CHAPTER three
Response Rate
30
National Medical Care Statistics 2014
CHAPTER 3: RESPONSE RATE
3.1 RESPONSE RATE
This chapter describes the survey sample and the response rate for NMCS 2014. A total of 139 public clinics and 1,002 private clinics were sampled in NMCS 2014. The clinics are listed in Appendix 5. The
response rates were calculated as the number of clinics that responded by returning the NMCS 2014 questionnaire divided by the number of clinics in the sample. Table 3.1.1 shows the number of clinics
sampled, number of clinics responded to the survey and the clinic response rate for each state or federal territory.
Table 3.1.1: Total number clinics sampled and responde
d
or NMCS 2014
State
f
deral territory Public
Private Number
o
f
linics sampled
Number
f
clinics responded
Response rate
Number o
f
linics sampled
Number
f
clinics responded
Response rate
Johor 11
10 90.9
117 43
36.7 Kedah
7 7
100.0 55
22 40.0
Kelantan 7
7 100.0
45 22
48.9 Melaka
26 23
88.5 31
14 45.2
Negeri Sembilan 6
5 83.3
40 19
47.5 Pahang
6 6
100.0 42
18 42.9
Perak 11
11 100.0
73 30
41.1 Perlis
9 7
77.8 10
7 70.0
Pulau Pinang 5
5 100.0
70 33
47.1 Sabah WP Labuan
9 7
77.8 65
26 40.0
Sarawak 10
10 100.0
34 16
47.1 Selangor WP Putrajaya
15 14
93.3 270
102 37.8
Terengganu 5
5 100.0
30 18
60.0 WP Kuala Lumpur
12 12
100.0 120
46 38.3
Total 139
129 92.
8
1,002 416
41.5
Overall, more than three quarters of public clinics from thirteen states and three federal territories responded to NMCS 2014. The maximum response rate was 100.0 while the minimum is 77.8, which
gave the overall response rate of 92.8 in public sector. As for private sector, the lowest response rate was only 37.6, bringing the overall response rate to 41.5, in spite of our fervent attempts to persuade
the GPs to participate. Response rates by encounters are reported in Table 3.1.2. These response rates were calculated as the
number of encounters that were recorded for NMCS 2014 divided by the expected number of encounters in the sample for each stratum to form a national representative data.
31
Chapter 3 : Response Rate
11 9
117 7
55 7
45 26
5 31
6 3
40 6
42 11
73 9
8 10
5 70
9 8
65 10
34 aya
15 3
270 5
30 12
120
139 002
Table 3.1.2: Total number encounters received
or NMCS 2014
State ederal
territory Public
Private Number
encounters expected
Number encounter
responded Response
rate Number
encounters expected
Number o
encounter responded
Response rate
Johor 1,164
1,753 100.0
3,597 1,295
36.0 Kedah
746 627
84.0 1,694
803 47.4
Kelantan 778
621 79.8
1,395 607
43.5 Melaka
450 2,357
100.0 941
325 34.5
Negeri Sembilan 697
510 73.2
1,223 739
60.4 Pahang
698 494
70.8 1,277
532 41.7
Perak 1,174
1,375 100.0
2,228 807
36.2 Perlis
152 581
100.0 320
323 100.0
Pulau Pinang 581
794 100.0
2,139 917
42.9 Sabah WP
Labuan 927
709 76.5
1,997 736
36.9 Sarawak
1,062 947
89.2 1,056
567 53.7
Selangor WP Putrajaya
1,627 1,707
100.0 8,265
2,691 32.6
Terengganu 498
383 76.9
929 575
61.9 WP Kuala Lumpur
397 2,612
100.0 3,671
1,200 32.7
Total 10,951
15,470 100.0
30,732 12,117
39.4
Response rate by encounters obtained from public clinics of all thirteen states and three federal territories were overwhelming and some exceeded 100.0. WP Kuala Lumpur recorded the highest
response rate with more than six times encounters that were required for the study, while the lowest was 70.8 from Pahang. As for private sector, the minimum response rate by encounters was 32.7
from WP Kuala Lumpur, while Perlis recorded the maximum response rate of 100.0. The overall response rate for public and private sector was 100.0 and 39.4, respectively.
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 and 33.0.
1,2
The same observation was made in Australia in the BEACH survey, with only 25.9 and 25.2 of the contactable general practitioners
agreed and completed the survey in 2013-14 and 2012-13 respectively.
3,4
32
National Medical Care Statistics 2014
3.2 THE ENC
O
ERS
A total of 27,813 encounters were collected for NMCS 2014. Of these, 226 encounters were excluded from analysis; 61 of incomplete forms and 165 with data inconsistencies. The final encounters for
analysis were 27,587; 15,470 from public and 12,117 from private. The dataset were weighted to adjust for over and under representativeness of data see Section 2.5. Table 3.2.1 shows the observed and
weighted total for each data element. The final weighted patient encounters were 325,818, and the results are presented as weighted estimates in this report.
Table 3.2.1: Observed and weighted dataset or NMCS 2014
Variable Observed
Weighted Overall
Public Private
Overall Public
Private
Encounters 27,587
15,470 12,117
325,818 131,624
194,194 Reasons for encounter
50,642 29,478
21,164 597,563
252,050 345,513
Diagnoses 38,151
23,760 14,391
436,743 203,868
232,874 Medications
70,711 38,296
32,415 864,552
327,087 537,465
Investigations 14,208
12,182 2,026
143,758 108,557
35,201 Advicecounselling and
procedures 12,926
9,500 3,426
136,708 77,670
59,038 Follow-up and referrals
9,841 8,143
1,698 100,709
72,418 28,291
REFERENCES
1. Teng CL, Tong SF, Khoo EM, Lee , Zailinawati AH, Mimi O, et al. Antibiotics for URTI and UTI –
prescribing in Malaysian primary care settings. Aust Fam Physician. 2011 May;405:325-9. 2. Mimi O, Tong SF, Nordin S, Teng CL, Khoo EM, Abdul-Rahman A, et al. A comparison of
morbidity patterns in public and private primary care clinics in Malaysia. Malays Fam Physician. 2011 Apr 30;61:19-25.
3. Britt H, Miller GC, Henderson J, Bayram C, Harrison C, alenti L, et al. General practice activity
in Australia 2013–14. Sydney Australia: Sydney University Press; 2014. General practice series; no. 36.
4. Britt H, Miller GC, Henderson J, Bayram C
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