Q1 2011 12 HMIS Report - Ministry of Health HMIS Report.pdf · Ministry of Health Resource Centre 4 2.0 HMIS Reporting 2.1 Completeness Table 1 below shows the extent to which the

MINISTRY OF HEALTH

RESOURCE CENTRE

QUARTERLY REPORT

JULY – SEPTEMBER 2011

Q1 Financial year 2011/12

Compiled: 29th

November 2011

Ministry of Health Resource Centre

2

Table of contents

1.0 Introduction .............................................................................................................................. 3

2.0 HMIS Reporting ......................................................................................................................... 4

2.1 Completeness ........................................................................................................................ 4

2.2 Timeliness .............................................................................................................................. 7

3.0 Section Analysis ......................................................................................................................... 8

3.1 Maternal and Perinatal conditions........................................................................................ 8

3.2 Antenatal ............................................................................................................................... 8

3.3 Maternity ............................................................................................................................. 11

3.4 HIV/AIDS Counseling and Testing ........................................................................................ 13

3.5 Essential Drugs, Vaccines and Contraceptives .................................................................... 14

4.0 Quarterly League Table ........................................................................................................... 18

4.1 Sorted by district ................................................................................................................. 18

APPENDIX: ..................................................................................................................................... 25


3

1.0 Introduction

The Health Management Information System facilitates data collection during health service

delivery which is critical for tracking performance and trend analysis. The HMIS has the

following categories of information: data on individual clients, information on curative services,

information on preventive services, resource management e.g. inventories (staff list, health

facility, equipment), logistics and commodities, finance / user fees and Village Health Teams

(Integrated Community Case Management).

The Ministry of Health Resource Centre is responsible for the collection, processing, analysis,

and dissemination of national health data collected through the Health Management

Information System (HMIS). The MoH Resource Centre is ensuring that quality and timely data

is collected through the revised HMIS tools to facilitate decision making, policy formulation as

well as accountability. The roll out and utilization of the revised HMIS tools by all the health

facilities nationwide started in July 2011 and the process is still continuing. The Resource

Centre has provided support to the district health teams and the health facilities throughout

this reporting period to appreciate and correctly utilize these HMIS tools through trainings and

support supervisions.

This report gives an account of the reporting from the health facilities across the country for the

period July – September 2011. The activities from the functioning health units are reported

using HMIS 105 and 108 for Outpatient and Inpatient, respectively to the districts. The district

then aggregates the health unit reports within their respective districts into HMIS 123 and HMIS

124 for Outpatient and Inpatient data, respectively.

This report compares performance for the various indicators with previous quarterly

performance. Also provided is the Quarterly District League Table for Q1 of FY2011/12

Information in this report has been generated to reflect trends of certain diseases/ conditions

in specific thematic areas like Malaria, Antenatal, Maternity, HIV/AIDS counseling and testing

Maternal and perinatal conditions and Essential drugs, vaccines and contraceptives.

In order for us to comprehend and appreciate the reporting status from the different districts in

terms of completeness and timeliness, graphical presentations have been incorporated.

The Resource Centre however still has a challenge of limited personnel who are dedicated to

data entry, cleaning and supporting in the basic analysis. This has contributed to a backlog in

the databank for reports to be entered in the electronic system especially for Inpatient data.


4

2.0 HMIS Reporting

2.1 Completeness

Table 1 below shows the extent to which the HMIS reports are submitted and captured in MoH-

RC from the various districts across the country. The total number of districts as of Q1

FY2011/12 is 112. All these districts are supposed to receive HMIS 105 and HMIS 108 reports

from the various health units and aggregate them into HMIS 123 and HMIS 124, respectively.

