ↑4.7 2006-2015 -

2.4. Prevalence of obesity 2015 30.6% ↑9.1 2006-2015 -

2.5. Prevalence of daily tobacco smoker,

male 2015 38.8% ↑3.9 2011-2015 -


female 2015 1.1% →0.0 2011-2015 -

P Public sector only

PP Public and private sector


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CHAPTER 1 INTRODUCTION


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BACKGROUND

National Health and Morbidity (NHMS) survey, a series of community-based survey on the pattern of

common health problems, health service utilisation and health expenditure in Malaysia reports a

steady uprising of cardiovascular risk factor prevalence from 1986 to 2015. The latest findings

support the current concerns of increasing disease burden with one in three Malaysians diagnosed

with hypertension; about one in five diagnosed with hypercholesterolemia; and one fifth found to be

suffering from diabetes (Institute for Public Health, 2015) . The high risk factor prevalence is

expected to contribute significantly to the incidence of cardiovascular diseases namely the acute

coronary syndrome (ACS) and stroke.

Health promotion and disease prevention remain the most efficient strategies to reduce burden of

disease. They provide opportunities to curb diseases at earlier stages when they are often more

responsive to treatment. However, the implementation of any preventive programmes or

interventions must be monitored and evaluated on a regular basis to understand the underlying

processes that may have resulted in unintended outcomes.

Many different divisions within the Ministry of Health have been collecting data in various aspect of

health care as part of administrative, academic, clinical and quality improvement work. Malaysian

Healthcare Performance unit (MHPU) was established to transform those various databases into

actionable information as well as to benchmark health performance against best practices locally or

internationally. We aim to identify variation in practices and health outcomes within the health

system in order to promote health care innovation and improvement of the care delivery.

This report is intended to serve as a foundation of a more comprehensive reporting work pertaining

to cardiac care performance in Malaysia. Cardiac care encompasses multitude of cardiovascular

services inclusive of cardiac and thoracic surgical services across all age categories (Ministry of

Health, Cardiothoracic Surgery Services Operational Policy, 2011). This current report focuses only

on performance assessment of acute coronary care before the year 2015 following a framework that

incorporates various health care system and quality domains used by the World Health Organization

WHO (World Health Organization, 2003).

The report consists of three chapters. The first chapter is an introduction to performance

assessment work, the report methodology and analysis. The second chapter describes the

demographic profiling of the population with acute coronary syndrome (ACS) diagnosis. The third

chapter reports statistics concerning the service inputs and resources, the critical aspect of process

of care in adults with acute coronary syndrome and the outcomes.

REPORT OBJECTIVES

1. To describe the magnitude of acute coronary syndrome burden in Malaysia.

2. To describe the performance of acute coronary care based on latest available data.

3. To show the performance trending information

4. To describe variation in performance by state

5. To benchmark performance against OECD countries or other selected comparator countries.

6. To propose strategy to improve Cardiovascular Health care nationwide, aiming to achieve

international standards


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METHODOLOGY & ANALYSIS

We employed disease-based approach to reflect performance across programme and services. The

choice of acute coronary care as the topic is in keeping with the findings of Malaysian Burden of

Disease and Injury study (Ahmad Faudzi Yusoff, Gurpreet Kaur, Mohd Azahadi Omar, & Amal Nasir

Mustafa, 2004) that revealed ischemic heart disease and cerebrovascular disease as the top

contributors to mortality and disability-adjusted life year (DALY) in Malaysia.

Literature search was done on the topic related to quality improvement and healthcare performance

assessment for coronary heart disease using online search engines. The searching was purposive

with priority given to review articles and local studies that mention performance in cardiac care or

its equivalence. A table comprising a list of indicators was constructed and filled along as new

indicators were found and described in the literature during the literature search period. The

indicators were grouped into the domains of input, process, outcome and impact that reflect

Donabedian’s conceptual model of assessing quality in health system (Avedis Donabedian, John R. C.

Wheeler, & Leon Wys, 1982). Each indicator was first deliberated by MHPU team members on the

suitability (relevance in local context) and potential data sources.

Majority of the indicators and their definition were taken verbatim from their respective source

documents. These are the commonly used indicators to describe health system performance

internationally. However, some of the indicators were replaced with an equivalent proxy to

accommodate local data definition and data availability. Corresponding data were synthesised from

published documents and reports; they were then reconstructed into a data frame in an electronic

spread sheet. Majority were published data of aggregate number or rate at either state or national

level. Detailed information on the datasets used and their sources, coverage, and levels of

disaggregation are given in Table 1.

Data cleaning process involved manual tracking of wrongly entered value by at least one other

person using the original source documents as reference. A statistician service was utilised for data

proof-reading and reviewing of mathematical formula and rate calculation. If any discrepancies,

correction will be done on the master spread sheet by the same person who constructed the data

frame.

Analysis largely involved visual analytics; plotting data using column or line graph- looking at the

trend over time or constructing three dimensional scatter plots- assessing the visual correlation. No

adjustment or standardization of rate was attempted.

In this report, performance is described in four ways:

1. Whether or not Malaysia has reached a specific achievement target.

- Health related activities and outcomes are measurable; a target is ideally set to assess

the progress of any implemented strategy in health promotion or intervention.

2. Whether there have been desirable changes in latest achievement compared to the

achievement in previous years.

- Desirable changes are expected trend in achievement based on historical data. An

increasing trend is desirable for positive outcomes while decreasing trend is desirable

for unwanted outcomes.


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3. The average annual rate of change (AAR) of the achievements over a time period ;

- AAR is calculated by taking the geometric mean of the annual percentage difference

between the baseline achievement (beginning value) and the current achievement

(ending value) with the assumption that the achievements have been compounding

discretely over the specified period. The mathematical formula is given by:

AAR = (

)(

)

4. Malaysia achievement in comparison with selected OECD countries and other comparator

countries.

- OECD has an online updated database that conglomerate common statistics from

various member countries in time series. OECD as a benchmark is our attempt to close

the gap so as to achieve the standard enjoyed by developed nations. OECD online

database can be accessed through stats.oecd.org

All indicators along with the data were discussed with and presented to the respective stakeholders

for reconciliation. Improvement and additional work were tailored according to the stakeholders’

suggestions and needs.

Findings are reported using the following symbols and colour codes: ↑ Increased since previous year Desirable change ↓ Decreased since previous year Indicator of concern → Remained the same since previous year Status quo - Missing or unavailable information

A note about making comparisons (limitation):

All indicators are presented in crude measure without adjustment to baseline characteristics or risks. Therefore, comparability of rates between different periods of data collection or regions is limited.

The report findings are based on secondary aggregated data. Degree of ascertainment, duplications, and missing data could not be fully verified.

Majority of data represents only the public institutions and Ministry of Health sector although the interpretations in this report are meant to describe the Malaysian scenarios as whole. Potentially, there are data from other sectors that have yet to be explored by the time this report is published

Due to the nature of this report that used aggregated data from multiple sources, direct causality or longitudinal relationship cannot be assessed and the findings cannot be inferred without estimate adjustment or predictive modelling.


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Table 1: Data availability, coverage, and levels of disaggregation of selected performance indicators

Indicator Time period Coverage Data source Domain

1. Number of Cardiologist 2009-2013 By state

By sector

NHEWS

(Published)

NCVD (Published)

Input

2. Number of Cardiothoracic surgeon 2009-2013 By state

By sector

NHEWS

(Published) Input

3. Cardiologist density per 100 000 population

2009-2013 By state NHEWS

(Published) Input

4. Cardio-thoracic surgeon density per 100 000 population

2009-2013 By state NHEWS

(Published) Input

5. Number of hospital with cardiac catheterization laboratory (ICL)

2012, 2014 By state

By sector

NHEWS

(Published)

NCVD

(Published)

Input

6. % of STEMI undergone fibrinolysis with door-to-needle time < 30 minutes

2013-2014 By state

MOH only

CKPP (Unpublished-data updated until January

2015)

Process of care

7. Median door-to-needle-time (minute) 2006-2013

National aggregate

MOH/MOE only

NCVD

(Published)

Process of

care

8. Median door-to-balloon time (minute) 2006-2013

National aggregate

MOH/MOE only

NCVD

(Published) Process of

care

9. % of STEMI not given fibrinolytic therapy due to missed thrombolysis time

2006-2013

National aggregate

MOH/MOE only

NCVD


care


6

Table 1: Data availability, coverage, and levels of disaggregation of selected performance indicators (continued)

Indicator Time period Coverage Data source Category

10. Rate of fibrinolytic therapy 2006-2013

National aggregate

MOH/MOE only

NCVD


care

11. Rate of primary PCI 2006-2010

National aggregate

MOH/MOE

NCVD


care

12.

Admission rate

for unstable angina

for STEMI

for NSTEMI

2010-2014 By state

By sector

SMRP (Unpublished-data updated

until July 2015)

Outcome

13. 30-day fatality rate after STEMI 2006-2013

National aggregate

MOH/MOE only

NCVD

(Published) Outcome

14. 30-day fatality rate after AMI 2008-2013 By state

By sector


until July 2015)

Outcome

15. In-hospital STEMI case fatality rate 2013-2014 By state

By sector


until July 2015)

Outcome

16. In-hospital UA/NSTEMI case fatality rate 2013-2014 By state

By sector


until July 2015)

Outcome

17.

Prevalence among general population

Hypertension

Hypercholesterolemia

Diabetes

Obesity

Daily tobacco male smoker

Daily tobacco female smoker

2006-2015 By state NHMS

(Published) Impact


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Table 1: Data availability, coverage, and levels of disaggregation of selected performance indicators (continued)

Indicator Time period Coverage Data source Category

18. Estimated mortality from cardiovascular disease

2012 National

aggregate OECD

(Published) Impact

19. In-hospital 30-day case-fatality after AMI 2011 National

aggregate OECD

(Published) Impact

NHEWS: National Healthcare Establishments & Workforce Statistics (Hospital) 2008-2009

National Healthcare Establishments & Workforce Statistics (Hospital) 2011

National Healthcare Establishments & Workforce Statistics (Hospital) 2012-2013

NCVD: Annual Report of the NCVD-ACS Registry Malaysia 2006

Annual Report of the NCVD-ACS Registry Malaysia 2007 & 2008



NHMS: The Third National Health and Morbidity Survey (NHMS III) 2006, Vol 2

National Health and Morbidity Survey 2011 (NHMS 2011). Vol. II: Non-Communicable Diseases

National Health and Morbidity Survey 2015 (NHMS 2015). Vol. II: Non-Communicable Diseases, Risk Factors & Other Health

Problems

NHMS 2015: Report on Smoking Status Among Malaysian Adults

OECD: Health at a Glance 2013 - © OECD 2013

Health at a Glance: Asia/Pacific 2014 - © OECD 2014

stats.oecd.org

CKPP: Cawangan Kualiti Penjagaan Perubatan, Bahagian Perkembangan Perubatan

SMRP: Sistem Maklumat Rawatan Perubatan


8

CHAPTER 2 MALAYSIAN CORONARY HEART DISEASE PROFILING


9

DISEASE DEMOGRAPHICS

The population demographic breakdown for coronary heart disease (CHD) in Malaysia is given by Figure 1 and Figure 2 for age group and ethnicity respectively. Until 2013, 31,677 patients had been diagnosed with ACS based on the NCVD ACS registry reports. The mean age for period 2006-2010 was 59. The mean age reduced to 58.5 subsequently for 2011-2013. Overall, more than half of those who had had CHD were younger than 60 years of age.

Aggregate level analysis of 2013 data finds, of the total registered patients, 79% were men and 21% were women (W.A Wan Ahmad & K.H Sim., 2015). In term of ethnicity, 52% were Malay, 22% were Chinese, 19% were Indian and 2.6% were non-Malaysians.

The racial distribution is reflective of general Malaysian ethnic composition made up mostly by the Malay ethnic group (Jabatan Perangkaan Malaysia, 2015). However, until 2013, only 19 out of total 351 hospitals (141 public vs 210 private) involved in NCVD registry. Therefore, due to case ascertainment bias, population inference of any statistical estimates in the report may be limited.

