NMCS PRIMARY CARE 2012 FullReport

National Medical Care Statistics 2012

March 2014

©Ministry of Health Malaysia

Published by

The National Healthcare Statistics Initiative (NHSI) National Clinical Research Centre

National Institutes of Health 3rd Floor, MMA House 124, Jalan Pahang 53000 Kuala Lumpur Malaysia

Tel : (603) 4043 9300/9400 Fax : (603) 4043 9500 Email : hsu@crc.gov.my

Website : http://www.crc.gov.my/nhsi

This report is copyrighted. Reproduction and dissemination of this report in part or in whole for research, educational or non-commercial purposes is authorised without any prior written permission from the copyright holders provided that the source is fully acknowledged.

Suggested citation:

Sivasampu S, Yvonne Lim, Norazida AR, Hwong WY, Goh PP, Hisham AN. National Clinical Research Centre. National Medical Care Statistics (NMCS) 2012. Kuala Lumpur 2014.

This report is also available electronically on the website of the National Healthcare Statistics Initiative at http://www.crc.gov.my/nhsi

Funding:

The National Healthcare Statistics Initiative was funded by a grant from Ministry of Health Malaysia (MRG Grant No. NMRR-09-842-4718)

✏✑ ✑ ✒ ✓ ✓ ✔ ✕ ✖ ✗✔ ✗ ✗

✕ ✘ ✘ ✓ ✓ ✔ ✕ ✗ ✔ ✗ ✙ ✙ ✔

Please note that there is potential for minor corrections of data in this report.

LIST OF TABLES iv

LIST OF FIGURES vi

ACKNOWLEDGEMENTS vii

NATIONAL MEDICAL CARE SURVEY 2012 PROJECT TEAM viii

ABBREVIATIONS ix

SYMBOLS x

EXECUTIVE SUMMARY 1

CHAPTER 1 : INTRODUCTION 5

1.1 Background 6

1.2 Objectives 6

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1.4 Research questions 7

CHAPTER 2 : METHODOLOGY 9

2.1 Sampling frame and sample size calculation 10

2.2 Survey dates 12

2.3 Data collection and follow-up 12

2.4 Research pack and questionnaire 13

2.5 Data management 13

2.6 Data analysis 17

2.7 Ethical issues 18

2.8 Limitations 18

CHAPTER 3 : RESPONSE RATE 19

3.1 The encounters 21

CHAPTER 4 : THE DOCTORS 23

4.1 Characteristics of the doctors 24

CHAPTER 5 : THE PATIENTS 27

5.1 Age-gender distribution of patients 28

5.2 Patient socio-demographic characteristics 28

5.3 Mode of payment 30

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CHAPTER 6 : REASONS FOR ENCOUNTER 33

6.1 Number of reasons for encounter per visit 34

6.2 Reasons for encounter by ICPC-2 components 34

6.3 Reasons for encounter by ICPC-2 chapters 36

6.4 Most common reasons for encounter in public and private clinics 38

CHAPTER 7 : DIAGNOSES 41

7.1 Number of diagnoses per encounter 42

7.2 Diagnoses by ICPC-2 component 43

7.3 Diagnoses by ICPC-2 chapter 44

7.4 Most common diagnoses managed in public and private clinics 46

CHAPTER 8 : MEDICATIONS 49

8.1 Number of medications prescribed per encounter 50

8.2 Type of medications prescribed 52

8.3 Most frequently prescribed medications in public and private clinics 58

CHAPTER 9 : INVESTIGATIONS 61

9.1 Number of investigations per encounter 62

9.2 Types of investigations 63

9.3 Investigations most frequently ordered in public and private clinics 67

9.4 Diagnoses with investigations ordered 69

CHAPTER 10: ADVICE/COUNSELLING AND PROCEDURES 71 10.1 Number of advice/counselling and procedures 72

10.2 Types of advice and counselling 72

10.3 Most common advice/counselling provided in public and

private clinics 74

10.4 Types of procedures 75

10.5 Most common procedures performed in public and private clinics 76 10.6 Diagnoses with advice/counselling and procedures 77

CHAPTER 11: FOLLOW-UPS AND REFERRALS 79

11.1 Number of follow-ups and referrals 80

11.2 Types of referrals 81

11.3 Diagnoses most frequently referred to hospital 82 11.4 Diagnoses most frequently referred to a specialist 83 APPENDICES

Appendix 1: NMCS 2012 Survey Form 86

Appendix 2: ICPC-2 and ICPC-2 PLUS Groups 88

Appendix 3: Participants of NMCS 2012 92

LIST OF TABLES

Table 2.1 Sample size for NMCS 2012 11

Table 2.2 Data entry error rate for NMCS 2012 14

Table 3.1 Total clinics sampled and responded for NMCS 2012 20

Table 3.2 Response rate for NMCS 2012 20

Table 3.3 Observed and weighted dataset for NMCS 2012 21

Table 4.1 Characteristics of doctors for NMCS 2012 24

Table 5.1 Characteristics of patient encounters in primary care clinics in 2012 29 Table 5.2 Duration of sick leave issued in primary care clinics in 2012 31 Table 6.1 Reasons for encounter by ICPC-2 components in primary care clinics in 2012 35 Table 6.2 Reasons for encounter by ICPC-2 components and sector 35 Table 6.3 Reasons for encounter by ICPC-2 chapters and common individual reasons

for encounter within chapter in primary care clinics in 2012 36 Table 7.1 Diagnoses by ICPC-2 components in primary care clinics in 2012 43 Table 7.2 Diagnoses by ICPC-2 chapters and common individual diagnoses

within chapter managed in primary care clinics in 2012 44 Table 7.3 Thirty most common diagnoses managed in public clinics in 2012 47 Table 7.4 Thirty most common diagnoses managed in private clinics in 2012 48 Table 8.1 Number of encounters for which medication was prescribed 50 Table 8.2 Prescribed medications by ATC level 1, 3 and 5 in primary care clinics in 2012 52 Table 8.3 Prescribed medications by ATC level 1 and sector in primary care clinics in 2012 57 Table 8.4 Thirty most frequently prescribed medications in public clinics in 2012 59 Table 8.5 Thirty most frequently prescribed medications in private clinics in 2012 60 Table 9.1 Types of investigations by ICPC-2 chapters and common individual test

within chapter in primary care clinics in 2012 63

Table 9.2 Top 10 diagnoses for which investigation was most frequently ordered

in primary care clinics in 2012 69

Table 10.1 Advice/counselling and procedures in primary care clinics in 2012 72 Table 10.2 Types of advice/counseling provided in primary care clinics in 2012 73

Table 10.3 Types of procedures performed in primary care clinics in 2012 74 Table 10.4 Ten most common diagnoses with advice/counseling

in primary care clinics in 2012 77

Table 10.5 Ten most common diagnoses with procedures in primary care clinics in 2012 78 Table 11.1 Follow-up and referrals in primary care clinics in 2012 80 Table 11.2 Types of referrals in public clinics in 2012 81 Table 11.3 Types of referrals in private clinics in 2012 82 Table 11.4 Diagnoses most frequently referred to hospital in 2012 83 Table 11.5 Diagnoses most frequently referred to specialist in 2012 84

Figure 5.1 Age-gender distribution of patients in primary care clinics in 2012 28 Figure 5.2 Mode of payment in primary care clinics in 2012 30 Figure 5.3 3HUFHQWDJHRISULPDU\FDUHHQFRXQWHUVLVVXHGPHGLFDOFHUWLÀFDWHLQ Figure 6.1 Number of patient reasons for encounter in primary care clinics in 2012 34 Figure 6.2 Top 10 reasons for encounter in public clinics in 2012 38 Figure 6.3 Top 10 reasons for encounter in private clinics in 2012 39 Figure 7.1 Number of diagnoses managed per encounter in primary care clinics in 2012 42 Figure 7.2 $JHJHQGHUVSHFLÀFUDWHVRIGLDJQRVHVPDQDJHGSHUHQFRXQWHUV

by sector in 2012 43

Figure 8.1 Number of medications prescribed per encounter in primary care clinics in 2012 50 Figure 8.2 $JHJHQGHUVSHFLÀFSUHVFULSWLRQUDWHVSHUHQFRXQWHUVE\VHFWRULQ Figure 9.1 Number of investigations ordered per encounter in primary care clinics in 2012 62 Figure 9.2 Top 10 investigations ordered in public clinics in 2012 68 Figure 9.3 Top 10 investigations ordered in private clinics in 2012 68 Figure 10.1 Ten most common advice/counseling provided in public clinics in 2012 74 Figure 10.2 Ten most common advice/counseling provided in private clinics in 2012 74 Figure 10.3 Ten most common procedures performed in public clinics in 2012 76 Figure 10.4 Ten most common procedures performed in private clinics in 2012 76

Acknowledgements

The National Healthcare Statistics Initiative team would like to thank the Director-General of Health, Malaysia for his continuous support for this survey and permission to publish this report.

Also, our sincere appreciation goes to the following for their participation, assistance, support and contribution:

‡ 'HSXW\'LUHFWRU*HQHUDORI+HDOWK5HVHDUFKDQG7HFKQLFDO6XSSRUW0LQLVWU\RI+HDOWK02+

‡ 'HSXW\'LUHFWRU*HQHUDORI+HDOWK0HGLFDO02+

‡ 'HSXW\'LUHFWRU*HQHUDORI+HDOWK3XEOLF+HDOWK02+

‡ 'LUHFWRURIWKH&OLQLFDO5HVHDUFK&HQWUH1DWLRQDO,QVWLWXWHVRI+HDOWK02+

‡ 'LUHFWRURIWKH)DPLO\+HDOWK'HYHORSPHQW'LYLVLRQ02+

‡ 'LUHFWRURIWKH3ODQQLQJDQG'HYHORSPHQW'LYLVLRQ02+

‡ 'LUHFWRURIWKH3ULYDWH0HGLFDO3UDFWLFH'LYLVLRQ02+&DZDQJDQ.DZDODQ$PDODQ3HUXEDWDQ

Swasta, CKAPS)

‡ 6WDWHOHYHO3ULYDWH0HGLFDO3UDFWLFH&RQWURO8QLWV8QLW.DZDODQ$PDODQ3HUXEDWDQ6ZDVWD

UKAPS).

‡ 0DOD\VLDQ 0HGLFDO &RXQFLO 0DOD\VLDQ 0HGLFDO $VVRFLDWLRQ $FDGHP\ RI )DPLO\ 3K\VLFLDQV Malaysia.

We thank the 392 medical doctors from both the public and private primary healthcare clinics who participated in the National Medical Care Survey (NMCS) between August and November 2012. This report would not have been possible without their support and contribution from these dedicated professionals.

Last but not least, our greatest appreciation to all those who have supported or contributed to the success of the National Medical Care Survey 2012 and the publication of this report.

Thank you.

National Healthcare Statistics Initiative (NHSI) Primary Care Team Healthcare Statistics Unit

National Clinical Research Centre Ministry of Health, Malaysia

NATIONAL MEDICAL CARE SURVEY 2012 PROJECT TEAM Principal Investigator Datuk Dr. Noor Hisham Abdullah

Principal Co-Investigator

Dr. Sheamini Sivasampu Dr. Goh Pik Pin

Research Evaluation Committee (REC)

Dr. Kamaliah Mohd. Noh Professor Dr. Khoo Ee Ming

Associate Professor Dr. Ng Chirk Jenn 3URIHVVRU'U7DXÀN7HQJ&KHRQJ/LHQJ Dr. Kaviyarasan Sailin

Associate Professor Dr. Jamaluddin Abdul Rahman Ms. Siti Fauziah Abu

Project Managers

Mr. Lim Ka Keat (September 2011 – September 2012) Ms. Yvonne Lim Mei Fong

Dr. Hwong Wen Yea, Amy

Survey Coordinators Ms. Aisyah Ali

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Ms. Sharmini Chandran

Mr. Shantha Kumar Chandrasekaran Ms. Kasturi Manoharan

Ms. Siti Aminah Ismail Ms. Hanan Hamimi Wahid Ms. Maryam Nazeera Suhaimi

Mr. Poovanesva Rao Yang Ketter Rahman

Data Analysis

Ms. Norazida Ab. Rahman Ms. Yvonne Lim Mei Fong Database Developers/Administrators Altus Solutions Sdn. Bhd.