FIGURE 1: BREAKDOWN OF CASES BY AGE GROUPS, 2013

FIGURE 2: BREAKDOWN OF CASES BY ETHNICITY, 2013

Data source: National Cardiovascular Disease Database (NCVD) Registry

20 - 30 1% 30 - 40

6%

40 - 50 17%

50 - 60 33%

60 - 70 25%

70 - 80 15%

≥ 80 3%

Malay 52%

Chinese 22%

Indian 19%

Bumiputera Sabah & Sarawak

4%

Others 2% Non-

Malaysian 3%


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FIGURE 3: AGE-SPECIFIC PREVALENCE OF ACS, 2010-2013

20-29 0.5 0.8 0.7 0.9 22%

30-39 4.5 4.7 6.0 7.7 20%

40-49 18 22 24 29 18%

50-59 45 49 53 74 19%

60-69 60 70 80 98 18%

70-79 84 98 99 127 15%

≥80 60 58 68 76 8.1%


What does this mean for Malaysia? 1. Prevalence of acute coronary syndrome (ACS) has increased in all age groups over the three

years period. 2. Rate of increase for age group 20-29 is the highest at 22% while the rate of increase for age

group ≥ 80 is the lowest at 8.1%. Incidence of ACS within the younger age groups is increasing

0.9 7.7

29

98

127

76

2010 2011 2012 2013

per

10

0 0

00

20-29

30-39

40-49

50-59

60-69

70-79

≥80

AAR


11

CORONARY HEART DISEASE RISK FACTORS PREVALENCE

“Kempen Cara Hidup Sihat” is a series of health promotion campaign that was launched since 1991 by the Ministry of Health (MOH) to help create public awareness, improve knowledge and promote health as a lifestyle goal (http://www.infosihat.gov.my). In 2013, “Kempen Nak Sihat” was launched as another initiative to encourage the public especially the youth to assimilate healthy lifestyle through active engagement in physical activity. The MOH also initiated “Komuniti Sihat Perkasa Negara” (KOSPEN) an inter-institutional collaborative program meant to boost the existing health promoting mechanism by engaging and empowering the community. Despite the on-going efforts, the prevalence of NCD and NCD risk factors continue to rise.

A situational analysis reveals that the implementation of NCD programs and activities most of the time were confined only within the health ministry territories (Ministry of Health Malaysia, 2010). In 2010 National strategic plan for NCD was implemented to encourage inter-sectorial collaboration and address a lack of policy in creating health promoting environment in Malaysia.

National Health Morbidity Survey (NHMS) demonstrates the NCD risk factors progression in Malaysia over a period of two decades (2006-2015). The prevalence of diabetes and hypercholesterolemia among the respondents aged 18 and above was showed to have increased over time.

FIGURE 4: NATIONAL HYPERTENSION PREVALENCE PROGRESSION 18+, 2006-2015

FIGURE 5: NATIONAL HYPERCHOLESTEROLEMIA PREVALENCE PROGRESSION 18+, 2006-2015

Data source: National Health and Morbidity Survey

FIGURE 6: NATIONAL DIABETES PREVALENCE PROGRESSION 18+, 2006-2015


FIGURE 7: NATIONAL DAILY SMOKER PREVALENCE PROGRESSION BY GENDER 15+, 2006-2015

32 33 30

61% 57%

2006 2011 2015

%

Overall Undiagnosed Known

21

35

48

76% 81%

2006 2011 2015

%

Overall

Undiagnosed

Known

11.6

15.2 17.5

53% 53%

2006 2011 2015

%

Overall Undiagnosed Known

33.3 38.8

1.1 1.1

2011 2015

%

Male

Female


12

Table 2: Cardiovascular disease (CVD) risk factor prevalence, 2015.

Period Value (%) Target AAR (%) Benchmark

2.1. Prevalence of hypertension 2015 30.3 - ↓0.7 The US

3

29.1

2.2. Prevalence of hypercholesterolemia 2015 47.7 - ↑9.7 Australia

4

32.8

2.3. Prevalence of diabetes 2015 17.5 - ↑4.7 OECD-34

5

7.0

2.4. Prevalence of obesity 2015 30.6 - ↑9.1 OECD-27

5

17.2


male 2015 38.8 - ↑3.9

OECD-325

22.8


female 2015 1.1 - →0.0

OECD-325

14.6

* AAR is calculated for period 2011-2015 for 2.4 & 2.5 2006-2015 for 2.1, 2.2, 2.3, 2.6 Data source: National Health and Morbidity Survey

Table 3: State variation of CVD risk factor prevalence, 2015.

Prevalence of

hypertension

Prevalence of

hypercholesterolemia

Prevalence of

diabetes

Prevalence of current

tobacco smoker

Kedah 37.5 ↓ 0.5% 53.5 ↑ 5.4% 25.4 ↑ 7.2% 26.5 ↑ 0.4%

Sarawak 37.3 ↓ 2.0% 48.6 ↑ 9.7% 14.8 ↑ 4.5% 25.4 ↑ 3.1%

Perak 36.4 ↓ 4.0% 48.3 ↑ 1.8% 19.4 ↑ 4.9% 21 ↑ 0.1%

Perlis 35.4 ↓ 3.7% 47.0 ↑ 1.0% 20.6 ↑ 4.8% 22.2 ↓ 4.3%

Kelantan 33.8 ↑ 4.9% 51.7 ↑ 11% 18.5 ↑ 5.2% 24.6 ↓ 1.2%

WP Kuala Lumpur 33.8 ↑ 5.7% 52.9 ↑ 16% 17.4 ↑ 3.7% 19.1 ↑ 2.2%

Negeri Sembilan 32.5 ↓ 1.2% 49.5 ↑ 5.7% 19.3 ↑ 2.6% 20.9 ↓ 1.2%

Penang 29.8 ↑ 1.2% 52.2 ↑ 12% 18.1 ↑ 2.2% 19.2 ↑ 0.4%

Pahang 28.5 ↓ 1.2% 56.2 ↑ 15% 14.8 ↑ 2.3% 25.5 ↓ 0.8%

Johor 27.4 ↓ 6.9% 45.8 ↑ 5.0% 19.8 ↑ 6.6% 22.2 ↑ 0.8%

Terengganu 26.9 ↑ 0.1% 52.1 ↑ 11% 18.6 ↑ 5.9% 22.2 ↓ 1.9%

Sabah & WP Labuan 26.8 ↓ 2.0% 40.9 ↑ 7.1% 14.2 ↑ 13% 28.4 ↑ 5.4%

Melaka 25.8 ↓ 5.8% 46.6 ↑ 6.7% 16.7 ↑ 1.1% 16.9 ↓ 1.9%

Selangor 25.5 ↓ 2.9% 43.5 ↑ 8.1% 15.5 ↑ 2.9% 20.9 ↑ 1.6%

WP Putrajaya 24.1 ↑ 1.7% 46.4 ↑ 8.6% 19.2 ↑ 22% 12.4 ↓ 5.6%

* AAR is calculated for period 2011-2015


3 Nwankwo T, Yoon SS, Burt V, Gu Q. Hypertension among adults in the United States: National Health and Nutrition Examination Survey, 2011–2012. NCHS data brief, no 133. Hyattsville, MD: National Center for Health Statistics. 2013 4 Australian Bureau of Statistics (4364.0.55.005), Australian Health Survey: Biomedical Results for Chronic Diseases 2011/12 5 http://stats.oecd.org/2015


13

What does this mean for Malaysia? 1. Cardiovascular risk factor (diabetes, hypercholesterolemia, smoking, obesity) prevalence is

increasing 2. About 80% of hypercholesterolemia cases were previously undiagnosed. In addition, more

than half of diabetes and hypertension cases were previously undiagnosed. 3. About one third of the population are obese (BMI ≥ 27.5kg/m2) 4. Majority of our daily smokers are male. The prevalence is almost twice as high as OECD. Only

about 1% of females are daily smoker and the prevalence has not changed since 2011.


14

CHAPTER 3 CARDIAC CARE PERFORMANCE INDICATORS


15

WHERE WE STAND

Malaysia continues to work within its capacity to pursue the goal of delivering a world-class health care system. Our national health priorities include enhancing the health care delivery system to increase access to quality care, and reducing the disease burden, both communicable and non-communicable diseases. While we have achieved commendable improvement in life expectancy and maternal and child mortality indicators, we are still behind the performance of countries with higher economic status. Key health challenges that we are facing include the changing disease pattern from communicable to non-communicable diseases and the increasing prevalence of cardiovascular risk factors hence the increasing burden of disease related to cardiovascular complications. WHO Global Health Estimate 2014 reported stroke and ischemic heart disease as the leading causes of death in Western Pacific Region, including Malaysia (World Health Organization, Global Burden of Disease (GBD), 2014). There are indeed variations and differences in term of capacity, processes and outcomes of a health system in different countries depending on its objectives. However, making OECD countries as benchmark will give us insight into the potential improvement that can be undertaken at our local settings given the aspiration of Malaysia becoming a developed nation.

FIGURE 8: MALAYSIAN RANKINGS OF SELECTED PERFORMANCE INDICATORS AMONG PEER COUNTRIES

Percentage

of daily smoker 2013

Estimated mortality from cardiovascular disease

2012*

In-hospital 30-day case-fatality

after AMI 2011**

Indonesia 37.9 Indonesia 336 Singapore 12.5

China 25.5 China 286.1 Japan 12.2 Germany 20.9 India 284.4 Malaysia 9.7† Malaysia 20.5 Malaysia 265.6 Korea Rp. 8.9

United Kingdom 20.0 OECD 160.6 Philippines 8.9 OECD-26 17.4 Germany 158.6 OECD-32 7.9

New Zealand 15.5 United States 158.3 United Kingdom 7.8 United States 13.7 United Kingdom 130.3 Canada 5.7

Singapore 13.2 New Zealand 119 United States 5.5 Australia 12.8 Australia 112.1 Australia 4.8

India 9.6 Singapore 110.1 New Zealand 4.5

*Age-standardised rates per 100 000 population ** Age-sex standardised rates (%) †Unadjusted rate, 2008

Data source: National Health and Morbidity Survey (NHMS) OECD Health Statistics stats.oecd.org

What does this mean for Malaysia?

1. Malaysia performance is below the OECD average for prevalence of daily tobacco smoker. 2. The high cigarette smoking prevalence seems to correlate with high CVD mortality in

Malaysia 3. Estimated cardiovascular mortality in Malaysia is 1.65 times higher than the OECD average. 4. For every 100 cases of AMI admitted to our hospitals, close to 10% succumbed to death

within 30-days.


16

HUMAN RESOURCES & FACILITY

Generating resources or inputs is one of the functions a health system performs along with stewardship, financing and health service provision. Inputs to the health system are combined to allow the delivery of a series of interventions or health actions with the final objectives mainly to improve the population health status. These inputs particularly human resources, physical resources such as facilities and equipment, and knowledge are factors that would enable health system to perform to its potential. Thus, a well-thought strategy for input generation is very critical. (The World Health Report Health Systems Improving Performance, 2000).

Inputs in term of adequate number of health care facilities and resources are also requisite to ensure universal accessibility to health care. In Malaysia, despite the highly subsidized public health care provision and additional service coverage offered by the private practices, issues like long queues, drug rationing or poor transportation system can be potential contributors to inequity in service delivery (Ministry of Health, 2015).

Table 4: Number & density of cardiologist, cardiothoracic surgeon and cardiac catheterization laboratory, 2013.

Year Achievement Target AAR (%)

Benchmark

Public Private Public Private

4.1. Number of Cardiologist 2013 53 194 - ↑13.4 ↑7.9 US6

25 901

4.2. Number of Cardiothoracic surgeon

2013 49 25 - ↑8.6 ↑7.3 -

4.3. Cardiologist per 1 000 000 population

2013 8 - - US

6

55.7

4.4. Cardio-thoracic surgeon per 1 000 000 population

2013 3 - - -

4.5. Cardiologist public : public ratio

2013 1 : 4 - - -

4.6. Cardiothoracic surgeon public : private ratio

2013 1 : 2 - - -

4.7. Number of hospital with cardiac catheterization laboratory

2014 14 55 - ↑3.8 ↑14.4 -

* AAR is calculated for period 2012-2014 for 4.7 2009-2013 for 4.1-4.6 Public refers to the Ministry of Health, Ministry of Education and Ministry of Defence data Data source: National Health Establishment & Workforce Statistics (NHEWS) Survey National Cardiovascular Disease Database (NCVD) Registry

6 Rodgers GP, Conti JB, Feinstein JA, et al. ACC 2009 Survey Results and Recommendations: Addressing the Cardiology Workforce Crisis: A Report of the ACC Board of Trustees Workforce Task Force. J Am Coll Cardiol. 2009;54(13):1195-1208. doi:10.1016/j.jacc.2009.08.001.