ACE Angiotensin converting enzyme

ATC :+2$QDWRPLFDO7KHUDSHXWLF&KHPLFDO&ODVVLÀFDWLRQV\VWHP BEACH Bettering the Evaluation and Care of Health

CI &RQÀGHQFH,QWHUYDO

CKAPS Cawangan Kawalan Amalan Perubatan Swasta

DG Director General of Health, Ministry of Health, Malaysia FMS Family Medicine Specialist

GP General Practice or Practitioner HbA1c Haemoglobin, type A1c

ICPC ,QWHUQDWLRQDO&ODVVLÀFDWLRQRI3ULPDU\&DUH IQR Interquartile range

KK Klinik Kesihatan

LCL /RZHU&RQÀGHQFH/LPLW

MOH Ministry of Health, Malaysia

MREC Medical Research and Ethics Committee, Ministry of Health Malaysia NCD Non-communicable disease

NCRC National Clinical Research Centre

NHEWS National Healthcare Establishment & Workforce Survey (Primary Care) NHSI National Healthcare Statistics Initiative

NIH National Institutes of Health NMCS National Medical Care Survey NMUS National Medicines Use Survey

NOS 1RWRWKHUZLVHVSHFLÀHG

REC Research Evaluation Committee RFEs Reasons for encounter

SOCSO Social Security Organisation

UCL 8SSHU&RQÀGHQFH/LPLW

UKAPS Unit Kawalan Amalan Perubatan Swasta WHO World Health Organisation

WONCA World Organization of National Colleges, Academies and Academic Associations of General Practitioners/Family Physicians

WP Wilayah Persekutuan

- Not applicable > More than

• More than or equal to < Less than

% Percentage

EXECUTIVE SUMMARY

The National Medical Care Survey (NMCS) is a provider-based survey, which aims to study the characteristics and morbidity pattern of patients, as well as healthcare activities in terms of investigations, procedures, counselling and visit disposition provided at primary care level in Malaysia.

7KLVVWXG\FRYHUHGSXEOLFDQGSULYDWHFOLQLFVIURPÀYHVHOHFWHGUHJLRQVLQ0DOD\VLD:3.XDOD/XPSXU 6HODQJRU :33XWUDMD\D.HODQWDQ.XFKLQJDQG.RWD.LQDEDOX7KHFOLQLFVZHUHVWUDWLÀHGDFFRUGLQJ to region and sector, and selected through random sampling. Doctors from these clinics were asked to JLYHGHWDLOVRQSDWLHQWVWKH\VDZRQRQHVSHFLÀFGD\ZKLFKZDVUDQGRPO\DOORFDWHGEHWZHHQ$XJXVWWR November 2012.

This report presents data collected from 69 public clinics and 120 private clinics. Doctors working at primary care clinics

A total of 408 doctors participated in NMCS 2012; 259 (63.5%) from public clinics and 149 (36.5%) from private clinics. Of these, 350 doctors provided their socio-demographic details (229 public doctors and 121 private doctors).

‡ RIWKHUHVSRQGHQWVZHUHIHPDOHV+LJKHUSURSRUWLRQRIIHPDOHVZDVVHHQLQSXEOLF clinics (76.4%; 175/229) as compared to private clinics (39.7%; 48/121).

‡ $OPRVWKDOIRIWKHGRFWRUVLQSXEOLFFOLQLFVDQGLQSULYDWHFOLQLFVDJHGEHWZHHQWR 39 years old. On the contrary, 62.8% of the doctors in private clinics and 6.9% in public clinics were over 50 years old.

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Patients seen at primary care clinics

There were 141,593 patient encounters recorded for NMCS 2012; 42,340 encounters (29.9%) were from public clinics and 99,253 encounters (70.1%) from private clinics.

‡ RIWKHSDWLHQWVVHHQZHUHIHPDOHVLQSXEOLFFOLQLFVDQGLQSULYDWHFOLQLFV ‡ 7KHPHGLDQDJHRISDWLHQWVZDV\HDUVDQGWKHDJHGLVWULEXWLRQZHUHDVIROORZV,QIDQWV\HDU

\HDUV\HDUV\HDUV\HDUVDQG•\HDUV (11.5%).

‡ 7KH DJH GLVWULEXWLRQV RI SDWLHQWV VHHQ LQ SXEOLF DQG SULYDWH FOLQLFV ZHUH VLPLODU EXW D ODUJHU percentage of older patients were seen in public clinics where 20.7% of patients in public clinics and RISDWLHQWVLQSULYDWHFOLQLFVZHUH•\HDUVROG

‡ 0DMRULW\ RI SDWLHQWV VHHQ ZHUH 0DOD\ IROORZHG E\ &KLQHVH ,QGLDQ DQG others (5.6%).

‡ RISDWLHQWVVHHQLQSULYDWHFOLQLFVSDLGRXWRISRFNHWDQGSDLGE\WKLUGSDUW\SD\HUV such as insurance. Visits to public clinics were all subsidised by government with a minimal charge of RM1 per encounter and is free for patients older than 60 years.

‡ 0HGLFDOFHUWLÀFDWHZHUHLVVXHGWRRISDWLHQWVLQSXEOLFFOLQLFVLQSULYDWHFOLQLFV The duration of sick leave ranged from half day to 21 days.

Reasons for seeking treatment at primary care clinics

Reason for seeking treatment is also otherwise known as reasons for encounter (RFEs). From the 141,593 patient encounters, 233,326 RFEs were recorded; 73,616 (31.5%) in public clinics and 159,710 (68.5%) in private clinics. Overall, there were 165 RFEs for every 100 patient encounters.

‡ 7KHPRVWFRPPRQ5)(SUHVHQWHGLQSXEOLFFOLQLFVZDVIROORZXSRUWUHDWPHQWIRUK\SHUWHQVLRQWKDW made up 17.7% (13,028) of all RFEs (31 per 100 encounters). This was followed by diabetes (20 per 100 encounters) and lipid disorder (19 per 100 encounters).

‡ $VIRUSULYDWHFOLQLFVIHYHUDQGFRXJKZHUHWKHPRVWFRPPRQ5)(VDQGERWKZHUHUHFRUGHGDWDUDWH of 25 per 100 encounters. Abdominal pain was the third highest and seen in 10 out of 100 encounters. Types of diagnosis

Of the 141,593 patient encounters at primary care clinics, 188,944 diagnoses were made with average 133 diagnoses made per 100 patient encounters. In public clinics, there were 68,877 diagnoses (36.5%) at a rate of 163 diagnoses per 100 encounters. Private clinics managed 120,067 diagnoses (63.5%) at a rate of 121 diagnoses per 100 encounters.

‡ 3DWLHQWVVHHQLQSXEOLFFOLQLFVZHUHPRVWO\IRUWUHDWPHQWRIQRQFRPPXQLFDEOHGLVHDVHV)RUHYHU\ 100 patient encounters, 33 had the diagnosis of hypertension and it was the commonest diagnosis. This was followed by lipid disorder (22 per 100 encounters) and diabetes (24 per 100 encounters). In private clinics however, hypertension diagnosis was made in only 5 out of 100 encounters, diabetes in 3 per 100 encounters and lipid disorder in 2 per 100 encounters.

‡ %\ FRPSDULVRQ PDMRULW\ RI WKH FDVHV ZKLFK SULYDWH SULPDU\ FDUH SURYLGHUV VDZ ZHUH IRU DFXWH illnesses. The most common diagnosis in private clinics was upper respiratory infection that contributed to 21.5% of all diagnoses in private clinics and diagnosed in 26 out of 100 encounters. Gastrointestinal infection was the second most common diagnosis, though it only constituted 5.0% of diagnoses (6 per 100 encounters).

Medications prescribed

A total of 479,856 medications were recorded, at an average of 254 medications per 100 encounters and 190 medications per 100 diagnoses. Public clinics prescribed a total of 130,484 medications (244 per 100 encounters; 150 per 100 diagnoses) and private clinics prescribed 255,788 medications (258 per 100 encounters; 213 per 100 diagnoses).

‡ 0HGLFDWLRQVZHUHSUHVFULEHGIRURIWRWDOHQFRXQWHUVLQSXEOLFFOLQLFV and 90.3% in private clinics.

‡ ,QSXEOLFFOLQLFVPHGLFDWLRQVPRVWFRPPRQO\SUHVFULEHGZHUHSDUDFHWDPROSHUHQFRXQWHUV metformin (17 per 100 encounters), amlodipine (16 per 100 encounters), lovastatin (15 per 100 encounters), and perindopril (13 per 100 encounters).

‡ 7KHWRSÀYHPHGLFDWLRQVSUHVFULEHGLQSULYDWHFOLQLFVZHUHSDUDFHWDPROSHUHQFRXQWHUV diphenhydramine (10 per 100 encounters), diclofenac (9 per 100 encounters), chlorphenamine (8 per 100 encounters), and butylscopolamine (8 per 100 encounters).

Investigations ordered

There were 53,028 investigations recorded, of which 64.4% was ordered by doctors at public clinics. The average rate of investigation ordered was 38 per 100 encounters; public clinics had 81 investigations per 100 encounters and private clinics had 19 investigations per 100 encounters.

‡ 0DMRULW\RIWKHLQYHVWLJDWLRQVUHFRUGHGZHUHODERUDWRU\WHVWV'LDJQRVWLFUDGLRORJ\LPDJLQJ test constituted 21.4% of all investigations.

‡ ,QSXEOLFFOLQLFVJOXFRVHWHVWZDVWKHPRVWIUHTXHQWO\RUGHUHGLQYHVWLJDWLRQSHUHQFRXQWHUV In private clinics, urine test was most common (4 per 100 encounters).

‡ 'LDEHWHVK\SHUWHQVLRQDQGOLSLGGLVRUGHUZHUHWKHPRVWFRPPRQGLDJQRVHVIRUZKLFKLQYHVWLJDWLRQV were ordered.

Advice/counselling and procedures

There were 36,782 advice/counselling (26 per 100 encounters) and 3,607 procedures (3 per 100 encounters) recorded in 2012.

‡ DGYLFHFRXQVHOOLQJZHUHSURYLGHGLQSXEOLFFOLQLFVDQGZHUHSURYLGHG in private clinics.

‡ $PRQJWKHW\SHVRIDGYLFHFRXQVHOOLQJSURYLGHGLQSULPDU\FDUHFOLQLFVZHUHJHQHUDODGYLFH HGXFDWLRQRQGLHWPHGLFDWLRQVÁXLGVLQWDNHDQGK\JLHQH

‡ RIWRWDOSURFHGXUHVZHUHSHUIRUPHGLQSXEOLFFOLQLFVZKLOHWKHUHVWZHUHGRQHLQ private clinics.

‡ 'UHVVLQJZDVWKHPRVWFRPPRQSURFHGXUHUHFRUGHGDQGDFFRXQWHGIRURIDOOSURFHGXUHV performed in primary care clinics.

Follow-up and referrals

There were 46,043 patient encounters (32.5%) arranged for follow-up after visit to primary care clinics. Arrangements for follow-up were made more frequent in public clinics (63 out of 100 encounters) compared to private clinics (19 out of 100 encounters).

Referral was provided for 5,873 patient encounters (4.1%) during visit to primary care clinics. Similar to follow-up, the referral rate was higher in public clinics (7 per 100 encounters) than private clinics (3 per 100 encounters).

‡ 5HIHUUDOVZHUHPRVWRIWHQPDGHWRKRVSLWDOSHUHQFRXQWHUVDQGVSHFLDOLVWSHU encounters).

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These data are by far the most comprehensive and detailed information on health care activities of both the public and private primary care clinics in Malaysia. Although the study was restricted to only clinics LQ VWDWHV DQG UHJLRQV VDPSOHG WKH ÀQGLQJV KDYH SURYLGHG D EHWWHU XQGHUVWDQGLQJ RI WKH GLVHDVH SDWWHUQV DQG SURFHVVHV RI FDUH LQ WKH 0DOD\VLDQ SULPDU\ FDUH VHWWLQJ 7KH ÀQGLQJV IURP WKLV VWXG\ together with those from the National Healthcare Establishment and Workforce Survey: Primary Care (NHEWS) are vital to form a clearer picture of the current primary healthcare system in Malaysia.

Chapter 1

Introduction

CHAPTER 1: INTRODUCTION

1.1 BACKGROUND

The National Healthcare Statistics Initiative (NHSI) is a family of surveys which aims to support evidence-based health policy-making and research in Malaysia. It was initiated in 2009 by the Healthcare Statistics Unit (HSU) in National Clinical Research Centre (NCRC) Kuala Lumpur in collaborations with various stakeholders. Over the past 4 years, the NHSI has grown and managed to gain recognition due to WKHXVHIXOQHVVRILWVGDWDZKLFKÀOOVLQWKHJDSEHWZHHQUHVHDUFKDQGSROLF\$QQXDOUHSRUWVDUHSXEOLVKHG IRUPRVWRIWKHVXUYH\VXQGHU1+6,EDVHGRQWKHLUUHVSHFWLYHÀQGLQJV

7KH1DWLRQDO0HGLFDO&DUH6XUYH\10&6LVRQHRIWKHIRXUPHPEHUVRI1+6,7KHÀUVW10&6ZDV launched in 2010 and have met with numerous challenges which have led to the suspension of the project IRUD\HDU+RZHYHUVRPHZHDNQHVVHVLQLWVPHWKRGRORJ\DQGGDWDTXDOLW\KDYHEHHQLGHQWLÀHGXSRQ consultation with local and international researchers as well as stakeholders during the year of suspension. With more staff and support from the stakeholders, the management team of NMCS managed to publish a short report based on NMCS 2010 data for public consumption.

In 2012, the survey was re-initiated with a revised methodology. A Research Evaluation Committee (REC) comprising of respected academicians from the universities, representatives from Family Health Division and Academy of Family Physician Malaysia as well as Pharmaceutical Services Division and a statistician has been set up to discuss and advise the NMCS team with regards to the planned objectives and methodology. The team has also managed to get good support from the Bettering the Evaluation and Care of Health (BEACH) management team, a Family Medicine Research Centre team from University of Sydney Australia1 who has given permission for NMCS 2012 questionnaire to be adapted from theirs. NMCS 2012 is hoped to bring about more valuable data to all.

1.2 OBJECTIVES General Objectives

1. To collect reliable and valid data in primary care setting.

2. To assess patient characteristics and morbidity pattern and the relationship these factors have with health service activity.

3. To provide accurate and timely data to various stakeholders including government bodies, primary care practitioners, consumers, researchers, and the pharmaceutical industry.

4. To establish an ongoing database of doctor/patient encounter information. 6SHFLÀF2EMHFWLYHV

To collect information on clinical activities in primary care setting in Malaysia including: ‡ 7KHFKDUDFWHULVWLFVRISDWLHQWVVHHQ

‡ 0RGHRISD\PHQWIRUSULPDU\FDUHVHUYLFHV ‡ 5HDVRQVSHRSOHVHHNPHGLFDOFDUH

‡ 3UREOHPVPDQDJHGDQGIRUHDFKSUREOHPPDQDJHG

o Pharmacological treatment prescribed, including the dose and frequency;

o Non-pharmacological treatment provided, including the procedures and counselling; o Investigations ordered, including pathology and imaging;

o Follow up in primary care and referrals to secondary or tertiary care; R ,VVXDQFHRIPHGLFDOFHUWLÀFDWHDQGGXUDWLRQRIVLFNOHDYH

The study also aims to provide more evidence on the prevalence of non-communicable diseases (NCDs) in primary care settings and their process of care, in line with the National Strategic Plan for Non-Communicable Disease (NSP-NCD) 2010 – 2014. In the National Strategic Plan, research has been LGHQWLÀHG DV RQH RI WKH VWUDWHJLHV WR SUHYHQW DQG FRQWURO 1&'V WKURXJK WKH PRQLWRULQJ RI FOLQLFDO management.2

1.3 DEFINITIONS

'HÀQLWLRQVRQSULPDU\FDUHIRUWKHSXUSRVHRIWKH10&6UHVHDUFKSURMHFWZHUHDGDSWHGIURPWKH American Association of Family Physicians.3 _{The few terms that was taken in:}

a) Primary care

7KHFDUHSURYLGHGE\SK\VLFLDQVVSHFLÀFDOO\WUDLQHGIRUDQGVNLOOHGLQFRPSUHKHQVLYHÀUVWFRQWDFW and continuing care for persons with any undiagnosed sign, symptom, or health concern (the “undifferentiated” patient) not limited by problem origin (biological, behavioural, or social), organ system, or diagnosis.

- The care involved includes health promotion, disease prevention, health maintenance, counselling, patient education, diagnosis and treatment of acute and chronic illnesses in a variety of health FDUH VHWWLQJV HJ RIÀFH LQSDWLHQW FULWLFDO FDUH ORQJWHUP FDUH KRPH FDUH GD\ FDUH HWF Primary care is performed and managed by a personal physician often collaborating with other health professionals, and utilising consultation or referral as appropriate.

b) Primary care setting

3ULPDU\FDUHVHWWLQJVHUYHVDVWKHSDWLHQW·VÀUVWSRLQWRIHQWU\LQWRWKHKHDOWKFDUHV\VWHPDQG as the continuing focal point for all needed health care services. Primary care practices provide patients with ready access to their own personal physician or to an established back-up physician when the primary physician is not available.

c) Primary care doctors

- Medical doctors or family medicine specialists (FMS) who are providing primary care in primary care setting.

Primary healthcare in Malaysia are provided by both public and private healthcare providers. Government clinics (Klinik Kesihatan) are funded by the government while private sector provides service on fee-for-service basis. In this report, the term ‘public clinic’ and ‘private clinic’ are used to describe these two types of primary care clinics.

1.4 RESEARCH QUESTIONS

No. Questions Answered by

1. What types of patients are seen by primary care

practitioners? Demographic characteristics

2. What is the source of payment for primary care services? Mode of payment

3. What motivates patients to seek care from primary care

setting? Patient’s reasons for visit

4. What are the actual diagnosis / problems managed by

primary care practitioners? Doctor’s diagnosis / Problems managed

5. What are the pharmacological treatments prescribed by

No. Questions Answered by

6. What are the procedures and imaging ordered by primary

care practitioners for the diagnosis / problems? Non-pharmacological interventions

7. What types of counselling are offered by primary care

practitioners for the diagnosis / problems? Non-pharmacological interventions

8. Is there any continuity of care in primary care setting? Referrals / Follow Up

9. What is the extent of the loss of productivity for the

morbidities in primary care setting?

0HGLFDOFHUWLÀFDWH0&DQGGXUDWLRQRI

sick leave

Each research question is described in separate chapter in this report. However, patients’ mode of payment DQGWKHLVVXDQFHRIPHGLFDOFHUWLÀFDWHDUHGLVFXVVHGLQWKHVDPHFKDSWHUDVWKHSDWLHQWV·GHPRJUDSKLF characteristics.

REFERENCES

1. The University of Sydney, Family Medicine Research Centre. Bettering the Evaluation and Care of Health (BEACH). [Viewed January 2014]. Available from: http://sydney.edu.au/medicine/fmrc/ beach/index.php

2. National Strategic Plan for Non-Communicable Disease 2010 – 2014. Ministry of Health Malaysia (2010).

3. American Association of Family Physicians (AAFP). Primary Care. [Viewed January 2014]. Available from: http://www.aafp.org/online/en/home/policy/policies/p/primarycare.html

Chapter 2

Methodology

CHAPTER 2: METHODOLOGY

The 2012 National Medical Care Survey (NMCS) is a prospective cross-sectional study. The observation unit was the patient encounters. As it was not possible to randomly select the encounters from all the study location, random sampling was done on the primary care clinics in the 5 selected regions instead. The chosen regions were

‡ Wilayah Persekutuan:3.XDOD/XPSXU:33XWUDMD\DDQG6HODQJRUWRUHÁHFWWKHFHQWUDO region of Peninsular Malaysia

‡ .HODQWDQWRUHÁHFWWKH(DVW&RDVWRI3HQLQVXODU0DOD\VLD ‡ .XFKLQJDQG.RWD.LQDEDOXWRUHÁHFW(DVW0DOD\VLD

A total period of 4 months was allocated for data collection from August 1st till November 30th 2012 where all sampled clinics were randomly allocated one day for data recording in their respective clinics. 2.1 SAMPLING FRAME AND SAMPLE SIZE CALCULATION

The sampling frame of public and private clinics was generated by matching the list of clinics from National Healthcare Establishments and Workforce Survey (NHEWS) 2010 with several sources:

‡ 7KHOLVWRISXEOLFFOLQLFVIURPWKH)DPLO\+HDOWK'HYHORSPHQW'LYLVLRQ0LQLVWU\RI+HDOWK Malaysia.

‡ 7KHOLVWRIUHJLVWHUHGSULYDWHFOLQLFVIURPWKH3ULYDWH0HGLFDO3UDFWLFH'LYLVLRQ0LQLVWU\RI+HDOWK Malaysia (often referred to as Cawangan/Unit Kawalan Amalan Perubatan Swasta (CKAPS/ UKAPS).

Both lists were updated as of 31st December 2011 and these were the most recent lists of clinics at the point of survey.

$VIRUFOLQLFVWKDWZHUHQRWPDWFKHGIURPWKHOLVWVVXEVHTXHQWYHULÀFDWLRQE\SKRQHFDOOVZDVGRQHWR determine the existence or current operational status of the establishments. Those that were found to be closed were removed from the sampling frame.

Inclusion and exclusion criteria for the clinics sampled in the survey were as follow:

Inclusion criteria

‡ MOH Health Clinics (Klinik Kesihatan) providing primary care services by medical doctors

‡ Private medical clinics registered with CKAPS and providing primary care services

Exclusion criteria

‡ Outpatient departments within hospital or maternity homes

‡ Public clinics with the following criteria:

- Klinik Kesihatan without medical doctors

- Clinics providing maternal and child health services only (Klinik Kesihatan Ibu dan Anak)

- Rural clinics (Klinik Desa)

- 1 Malaysia Clinics

- Primary care clinics in universities

‡ Private clinics with the following criteria:

- In-house clinics/company clinics

- Clinics providing specialised care/specialist clinics e.g. paediatric, cardiology, occupational therapy

- Diagnostic centres - Aesthetic clinics - Charity clinics

6DPSOHVHOHFWLRQZDVFRQGXFWHGE\VWUDWLÀHGUDQGRPVDPSOLQJLQFRUSRUDWLQJVHYHUDOVWDJHVWRREWDLQWKH encounters needed.

Stage 1: Selection of sampling regions (convenience/purposive sampling)

‡ :3.XDOD/XPSXU6HODQJRUDQG:33XWUDMD\D.HODQWDQ.XFKLQJDQG.RWD.LQDEDOX 6WDJH6WUDWLÀFDWLRQE\VHFWRU

‡ (DFKUHJLRQZDVIXUWKHUVWUDWLÀHGWRSXEOLFRUSULYDWHVHFWRU

Stage 3: Sampling of clinics

‡ 5DQGRPVDPSOLQJRIFOLQLFVEDVHGRQUDQGRPQXPEHUVJHQHUDWHGXVLQJ0LFURVRIW([FHO,QFOXVLRQ and exclusion criteria were taken into account during sampling process.

Stage 4: Sampling of doctors

‡ $OOGRFWRUVLQWKHVDPSOHGFOLQLFVZKRZHUHSUDFWLVLQJRQWKHVXUYH\GD\ZHUHLQFOXGHG ‡ /RFXPGRFWRUVZHUHLQFOXGHG

‡ 6SHFLDOLVWVZHUHH[FOXGHGZLWKH[FHSWLRQRIIDPLO\PHGLFLQHVSHFLDOLVWV

Stage 5: Sampling of encounters

‡ $OOHQFRXQWHUVVHHQE\WKHGRFWRUVRQWKHVXUYH\GDWHZLWKPLQLPXPRIHQFRXQWHUVUHTXLUHGIRU public clinics and minimum of 20 encounters per private clinic.

The sample size which is the needed number of encounters for the NMCS 2012 was determined based on the morbidity data from NMCS 2010 as well as total primary care attendances from NHEWS Primary Care 2010.