17

FIGURE 9: PROPORTION OF CARDIOLOGIST (PUBLIC VS PRIVATE) AND THE TOTAL CARDIOLOGIST DENSITY BY STATE, 2013

FIGURE 10: PROPORTION OF CARDIOTHORACIC SURGEON (PUBLIC VS PRIVATE) AND THE TOTAL CARDIOTHORACIC SURGEON BY STATE, 2013

Data source: National Health Establishment & Workforce Statistics (NHEWS) Survey

42

23

13

8 7

5 5 5 4 4 3 3 2 0 0

8

0%

50%

100%

Den

sity

Private Public Average Density per 1 000 000

15

9

5

2 2 2

1 1 1 1

0 0 0 0 0

3

0%

50%

100%

Den

sity

Private Public Average Density per 1 000 000


18

Table 5: State variation of number & density (per 1 000 000 population) of cardiologist, cardiothoracic surgeon and cardiac catheterization laboratory, 2013.

Cardiologist density Cardiothoracic surgeon density

Hospital with

catheterization lab†

Public Private Public Private Public Private

Kuala Lumpur 8 65 42 5 21 15 3 9 Selangor 7 41 8 2 11 2 2 14

Pulau Pinang 9 28 23 6 8 9 1 9 Sarawak 8 9 7 4 1 2 1 4

Johor 6 9 4 3 1 1 1 3 Perak 1 11 5 0 2 1 1 3

Melaka 0 11 13 0 4 5 0 3 Kedah 4 6 5 0 0 0 1 5

Sabah & Labuan 2 4 2 1 1 1 1 1 Kelantan 3 2 3 3 0 2 1 1

N. Sembilan 0 5 5 0 0 0 0 2 Pahang 2 2 3 1 0 1 1 1

Terengganu 3 1 4 0 0 0 1 0 Perlis 0 - 0 0 0 0 0 0

Putrajaya 0 0 0 0 0 0 - -

† Data for year 2014 Data source: National Health Establishment & Workforce Statistics (NHEWS) Survey National Cardiovascular Disease Database (NCVD) Registry

What does this mean for Malaysia? 1. The growth of human resources (Cardiologist and Cardiothoracic surgeon) in public sectors is

at a higher rate compared to the private sectors. 2. Private sectors have more cardiac catheterization laboratory than public sectors. 3. There is marked variation/difference in resource of manpower between states, majority

concentrated in West Coast of Malaysian Peninsular mainly in Klang Valley, Penang and Melaka, least in East Coast and East Malaysia

4. In addition, majority of cardiologist are based in private sector. Melaka and Negeri Sembilan especially are states with no public hospital cardiologist. The increasing burden of cardiovascular disease may have a heavier impact on the public sector if such gap remained unfilled.

5. These scenarios highlight the issues concerning accessibility to health care especially in the states with relative lack of facility and skilled professionals.


19

PROCESS OF CARE

Time is the determining factor of success in management of acute coronary syndrome. Initiation of treatment in an acute setting involves accurate clinical diagnosis of cardiac ischemia or infarction in a timely fashion starting from the point of contact with the healthcare provider. The recommended time for initiation of fibrinolytic therapy for acute ST elevation myocardial infarction (STEMI) is within 30 minutes. The recommended time for initiation of primary PCI for STEMI from the point of medical contact is within 90 minutes (in primary-PCI capable centres) (Clinical Practice Guidelines Management of Acute ST Segment Elevation Myocardial Infarction, 2014).

Cawangan Kualiti Penjagaan Perubatan (CKPP), Medical Development Division, Ministry of Health is collecting hospital data concerning door-to-needle (DTN) time and reported them as aggregate percentage of ST elevation Myocardial Infarction (STEMI) patients receiving thrombolytic therapy within 30 minutes of presentation at the Emergency Department by state. For atypical symptoms or ECG, time-to-treatment is counted from the time of the first diagnostic ECG changes to the thrombolytic therapy given.

Malaysian National Cardiovascular Disease Database (NCVD) is another set of database that collects information about cardiovascular disease in Malaysia. NCVD records the individual time lapse of reperfusion therapy initiation from the time of presentation to healthcare facility. Door-to-balloon (DTB) time in NCVD is recorded only for patients diagnosed with STEMI undergoing primary PCI. Findings in NCVD report for DTN and DTB have already excluded transfer-in cases.

FIGURE 11: MEDIAN DTN TIME 2006-2013

FIGURE 12: MEDIAN DTB TIME 2006-2013

National Cardiovascular Disease Database (NCVD) Registry

1349 1435 1440 1440 1440 1390 1380 1440

60 53 50

45 45 40

45 49

2006 2007 2008 2009 2010 2011 2012 2013

Minutes

30

1440 1410 1195 1391 1410 1305 1440 1440

133

112 114 119 108

120 113.5 104

2006 2007 2008 2009 2010 2011 2012 2013

Minutes

90


20

FIGURE 13: RATE OF FIBRINOLYSIS, 2006-2013

FIGURE 14: RATE OF PRIMARY PCI, 2006-2013

Data source: National Cardiovascular Disease Database (NCVD) Registry Table 6: Percentage of STEMI patients who received timely fibrinolysis therapy and the median time-to-intervention, 2013.

Period Achievement Target AAR (%) Benchmark

6.1. % of STEMI undergone fibrinolysis with door-to-needle time < 30 minutes

2014 94% >85% ↓0.3 US7

46.8%

6.2. Median door-to-needle-time (minute)

2013 49 <30 - -

6.3. Median door-to-balloon time (minute)

2013 104 <90 - US

7

59

6.4. % of STEMI not given fibrinolytic therapy due to missed thrombolysis time

2013 11% - ↓2.4 -

6.5. Rate of fibrinolytic therapy 2013 74% - ↑0.8 -

6.6. Rate of primary PCI 2013 10% - ↑3.5 -

* AAR is calculated for period 2013-2014 for 6.1 2006-2013 for 6.4-6.6 7

Includes transferred-in cases for fibrinolysis. Data source: CKPP Medical Development Division, Ministry of Health National Cardiovascular Disease Database (NCVD) Registry

7 Masoudi FA, Ponirakis A, Yeh RW, et al. Cardiovascular Care Facts: A Report From the National Cardiovascular Data Registry: 2011. J Am Coll Cardiol. 2013;62(21):1931-1947. doi:10.1016/j.jacc.2013.05.099

70 73 75 75 75 80 72 74

% 8 7 6 5

8 6

11 10 %


21

FIGURE 15: STATE VARIATION OF DOOR-TO-NEEDLE TIME ACHIEVEMENT IN PUBLIC HOSPITALS, 2014 VS 2013

Data source: CKPP Medical Development Division, Ministry of Health

What does this mean for Malaysia? 1. More than half of eligible patients did not receive fibrinolysis and primary PCI within the

standard initiation time; 30 minutes and 90 minutes respectively before 2013. 2. The time lapse trend is improving for both thrombolysis and primary PCI since 2006. The

trend observed for DTN is the result of the decision that was made to initiate treatment at the earliest medical contact in the hospital Emergency Department (ED), as compared to initiation of treatment after admission to Cardiac Intensive Care Unit for thrombolysis in the past.

3. More recent data of 2014 shows improvement in DTN whereby 94% of the eligible cases received fibrinolytic therapy within 30 minutes of arrival to Emergency Department.

4. We have no data with regard to these parameters in most private hospitals since the reporting in NCVD ACS registry is still of voluntary basis, mainly involving KKM hospitals, IJN and the university hospitals (mainly UMMC).

79%

94%

85%

0%

100%

Door-to-needle time achievement < 30 minutes

2013

2014

Target

≡


22

HEALTH OUTCOME

ADMISSION RATE

Acute coronary syndrome regardless severity requires admission for stabilization and close monitoring. Routine in-patient management involves assessment of mortality risk and potential recurring ischemic event to strategize the next best therapeutic intervention. Patients will be followed up once discharged from the hospital for re-evaluation of existing cardiovascular complications or complications following the acute event. The assessment of complication will include heart failure as a result of underlying coronary artery disease.

Sistem Maklumat Rawatan Perubatan (SMRP) and e-Reporting are the Ministry of Health database of public and private hospital admissions and discharges. Patient discharge diagnoses in the database are coded with ICD-10 system for routine internal reporting purposes. The codes used to generate data for admission rate computation in this report are as follows:

Discharge diagnosis as ST-elevation myocardial infarction (STEMI): I21.0, I21.1, I21.2, I21.3

Discharge diagnosis as non- ST-elevation myocardial infarction (NSTEMI): I21.4

Discharge diagnosis as unstable angina (UA): I20.0

The data were restricted to population aged 15+ for each principal diagnosis code as defined above.

FIGURE 16: HOSPITAL ADMISSION RATE FOR STEMI

FIGURE 17: HOSPITAL ADMISSION RATE FOR NSTEMI

FIGURE 18: HOSPITAL ADMISSION RATE FOR UNSTABLE ANGINA

Data source: Sistem Maklumat Rawatan Perubatan (SMRP)

21

14

20 15

20

2010 2011 2012 2013 2014

per

100

000

Public Private

30

8 12 14

20

2010 2011 2012 2013 2014

per

100

000

Public Private

99 130 144

100 112

2010 2011 2012 2013 2014

per

100

000

Public Private


23

Table 7: Hospital admission rate (per 100 000 population) for acute coronary syndrome (ACS), 2013.

Period Value Standard AAR (%) Benchmark

7.1. Admission rate for UA 2013 112 - ↓4.8 -

7.2. Admission rate for STEMI 2013 20 - ↑12 -

7.3. Admission rate for NSTEMI 2013 20 - ↑36 -

* AAR is calculated for period 2010-2013


Table 8: State variation of hospital admission rate for ACS (per 100 000 population), 2013.

Admission rate STEMI Admission rate NSTEMI Admission rate UA

Perlis 17 ↑ 115% 83 - - 583 ↑ 32%

Negeri Sembilan 30 ↑ 67% 64 ↑ 18% 292 ↑ 1.4%

Putrajaya 2 - - 4 - - 164 - -

Pahang 27 ↑ 50% 25 ↑ 102% 148 ↑ 4.1%

Kelantan 34 ↑ 46% 8 ↑ 174% 124 ↑ 1.8%

Johor 13 ↑ 18% 25 ↑ 67% 143 ↓ 2.5%

Perak 42 ↑ 58% 46 ↑ 19% 136 ↓ 13%

Kedah 4 ↓ 54% 2 ↓ 42% 89 ↓ 20%

Pulau Pinang 32 ↑ 21% 9 ↑ 7% 127 ↓ 15%

Melaka 36 ↑ 40% 50 ↑ 10% 159 ↓ 2.4%

Sarawak 16 ↑ 11% 14 ↑ 60% 58 ↑ 15%

Labuan 23 ↓ 1.5 0 - - 77 ↓ 41%

Kuala Lumpur 32 ↑ 26% 20 ↑ 74% 84 ↓ 4.3%

Terengganu 14 ↑ 2.6% 17 - - 213 ↓ 0.8%

Selangor 13 ↓ 14% 16 ↑ 63% 76 ↓ 10%

Sabah 9 ↑ 34% 3 ↑ 61% 36 ↑ 14%

AAR is calculated for period 2010-2013

AAR is calculated for period 2012-2013 for Labuan

AAR is not calculated for Putrajaya due to incomplete data


What does this mean for Malaysia? 1. The increasing admission rate for both STEMI and NSTEMI within 2010-2014 periods reflects

the growing burden of disease attributable to increasing prevalence of cardiovascular risk factors.

2. Admission for UA has decreased in most states. 3. The apparent increase in admission rate for NSTEMI with concurrent decrease for UA in

most states could be due to improvement in clinical diagnosis made in cardiology ward. Suspected ACS cases which were managed in Cardiology ward as opposed to general medical ward received more comprehensive reviews by the cardiologist hence accuracy in diagnosis.


24

30-DAY CASE FATALITY AFTER ACUTE MYOCARDIAL INFARCTION

Mortality following an AMI or STEMI represents an important outcome (potentially related to quality of care) high rates of which warrant thorough investigation. The 30-day case fatality measures are estimates of deaths from any cause within 30 days of a hospital admission of an AMI or STEMI.

The decision to measure event within 30 days instead of over longer time periods (like 90 days) is made because longer periods may be impacted by factors outside of hospitals’ control such as complicating illnesses, patients’ own behaviour, or care provided to patients after discharge.

In addition, the variation observed in mortality over a period of time may reflect differences in general environments (such as coordination of care, patient safety policies, and staffing) or variation in care processes. It can also be due to differences in baseline individual risk. Therefore, computation of standardized rates is pivotal if we were to compare achievement between different periods or regions. However, the scope of current report is limited to interpretation of crude rates only.

FIGURE 19: 30-DAY CASE FATALITY RATE AFTER STEMI, 2006-2013

FIGURE 20: 30-DAY CASE FATALITY RATE AFTER AMI, 2006-2013


21 19

15 12 12 12 12 11 %

25 21

16 14 15 11 11 11 %


25

FIGURE 21: STATE VARIATION OF IN-HOSPITAL NSTEMI/UA CASE FATALITY RATE, 2013 VS 2014

FIGURE 22: STATE VARIATION OF IN-HOSPITAL STEMI CASE FATALITY RATE, 2013 VS 2014


5.2 4.9

3.7

3.3 3.0

2.7 2.6 2.6 2.4 2.2 2.1 2.1 1.7

1.2

0.5

%

Unstable Angina/ NSTEMI fatality rate 2013 Private

2013 Public

2014 Public

65

26 20 19

15 11 11 11 11 10 10 9 7 7

3.3

%

STEMI fatality rate

2013 Private

2013 Public

2014 Public


26

Table 9: 30-day case fatality rate for ACS patients, 2013

Period

Value

(%) Standard

AAR

(%) Benchmark

9.1. 30-day case fatality rate after

STEMI 2013 11.4 - ↓13 -

9.2. 30-day case fatality rate after acute

myocardial infarction (AMI) 2013 10.9 - ↓11

OECD-238

8.3

9.3. In-hospital STEMI case fatality rate 2013 5.9 - ↓8.7 -

9.4. In-hospital NSTEMI/UA case fatality

rate 2013 3.3 - ↓16 -

8 Age-standardized rate

* AAR is calculated for period 2006-2013 for 9.1, 9.2 2008-2013 for 9.3, 9.4 AMI refers to STEMI & NSTEMI (ICD-10 I21) Data source: National Cardiovascular Disease Database (NCVD) Registry

What does this mean for Malaysia? 1. 30-days mortality after AMI is reducing since 2006 consistent with the increasing rate of

primary PCI and improvement seen in DTN and DTB. 2. Further improvement in mortality can be expected if issues with resources distribution could

be ameliorated.

8 http://stats.oecd.org/2015

http://stats.oecd.org/2015


27

CONCLUSION

Areas where Malaysia is doing well:

Positive growth of human resource (Cardiologist and Cardiothoracic surgeons) with higher

rate of growth in public sector compared to private.

Declining percentage of patients who missed thrombolysis due to late presentation

The percentage of STEMI receiving fibrinolysis within standard time 30 minutes in public

hospitals is above 90% on average

Percentage of patient receiving primary PCI is increasing.

Declining 30-day case fatality rate after AMI

Areas for concern:

High and increasing prevalence of ACS risk factors including diabetes, hypercholesterolemia, hypertension, obesity and smoking with a significant proportion of them were undiagnosed.

More young people are inflicted with ACS

Increasing number of admission for AMI

We have yet to achieve our target in number of human resources for cardiologist and

cardiothoracic surgeon.

Uneven distribution of human resources & cardiac facilities between states

Public and private health sector disparity in term of capacity of human resources for

Cardiologist and cardiothoracic surgeon.

Public and private health sector disparity in term of number of cardiac catheterization lab

available

More than half STEMI patients did not receive timely primary PCI

Fatality rate for AMI comparatively higher than OECD countries.

Low ascertainment of ACS cases from limited number of data provider due to the voluntary basis of data entry into NCVD database.


28

RECOMMENDATIONS

Investing in prevention of disease and disability is known to be the most cost effective

investment in healthcare. The existing health promotion program at community level

programmes can be made extensive with collaboration from sectors outside of ministry of

health. It will be a good move if KOSPEN is made to not only cover residential areas but work

places as well.

Enhancing public health promotion and intervention should focus on the lowering the

prevalence of current smokers, early detection and treatment of hypertension, diabetes and

hypercholesterolemia.

We should leverage fully on information technologies and social media to present and

promote health information in line with today’s expectations, with the aim of providing

evidence-based and authoritative information and provide self-empowerment.

It is also essential to put our priority on cardiovascular diagnostics and amenities in order to

identify the high risk patients for an early intervention. Establishment of new public cardiac

facility and specialty centre as well as intensification of training programmes are mandatory

in view of the ever increasing disease burden. In areas like in Sarawak or Sabah, inter-facility

transfer issues can be the limiting factor that needs focal attention. After all the outcome of

acute cardiovascular diseases are very much related to speed of treatment and availability of

tertiary level specialist medical services with cardiac catheterization laboratory.

To optimise use of available resources and facilities through public-private partnership for a

more sustainable system that further improves the outcome. We must first create a model

of resource sharing that is fair to both parties.

To involve various stakeholders including personnel from Ministry of Education early in planning of health related activities and policies on the mission to prevent, restore and maintain good health for our citizen.

Evaluation of performance must include risk adjustment for fair comparisons. Poor outcome

or unmet objectives of any program implementation should trigger a mechanism for

investigation that will include focus and systematic data collection.

To make mandatory of reporting of cardiac cases to NCVD by creating a KPI for the State

Health Directors. NCVD use should expand to include many more health facilities and

institute both in public and private sectors.


29

BIBLIOGRAPHY

Ahmad Faudzi Yusoff, Gurpreet Kaur, Mohd Azahadi Omar, & Amal Nasir Mustafa. (2004). Malaysian Burden of Disease and Injury Study. Kuala Lumpur: Institute for Public Health.

Avedis Donabedian, John R. C. Wheeler, & Leon Wys. (1982). Quality, Cost, and Health: An Integrative Model. Medical Care, 975-992.

Clinical Practice Guidelines Management of Acute ST Segment Elevation Myocardial Infarction. (2014). Putrajaya.

http://www.infosihat.gov.my/infosihat/projekkhas/kospen.php. (n.d.). Bahagian Pendidikan Kesihatan Kementerian Kesihatan Malaysia. Retrieved 17 November, 2016, from KOSPEN: http://www.infosihat.gov.my/infosihat/projekkhas/kospen.php

Institute for Public Health. (2015). National Health & Morbidity Survey (Non-Communicable Diseases, Risk Factors & Other Health Problems.

Jabatan Perangkaan Malaysia. (2015). Anggaran Penduduk Semasa Malaysia.

Ministry of Health. (2011). Cardiothoracic Surgery Services Operational Policy.

Ministry of Health. (2015). Country Health Plan.

Ministry of Health Malaysia. (2010). National Strategic Plan For Non-Communicable Disease.

The World Health Report Health Systems Improving Performance. (2000). Switzerland.

W.A Wan Ahmad, & K.H Sim. (2015). Annual Report of the NCVD-ACS REgistry.

World Health Organization. (2003). Health systems performance assessment: debates, methods and empricism. Retrieved from WHO | World HEalth Organization: www.who.int

World Health Organization. (2014). Global Burden of Disease (GBD). Retrieved November, 2016, from http://www.who.int/healthinfo/global_burden_disease/gbd/en/


30

GLOSSARY

Acute Coronary Syndrome (ACS)

ACS encompasses clinical features comprising chest pain or overwhelming shortness of breath, is defined by accompanying clinical, ECG and biochemical features. ACS comprises the following: 1. Unstable Angina Pectoris (UAP) 2. Non-ST-elevation Myocardial Infarct (NSTEMI) 3. ST-elevation Myocardial Infarct (STEMI). (NCVD-ACS 2009-2010)

Admission Admission (or inpatient admission) is the formal acceptance by a hospital of a patient who will occupy a hospital bed, crib or bassinet for observation, care, diagnosis or treatment and will have a medical record maintained for him/her. (NHEWS 2012 – 2013)

Cardiovascular disease

Cardiovascular diseases cover a range of illnesses related to the circulatory system, including ischemic heart disease (often referred to as heart attack) and cerebrovascular diseases such as stroke. (Health at a Glance 2015: OECD Indicators)

Current smoker Smoker who daily or occasionally smokes any tobacco product. (NHMS 2015: Report on Smoking Status Among Malaysian Adults)

Daily smoker Person who currently smokes any tobacco product every day. (NHMS 2015: Report on Smoking Status Among Malaysian Adults)

Diabetes A metabolic disorder of multiple etiologies characterized by chronic high blood glucose levels with disturbance of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action or both. (NHMS Vol.2 2006)

Door-to-balloon time The duration between time patients presented to the health care centre to time of first intra-coronary device used and performed in the same centre. (NCVD-ACS 2009-2010)

Door-to-needle time The duration between time patients presented to the health care centre to time intravenous fibrinolytic therapy administered or initiated in the same centre. (NCVD-ACS 2009-2010)

Hospital An institution with primary function to provide inpatient diagnostic and therapeutic services for a variety of medical conditions both surgical and non-surgical. (NHEWS 2012-2013)

Inpatient care In-patient care refers to care for a patient who is formally admitted (or ‘hospitalised’) to an institution for treatment and/or care and stays for a minimum of one night in the hospital or other institution providing in-patient care. (https://stats.oecd.org/glossary/detail.asp?ID=1364)

Ischemic heart disease

Ischemic heart disease (IHD) is caused by the accumulation of fatty deposits lining the inner wall of a coronary artery, restricting blood flow to the heart. (Health at a Glance 2015: OECD Indicators)

Known hypercholesterolemia

Self-reported status by subject in NHMS survey, as having diagnosed with hypercholesterolemia previously by medical personnel.

Known hypertension Self-reported status by subject in NHMS survey, as having diagnosed with hypertension previously by medical personnel.

Obesity Obesity is a complex, multifactorial condition characterized by excess body fat (CPG 2004- BMI ≥ 27.5 kg/m2; WHO 1998- BMI ≥ 30 kg/m2). Generally, men with >25% body fat and women with >35% body fat are considered obese (CPG Management of Obesity, 2004).

Prevalence Statistical concept referring to the number of occurrences of an event of interest that are present in a particular population at a given time.

Smoking cessation Smoking cessation or quitting smoking is a process of discontinuing the practice of inhaling a smoked substance. (NHMS 2015: Report on


31

Smoking Status Among Malaysian Adults) Tobacco Common name given to the plants of the genus Nicotiana, especially the

Nicotiana tabacum from South America, from which the substance called nicotine, is extracted. (NHMS 2015: Report on Smoking Status Among Malaysian Adults)

Tobacco products Two types of tobacco products: 1. Smoked tobacco: manufactured cigarettes, hand-rolled cigarettes, kreteks, other smoked tobacco such as pipe, curut/cigar/cigarillos, water pipes/shisha/hookah, bidis and others. 2. Smokeless tobacco: snuff by keeping in mouth/nose, chewing tobacco, betel quid with tobacco, electronic cigarettes and others. (NHMS 2015: Report on Smoking Status Among Malaysian Adults)

Undiagnosed hypercholesterolemia

Not known to have hypercholesterolemia and has a total blood cholesterol level equals to or more than 5.2 mmol/L. (NHMS Vol.2 2015)

Undiagnosed hypertension

Not known to have hypertension and has an average systolic blood pressure equals to or more than 140mmHg and/or diastolic blood pressure equal to or more than 90mmHg. (NHMS Vol.2 2015)


32

APPENDIX


33

Data table 1: Distribution of patients by age group and ethnicity

Year 2006 2007 2008 2009 2010 2011 2012 2013

No. % No. % No. % No. % No. % No. % No. % No. %

20 - <30 23 1 20 1 19 1 21 1 27 1 44 1 44 1 53 0.8

30 - <40 143 4 161 4 149 5 182 5 185 5 200 5 263 5.7 354 5.8

40 - <50 621 18 681 19 489 17 628 17 603 18 749 18.6 824 18 1033 16.8

50 - <60 1054 31 1118 31 856 30 1079 30 1088 32 1250 30.8 1387 30.2 2011 32.8

60 - <70 881 26 961 26 769 27 933 26 811 24 999 24.6 1207 26.3 1558 25.4

70 - <80 571 17 592 16 469 16 596 17 540 16 658 16.3 687 15 915 15.0

≥ 80 129 4 113 3 100 4 155 4 147 4 147 3.7 177 3.8 203 3.4

Malay 1684 49 1740 48 1426 50 1787 50 1712 50 1991 49.2 2292 50 3176 51.8

Chinese 786 23 853 23 660 23 764 21 697 20 868 21.4 993 21.6 1313 21.5

Indian 799 23 847 23 601 21 866 24 780 23 897 22.3 883 19.2 1124 18.5

Orang asli 0 0 2 0 0 0 1 0 4 0 2 0 1 0 5 0.0

Kadazan 2 0 26 1 9 0 22 1 35 1 33 0.8 37 0.8 65 1.0

Melanau 0 0 0 0 2 0 2 0 3 0 4 0 1 0 5 0.0

Murut

1 0 1 0 1 0 4 0 6 0

Bajau 1 0 28 1 24 1 15 0 36 1 30 0.8 35 0.8 48 0.8

Bidayuh 28 1 12 0 15 1 9 0 6 0 17 0.5 24 0.6 39 0.6

Iban 48 1 41 1 31 1 35 1 19 1 42 1 70 1.6 72 1.2

Sikh 1 0 4 0 4 0 13 0 10 0 0 0 0 0 0 0

Other Malaysian

36 1 46 1 26 1 30 1 46 1 70 1.8 117 2.6 117 2

Foreigner 37 1 43 1 45 2 49 1 52 2 92 2.2 132 2.8 157 2.6

Not available 0 0 4 0 8 0

Data source: Annual Report of NCVD-ACS Registry 2007&2008 (page 9) Annual Report of NCVD-ACS Registry 2009&2010 (page 11) Annual Report of NCVD-ACS Registry 2011-2013(page 7)