7KHÀQDOVDPSOHFRQVLVWVRISXEOLFFOLQLFVDQGSULYDWHFOLQLFV7DEOH

Table 2.1: Sample size for NMCS 2012

State/Region

Number of clinics

Public Private

Selangor & WP Putrajaya 39 187

WP Kuala Lumpur 8 107

Kelantan 20 57

Kota Kinabalu 4 21

Kuching 4 11

2.2 SURVEY DATES

All sampled clinics were given one randomly assigned date for data collection, which was a working day for all. The following days were excluded:

‡ SXEOLFKROLGD\V

‡ ZHHNHQGVLQFOXGLQJ)ULGD\6DWXUGD\DQG6XQGD\

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‡ ZRUNLQJGD\VLQEHWZHHQSXEOLFKROLGD\V

If the clinic was closed on the survey date, the doctor had the option to change the survey date to the next available working day. The research team however was informed of the new survey date.

2.3 DATA COLLECTION AND FOLLOW-UP

7KH VDPSOHG FOLQLFV ZHUH HDFK VHQW DQ LQYLWDWLRQ OHWWHU WR DWWHQG D EULHÀQJ LQ HDFK VWDWH %ULHÀQJV for doctors in the public clinics were held on weekdays whereas for private doctors, it was during the weekends from June to July 2012. A research pack which contained the survey forms and instructions ZHUHGLVWULEXWHGGXULQJWKHEULHÀQJV

7RHQFRXUDJHIXUWKHUSDUWLFLSDWLRQFOLQLFVWKDWGLGQRWDWWHQGWKHEULHÀQJZHUHODWHUFRQWDFWHGE\SKRQH If the doctor refused to participate in the survey, the team did not pursue further. However, if they agree to participate the research pack would be sent either

‡ E\FRXULHUIROORZHGE\WHOHSKRQHFDOOWRHQVXUHWKDWWKHUHVHDUFKNLWKDGEHHQUHFHLYHG%ULHÀQJ would be done over the phone to explain about the survey form.

‡ E\SHUVRQDOYLVLWWRWKHFOLQLFVZLWKLQWKHYLFLQLW\RI.ODQJ9DOOH\DQGDVKRUWSULYDWHEULHÀQJ would be given to the doctor/nurse in-charge

Two weeks and one day before the survey date, a reminder via telephone was made to the clinic about the project and to answer any questions pertaining to the survey. Instructions would be repeated when necessary. After the survey date, follow-up phone call(s) were made if the research pack was not returned after 3 weeks, and subsequently at 5 weeks.

Various approaches were also taken to increase the acceptance and response rate of private clinics. This included the following:

a) Approaching the manager/senior management of the chain clinics/group practices

E 2UJDQLVLQJSULYDWHLQGLYLGXDOEULHÀQJVDORQJVLGH0HGLFDO3UDFWLFH'LYLVLRQ·VHQIRUFHPHQW activities

c) Getting support and assistance from Malaysian Medical Association (MMA) at the state level 8SRQFRPSOHWLRQRIGDWDFROOHFWLRQSDUWLFLSDQWVZHUHJLYHQFHUWLÀFDWHVZKLFKWKH\ZRXOGODWHUXVHWR claim for continuing professional development (CPD) points. An individualised feedback, questionnaire on primary care prescribers, and a copy of the National Medical Care Statistics 2012 report were also sent to all participants.

2.4 RESEARCH PACK AND QUESTIONNAIRE

A pre-testing session of the questionnaire was carried out by requesting a convenience sample of doctors from public and private clinics to complete the forms. A total of 32 encounters were recorded, and FRPPHQWVIURPWKHGRFWRUVZHUHWDNHQLQWRFRQVLGHUDWLRQ7KH10&6IRUPZDVIXUWKHUPRGLÀHG DQGWKHÀQDOLVHGIRUPLVHQFORVHGLQ$SSHQGL[(DFKUHVHDUFKSDFNFRQWDLQHG

Survey Pads Each pad has - 40 forms

- One set of instructions - One case study

- One example of a completed form

6XUYH\'DWH1RWLÀFDWLRQ Survey date and day

Project Summary Purpose and objective of NMCS 2012

Public Notice Notice to be displayed in the participating clinic to inform patient that the

clinic is currently undertaking a MOH survey

Data Dictionary One-page description of variables in the survey form

ICPC-2-code List ICPC-2-Code list

Also included in the research pack:

Call Letter Letter signed by State Health Directors to inform the participating clinics of

the survey

Prepaid Envelope Two sets (1 for National Healthcare and Establishment Survey (NHEWS) and 1 for NMCS). The one for NHEWS contains a NHEWS survey form and a small envelope containing the user ID and password for those who prefer online questionnaire for NHEWS.

*NHEWS Primary Care is a 4-pages questionnaire focusing on services and workforce in the primary care setting

Report NHEWS 2010 Primary Care Report

2.5 DATA MANAGEMENT 2.5.1 Data entry

All data entry was done through the use of data entry web application and performed by trained data entry personnel.

Prior to the start of data entry, data entry personnel were given reading materials containing the detailed GHVFULSWLRQ RI VWXG\ H[DPSOHV RI IRUPV FODVVLÀFDWLRQ DQG FRGLQJ V\VWHPV DQG GDWD HQWU\ UXOHV DQG regulations. This was followed by two sessions of data entry training which lasted for 2 hours each. Session 1: Demonstration

‡ 3UHVHQWDWLRQRQGDWDHQWU\PRGXOH ‡ /LYHGHPRQVWUDWLRQRIGDWDHQWU\PRGXOH ‡ /LYHGHPRQVWUDWLRQRIFRGLQJV\VWHP ‡ 'LVFXVVLRQRQGDWDHQWU\DQGFRGLQJV\VWHP

Session 2: Question and answer

‡ 'LVFXVVLRQRQGDWDHQWU\DQGFRGLQJLVVXHVDIWHUFOHDQLQJDQGUHYLHZLQJWKHGHPRHQWULHV ‡ 8SGDWHRQWKHFRGLQJUXOHV

2.5.2 Quality check on data entry

Double data entry was incorporated as part of the quality check on data. This form of quality check has been recommended and known to correct data entry errors from the original entry.1

Double data entry was done for approximately 10.0% of the total entries in two batches where batch 1 was completed in November 2012 and batch 2 in February 2013. The selection of clinics for the double entry was random and data entry personnel were blinded towards the double data entry process.

Type of entry Number of forms

Single data entry 11,220

Double data entry 1,377

)RUHDFKEDWFKRIGRXEOHGDWDHQWU\DOOGLVFUHSDQFLHVEHWZHHQWKHÀUVWDQGVHFRQGVHWRIUHFRUGVZHUH YHULÀHG E\ FKHFNLQJ HLWKHU ZLWK WKH RULJLQDO IRUPV RU WKH FRGLQJ GHÀQLWLRQV 7UXH HQWU\ HUURUV ZHUH LGHQWLÀHGDQGDFRUUHFWWKLUGUHFRUGZDVXSGDWHGLQWRWKHGDWDEDVH7KHSHUFHQWDJHRIGDWDHQWU\HUURU for each available variable was then calculated. The maximum data entry error percentage from each batch was then compared.

Table 2.2: Data entry error rate for NMCS 2012

Variable

Data entry error (%)

Batch 1 Batch 2

Coded variables

ICPC code 5.85 8.96

ATC code 0.23 5.28

Non-coded variables

Visit disposition 7.63 0.87

Gender 5.02 1.84

The two variables for the non-coding section were the variables with the highest data entry error rate for batch 1. There was marked improvement in error rate for these variables from batch 1 to batch 2. Increase of data entry error rate for the coded variables can be attributed to recruitment of new data entry personnel, resulting in more variation in coding. Most of the coding errors were systematic errors; data entry personnel had a misconception of the way a certain disease/medication is coded, thus making a repetitive error of the same nature.

There does not appear to be a general consensus of acceptable data entry error rate worldwide. Previous study has shown that error rates detected by double-entry method for clinical databases were 2.3 to 5.2% (demographic data) and 10.0 to 26.9% (treatment data).2 _{Similarly, Fontaine P et al. reported an overall}

All the errors which were detected (coded and non-coded) were corrected by referring to the original forms and by discussion among the investigators and the Research Evaluation Committee. Further systematic checks were also conducted during data cleaning to ensure validity and reliability of the data. A protocol with validation rules for cleaning as well as data inconsistency rules was created for data cleaning. &ODVVLÀFDWLRQRIGDWD'DWDFRGLQJ

,QWHUQDWLRQDO&ODVVLÀFDWLRQRI3ULPDU\&DUH,&3&

7KH ,QWHUQDWLRQDO &ODVVLÀFDWLRQ RI 3ULPDU\ &DUH 6HFRQG (GLWLRQ ,&3& ZDV XVHG WR FODVVLI\ WKH following data elements:

‡ 5HDVRQVIRUHQFRXQWHU ‡ 'LDJQRVHV

‡ ,QYHVWLJDWLRQV ‡ 3URFHGXUHV

‡ $GYLFHFRXQVHOOLQJ

The ICPC-2 is accepted by the World Health Organization (WHO) as a member of the WHO Family of ,QWHUQDWLRQDO&ODVVLÀFDWLRQV4 _{It was published in 1987 by the World Organisation of Family Doctors}

:21&$DQGXVHGLQPRUHWKDQFRXQWULHVDVWKHVWDQGDUGIRUGDWDFODVVLÀFDWLRQLQSULPDU\FDUH The ICPC-2 has a bi-axial structure, with 17 chapters based on body systems and seven components with rubrics bearing a letter and two-digit numeric code.

ICPC-2 Chapters

A General R Respiratory

B Blood, immune system S Skin

D Digestive T Endocrine, nutritional & metabolic

F Eye U Urological

H Ear W Women’s health, pregnancy, family planning

K Circulatory X Female genital

L Musculoskeletal Y Male genital

N Neurological Z Social problems

P Psychological

ICPC-2 Components Code

1. Complaints and symptoms 01 - 29

2. Diagnostics, screening and preventive 30 - 49

3. Medication, treatment, procedures 50 - 59

4. Test results 60 - 61

5. Administrative 62

6. Referrals 63 - 69

7KH GDWD ZHUH HQWHUHG DQG FRGHG XVLQJ ,&3& 3/86 DQ H[WHQGHG FOLQLFDO WHUPLQRORJ\ FODVVLÀHG according to ICPC-2. ICPC-2 PLUS coding system contains extended terms commonly used in general SUDFWLFHWKDWDUHPRUHVSHFLÀFDQGKHOSVWRHQVXUHDFFXUDWHFODVVLÀFDWLRQWR,&3&GXULQJGDWDHQWU\ ICPC-2 PLUS was developed in 1995, and is maintained and regularly updated by the Family Medicine Research Centre (FMRC) of the University of Sydney.5 _{Also known as BEACH coding system, ICPC-2}

PLUS is primarily used in Australia especially for the national study of general practice activity, the BEACH program.

The National Clinical Research Centre has been granted a free research licence from WONCA for the usage of ICPC-2 codes which is valid from February 2011 till end of 2014 whereas the ICPC-2 PLUS was obtained under a free licence from the University of Sydney.

5HVXOWVZHUHUHSRUWHGDWWKH,&3&FODVVLÀFDWLRQOHYHO6RPHRIWKHGLDJQRVHVZHUHJURXSHGWRJHWKHUE\ FRPELQLQJVHYHUDO,&3&RU,&3&3/86FRGHV$SSHQGL[+RZHYHUFODVVLÀFDWLRQRISDWKRORJ\DQG LPDJLQJWHVWDFFRUGLQJWR,&3&FDQEHYHU\EURDGHJ+E$FWHVWLVFODVVLÀHGXQGHU7%ORRGWHVW endo/metabolic). Hence, results for Chapter 9: Investigations were presented as ICPC-2 PLUS.

Anatomical Therapeutic Chemical (ATC)

0HGLFDWLRQVZHUHFRGHGDQGFODVVLÀHGXVLQJWKH$QDWRPLFDO7KHUDSHXWLF&KHPLFDO$7&FODVVLÀFDWLRQ system. ATC has been recommended by the WHO and used in many countries including Malaysia, as a global standard for classifying medications for drug utilisation research, evaluating trend of drug consumption and for international comparisons.6,70HGLFDWLRQVDUHFODVVLÀHGLQWRJURXSVDWÀYHGLIIHUHQW

levels, with the following example: ‡ /HYHO&&DUGLRYDVFXODUV\VWHP

‡ /HYHO&6HUXPOLSLGUHGXFLQJDJHQWV

‡ /HYHO&$&KROHVWHURORIWULJO\FHULGHUHGXFHUV ‡ /HYHO&$$+0*&R$UHGXFWDVHLQKLELWRUV ‡ /HYHO&$$6LPYDVWDWLQ

The ATC licence was purchased from the WHO Collaborating Centre for Drug Statistics Methodology. Medications were entered as free text in generic (non-proprietary) or brand name, and coded by trained GDWDHQWU\SHUVRQQHODFFRUGLQJWRWKH*XLGHOLQHVIRU$7&&ODVVLÀFDWLRQDQG'''DVVLJQPHQW6 _In

certain cases, the doctors might not specify the medications to the generic level hence it could only be coded to ATC level 3 or 4.