34

Indicator: Number of cardiologist (Table 4 & Table 5)

Data table 2: Number of cardiologist

State 2009 2010 2011 2012 2013 2014

Johor 7 6 8 7 9 8

Kedah 3 6 6 5 6 8

Kelantan 3 2 2 3 2 2

WP Kuala Lumpur 43 52 52 49 65 63

Melaka 11 11 11 8 11 8

Negeri Sembilan 1 3 4 3 5 3

Pahang 2 1 2 2 2 5

Perak 11 10 10 12 11 13

Perlis 0 0 0 0 0 0

Pulau Pinang 19 19 19 26 28 28

Sabah & WP Labuan 4 3 3 4 4 5

Sarawak 12 9 9 9 9 10

Selangor 25 32 33 25 41 30

Terengganu 2 1 1 1 1 1

WP Putrajaya - - - - - -

Malaysia 143 155 160 154 194 184

Johor 3 5 5 2 6 2

Kedah 1 0 1 2 4 0

Kelantan 3 3 3 0 3 1

WP Kuala Lumpur 8 9 8 6 8 9

Melaka 0 0 0 0 0 0

Negeri Sembilan 0 0 0 0 0 0

Pahang 1 3 2 3 2 3

Perak 0 0 1 0 1 1

Perlis 0 0 0 0 0 0

Pulau Pinang 5 8 2 4 9 5

Sabah & WP Labuan 2 3 4 2 2 1

Sarawak 3 7 6 5 8 8

Selangor 6 9 7 7 7 4

Terengganu 0 0 0 1 3 1


Malaysia 32 47 39 32 53 35

Data WP Putrajaya is incorporated into Selangor Data source: NHEWS 2008-2009 (page 86) NHEWS 2012-2013 (page 60-61) Annual Report of NCVD-ACS Registry 2009-2010 (page 5) Annual Report of NCVD-ACS Registry 2011-2013(page 3)

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Indicator: Density of cardiologist (Table 4 & Table 5)

Data table 3: Density of cardiologist

State 2009 2010 2011 2012 2013 2014

Johor 0.03 0.33 0.38 0.03 0.43 0.028

Kedah 0.02 0.31 0.35 0.04 0.49 0.039

Kelantan 0.04 0.32 0.31 0.02 0.3 0.017

WP Kuala Lumpur 0.3 3.64 3.54 0.32 4.21 0.418

Melaka 0.14 1.34 1.32 0.09 1.29 0.094

Negeri Sembilan 0.01 0.29 0.38 0.03 0.47 0.027

Pahang 0.02 0.27 0.26 0.03 0.25 0.051

Perak 0.05 0.43 0.46 0.05 0.49 0.057

Perlis 0 0 0 0 0 0

Pulau Pinang 0.15 1.73 1.32 0.19 2.27 0.2

Sabah & WP Labuan 0.02 0.18 0.21 0.02 0.17 0.016

Sarawak 0.06 0.65 0.6 0.05 0.66 0.068

Selangor 0.06 0.75 0.72 0.06 0.84 0.058

Terengganu 0.02 0.1 0.09 0.02 0.36 0.017


Malaysia 0.06 0.71 0.69 0.06 0.83 0.073

2009, 2012 &2014 population per 10 000 2010, 2011 &2013 population per 100 000 Data WP Putrajaya is incorporated into Selangor

Data source: NHEWS 2008-2009 (page 86) NHEWS 2012-2013 (page 60-61) Annual Report of NCVD-ACS Registry 2009-2010 (page 5) Annual Report of NCVD-ACS Registry 2011-2013(page 3)


36

Indicator: Number of cardiothoracic surgeon (Table 4 & Table 5)

Data table 4: Number of cardiothoracic surgeon

State 2009 2010 2011 2012 2013

Johor 0 1 1 - 1

Kedah 0 0 0 - 0

Kelantan 0 0 0 - 0

WP Kuala Lumpur 14 19 22 - 21

Melaka 5 4 3 - 4

Negeri Sembilan 0 0 0 - 0

Pahang 0 0 0 - 0

Perak 1 1 1 - 2

Perlis 0 0 0 - 0

Pulau Pinang 6 8 9 - 8

Sabah & WP Labuan 0 0 0 - 1

Sarawak 1 1 1 - 1

Selangor 10 7 8 - 11

Terengganu 0 0 0 - 0

WP Putrajaya - - - - -

Malaysia 37 41 45 - 49

Johor 3 4 4 - 3

Kedah 0 0 0 - 0

Kelantan 2 2 2 - 3

WP Kuala Lumpur 3 5 5 - 5

Melaka 0 0 0 - 0


Pahang 0 0 0 - 1

Perak 0 0 0 - 0

Perlis 0 0 0 - 0

Pulau Pinang 3 3 2 - 6

Sabah & WP Labuan 0 1 2 - 1

Sarawak 1 2 2 - 4

Selangor 6 6 7 - 2



Malaysia 18 23 24 - 25

Data WP Putrajaya is incorporated into Selangor Data source: NHEWS 2008-2009 (page 86-87) NHEWS 2012-2013 (page 60-61, 72-73) Annual Report of NCVD-ACS Registry 2009-2010 (page 5)

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Indicator: Density of cardiothoracic surgeon (Table 4 & Table 5)

Data table 5: Density of cardiothoracic surgeon

State 2009 2010 2011 2012 2013

Johor 0.01 0.15 0.15 - 0.12

Kedah 0 0 0 - 0

Kelantan 0.01 0.13 0.12 - 0.18

WP Kuala Lumpur 0.1 1.43 1.59 - 1.5

Melaka 0.07 0.49 0.36 - 0.47


Pahang 0 0 0 - 0.06

Perak 0 0.04 0.04 - 0.08

Perlis 0 0 0 - 0

Pulau Pinang 0.06 0.7 0.69 - 0.86

Sabah & WP Labuan 0 0.03 0.06 - 0.06

Sarawak 0.01 0.12 0.12 - 0.19

Selangor 0.03 0.24 0.27 - 0.23



Malaysia 0.02 0.23 0.24 - 0.25

2009 population per 10 000 2010, 2011 &2013 population per 100 000 Data WP Putrajaya is incorporated into Selangor Data source: NHEWS 2008-2009 (page 87) NHEWS 2012-2013 (page 72-73)


38

Indicator: Number of Hospital with Catheterization Laboratory (Table 4 & Table 5)

Data table 6: Number of Hospital with Catheterization Laboratory in Malaysia by state and sector, 2012& 2014

Private Public

State 2012 2014 2012 2014

Malaysia 42 55 13 14

Perlis 0 0 0 0

Kedah 3 5 1 1

Pulau Pinang 7 9 1 1

Perak 3 3 1 1

Selangor & WP Putrajaya 9 14 2 2

WP Kuala Lumpur 8 9 2 3

Negeri Sembilan 2 2 0 0

Melaka 3 3 0 0

Johor 2 3 1 1

Pahang 1 1 1 1

Kelantan 1 1 1 1

Terengganu 0 0 1 1

Sabah & WP Labuan 0 1 1 1

Sarawak 3 4 1 1

Data source: NCVD 2009 &2010 (page 6) NCVD 2011 -2013 (page 4)


39

Data table 7: Population by states aged 15 years old and above

State 2010 2011 2012 2013 2014

Malaysia 20766700 21271000 21733400 22430000 22935000

Johor 2448900 2500900 2546500 2575100 22935000

Kedah 1378300 1407900 1442300 1487100 2665100

Kelantan 1049000 1081000 1113700 1143900 1516400

WP Kuala Lumpur 1306000 1325600 1337200 1356100 1180000

Labuan 61700 63100 64100 65100 1368000

Melaka 605500 618700 632900 645800 67200

Negeri Sembilan 751400 771500 784300 801600 661000

Pahang 1051800 1080700 1105800 1131900 811600

Perak 1733200 1768700 1802600 1838000 1157800

Perlis 173600 176100 178100 181100 1863300

Pulau Pinang 1213400 1243100 1267100 1308200 183700

WP Putrajaya 50200 51800 51400 51700 1325500

Sabah 2341000 2426600 2511500 2677100 51300

Sarawak 1768100 1814800 1859100 1936900 2735000

Selangor 4129800 4213900 4295000 4471700 4598200

Terengganu 704400 726700 741500 758800 783700

Sabah & WP Labuan 2402700 2489700 2575600 2742200 2802200

Data source: Department of Statistics Malaysia


40

Indicator: Admission rate of unstable angina (Table 7 & Table 8)

Data table 8: Number of admission for unstable angina (Aged 15 years old and above)

State 2010 2011 2012 2013 2014

Johor 3,374 3,542 2,875 3,403 3,189

Kedah 2,149 2,293 1,887 1,049 1,548

Kelantan 1,197 1,388 1,345 1,399 1,100

WP Kuala Lumpur 1,042 1,134 101 625 482

WP Labuan - - 83 50 59

Melaka 870 1,225 588 867 954

Negeri Sembilan 2,046 2,875 2,116 2,230 2,255

Pahang 1,347 1,611 1,188 1,637 1,751

Perak 3,404 3,643 1,849 2,382 2,375

Perlis 445 768 1,061 1,055 1,118

Pulau Pinang 1,869 1,958 472 1,216 1,143

WP Putrajaya - - - 85 133

Sabah 568 781 800 952 823

Sarawak 616 515 404 1,057 903

Selangor 3,829 4,212 2,580 2,779 3,323

Terengganu 1,535 1,789 1,558 1,617 1,563

Institusi 11 17 - - -

Malaysia 24,302 27,751 18,907 22,403 22,719

Johor 402 349 339 279 -

Kedah 229 386 246 268 -

Kelantan 39 51 23 21 -

WP Kuala Lumpur 206 189 297 511 -

WP Labuan 0 0 0 0 -

Melaka 163 194 224 158 -

Negeri Sembilan 56 102 98 108 -

Pahang 35 66 46 42 -

Perak 221 163 119 124 -

Perlis 0 0 0 0 -

Pulau Pinang 678 694 611 446 -


Sabah 2 4 3 9 -

Sarawak 65 60 95 62 -

Selangor 498 579 631 611 -

Terengganu 2 0 6 0 -

Institusi - - - - -

Malaysia 2,596 2,837 2,738 2,639 -

Data as of July 2015 Data source: Sistem Maklumat Rawatan Perubatan (SMRP)-unpublished

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Data table 9: Admission rate for unstable angina (Aged 15 years old and above) per 100 000 populations (Table 7 & Table 8)

State 2010 2011 2012 2013

Johor 154 156 126 143

Kedah 173 190 148 89

Kelantan 118 133 123 124

WP Kuala Lumpur 96 100 30 84

WP Labuan 0 0 129 77

Melaka 171 229 128 159


Pahang 131 155 112 148

Perak 209 215 109 136

Perlis 256 436 596 583


WP Putrajaya - - - 164

Sabah 24 32 32 36

Sarawak 39 32 27 58

Selangor 105 114 75 76

Terengganu 218 246 211 213

Malaysia 130 144 100 112



42

Indicator: Admission rate of STEMI (Table 7 & Table 8)

Data table 10: Number of admission for STEMI (Aged 15 years old and above)

State 2010 2011 2012 2013 2014

Johor 159 312 284 309 682

Kedah 612 260 257 53 329

Kelantan 116 192 359 390 393

WP Kuala Lumpur 148 132 25 125 213

WP Labuan - - 15 15 12

Melaka 78 108 109 186 139

Negeri Sembilan 44 67 168 235 314

Pahang 79 298 330 307 430

Perak 158 714 303 710 477

Perlis 3 14 6 31 90

Pulau Pinang 67 299 87 256 289

WP Putrajaya - - - 1 20

Sabah 85 151 216 235 285

Sarawak 206 113 101 300 395

Selangor 760 953 301 347 615

Terengganu 91 44 56 106 114

Institusi 0 1 - - -

Malaysia 2,606 3,658 2,617 3,606 4,797

Johor 37 33 25 28 -

Kedah 2 1 4 11 -

Kelantan 0 0 1 0 -

WP Kuala Lumpur 58 60 128 303 -

WP Labuan 0 0 0 0 -

Melaka 1 1 10 44 -


Pahang 7 6 5 4 -

Perak 27 26 48 56 -

Perlis 0 0 0 0 -

Pulau Pinang 157 238 235 168 -


Sabah 0 0 0 0 -

Sarawak 1 3 4 6 -

Selangor 70 124 198 229 -


Institusi - - - - -

Malaysia 1,483 2,405 2,866 4,064 -


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Data table 11: Admission rate for STEMI (Aged 15 years old and above) per 100 000 populations (Table 7 & Table 8)

State 2010 2011 2012 2013

Johor 8 14 12 13

Kedah 45 19 18 4

Kelantan 11 18 32 34

Kuala Lumpur 16 14 11 32

Labuan 0 0 23 23

Melaka 13 18 19 36


Pahang 8 28 30 27

Perak 11 42 19 42

Perlis 2 8 3 17


Putrajaya - - - 2

Sabah 4 6 9 9

Sarawak 12 6 6 16

Selangor 20 26 12 13

Terengganu 13 6 8 14

Malaysia 14 20 15 20



44

Indicator: Admission rate of NSTEMI (Table 7 & Table 8)

Data table 12: Number of admission for NSTEMI (Aged 15 years old and above)

State 2010 2011 2012 2013 2014

Johor 133 312 423 623 1,180

Kedah 119 288 241 25 235

Kelantan 3 11 18 90 116

WP Kuala Lumpur 44 26 3 33 223

WP Labuan - - 1 0 0

Melaka 226 137 245 320 499


Pahang 30 121 98 281 413

Perak 386 648 702 800 1,272

Perlis 0 0 4 150 177

Pulau Pinang 41 46 9 53 281

WP Putrajaya - - n.a 2 31

Sabah 19 70 175 91 157

Sarawak 63 51 49 274 352

Selangor 125 335 534 685 894

Terengganu 0 1 13 126 428

Institusi 1 1 - - -

Malaysia 1,483 2,405 2,866 4,064 6,968

Johor 0 4 17 33 -

Kedah 0 0 0 0 -

Kelantan 1 0 0 0 -


WP Labuan 0 0 0 0 -

Melaka 3 0 14 2 -


Pahang 2 0 0 2 -

Perak 79 78 53 40 -

Perlis 0 0 0 0 -

Pulau Pinang 51 90 76 69 -


Sabah 0 0 0 0 -

Sarawak 0 0 12 6 -

Selangor 28 4 5 28 -


Institusi - - - - -

Malaysia 172 179 230 425 -


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Data table 13: Admission rate for NSTEMI (Aged 15 years old and above) per 100 000 populations (Table 7 & Table 8)

State 2010 2011 2012 2013

Johor 5 13 17 25

Kedah 9 20 17 2

Kelantan 0 1 2 8

Kuala Lumpur 4 2 4 20

Labuan 0 0 2 0

Melaka 38 22 41 50


Pahang 3 11 9 25

Perak 27 41 42 46

Perlis 0 0 2 83


Putrajaya - - - 4

Sabah 1 3 7 3

Sarawak 4 3 3 14

Selangor 4 8 13 16

Terengganu 0 0 2 17

Malaysia 8 12 14 20



46

Indicator: UA/NSTEMI case fatality rate (Table 9)

Data table 14: Number of mortality for unstable angina

State 2010 2011 2012 2013 2014

Johor 210 258 148 189 21

Kedah 206 188 128 43 17

Kelantan 124 132 87 28 9


WP Labuan - - 1 1 0

Melaka 43 9 1 6 2


Pahang 72 77 32 33 9

Perak 350 353 80 27 7

Perlis 50 69 60 46 0

Pulau Pinang 241 217 57 79 3


Sabah 48 59 40 33 2

Sarawak 33 28 8 32 3

Selangor 199 172 34 17 8


Institusi 11 16 - - -

Malaysia 1,878 1,858 783 582 91

Johor 2 3 2 3 -

Kedah 2 0 8 5 -

Kelantan 2 3 0 0 -


WP Labuan 0 0 0 0 -

Melaka 1 4 0 0 -


Pahang 0 1 1 0 -

Perak 0 2 1 1 -

Perlis 0 0 0 0 -


WP Putrajaya 0 0 0 0 -

Sabah 0 0 0 0 -

Sarawak 1 0 0 0 -

Selangor 5 1 3 0 -


Institusi - - - - -

Malaysia 26 24 24 19 -


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Indicator: UA/NSTEMI case fatality rate (Table 9)

Data table 15: Number of mortality for NSTEMI

State 2010 2011 2012 2013 2014

Johor 13 37 45 74 122

Kedah 15 16 8 1 30

Kelantan 0 0 0 9 23


WP Labuan - - 0 0 0

Melaka 24 22 24 44 74


Pahang 7 17 7 8 37

Perak 35 44 49 103 129

Perlis 0 0 0 7 7



Sabah 1 7 15 4 22

Sarawak 3 5 5 10 25

Selangor 8 26 31 54 63


Institusi 1 0 - - -

Malaysia 138 213 203 377 686

Johor 0 0 0 0 -

Kedah 0 0 0 0 -

Kelantan 0 0 0 0 -


WP Labuan 0 0 0 0 -

Melaka 1 0 1 0 -


Pahang 0 0 0 0 -

Perak 3 1 1 1 -

Perlis 0 0 0 0 -



Sabah 0 0 0 0 -

Sarawak 0 0 0 0 -

Selangor 1 0 0 0 -


Institusi - - - - -

Malaysia 5 4 3 3 -


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Data table 16: UA/NSTEMI case fatality rate (Table 9)

State 2008 2009 2010 2011 2012 2013

Johor 6.0 6.1 5.8 7.1 5.3 6.1

Kedah 8.8 9.3 8.9 6.9 6.1 3.7

Kelantan 7.4 9.2 10.2 9.3 6.3 2.5

WP Kuala Lumpur 3.0 3.6 4.8 4.7 2.2 2.1

WP Labuan - - - - 1.2 2.0

Melaka 11.3 13.8 5.5 2.2 2.4 3.7

Negeri Sembilan 8.2 8.7 7.3 5.1 2.3 2.0

Pahang 3.4 5.4 5.6 5.3 3.0 2.1

Perak 15.1 11.5 9.5 8.8 4.8 3.9

Perlis 12.5 13.2 11.2 9.0 5.6 4.4

Pulau Pinang 5.9 10.2 9.5 8.2 5.7 4.7


Sabah 6.8 6.8 8.3 7.7 5.6 3.5

Sarawak 4.6 4.6 5.0 5.3 2.3 3.0

Selangor 6.8 7.8 4.8 3.9 1.8 1.7

Terengganu 6.5 4.0 5.9 4.8 3.7 1.7

Malaysia 8.1 8.5 7.2 6.3 4.1 3.3



49

Indicator: STEMI case fatality rate (Table 9)

Data table 17: Number of mortality for STEMI

State 2010 2011 2012 2013 2014

Johor 11 38 22 23 78

Kedah 61 19 16 5 48

Kelantan 7 16 26 29 26


WP Labuan - - 0 1 0

Melaka 7 14 6 18 36


Pahang 12 30 18 27 44

Perak 17 59 53 38 91

Perlis 0 0 0 1 3



Sabah 4 20 10 12 32

Sarawak 21 9 8 24 43

Selangor 67 72 18 21 43


Institusi 0 0 - - -

Malaysia 243 309 202 246 561

Johor 0 1 2 0 -

Kedah 0 0 0 0 -

Kelantan 0 0 0 0 -


WP Labuan 0 0 0 0 -

Melaka 0 0 1 0 -


Pahang 0 0 0 0 -

Perak 0 1 1 0 -

Perlis 0 0 0 0 -



Sabah 0 0 0 0 -

Sarawak 0 0 0 0 -

Selangor 2 4 3 5 -


Institusi - - - - -

Malaysia 8 14 16 19 -


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Data table 18: STEMI case fatality rate

State 2008 2009 2010 2011 2012 2013

Johor 1.8 6.4 5.6 11.3 7.8 6.8

Kedah 10.5 13.8 9.9 7.3 6.1 7.8

Kelantan 4.4 6.4 6.0 8.3 7.2 7.4

WP Kuala Lumpur 9.6 6.4 7.8 5.2 4.6 5.1

WP Labuan - - - - 0.0 6.7

Melaka 22.2 0.0 8.9 12.8 5.9 7.8

Negeri Sembilan 7.5 12.5 12.5 8.3 8.3 5.4

Pahang 10.2 9.5 14.0 9.9 5.4 8.7

Perak 2.5 5.4 9.2 8.1 15.4 5.0

Perlis 12.5 0.0 0.0 0.0 0.0 3.2

Pulau Pinang 10.1 8.1 5.4 3.5 3.1 3.8


Sabah 7.1 4.8 4.7 13.2 4.6 5.1

Sarawak 7.9 6.2 10.1 7.8 7.6 7.8

Selangor 12.7 9.7 8.3 7.1 4.2 4.5

Terengganu 11.0 3.8 8.8 11.4 5.3 9.4

Malaysia 9.4 8.2 8.5 7.8 6.7 5.9



51

Indicator: % of STEMI not given fibrinolytic therapy due to missed thrombolysis time (Table 6)

Data table 19: Percentage of STEMI patients receiving thrombolytic therapy within 30 minutes of presentation at the Emergency Department in 2013

Percentage of ST elevation Myocardial Infarction (STEMI)

patients receiving thrombolytic therapy within 30 minutes of

presentation at the Emergency Department

Non STEMI / Unstable Angina

Case Fatality Rate

STEMI Case

Fatality Rate

Indicator Data : 2013

≥ 70% ≤ 10% ≤ 15% Standard

173 2 21 Num Hospital Kuala

Lumpur 195 204 356 Deno

88.72% 0.98% 5.90% Perf

702 141 104 Num

Johor 761 5206 1508 Deno

92.25% 2.71% 6.90% Perf

40148 71 57 Num

Kedah 40270 2992 1187 Deno

99.70% 2.37% 4.80% Perf

467 46 54 Num

Kelantan 540 2281 706 Deno

86.48% 2.02% 7.65% Perf

18 0 2 Num

Labuan 18 51 28 Deno

100.00% 0.00% 7.14% Perf

186 42 45 Num

Melaka 202 2455 664 Deno

92.08% 1.71% 6.78% Perf

342 31 23 Num

N. Sembilan 351 2777 650 Deno

97.44% 1.12% 3.54% Perf

566 95 67 Num

Perak 657 3892 1343 Deno

86.15% 2.44% 4.99% Perf

2220 14 72 Num

Pahang 2354 1621 639 Deno

94.31% 0.86% 11.27% Perf

239 93 31 Num

Penang 279 2974 600 Deno

85.66% 3.13% 5.17% Perf

84 16 14 Num

Kangar 114 900 174 Deno

77.19% 2.40% 9.28% Perf


52

30 10 7 Num

Putrajaya 30 198 67 Deno

100.00% 4.40% 11.11% Perf

952 120 92 Num

Selangor 1077 6684 1448 Deno

88.39% 1.80% 6.35% Perf

189 23 35 Num

Terengganu 201 1621 432 Deno

94.03% 1.42% 8.10% Perf

283 19 29 Num

Sabah 299 1283 517 Deno

94.65% 1.48% 5.61% Perf

275 13 21 Num

Sarawak 353 947 324 Deno

77.90% 1.37% 6.48% Perf

Data source: Unit Survelan Pencapaian Klinikal, CKPP, BPP, Jan 2015 (Data 2013)

Indicator: % of STEMI not given fibrinolytic therapy due to missed thrombolysis time (Table 6)

Data table 20: Percentage of STEMI patients receiving thrombolytic therapy within 30 minutes of presentation at the Emergency Department in 2014

Percentage of ST elevation Myocardial Infarction (STEMI)

patients receiving thrombolytic therapy within (≤) 30 minutes of presentation at the Emergency