2.6 DATA ANALYSIS 2.6.1 Weighting

The data presented in this report were weighted to adjust for over and under representativeness of any VWUDWDLQWKHVDPSOHDVZHOODVWRDFFRXQWIRUQRQUHVSRQGHQWV7HQZHLJKWLQJVWUDWDZHUHGHÀQHGIRU the study population, by state/region and sector. The components incorporated in the estimation of total weights are described below.

Sampling weight

The sampling weight of each stratum calculated as follow: W_j = N_j/n_j

where

N is the total encounters for primary care clinics per day in the state/region (population), and n is the total encounters expected (sample) for strata j.

j = strata according to sector and state/region Strata according to state/region and sector

State/Region Sector Stratum

Selangor & WP Putrajaya

Public 1

Private 2

WP Kuala Lumpur

Public 3

Private 4

Kelantan

Public 5

Private 6

Kota Kinabalu

Public 7

Private 8

Kuching

Public 9

Private 10

$GMXVWPHQWIRUQRQUHVSRQVHSRVWVWUDWLÀFDWLRQZHLJKW

To account for less than 100% response rate, adjustment for the response is required. The non-response adjustment weight was calculated as a ratio of number of expected encounters as the numerator and number of responding encounters as the denominator.

Total weights

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2.6.2 Statistical Analysis

STATA Version 11 (StataCorp. 2009. Stata Statistical Software: Release 11. College Station, TX; StataCorp LP.) and IBM SPSS Statistics for Windows (Version 20.0. Armonk, NY: IBM Corp) were used for data analysis. Results were presented as number of observations, proportions, and rate per 100 encounters

DORQJZLWKFRQÀGHQFHLQWHUYDO&,5DWHSHUGLDJQRVHVZHUHUHSRUWHGIRUPDQDJHPHQWWKDWFDQ occur at more than once per diagnosis.

2.7 ETHICAL ISSUES

The study was approved by the Medical Research and Ethics Committee (MREC), MOH. As per previous study, a public notice was placed at each participating clinic to inform patients that their data would be collected for research purposes. Patients had the right to decline to participate at any point of time throughout the study period.

2.8 LIMITATIONS

1. Only 3 states (Selangor and WP Putrajaya, WP Kuala Lumpur, and Kelantan) and 2 regions .RWD.LQDEDOXDQG.XFKLQJZHUHVXUYH\HG7KHVWXG\UHVXOWVZLOORQO\UHÁHFWWKHPRUELGLW\DQG prescription pattern in these state and regions and cannot be projected to represent the entire nation. 2. The survey is self-administered and therefore precision of data depends largely on the completeness

RIUHFRUGLQJE\UHVSRQGHQWVKHQFHPD\QRWQHFHVVDULO\UHÁHFWWKHDFWXDOSUDFWLFH

7KH VXUYH\ LV HQFRXQWHUEDVHG DQG UHÁHFWV WKH PRUELGLW\ SDWWHUQ REVHUYHG LQ WKH SULPDU\ FDUH setting rather than the prevalence of disease in the community.

7KH PRUELGLW\ SDWWHUQV UHÁHFW RQO\ WKRVH PRUELGLWLHV PDQDJHG GXULQJ WKH UHFRUGHG HQFRXQWHUV There may be co-morbidity in the same patient which was not expected to be managed during the encounter and hence was not recorded.

5. The survey is a cross-sectional study. Therefore, no conclusions may be generated on the outcomes of management of acute and chronic diseases in the primary care setting. Prescriptions, procedures, imaging and referrals reported were those provided at the present point of encounter and did not necessarily indicate that the patient has not already received them in a previous encounter.

REFERENCES

1. Atkinson I. Accuracy of data transfer: double data entry and estimating levels of error. J Clin Nurs. 2012; 21(19-20):2730-5.

2. Goldberg SI, Niemierko A, Turchin A. Analysis of Data Errors in Clinical Research Databases. AMIA Annu Symp Proc. 2008;2008:242-246.

3. Fontaine P, Mendenhall TJ, Peterson K, Speedie SM. The “Measuring Outcomes of Clinical Connectivity” (MOCC) Trial: Investigating Data Entry Errors in the Electronic Primary Care Research Network (ePCRN) J Am Board Fam Med. 2007;20(2):151-9.

:RUOG+HDOWK2UJDQL]DWLRQ)DPLO\RILQWHUQDWLRQDOFODVVLÀFDWLRQV*HQHYD:+2>9LHZHG )HEUXDU\@$YDLODEOHIURPKWWSZZZZKRLQWFODVVLÀFDWLRQVHQ:+2),&)DPLO\SGI

)DPLO\0HGLFLQH5HVHDUFK&HQWUH7KH8QLYHUVLW\RI6\GQH\,&3&,QWHUQDWLRQDO&ODVVLÀFDWLRQ of Primary Care. [Viewed January 2014]. Available from: http://sydney.edu.au/medicine/fmrc/icpc-2/ index.php

:+2&ROODERUDWLQJ&HQWUHIRU'UXJ6WDWLVWLFV0HWKRGRORJ\*XLGHOLQHVIRU$7&&ODVVLÀFDWLRQDQG DDD Assignment 2012. Oslo 2011. [Viewed February 2014]. Available from: www.whocc.no

7. Pharmaceutical Services Division and Clinical Research Centre, Ministry of Health Malaysia. Malaysian Statistics on Medicine 2008. Kuala Lumpur 2013.

Chapter 3

Response Rate

CHAPTER 3: RESPONSE RATE

This chapter describes the survey sample and response rate for NMCS 2012. Table 3.1 shows the number of clinics sampled and number of clinics responded to the survey. A total of 69 public clinics and 120 private clinics participated in NMCS 2012, and listed in Appendix 3. The response rates were then calculated as the number of encounters that were recorded for NMCS 2012 divided by the expected number of encounters in the sample (Table 3.2).

Table 3.1: Total clinics sampled and responded for NMCS 2012

State/Region Sector Number of clinics sampled

Number of clinics responded

Percentage of clinics responded (%)

Selangor & WP Putrajaya

Public 39 34 87.2

Private 187 53 28.3

WP Kuala Lumpur Public 8 8 100.0

Private 107 30 28.0

Kelantan Public 20 19 95.0

Private 57 24 42.1

Kota Kinabalu Public 4 4 100.0

Private 21 9 42.9

Kuching Public 4 4 100.0

Private 11 4 36.4

Total Public 75 69 92.0

Private 383 120 31.3

Table 3.2: Response rate for NMCS 2012

State/Region Sector Total encounters expected

Total encounters responded

Response rate (%)

Selangor & WP Putrajaya

Public 1,777 4,172 100.0

Private 5,375 1,766 32.9

WP Kuala Lumpur

Public 384 698 100.0

Private 3,040 717 23.6

Kelantan

Public 931 979 100.0

Private 1,636 892 54.5

Kota Kinabalu

Public 253 1,255 100.0

Private 595 218 36.6

Kuching

Public 566 1,753 100.0

Private 327 147 45.0

Total

Public 3,911 8,857 100.0

5HVSRQVHUDWHREWDLQHGIURPSXEOLFFOLQLFVRIDOOÀYHVWDWHVDQGUHJLRQVZHUHRYHUZKHOPLQJDQGH[FHHGHG 100.0%. However, the maximum response rate was reported as 100.0% as in Table 3.2. As for private sector, despite our fervent attempts to persuade the private GPs to participate the response rate for WP Kuala Lumpur was only 23.6%, bringing down the overall response rate for private sector to 34.0%. The low response rate however, has already been anticipated and accounted for. When calculating sample size, the sampling matrix had included an estimation of a 30.0% drop-out rate from the public and a 70.0% drop-out rate from the private sector. This huge estimated rate of drop-out from the private sector was expected based on previous studies conducted comparing public and private health sectors in Malaysia. The reported response rate from private clinics in these studies was between 26.0% to 33.0%.1, 2

3.1 THE ENCOUNTERS

A total of 12,597 encounters were collected for NMCS 2012. Of these, 28 encounters were excluded from DQDO\VLVRILQFRPSOHWHIRUPVDQGRIGDWDLQFRQVLVWHQFLHV7KHÀQDOHQFRXQWHUVIRUDQDO\VLVZHUH 12,569; 8,837 from public and 3,732 from private. The dataset were weighted to adjust for over and under representativeness of data (see section 2.6.1). Table 3.3 shows the observed and weighted total for each GDWDHOHPHQW7KHÀQDOZHLJKWHGSDWLHQWHQFRXQWHUVZHUHDQGWKHZHLJKWHGGDWDVHWZHUHXVHGWR describe the results in this report.

Table 3.3: Observed and weighted dataset for NMCS 2012

Variable

Observed Weighted

Overall Public Private Overall Public Private

Encounters 12,569 8,837 3,732 141,593 42,340 99,253

Reasons for encounter 21,359 15,452 5,907 233,326 73,616 159,710

Diagnoses 18,904 14,429 4,475 188,944 68,877 120,067

Medications 31,377 21,709 9,668 359,272 103,484 255,788

Investigations 7,687 6,983 704 53,028 34,139 18,889

Advice/counselling and procedures

5,540 4,831 709 40,389 22,372 18,017

Follow-up and referrals 10,935 9,951 984 73,672 47,652 26,020

REFERENCES

1. Teng CL, Tong SF, Khoo EM, Lee V, Zailinawati AH, Mimi O et al. Antibiotics for URTI and UTI -- prescribing in Malaysian primary care settings. Australian Family Physician. 2011; 40(5):325-9. 2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, A Abdul-Rahman et al. A comparison of morbidity

patterns in public and private primary care clinics in Malaysia. Malaysian Family Physician. 2011; 6(1):19-25.

Chapter 4

The Doctors

CHAPTER 4: THE DOCTORS

This chapter reports the characteristics of doctors who participated and recorded the primary care visits for NMCS 2012. Data for these doctors were obtained through linkage with National Healthcare and Establishments Workforce Survey: Primary Care (NHEWS) database which captured information on services and workforce in primary care setting, including the doctors’ socio-demographic details. NHEWS TXHVWLRQQDLUHZHUHLQFOXGHGLQWKH10&6UHVHDUFKSDFNDQGWKHGRFWRUVZHUHDVNHGWRÀOOLQERWKVHWVRI questionnaire. Details on NHEWS Primary Care were described elsewhere.1

A total of 408 doctors from public and private clinics participated in the NMCS 2012. The data for the doctors were not weighted and extrapolated due to scarcity of national sample frame of doctors practising in primary care clinics in Malaysia.

4.1 CHARACTERISTICS OF THE DOCTORS

)URPWKHWRWDORIGRFWRUVZKRSDUWLFLSDWHGLQ10&6GRFWRUVÀOOHGLQERWK10&6DQG NHEWS questionnaire thus providing their socio-demographic details. Table 4.1 shows the characteristics of doctors who participated in NMCS 2012.

‡ 0DMRULW\RIWKHGRFWRUVZHUHIHPDOHV,QSXEOLFFOLQLFVRIWKHGRFWRUVZHUHIHPDOHV whereas there were only 39.7% female doctors in private clinics.

‡ 2YHUDOOPRVWGRFWRUVDJHGEHWZHHQDQG\HDUVROGPHGLDQ\HDUV,45\HDUV,QSXEOLF clinics, nearly half of the doctors (48.0%) were of this age group. In contrast, 62.8% of the doctors in private clinics were 50 years old and older.

‡ /HVV WKDQ RI WKH GRFWRUV KDG SRVWJUDGXDWH TXDOLÀFDWLRQ 2I WKHVH PDMRULW\ ZHUH IDPLO\ medicine specialist.

‡ 'RFWRUVLQWKHSULYDWHFOLQLFVLQJHQHUDOZRUNHGORQJHUKRXUVPHGLDQKRXUVZHHNWKDQWKRVHLQ the public clinics (median 40 hours/week).