Department

Non STEMI / Unstable

Angina Case Fatality Rate

STEMI Case Fatality Rate

Indicator Data : 2014

≥ 85% ≤ 10% ≤ 15% Standard

37 0 5 Num

Perlis 47 0 76 Deno

78.72%

6.58% Perf

158 0 14 Num

Kelantan 168 0 203 Deno

94.05%

6.90% Perf

60 8 0 Num

Terengganu 64 478 196 Deno

93.75% 1.67% 0.00% Perf

408 0 2 Num

Selangor 432 0 206 Deno

94.44%

0.97% Perf

115 24 22 Num

Melaka 115 942 234 Deno

100.00% 2.55% 9.40% Perf


53

306 15 25 Num

Johor 332 657 247 Deno

92.17% 2.28% 10.12% Perf

213 6 12 Num

Kedah 234 470 160 Deno

91.03% 1.28% 7.50% Perf

69 11 8 Num

HKL 77 178 182 Deno

89.61% 6.18% 4.40% Perf

32 0 0 Num JKWPKL & Putrajaya

36 0 0 Deno

88.89%

Perf

2 0 0 Num

Labuan 2 0 0 Deno

100.00%

Perf

103 1 0 Num

N. Sembilan 104 216 3 Deno

99.04% 0.46% 0.00% Perf

65 2 13 Num

Pahang 67 171 182 Deno

97.01% 1.17% 7.14% Perf

229 12 4 Num

Perak 252 587 259 Deno

90.87% 2.04% 1.54% Perf

136 0 6 Num

Penang 151 0 240 Deno

90.07%

2.50% Perf

87 0 4 Num

Sabah 109 0 202 Deno

79.82%

1.98% Perf

113 2 8 Num

Sarawak 118 293 105 Deno

95.76% 0.68% 7.62% Perf

Data source: Unit Survelan Pencapaian Klinikal, CKPP, BPP, Jan 2015 (Data 2014)


54

Indicator: Median door-to-needle time (Table 6) Median door-to-balloon time

Data table 21: Door to needle and balloon time distribution for patients with STEMI by year, 2006-2013

Data source: Annual Report of NCVD-ACS Registry 2009-2010 (page 96) Annual Report of NCVD-ACS Registry 2011-2013 (page 85)

STEMI only

Year 2006 2007 2008 2009 2010 2011 2012 2013

Door-to-needle time, minutes

N 745 827 794 832 921 1009 960 1387

Mean (SD)

103 (143)

91 (131)

112 (195)

100 (186)

119 (217)

105.7 (201.8)

134.6 (240.1)

132.9 (226.9)

Median (min, max)

60 (2,1349)

53 (1,1435)

50 (1,1440)

45 (2,1440)

45 (3,1440)

40 (2,1390)

45 (1,1380)

49 (1,1440)

IQR 90 70 72 68 73 55 78.5 85

Door-to-balloon time, minutes

N 151 126 99 134 123 113 256 203

Mean (SD) 237

(292) 215

(266) 214

(260) 265

(338) 192

(224) 216.5 (252)

246.4 (321.1)

214.9 (301)

Median (min, max)

133 (35,1440)

112 (25,1410)

114 (11,1195)

119 (24,1391)

108 (13,1410)

120 (5,1305)

113.5 (15,1440)

104 (5,1440)

IQR 135 154 139 186 134 133 164 119


55

Indicator: Fibrinolytic therapy rate (%) (Table 6) Percutaneous Coronary Intervention (PCI) rate (%)

Data table 22: Summary of treatment for patients with ACS by ACS stratum, NCVD-ACS Registry, 2006-2010 (STEMI data ONLY)

Data source: Annual Report of NCVD-ACS Registry 2007 & 2008 (page 67) Annual Report of NCVD-ACS Registry 2009 & 2010 (page 84) Annual Report of NCVD-ACS Registry 2011 - 2013 (page 70)

STEMI only

Year 2006 2007 2008 2009 2010 2011 2012 2013

Fibrinolytic therapy, n (%)

Given 1018 (70)

1231 (73)

1143 (75)

1258 (75)

1347 (75)

1131 (80)

1109 (72)

1477 (74)

Given at another centre prior to transfer

- - - - - 446

(22.6) 577

(24.8) 747

(24.8)

Not given–proceeded directly to primary angioplasty

117 (8)

113 (7)

90 (6)

90 (5)

140 (8)

119 (6)

264 (11.3)

308 (10.2)

Not given-Contraindicated 70 (5) 63 (4) 56 (4) 82 (5) 64 (4) 63

(3.2) 92 (4)

130 (4.4)

Not given–Missed thrombolysis 193 (13)

226 (13)

168 (11)

201 (12)

202 (11)

216 (10.8)

279 (12)

332 (11)

Not given–Others** 47 (3) 54 (3) 77 (5) 50 (3) 49 (3) - - -

Not given–patients refusal - - - - - 7

(0.4) 8

(0.3) 19

(0.6)

Not applicable - - - - - 3 6 15

Not available - - - - - 11 11 26

Missing - - - - - 59 40 7

Total 1445 1687 1534 1681 1802 1982 2329 3013

PCI, n (%)

Yes 227 (21)

370 (18)

277 (17)

341 (20)

275 (15)

401 (24.2)

747 (34.6)

1070 (38)

No 965 (79)

1221 (82)

1133 (83)

1340 (80)

1527 (85)

1253 (75.8)

1409 (65.4)

1729 (61.2)

Unknown 253 (18)

96 (6)

124 (8)

- - - - -

Not applicable - - - - - - - 24

(0.8)

Missing - - - - - 401 230 238

Total 1445 1687 1534 1681 1802 2055 2386 3061


56

Indicator: 30-days all-cause mortality rate for registered STEMI patient after fibrinolytic therapy (Table 6)

Data table 23: Outcomes for patients with STEMI by fibrinolytic therapy

Outcome

In-hospital 30-day

Yes No Yes No

No. % No. % No. % No. %

2006 Alive 941 92 368 86 830 82 305 71

Died 77 8 59 14 188 18 122 29

2007 Alive 1123 91 390 86 1023 83 350 77

Died 108 9 66 14 208 17 106 23

2008 Alive 1045 91 343 88 993 87 314 80

Died 98 9 48 12 150 13 77 20

2009 Alive 1163 92 363 86 1130 90 345 82

Died 95 8 60 14 128 10 78 18

2010 Alive 1255 93 394 87 1213 90 377 83

Died 92 7 61 13 134 10 78 17

2011 Alive 1418 90 358 88.4 1402 89 349 86.2

Died 159 10 47 11.6 175 11 56 13.8

2012 Alive 1521 90.2 551 85.6 1508 89.4 540 84

Died 165 9.8 92 14.4 178 10.6 103 16

2013 Alive 2015 90.6 686 87 1990 89.4 676 85.6

Died 209 9.4 103 13 234 10.6 113 14.4

Data source: NCVD-ACS Registry 2009-2010 (page 117) NCVD-ACS Registry 2007-2008 (page 101) NCVD-ACS Registry 2011-2013 (page 106)


57

Indicator: 30 days all-cause mortality rate for registered STEMI patient after primary PCI (Table 6)

Data table 24: Outcomes for patients with STEMI by Percutaneous Coronary Intervention

Outcome

In-hospital 30-day

Yes No Yes No

No. % No. % No. % No. %

2006 Alive 282 92 1027 90 259 84 876 77

Died 26 8 110 10 49 16 261 23

2007 Alive 270 91 1243 89 253 85 1120 81

Died 27 9 147 11 44 15 270 19

2008 Alive 233 90 1155 91 218 84 1089 85

Died 25 10 121 9 40 16 187 15

2009 Alive 322 94 1204 90 316 93 1159 86

Died 19 6 136 10 25 7 181 14

2010 Alive 252 92 1397 91 247 90 1343 88

Died 23 8 130 9 28 10 184 12

2011 Alive 376 93.8 1096 87.4 366 91.2 1087 86.8

Died 25 6.2 157 12.6 35 8.8 166 13.2

2012 Alive 682 91.2 1235 87.6 673 90 1222 86.8

Died 65 8.8 174 12.4 74 10 187 13.2

2013 Alive 987 92.2 1523 88 972 90.8 1504 87

Died 83 7.8 206 12 98 9.2 225 13

Data source: NCVD-ACS Registry 2009-2010 (page 117) NCVD-ACS Registry 2007-2008 (page 101) NCVD-ACS Registry 2011-2013 (page 106)


58

Indicator: Prevalence of hypertension (Table 2)

Data table 25: Prevalence of overall, known and undiagnosed hypertension (Aged 18 years old and above)

Hypertension(%)

Overall Known Undiagnosed

2011 2015 2011 2015 2011 2015

Malaysia 32.7 30.3 12.8 13.1 19.8 17.2

Johor 36.4 27.4 14.0 11.2 22.4 16.2

Kedah 38.2 37.5 14.2 14.3 24.0 23.2

Kelantan 27.9 33.8 11.1 10.6 16.9 23.2

Melaka 32.8 25.8 16.0 13.1 16.9 12.7

Negeri Sembilan 34.1 32.5 15.1 16.1 19.0 16.4

Pahang 29.9 28.5 11.9 10.7 17.9 17.8

Penang 28.4 29.8 11.2 12.6 17.2 17.2

Perak 42.9 36.4 18.0 17.3 24.9 19.1

Perlis 41.1 35.4 12.8 14.2 28.3 21.1

Selangor 28.7 25.5 11.4 12.4 17.4 13.1

Terengganu 26.8 26.9 10.4 11.5 16.3 15.3

Sabah & WP Labuan 29.1 26.8 10.3 12.9 18.8 13.9

Sarawak 40.5 37.3 14.6 16.5 25.9 20.8

WP Kuala Lumpur 27.1 33.8 11.8 11.2 15.3 22.6

WP Putrajaya 22.5 24.1 9.8 10.0 12.7 14.1

Data source: NHMS 2011, Vol II (page 21-25) NHMS 2015, Vol II (page 33-37)


59

Indicator: Prevalence of hypercholesterolemia (Table 2)

Data table 26: Prevalence of overall, known and undiagnosed hypercholesterolemia (Aged 18 years old and above)

Hypercholesterolemia(%)


2011 2015 2011 2015 2011 2015

Malaysia 35.1 47.7 8.4 9.1 26.6 38.6

Johor 37.7 45.8 10.1 7.0 27.6 38.8

Kedah 43.4 53.5 7.9 7.4 35.5 46.1

Kelantan 33.8 51.7 3.6 5.3 30.2 46.5

Melaka 35.9 46.6 8.0 8.4 27.9 38.1

Negeri Sembilan 39.7 49.5 8.7 11.2 31.1 38.4

Pahang 31.7 56.2 6.5 6.1 25.2 50.2

Penang 32.7 52.2 7.9 12.2 24.8 40.1

Perak 45.0 48.3 13.8 11.8 31.2 36.5

Perlis 45.1 47.0 9.0 13.8 36.1 33.1

Selangor 31.9 43.5 8.5 9.5 23.5 34

Terengganu 34.9 52.1 4.4 7.7 30.4 44.4

Sabah & WP Labuan 31.1 40.9 5.3 8.3 25.8 32.6

Sarawak 33.5 48.6 8.9 12.6 24.6 36.1

WP Kuala Lumpur 29.4 52.9 10.8 8.6 18.6 44.4

WP Putrajaya 33.3 46.4 9.1 7.1 24.2 39.3

Data source: NHMS 2011, Vol II (page 27-31) NHMS 2015, Vol II (page 39-43)


60

Indicator: Prevalence of diabetes mellitus (Table 2)

Data table 27: Prevalence of overall, known and undiagnosed diabetes mellitus (Aged 18 years old and above)

Diabetes Mellitus(%)