Table 4.1: Characteristics of doctors for NMCS 2012

Characteristics Number Percentage

Gender 350 100.0

Male 127 36.3

Female 223 63.7

Missing (n = 58)

Age group (year) 350 100.0

<30 78 22.3

30-39 125 35.7

40-49 55 15.7

50-59 55 15.7

• 37 10.6

Missing (n = 58)

Type of primary care establishment 408 100.0

Public clinic 259 63.5

Private clinic 149 36.5

Characteristics Number Percentage

3RVWJUDGXDWHTXDOLÀFDWLRQ 350 100.0

Family Medicine 16 4.6

Others: public health, occupational medicine, health services management 6 1.7

None 328 93.7

Missing (n = 58)

Working hours per doctor per week (hours)(a) _{42 (40-45)}

Public 40 (40-45)

Private 48 (42-60)

(a) displayed as median (interquartile range)

REFERENCE

1. Hwong WY, Sivasampu S, Aisyah A, Shantha Kumar C, Goh PP, Hisham AN. National Clinical Research Centre. National Healthcare Establishment and Workforce Statistics (Primary Care) 2012. Kuala Lumpur 2014.

Chapter 5

The Patients

CHAPTER 5: THE PATIENTS

This chapter reports the socio-demographic characteristics of the patient encounters. Mode of payment IRUSULPDU\FDUHVHUYLFHVLVVXDQFHRIPHGLFDOFHUWLÀFDWHDQGGXUDWLRQRIVLFNOHDYHJLYHQDWSULPDU\FDUH visits are also discussed in this chapter.

5.1 AGE-GENDER DISTRIBUTION OF PATIENTS

The overall distribution of patients at the point of encounter by age and gender was presented in Figure 5.1.

‡ 2YHUDOOIHPDOHVDFFRXQWHGIRURIHQFRXQWHUV

‡ 7KHSHUFHQWDJHRISDWLHQWYLVLWVLQFUHDVHGZLWKDJHIURPEHORZ\HDUROGVSHDNHGDWDJHVRI years and declined as the age increased.

‡ 7KHODUJHVWGLIIHUHQFHLQWKHSURSRUWLRQRISDWLHQWVE\JHQGHULVREVHUYHGDPRQJWKRVHDJHG \HDUV IHPDOH YHUVXV PDOH 7KLV REVHUYHG GLIIHUHQFH OLNHO\ UHÁHFWV WKH KLJKHU numbers of antenatal visits within this female reproductive age group and the greater likelihood of delay in seeking help during illness among the males.1

Figure 5.1: Age-gender distribution of patients in primary care clinics in 2012

5.2 PATIENT SOCIO-DEMOGRAPHIC CHARACTERISTICS Table 5.1 shows the socio-demographic characteristics of the patients. ‡ 7KHSULYDWHFOLQLFVVHHDODUJHUVKDUHRISDWLHQWHQFRXQWHUV

‡ 0RVWSDWLHQWVZHUHHLWKHU0DOD\VLDQVRUSHUPDQHQWUHVLGHQWVRI0DOD\VLD7KHSURSRUWLRQRI encounters by non-Malaysians (7.8%) corresponds to the reported 8.2% of non-citizens from the total general population.2

‡ 0DMRULW\RISDWLHQWVSUHVHQWLQJWRSULPDU\FDUHFOLQLFVZHUH0DOD\V7KHGLVWULEXWLRQRI ethnicity reported for NMCS 2012 were similar to general population data as reported by the Department of Statistics Malaysia.2

‡ 1HDUO\RIWKHSDWLHQWVZKRYLVLWHGSULPDU\FDUHZHUH\HDUVDQGROGHU7KHHOGHUO\• years) currently make up 5.3% of the Malaysian population and this number is projected to reach 7.3% by 2021.3 _{Thus, the proportion of attendances by patients of this age group and complexity of}

morbidities in primary care is anticipated to increase as the population ages. Male

Percent

Age Group (years)

Female

<1 1-4 5-19 20-39 40-59 >60 1.9

30 25 20 15 10 5 0

3.0 5.0 16.9 12.7 5.1

1.7 3.0 4.5 26.1 13.3 6.6

Table 5.1: Characteristics of patient encounters in primary care clinics in 2012

Patient Characteristics Number Percentage 95% CI

LCL UCL

Gender(a) _137,604

Male 61,702 44.8 44.6 45.1

Female 75,902 55.2 54.8 55.6

Missing (n = 3,989)

Age group (year)(a) _140,145

<1 5,115 3.7 3.6 3.8

1-4 8,587 6.1 6.0 6.3

5-19 13,530 9.7 9.5 9.8

20-39 60,671 43.3 43.0 43.6

40-59 36,130 25.8 25.6 26.0

• 16,111 11.5 11.3 11.7

Missing (n = 1,448)

Nationality(a) _138,686

Malaysian + permanent resident 127,855 92.2 92.0 92.3

Foreigner 10,830 7.8 7.7 8.0

Missing (n = 2,907)

Type of primary care clinic 141,593

Public 42,340 29.9 29.7 30.1

Private 99,253 70.1 69.9 70.3

Ethnicity(a) _129,607

Malay 82,353 63.5 63.3 63.8

Chinese 25,188 19.4 19.2 19.7

Indian 14,805 11.4 11.3 11.6

Others(b) _{7,260 5.6 5.5 5.7}

Missing (n = 11,986)

Seen at clinic in the last 2 years(a) _124,562

Yes 90,891 73.0 72.7 73.2

No 33,671 27.0 26.8 27.3

Missing (n = 17,031)

(a) Missing data were excluded from analysis

5.3 MODE OF PAYMENT

Figure 5.2 describes the mode of payment for encounters in primary care clinics.

‡ 7KLUW\WZRSHUFHQWRISDWLHQWHQFRXQWHUVZHUHVXEVLGLVHGE\WKHJRYHUQPHQWUHÁHFWLQJWKHSURSRUWLRQ of visits to public clinics.

‡ $PRQJYLVLWVWRSULYDWHFOLQLFVRIHQFRXQWHUVZHUHRXWRISRFNHWSD\PHQWZKLOHRIWKHP were either fully or partially paid by third party payers. Third party payer payments include those by private insurance, employer and managed care organisations.

‡ 7KHUHZHUHIHZFDVHVZKHUHE\SD\PHQWZDVPDGHWKURXJKFRPELQDWLRQRIRXWRISRFNHWDQGWKLUG party payers.

‡ $VPDOOSURSRUWLRQRIYLVLWVWRSULPDU\FDUHFOLQLFVZHUHQRWFKDUJHGDQ\IHH

Figure 5.2: Mode of payment in primary care clinics in 2012

5.4 MEDICAL CERTIFICATE AND DURATION OF SICK LEAVE

$ WRWDO SDWLHQWV ZHUH LVVXHG PHGLFDO FHUWLÀFDWHV ZKHQ YLVLWLQJ SULPDU\ FDUH FOLQLFV )LJXUH&RPSDULVRQE\VHFWRUVUHYHDOHGWKDWPHGLFDOFHUWLÀFDWHVZHUHJLYHQWRRISDWLHQWV visiting public clinics and 34.9% of patients at private clinics. The number of days of sick leave that were documented ranged from half day to 21 days (Table 5.2).

Ra te pe r 1 0 0 e nc o unt e rs 36.4 31.8 31.5 0.2 0.2 40 35 30 25 20 15 10 5 0

Out - of -pocket Out - of -pocket +

Third party prayer Government subsidy Third party prayer No payment

)LJXUH3HUFHQWDJHRISULPDU\FDUHHQFRXQWHUVLVVXHGPHGLFDOFHUWLÀFDWHLQ

Table 5.2: Duration of sick leave issued in primary care clinics in 2012

Duration of sick leave (day) Number Rate per 100 encounters

95% CI

LCL UCL

0.5 - 1 27,844 83.0 82.6 83.4

1.5 - 2 5,045 15.0 14.7 15.4

3 - 7 637 1.9 1.8 2.1

>7 21 0.1 0.0 0.1

Subtotal(a) _{33,547 100.0 100.0 100.0}

D7RWDOHQFRXQWHUVZLWKGHWDLOVRQWKHGXUDWLRQRIVLFNOHDYHIRUZKLFKDPHGLFDOFHUWLÀFDWHZDVLVVXHG

REFERENCES

1. Galdas PM, Cheater F, Marshall P. Men and health help-seeking behaviour: literature review. J Adv Nurs. 2005;49(6):616-23.

2. Department of Statistics, Malaysia. Population distribution and basic demographic characteristics 2010. [Viewed January 2014]. Available from: http://www.statistics.gov.my/portal/download_ 3RSXODWLRQÀOHVFHQVXV7DEXUDQB3HQGXGXNBGDQB&LULFLULB$VDVB'HPRJUDÀSGI

3. Department of Statistics, Malaysia. Population projections 2010-2040. Nov 2012. [Viewed January @ $YDLODEOH IURP KWWSZZZVWDWLVWLFVJRYP\SRUWDOGRZQORDGB3RSXODWLRQÀOHVSRSXODWLRQB projections/Population_Projection_2010-2040.pdf

Yes No 28.7%

Chapter 6

Reasons For Encounter

CHAPTER 6: REASONS FOR ENCOUNTER

Reasons for encounter (RFE) or patients’ presenting complaint refers to the reasons why a patient seeks health care; whether due to a symptom or complaint, follow-up on a known problem, request for screening or diagnostic investigations, request for medical management or administrative procedures. The documentation of RFE is important in the patient-centred approach as it takes into consideration the patient’s perspective of why he or she seeks health services. The RFE also serves as the basis for HVWDEOLVKLQJDGLDJQRVLVDQGLQÁXHQFHVWKHSURFHVVHVRIFDUHDQGPDQDJHPHQWZKLFKIROORZV1

This chapter reports the RFE of the patients. Doctors were allowed to record RFEs based on three major types of complaints; symptoms, a follow-up on a known diagnosis or a procedure or administrative request. 6.1 NUMBER OF REASONS FOR ENCOUNTER PER VISIT

Figure 6.1 shows the number of RFEs at encounter. There were 233,326 RFEs recorded for NMCS 2012. Approximately 50.0% of encounters in both public and private clinics had only one RFE. Majority of patients had between one to three RFEs at the point of visit. There were 3,201 encounters (2.3%) with no known RFEs and recorded as not available (nil).

Figure 6.1: Number of patient reasons for encounter in primary care clinics in 2012

6.2 REASONS FOR ENCOUNTER BY ICPC-2 COMPONENTS Table 6.1 shows the distribution of RFEs by ICPC-2 components.

‡ 0RUHWKDQKDOIRIWRWDO5)(VZHUHEDVHGRQV\PSWRPVDQGFRPSODLQWV

‡ 5)(VGHVFULEHGDVGLVHDVHFRQVWLWXWHGRI5)(V0RVWZHUHIRU‘other diagnoses, diseases’ which LQFOXGHGLVHDVHVWKDWGRQRWIDOOLQWRWKHFODVVLÀFDWLRQRILQIHFWLRXVGLVHDVHVQHRSODVPVLQMXULHVRU congenital anomalies.

‡ 5)(V ZHUH DOVR H[SUHVVHG DV SURFHVV RI FDUH WKRXJK LW DFFRXQWHG IRU OHVV WKDQ RI 5)(V These include diagnostic and preventive procedures, request for medications, test results, medical FHUWLÀFDWHRUUHIHUUDOV

Nil One Two Three >Four

Public 1.1 49.2 29.1 16.7 3.8

Private 2.8 51.9 30.8 11.6 2.9

0 10 20 30 40 50 60

P

e

rc

e

nt

o

f

e

nc

o

unt

e

rs

(%)

Table 6.1: Reasons for encounter by ICPC-2 components in primary care clinics in 2012

ICPC-2 component Number

Percentage of all RFEs (n = 233,326)

Rate per 100 encounters (n = 141,593)

95% CI

LCL UCL

Symptoms & complaints 138,664 59.43 97.93 97.86 98.00

Diagnosis, diseases 71,580 30.68 50.55 50.29 50.81

Infectious diseases 10,439 4.47 7.37 7.24 7.51

Neoplasms 100 0.04 0.07 0.06 0.09

Injuries 2,298 0.98 1.62 1.56 1.69

Congenital anomalies 68 0.03 0.05 0.04 0.06

Other diagnoses, diseases 58,675 25.15 41.44 41.18 41.70

Diagnostic and preventive

procedures 19,899 8.53 14.05 13.87 14.24

Treatment procedures, medication 2,474 1.06 1.75 1.68 1.82

Test results 538 0.23 0.38 0.35 0.41

Administrative 114 0.05 0.08 0.07 0.10

Referral and other reasons for

encounter 57 0.02 0.04 0.03 0.05

Total 233,326 100.00 164.78 -

-'LVWULEXWLRQRI5)(VE\,&3&FRPSRQHQWZDVIXUWKHUVWUDWLÀHGE\VHFWRUWRFRPSDUHWKHGLIIHUHQFHV between RFEs recorded in public and private clinics (Table 6.2). Interestingly, majority of the RFEs presented in public clinics were described as diseases (50.4%) whereas 70.6% of RFEs at private clinics were of symptoms and complaints.

Table 6.2: Reasons for encounter by ICPC-2 components and sector

ICPC-2 Component

Public Private

Number Percentage

of all RFEs Number

Percentage of all RFEs

Symptoms & complaints 25,951 35.25 112,713 70.57

Diagnosis, diseases 37,122 50.43 34,458 21.58

Infectious diseases 1,161 1.58 9,277 5.81

Neoplasms 18 0.02 82 0.05

Injuries 344 0.47 1,955 1.22

Congenital anomalies 31 0.04 37 0.02

2WKHUVSHFLÀFGLVHDVHV 35,568 48.32 23,107 14.47

Diagnostic and preventive procedures 9,887 13.43 10,011 6.27

Treatment procedures, medication 339 0.46 2,135 1.34

Test results 211 0.29 328 0.21

Administrative 77 0.10 37 0.02

Referral and other reasons for encounter 29 0.04 28 0.02

6.3 REASONS FOR ENCOUNTER BY ICPC-2 CHAPTERS

Table 6.3 shows the distribution of patients’ RFE by ICPC-2 chapters and the most common RFEs within each chapter (constituting at least 0.5% of all RFEs).

‡ 2QDYHUDJHWKHUHZHUH5)(VUHFRUGHGSHUSDWLHQWHQFRXQWHUV

‡ 5)(VUHODWHGWRUHVSLUDWRU\GLVHDVHVZHUHWKHFRPPRQHVWDQGSUHVHQWHGDWDUDWHRISHU encounters. Cough formed the majority and seen in 22 out of 100 encounters.

‡ 5)(VRIJHQHUDODQGXQVSHFLÀHGQDWXUHZHUHVHFRQGDWDUDWHRISHUHQFRXQWHUV:LWKLQWKLV chapter, fever was most frequently recorded.

‡ 5)(V UHODWHG WR HQGRFULQHPHWDEROLF DQG FDUGLRYDVFXODU GLVHDVHV ZHUH PRVWO\ IRU IROORZXS RQ chronic diseases.

Table 6.3: Reasons for encounter by ICPC-2 chapters and common individual reasons for encounter within chapter in primary care clinics in 2012

Reasons for encounter Number

Percentage of all RFEs (n = 233,326)

Rate per 100 encounters (n = 141,5 93)

95% CI LCL UCL

Respiratory 53,742 23.0 38.0 37.7 38.2

Cough 30,937 13.3 21.8 21.6 22.1

Sneezing/nasal congestion 5,308 2.3 3.8 3.7 3.8

Throat symptom/complaint 5,198 2.2 3.7 3.6 3.8

,QÁXHQ]D 3,708 1.6 2.6 2.5 2.7

Asthma 2,883 1.2 2.0 2.0 2.1

Upper respiratory infection,

acute 2,494 1.1 1.8 1.7 1.8

*HQHUDODQGXQVSHFLÀHG 46,742 20.0 33.0 32.8 33.3

Fever 29,355 12.6 20.7 20.5 20.9

Medical examination - general* 5,358 2.3 3.8 3.7 3.9

Dressing/pressure/compress/

tamponade 1,629 0.7 1.2 1.1 1.2

Diagnostic radiology/imaging 1,485 0.6 1.0 1.0 1.1

Pain general/multiple sites 1,358 0.6 1.0 0.9 1.0

Trauma/injury NOS 1,193 0.5 0.8 0.8 0.9

Digestive 32,101 13.8 22.7 22.5 22.9

Abdominal pain* 11,870 5.1 8.4 8.2 8.5

Diarrhoea 8,093 3.5 5.7 5.6 5.8

Vomiting 5,157 2.2 3.6 3.5 3.7

Dyspepsia/indigestion 1,318 0.6 0.9 0.9 1.0

Reasons for encounter Number

Percentage of all RFEs (n = 233,326)

Rate per 100 encounters (n = 141,593)

95% CI LCL UCL Endocrine/metabolic and

nutritional 23,947 10.3 16.9 16.7 17.1

Diabetes* 11,408 4.9 8.1 7.9 8.2

Diabetes, non-insulin

dependent 11,071 4.7 7.8 7.7 8.0

Diabetes, insulin dependent 337 0.1 0.2 0.2 0.3

Lipid disorder 10,423 4.5 7.4 7.2 7.5

Cardiovascular 20,790 8.9 14.7 14.5 14.9

Hypertension* 18,173 7.8 12.8 12.7 13.0

Musculoskeletal 12,764 5.5 9.0 8.9 9.2

Musculoskeletal symptom/

complaint* 7,496 3.2 5.3 5.2 5.4

Back problem* 3,440 1.5 2.4 2.4 2.5

Pregnancy, childbearing, family

planning 10,935 4.7 7.7 7.6 7.9

Medical examination -

pregnancy* 9,259 4.0 6.5 6.4 6.7

Skin 9,848 4.2 7.0 6.8 7.1

Rash* 2,668 1.1 1.9 1.8 2.0

Pruritus 1,929 0.8 1.4 1.3 1.4

Neurological 8,784 3.8 6.2 6.1 6.3

Headache 5,428 2.3 3.8 3.7 3.9

Vertigo/dizziness 2,054 0.9 1.5 1.4 1.5

Eye 4,455 1.9 3.1 3.1 3.2

Red eye 1,057 0.5 0.7 0.7 0.8

Female genital 3,140 1.3 2.2 2.1 2.3

Menstrual problems* 1,829 0.8 1.3 1.2 1.4

Urological 2,241 1.0 1.6 1.5 1.6

Ear 1,603 0.7 1.1 1.1 1.2

Psychological 1,286 0.6 0.9 0.9 1.0

Blood, blood forming organs and

immune mechanism 534 0.2 0.4 0.3 0.4

Male genital 380 0.2 0.3 0.2 0.3

Social problems 34 0.0 0.0 0.0 0.0

*Multiple ICPC-2 codes (see Appendix 2)

Table 6.3 (continued): Reasons for encounter by ICPC-2 chapters and common individual reasons for encounter within chapter in primary care clinics in 2012

6.4 MOST COMMON REASONS FOR ENCOUNTER IN PUBLIC AND PRIVATE CLINICS Figure 6.2 and Figure 6.3 show the 10 most common reasons for encounter in public and private clinics, in decreasing order irrespective of ICPC-2 chapter or components.

‡ 2IWRWDO5)(VUHFRUGHGIRU10&6ZHUHIURPSXEOLFFOLQLFV

‡ 3DWLHQWVZKRDWWHQGHGSXEOLFFOLQLFVSUHVHQWHGZLWKVOLJKWO\PRUH5)(SHUHQFRXQWHUSHU encounters) than those seen in private clinics (161 per 100 encounters).

‡ $GLVWLQFWGLIIHUHQFHZDVREVHUYHGEHWZHHQFRPPRQHVW5)(VLQWKHWZRSULPDU\FDUHVHFWRUV7KH top three RFEs reported in public clinics were for chronic diseases whereas in private clinics most RFEs were for acute complaints.

‡ (LJKWHHQSHUFHQWRISDWLHQWVDWSXEOLFFOLQLFVFDPHIRUSUHJQDQF\H[DPLQDWLRQDQGWKLVZDVOLVWHG among 10 commonest RFEs. However, the proportion of patient who visited private clinics for pregnancy examination was smaller (1.6 per 100 encounters).

Figure 6.2 Top 10 reasons for encounter in public clinics in 2012

2.6 3.3

3.6 4.1

11.6 15.7

18.0 19.4

20.0

30.8

0 5 10 15 20 25 30 35 Medical exam - general*

Musculoskeletal symptom/complaint* Sneezing/nasal congestion Abdominal pain* Fever Cough Medical exam - pregnancy* Lipid disorder Diabetes* Hypertension*

Rate per 100 encounters

REFERENCE

1. Solera JK, Okkes I. Reasons for encounter and symptom diagnoses: a superior description of patients’ problems in contrast to medically unexplained symptoms (MUS). Family Practice. 2012; 29(3):272-82.

Figure 6.3 Top 10 reasons for encounter in private clinics in 2012

*Multiple ICPC-2 code (see Appendix 2)

4.3 4.4 4.6 4.6 5.2

6.1 7.2

10.2

24.5 24.6

0 5 10 15 20 25 30

Medical exam - general* Vomiting Headache Throat symptom/complaint Hypertension* Musculoskeletal symptom/complaint* Diarrhoea Abdominal pain* Cough Fever

Chapter 7

Diagnoses

CHAPTER 7: DIAGNOSES

This chapter highlights the diagnoses recorded by the doctors during patient visit to primary care clinics. The doctors could record up to six diagnoses per encounter. However the diagnoses reported are limited to disease/condition managed at the time of visit.

7.1 NUMBER OF DIAGNOSES PER ENCOUNTER

Number of diagnoses per visit in public and private clinics is presented in Figure 7.1. Overall, 90.0% of the encounters have a range of one to two diagnoses per encounter. Majority of the visits were associated with a single diagnosis, especially in private clinics and there were relatively fewer patients presented with three or more diagnoses.

Figure 7.1 Number of diagnoses managed per encounter in primary care clinics in 2012

There were 188,944 diagnoses in total, at a rate of 133.4 per 100 encounters. Distributions of total diagnoses according to sectors were as follow:

‡ 3XEOLFFOLQLFVGLDJQRVHVSHUHQFRXQWHUV ‡ 3ULYDWHFOLQLFVGLDJQRVHVSHUHQFRXQWHUV

)LJXUHVKRZVWKHDJHJHQGHUVSHFLÀFUDWHVRIGLDJQRVHVLQSXEOLFDQGSULYDWHFOLQLFV

‡ 7KHQXPEHURIGLDJQRVHVSHUHQFRXQWHULQFUHDVHGZLWKWKHSDWLHQWV·DJHHVSHFLDOO\DPRQJSDWLHQWV in public clinics.

‡ 7KHGLIIHUHQFHVLQGLDJQRVLVUDWHVEHWZHHQWKHWZRVHFWRUVZDVPRVWSURPLQHQWLQSDWLHQWVRIERWK genders aged 20 years onwards, where patients in public clinics were associated with a notably higher rate of diagnoses.

‡ ,QSXEOLFFOLQLFVIHPDOHSDWLHQWVDJHG\HDUVDQGDERYHKDGPRUHGLDJQRVHVSHUHQFRXQWHUWKDQ their male counterparts. As for patients under 5 years old, the diagnosis rates for males were higher. ‡ ,QSULYDWHFOLQLFVWKHGLDJQRVLVUDWHVDSSHDUHGWREHDOPRVWVLPLODUZKHQPDOHVDQGIHPDOHVZHUH

compared in each age group.

One Two Three •)RXU

59.5

3XEOLF 22.3 14.9 3.3

82.8

3ULYDWH 14.3 2.4 0.6

P e rc e nt o f e nc o unt e rs (%) 0 10 20 30 40 50 60 70 80 90

)LJXUH$JHJHQGHUVSHFLÀFUDWHVRIGLDJQRVHVPDQDJHGSHUHQFRXQWHUVE\VHFWRULQ 2012

7.2 DIAGNOSES BY ICPC-2 COMPONENT

The diagnoses were categorised by ICPC-2 components to describe the distribution of diagnoses managed in primary care, as listed in Table 7.1. Diseases were used as diagnosis in 72.6% of all cases; majority were for ‘other diagnoses’ (41.7%), followed by infections (29.5%), injuries (1.2%), neoplasm (0.1%) and congenital anomalies (0.1%). Symptoms or complaints were used as diagnosis in 19.8% of all diagnoses while diagnostic and preventive procedures (e.g. immunisations, medical examination) accounted for 7.2%.