2006 2011 2015 2006 2011 2015 2006 2011 2015

Malaysia 11.6 15.2 17.5 7 7.2 8.3 4.5 8 9.2

Johor 11.1 13.4 19.8 7 7.6 8.8 4.1 5.9 11

Kedah 13.6 22.5 25.4 9.3 9.1 9.3 4.3 13.4 16.1

Kelantan 11.7 19.7 18.5 6.8 8 7.1 4.9 11.7 11.3

Melaka 15.2 17.1 16.7 11.4 10.4 8.3 3.9 6.6 8.4

Negeri Sembilan 15.3 22 19.3 8.8 11.5 10.5 6.6 10.5 8.8

Pahang 12.1 16.7 14.8 8.1 8.6 6.3 4 8.1 8.6

Penang 14.9 15 18.1 8.9 8.5 9 6 6.4 9.1

Perak 12.6 16.2 19.4 7.6 10.1 11.9 5 6.1 7.4

Perlis 13.5 24.8 20.6 8 8.7 10.9 5.5 16.1 9.7

Selangor 12 16.5 15.5 8.3 6.5 7.8 3.8 10.1 7.7

Terengganu 11.1 11.6 18.6 5.7 7.1 8.7 5.4 4.5 9.9

Sabah 4.9 9 14.2 2.4 2.6 5.9 2.5 6.4 8.3

Sarawak 10 12.3 14.8 4.1 5.1 8.3 6 7.3 6.6

WP Kuala Lumpur 12.6 11.3 17.4 6.6 7.2 8.1 6 4.1 9.3

WP Labuan 7.9 - - 4.8 - - 3.2 - -

WP Putrajaya - 8.8 19.2 - 4.6 5.3 - 4.2 13.9

Data source: NHMS 2006, Vol II (page 254-263) NHMS 2011, Vol II (page 13-17) NHMS 2015, Vol II (page 25-30)


61

Indicator: Prevalence of obesity (Table 2)

Data table 28: Prevalence of obesity (Aged 18 years old and above)

Obesity (BMI ≥ 27.5 kg/m2)

2006 2011 2015

Malaysia 14 27.2 30.6

Johor 14.1 28.6 29.8

Kedah 15.5 28.2 33.2

Kelantan 12.5 29.4 28.8

Melaka 17.4 29.3 36

Negeri Sembilan 18.6 28.2 35.6

Pahang 15.3 28.2 32.5

Penang 13.7 26.9 27.8

Perak 12.9 30.1 29.5

Perlis 17.2 34.6 36

Selangor 16 28.2 32.7

Terengganu 15.2 28.1 32.5

Sabah 9.7 21.1 23.9

Sarawak 11.5 26.7 32.3

WP Kuala Lumpur 12.5 22.8 29.6

WP Labuan 14.6 - -

WP Putrajaya - 27.4 43

Data source: NHMS 2006, Vol II (page 780) NHMS 2011, Vol II (page 57) NHMS 2015, Vol II (page 59)


62

Indicator: Prevalence of current tobacco smoker (Table 3)

Data table 29: Prevalence of current tobacco smoker (Aged 18 years old and above)

Current Tobacco Smoker (%)

2006 2011 2015

Johor 20.7 19.9 22.2

Kedah 25.6 21.7 26.5

Kelantan 27.3 18.7 24.6

Melaka 20 17.1 16.9

Negeri Sembilan 23.3 19.4 20.9

Pahang 27.4 20.6 25.5

Penang 18.5 16.5 19.2

Perak 20.9 16.1 21.0

Perlis 33.1 22.6 22.2

Selangor 18.1 18.8 20.9

Terengganu 26.5 20.5 22.2

Sabah & WP Labuan - 23.0 28.4

Sarawak 19.3 19.1 25.4

WP Kuala Lumpur 15.7 17.4 19.1

WP Putrajaya - 15.6 12.4

Data in 2011 for aged 10 years old and above Data source: NHMS 2006, Vol II (page 614) NHMS 2011, Vol III (page 127) NHMS 2015, Vol II (page 92)


63

Data table 30: Cardiovascular disease, estimated mortality rates (per 100 000), 2012

Country 2012

Korea, Rep. 89.5

Sweden 167.3

Japan 96.5

Finland 170.5

Israel 98.6

Austria 176.4

Canada 104.8

Thailand 180.2

Singapore 110.1

Cambodia 187.0

France 111.8

Greece 195.3

Australia 112.1

Solomon Islands 202.8

Spain 116.9

Viet Nam 210.1

New Zealand 119.0

Nepal 233.6

Netherlands 120.3

Asia-20 241.6

Switzerland 121

Pakistan 243.4

Chile 122.4

Sri Lanka 258.0

Denmark 123.1

Czech Republic 258.8

Portugal 124.8

Malaysia 265.6

Luxembourg 127.2

Poland 274.8

Italy 129.7

India 284.4

Ireland 129.8

China 286.1

Papua New Guinea 130.0

Myanmar 286.4

United Kingdom 130.3

Turkey 286.7

Iceland 132.9

Estonia 288

Belgium 134.5

Lao PDR 302.1

Norway 139.9

Korea, DPR 304.6

Mexico 149.8

Hungary 315.4

Bangladesh 155.2

Slovakia 320.8

Slovenia 155.6

Fiji 322.0

Brunei Darussalam

157.6

Philippines 335.0

United States 158.3

Indonesia 336.0

Germany 158.6

Mongolia 510.7

OECD 160.6

Age standardized Source: WHO Global Burden of Disease, 2014; Department of Health, Hong Kong, China, 2014; Disease Registry, Macao, China, 2014.


64

Data table 31: Prevalence of daily smoker male, 2015 (or nearest year)

Country 2015

Australia 14.7

Korea 36.6

Austria 26.5

Latvia 37

Belgium 21.6

Luxembourg 16

Canada 16.3

Mexico 11.9

Czech Republic 26.4

Netherlands 21.7

Denmark 16

New Zealand 16.1

Estonia 31.4

Norway 13

Finland 17.2

Poland 28.8

France 25.8

Portugal 23.5

Germany 25.1

Slovak Republic 30.4

Greece 33.8

Slovenia 21.8

Hungary 31.6

Spain 27.6

Iceland 10.2

Sweden 12.1

Ireland 20

United Kingdom 22

Israel 23.2

United States 14

Italy 24.9

OECD-32 22.8

Japan 32.2

Source: stats.oecd.org

Data table 32: Prevalence of daily smoker female, 2015 (or nearest year)

Country 2015

Australia 11.3

Korea 4

Austria 22.1

Latvia 14.6

Belgium 16.4

Luxembourg 13.9

Canada 11.7

Mexico 3.6

Czech Republic 18.5

Netherlands 16.7

Denmark 17

New Zealand 13.9

Estonia 15.8

Norway 13

Finland 14

Poland 17.2

France 19.4

Portugal 10.9

Germany 17.1


Greece 21.4

Slovenia 16

Hungary 20.8

Spain 18.6

Iceland 10.7

Sweden 11.7

Ireland 17

United Kingdom 17

Israel 11.4

United States 11.8

Italy 15.8

OECD-32 16.3

Japan 8.5


http://stats.oecd.org/OECDStat_Metadata/ShowMetadata.ashx?Dataset=HEALTH_LVNG&Coords=%5bCOU%5d.%5bDEU%5d&ShowOnWeb=true&Lang=en

http://stats.oecd.org/OECDStat_Metadata/ShowMetadata.ashx?Dataset=HEALTH_LVNG&Coords=%5bCOU%5d.%5bISR%5d&ShowOnWeb=true&Lang=en


65

Data table 33: Prevalence of obesity, 2014 (or nearest year)

Country 2014

Austria 14.7

Korea 2.6

Belgium 14

Latvia 21.3

Canada 19.6

Luxembourg 15.6

Czech Republic 19.3

Netherlands 13.3

Denmark 14.9

Poland 17.2

Estonia 20.4

Portugal 16.6

Finland 18.3


France 15.3

Slovenia 19.2

Germany 16.9

Spain 16.7

Greece 17.3

Sweden 14

Hungary 21.2

Turkey 19.9

Ireland 23

United Kingdom 20.1

Israel 17.8

United States 29.5

Italy 10.3

OECD-27 17.2


Data table 34: Prevalence of diabetes, 2015

Country 2015

Australia 5.1

Korea, Rep. 7.2

Austria 6.9

Luxembourg 4.7

Belgium 5.1

Mexico 15.8

Canada 7.4

Netherlands 5.5

Chile 10

New Zealand 7.3

Czech Republic 7.4

Norway 6

Denmark 7.2

Poland 6.2

Estonia 4.4

Portugal 9.9

Finland 6

Slovak Republic 7.8

France 5.3

Slovenia 7.8

Germany 7.4

Spain 7.7

Greece 5.2

Sweden 4.7

Hungary 7.3

Switzerland 6.1

Iceland 6.1

Turkey 12.8

Ireland 4.4

United Kingdom 4.7

Israel 7.5

United States 10.8

Italy 5.1

OECD-34 7.01

Japan 5.7

Source: IDF 2015 (page 112)


66

Data table 35: In-hospital case-fatality rates within 30 days after admission for AMI, 2011 (or nearest year)

Country 2011

Denmark 3.0

Belgium 7.6

New Zealand 4.5

Slovak Republic 7.6

Norway 4.5

Austria 7.7

Sweden 4.5

United Kingdom 7.8

New Zealand 4.5

OECD-32 7.9

Australia 4.8

Portugal 8.4

Poland 5.2

Spain 8.5

United States 5.5

Luxembourg 8.8

Canada 5.7

Germany 8.9

Iceland 5.7

Korea 8.9

Italy 5.8

Philippines 8.9

Switzerland 5.9

Malaysia 9.7

France 6.2

Turkey 10.7

Czech Republic 6.8

Chile 10.8

Ireland 6.8

Japan 12.2

Netherlands 6.8

Singapore 12.5

Finland 7.0

Hungary 13.9

Slovenia 7.0

Mexico 27.2

Israel 7.1

Age and sex standardized Source: Health at a Glance 2014 (page 93)

Data table 36: 30 day mortality after admission to hospital for AMI based on admission data, 2013

Country 2013

Australia 4.1

Korea 8.3

Austria 10

Latvia 15.4

Canada 6.7

Mexico 28.2

Czech Republic 6.7

New Zealand 6.6

Denmark 5.7

Norway 6.7

Estonia 11.5

Poland 4.7

Finland 6.5

Portugal 9.4

France 7.2

Slovenia 5.2

Germany 8.7

Spain 7.8

Ireland 6.4

Sweden 4.5

Israel 6.7

United Kingdom 7.6

Italy 5.5

OECD-23 8.3

Age and sex standardized Source: stats.oecd.org


67

INDICATOR OPERATIONAL DEFINITION

No. Indicator Numerator Denominator Constant

1 Density of Cardiologist by state and year

Number of Cardiologist by state and year

Total midyear population

per 1 000 000

2 Density of Cardio-thoracic surgeon by state and year

Number of Cardio-thoracic surgeon by state and year

Total midyear population

per 1 000 000

3

% of ST elevation Myocardial Infarction (STEMI) patients receiving thrombolytic therapy within 30 minutes of presentation at the Emergency Department

Number of patients with STEMI who received thrombolytic therapy < 30 minutes of presentation in the Emergency Department

Patients with STEMI who received thrombolytic therapy

per 100

4

% of STEMI not given fibrinolytic therapy due to missed thrombolysis time

Number of patients who had STEMI not given fibrinolytic therapy due to missed thrombolysis time

Total number of patients who had STEMI

per 100

5 Rate of fibrinolytic therapy

Number of fibrinolytic therapy


per 100

6 Rate of primary PCI Number of primary PCI Total number of patients who had STEMI

per 100

7 Admission rate for unstable angina (UA)

Total number of hospital discharge with UA

Total midyear populations of 15 years old and above

per 100 000

8 Admission rate for STEMI

Total number of hospital discharge with STEMI


per 100 000

9 Admission rate for NSTEMI

Total number of hospital discharge with NSTEMI


per 100 000

10 30-day case fatality rate for STEMI

Total number of patients who died within 30 days post STEMI


per 100


68

11 30-day case fatality rate for AMI

Total number of patients who died within 30 days post STEMI/ NSTEMI

Total number of patients who had STEMI/ NSTEMI

per 100

13 STEMI case fatality rate

Number of patients admitted with STEMI and died in hospital

Total number of STEMI hospital discharge cases

per 100

14 UA/NSTEMI case fatality rate

Number of patients admitted with NSTEMI and died in hospital

Total number of NSTEMI /UA hospital discharge cases

per 100

15 Prevalence of hypertension

Number of persons with known and undiagnosed hypertension


per 100

16 Prevalence of hypercholesterolemia

Number of persons with known and undiagnosed hypercholesterolemia


per 100

17 Prevalence of diabetes Total number of persons with known and undiagnosed diabetes


per 100

18 Prevalence of obesity Number of persons with obesity (BMI ≥ 27.5 OR BMI ≥ 30.0)


per 100

19 Prevalence of daily tobacco smoker, male

Number of male who reported daily tobacco smoking


per 100

20 Prevalence of daily tobacco smoker, female

Number of female who reported daily tobacco smoking


per 100


69

Documents

Cardiac Care Performance Report: Acute Coronary Care