Table 7.1: Diagnoses by ICPC-2 components in primary care clinics in 2012

ICPC-2 Component Number

Percentage of all diagnoses (n = 188,844)

Rate per 100 encounters (n = 141,593)

95% CI LCL UCL

Diagnosis, diseases 137,134 72.58 96.85 96.76 96.94

Infections 55,792 29.53 39.40 39.15 39.66

Injuries 2,278 1.21 1.61 1.54 1.68

Neoplasms 190 0.10 0.14 0.12 0.15

Congenital anomalies 139 0.07 0.10 0.08 0.12

Other diagnoses, diseases 78,736 41.67 55.61 55.35 55.87

Symptoms and complaints 37,328 19.76 26.36 26.13 26.59

Diagnostics and preventive procedures 13,620 7.21 9.62 9.47 9.77

Medications, treatments and therapeutics 613 0.32 0.43 0.40 0.47

Results 123 0.06 0.09 0.07 0.10

Referrals and other RFEs 93 0.05 0.07 0.05 0.08

Administrative 33 0.02 0.03 0.02 0.03

217.0 229.2 160.9 157.3 0 50 100 200 250

<1 year 1-4 years 5-19 years 20-39 years 40-59 years >60 years

Ra te pe r 1 0 0 e nc o unt e rs

Age group (years)

Public, male Public, female Private, male Private, female

APPENDIX 3: PARTICIPANTS OF NMCS 2012

PUBLIC CLINICS

Public Clinics (Selangor)

1 Klinik Kesihatan Bagan Terap 17 Klinik Kesihatan Rawang 2 Klinik Kesihatan Batu 14, Hulu Langat 18 Klinik Kesihatan Salak

3 Klinik Kesihatan Batu 9 19 Klinik Kesihatan Selayang Baru 4 Klinik Kesihatan Batu Arang 20 Klinik Kesihatan Semenyih 5 Klinik Kesihatan Bestari Jaya 21 Klinik Kesihatan Serendah 6 Klinik Kesihatan Bukit Changgang 22 Klinik Kesihatan Sungai Besar 7 Klinik Kesihatan Bukit Kuda 23 Klinik Kesihatan Sungai Buloh 8 Klinik Kesihatan Dengkil 24 Klinik Kesihatan Sungai Selisek 9 Klinik Kesihatan Gombak Setia 25 Klinik Kesihatan Taman Ehsan 10 Klinik Kesihatan Ijok 26 Klinik Kesihatan Telok Datok

11 Klinik Kesihatan Jeram 27 Klinik Kesihatan Telok Panglima Garang 12 Klinik Kesihatan Kajang 28 Klinik Kesihatan Ulu Yam Bharu 13 Klinik Kesihatan Pandamaran 29 Poliklinik Komuniti Kapar 14 Klinik Kesihatan Parit Baru 30 Poliklinik Komuniti Meru 15 Klinik Kesihatan Pelabuhan Klang 31 Poliklinik Komuniti Sekinchan 16 Klinik Kesihatan Rasa 32 Poliklinik Komuniti Sungai Air Tawar

Public Clinics (WP Putrajaya)

1 Klinik Kesihatan Putrajaya

2 Klinik Kesihatan Putrajaya Presint 3

Public Clinics (WP Kuala Lumpur)

1 Klinik Kesihatan Bandar Tun Razak 5 Klinik Kesihatan Pantai

2 Klinik Kesihatan Batu 6 Klinik Kesihatan Petaling Bahagia 3 Klinik Kesihatan Cheras 7 Klinik Kesihatan Sungai Besi 4 Klinik Kesihatan Jinjang 8 Poliklinik Komuniti Tanglin

Public Clinics (Kelantan)

1 Klinik Kesihatan Aring 2 11 Klinik Kesihatan Kemahang 2 Klinik Kesihatan Bachok 12 Klinik Kesihatan Lundang Paku 3 Klinik Kesihatan Badang 13 Klinik Kesihatan Penambang 4 Klinik Kesihatan Balai 14 Klinik Kesihatan Selising 5 Klinik Kesihatan Bandar Gua Musang 15 Klinik Kesihatan Temangan 6 Klinik Kesihatan Bandar Kuala Krai 16 Klinik Kesihatan Tendong 7 Klinik Kesihatan Beris Panchor 17 Klinik Kesihatan Tok Uban 8 Klinik Kesihatan Bunohan 18 Klinik Kesihatan Wakaf Bharu 9 Klinik Kesihatan Jeram Tekoh 19 Klinik Kesihatan Wakaf Che Yeh 10 Klinik Kesihatan Kedai Lalat

Public Clinics (Kota Kinabalu, Sabah)

1 Klinik Kesihatan Inanam 3 Klinik Kesihatan Menggatal 2 Klinik Kesihatan Luyang 4 Klinik Kesihatan Telipok

Public Clinics (Kuching, Sarawak)

1 Klinik Kesihatan Batu Kawa 3 Klinik Kesihatan Kota Sentosa

PRIVATE CLINICS

Private Clinics (Selangor)

1 Drs Young Newton & Rakan-Rakan, Petaling Jaya

28 Klinik Dr. Fauziah 2 Kelinik Lim, Jln Berangan 29 Klinik Dr. I. Chin 3 Kelinik Mohan, Jln Kg Jawa 30 Klinik Dr. Suhaida 4 Klinik & Surgeri Bukit Rimau 31 Klinik Fadzilyana

5 Klinik & Surgeri Chuah 32 Klinik Famili Bandar Puteri, Puchong

6 Klinik & Surgeri Sidhu 33 Klinik Famili Dr Wan Kamariah Sdn. Bhd, Batu Caves

7 Klinik Abd Hamid, Sekinchan 34 Klinik Famili Shah Alam, Kota Kemuning 8 Klinik Alam Medic, Taman Tasik Prima 35 Klinik Famili Shah Alam, Seksyen 27 9 Klinik Alam Medic (Kota Kemuning) 36 .OLQLN)DPLOL6RÀD

10 Klinik Alam Medic, Taman Sri Muda 37 Klinik Famili TTDI

11 Klinik Alam Medic, Tmn Puchong Perdana 38 Klinik Faridah & Dr Rashid, Shah Alam 12 Klinik Alam Megah, Shah Alam 39 Klinik Fatimah

13 Klinik Amardev & Surgery 40 Klinik Fauziah Dan Rakan-Rakan 14 Klinik Anis, Shah Alam 41 Klinik Guan Sdn. Bhd

15 Klinik Antarabangsa 42 Klinik Hamzah, Klang 16 Klinik Aspalela, Pinggiran Subang 43 Klinik Hanita, Kajang

17 Klinik Azlina & Sharifah 44 Klinik Hasniah Elani, Batu Caves 18 Klinik Bahari 45 Klinik Hayati, Batu Caves 19 Klinik Bandaran, Subang Jaya 46 Klinik Hooi, Cheras

20 Klinik Bandaran, Kota Kemuning 47 Klinik Idzham (Tmn Wangsa Ukay) 21 Klinik Bandaran USJ 48 Klinik Johari Dan Anita

22 Klinik C J Kwek, Subang Jaya 49 Klinik Kathy Am

23 Klinik Chieng, Klang 50 Klinik Keluarga Jugra, Banting 24 Klinik Chin, Puchong 51 Klinik Keluarga Lee, Subang Jaya 25 Klinik Dan Surgeri Jaspal, Klang 52 Klinik Kumpulan Medic

26 Klinik Dr Shamsuddin, Sg Buloh 53 Klinik Mediviron (Formerly Kelinik Bina) 27 Klinik Dr Suraya

Private Clinics (WP Kuala Lumpur)

1 Drs Young Newton & Rakan-Rakan, Damansara Heights

16 Klinik Leela Ratos & Rakan-Rakan 2 Drs. Young, Newton Dan Rakan-Rakan, Capital

Square

17 Klinik Medi Al Hilmi 3 Klinik Ahmad-Shan Dan Surgeri 18 Klinik Medic Bestari

4 Klinik Ashvini 19 Klinik Mediviron, Bukit Jalil 5 Klinik Catterall, Khoo And Raja Malek 20 Klinik Rakyat

6 Klinik Chin Chee Yeong 21 Klinik Rapha Goodwill 7 Klinik Chong & Rakan-Rakan 22 Klinik Reddy Setapak 8 Klinik Dan Surgeri Sri Damansara 23 Klinik Senan

9 Klinik Dr Shashikala Sdn Bhd 24 Klinik Sharani 10 Klinik Dr. Rahim Omar & Rakan-Rakan 25 Klinik Tan & Mano 11 Klinik Famili Seri Petaling 26 Klinik Yong 12 Klinik Genting Unimed 27 Kumpulan Medic

13 Klinik Harun 28 Poliklinik & Surgeri Kong 14 Klinik K.H.Ong 29 Poliklinik Lourdes

Private Clinics (Kelantan)

1 Klinik A Wahab 13 Klinik Mardhiah

2 Klinik Chong 14 Klinik Murni

3 Klinik Dr Che Ku 15 Klinik Nik

4 Klinik Dr. Wan Abdul Kadir 16 Klinik Pancho 5 Klinik Dr. Yasiman Perdana 17 Klinik Penawar

6 Klinik Dr. Roslan 18 Klinik Perdana Cawangan Islah 7 Klinik Dr. Wan 19 Klinik Perdana Pengkalan Chepa

8 Klinik Keluarga 20 Klinik Raju

9 Klinik Kok Lanas 21 .OLQLN5RVGDQ +DÀG]DK 10 Klinik Lee 22 Klinik Sayyida Sdn. Bhd.

11 Klinik Lua 23 Klinik Shafee

12 Klinik Mahmood (Cawangan Wakaf Bharu) 24 Klinik Wakaf Siku 3

Private Clinics (Kota Kinabalu, Sabah)

1 Klinik & Surgeri Dr C. F. Pang Sdn. Bhd 6 Klinik Malaysia (Cawangan Centre Point) 2 Klinik & Surgeri Dr Harvinder 7 Klinik Sihat

3 Klinik & Surgeri Lau & Choong 8 Permai Polyclinics Lintas Plaza

4 Klinik Aslam 9 Poliklinik Rakyat - Cawangan Kota Kinabalu 5 Klinik Dr. Baharin

Private Clinics (Kuching, Sarawak)

1 Klinik Bina 3 Klinik Sharifah Ihsan

APPENDIX 4: LIST OF DEFINITIONS

VARIABLE DEFINITION

Encounter A professional interaction between a patient and healthcare provider(s) for the purpose of providing healthcare service(s) or assessing the health status of a patient.

Morbidity Departure from a state of physical or psychological well-being resulting from disease, illness, injury or sickness.

Provider A person to whom patient has access when contacting the healthcare system and helps in identifying or preventing or treating illness or disability.

Government subsidy

Funding for treatment is supported by government agencies such as Ministry of Health. These agencies include a variety of permanent or semi-permanent organisation in the machinery of government that is responsible for the oversight

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Third party payers Any organisation other than the patient or healthcare provider involved in the

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‡ Panel Company: Private employer or corporations. These include all resident

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resident institutional units. They are simply characterised by the fact that they are not subject to control by the government or from abroad.

‡ Private insurance: 6RFLDO LQVXUDQFH EHQHÀWV SD\DEOH WR KRXVHKROGV E\ insurance enterprises or other institutional units administering private funded social insurance schemes.

‡ Managed Care Organisation (MCO): Any organisation or body with whom a private healthcare facility or service makes a contract or has an arrangement

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system through one or a combination of mechanisms. It combines functions of health insurance, delivery of care and administration (e.g. Integrated Healthcare Management (IHM)).

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Reasons for encounter (RFEs)

The subjective reason(s) given by the patient for seeking health care. These can be a symptom, complaint, follow-up on a known problem, or request for a service. Diagnosis A statement that describes the reason for a disease, illness, or problem presented

by a patient through evaluation of patient history, examination and review of laboratory data.

Investigation A test or examination done to establish a diagnosis (e.g. full blood count, chest X-ray).

Procedures A course of action done to establish diagnosis or for treatment.

Advice/counselling The act of giving advice to patients as needed. This refers to health education, advice or counselling delivered by healthcare providers during encounter.

Follow-up The act of maintaining periodic contact with patient for continuous care.

Referral The process of directing patient to a different place or person for further management.