The HMIS 123 and HMIS 124 reports constitute information collected from the Outpatient and

Inpatient sections of the health units, respectively. It can be observed from Table 1 below and

Figure 1 below that Inpatient completeness in reporting is low as compared to Outpatient

completeness in reporting with an average of 67% for inpatient and 87% for outpatient for this

reporting period

Table 1: Reporting Trends 2010/2011

Reporting Trends 2010/2011

Q1

2010/11

Q2

2010/11

Q3

2010/11

Q4

2010/11

Q1

2011/12

% OPD Completeness 90 86 96 94 85

% IPD Completeness 74 62 87 86 80

% of HFs Reporting OPD 94 94 92 94 91

% of HFs Reporting IPD 75 86 83 82 73


5

Figure 1: Reporting Trends FY2010/2011 and Q1 FY2011/12

74%

62%

86%80%

94% 94% 94%91%

86%83%

73%

92%

0%

20%

40%

60%

80%

100%

120%

Q1

2010/11

Q2

2010/11

Q3

2010/11

Q4

2010/11

Q1

2011/12

Quarters

Pe

rce

nta

ge

% OPD Completeness % IPD Completeness % of HFs Reporting

OPD

% of HFs Reporting

IPD

Furthermore on the results above, the proportion of health units reporting for Outpatient

(average=93%) is consistently higher that for Inpatient (average = 80%) as seen in Fig 1 above.


6

Figure 2: Outpatient Reporting per month

Figure 3: Inpatient Reporting per month


7

Figure 2 and 3 above show the trends in number of reports for Outpatient and Inpatient

respectively by month from July 2010 to September 2011 the end of this reporting period.

2.2 Timeliness

The timeliness of reporting in HMIS is derived from the reports received and compared to the

date at which the report was submitted and received at MoH-RC through any means (hand

copy, email/electronic, faxed/scanned, etc...) and the expected date for these reports to be

submitted that is 28th

of the following month for HMIS 123 and HMIS 124. The computation is

independent of the districts who never submitted reports but dependent on reports submitted.

Figure 4: Outpatient & Inpatient Reporting Timeliness FY 2010/11 and Q1 FY2011/12

All efforts have been undertaken by the MoH-RC team to encourage the District Heath Teams

through the DHOs and district biostatisticians to compile and submit these reports in a timely

manner.

From Figure 4 above, it can be seen that for Inpatient and Outpatient timelines, the trend

evolves almost similarly. This is expected because in most cases the district

biostatisticians/HMIS focal persons compile and submit these two reports together. It’s only in

a few cases where report submission for HMIS 123 and 124 are different in time. Furthermore,


8

for reports that have been submitted over time per month the trend shows an improvement in

timeliness reporting.

3.0 Section Analysis

3.1 Maternal and Perinatal conditions

In this section we present a view of the total cases reported from Q1-2010/11 to the current

quarter Q1-2011/12 for abortion and Malaria in pregnancy. There is decline in the number of

abortions reported from the previous quarter 67883 to the current quarter 51235. The malaria

cases in pregnancy have also reduced from an average of 13500 to 9880 in the current

reporting period.

Figure 4: Trends of Malaria in Pregnancy and abortion for the periods given below

3.2 Antenatal

This section present trends for the quarters below for ANC re-attendance, New ANC attendance

and postnatal visits. Figure 5 below shows a relatively stable trend in reporting for New ANC

attendance .There has been a reduction in Q1-2011/12 for new ANC attendance as well for the

ANC re-attendance (4th

visit). During this reporting period, the postnatal visits have also

reduced as compared to the 4 previous quarter national wide.


9

Figure 5: Trends in Antenatal ANC Attendance for the period 2010/11

Presented in Figure 6 below are the trends in the ANC referral from units and referrals to unit.

It can be envisaged that the total referrals from units have been remained stable. A trend line

inserted indicates a stable horizontal trend. On the other hand, the referrals to the units have

had an increasing trend though not significant.

Figure 6: Trends in Antenatal Referrals to and from unit for the period 2010/11


10

Figure 7 below shows the distribution of the IPT doses (IPT 1 and IPT 2) administered during the

antenatal sessions over the reported quarters. For both the 1st

and 2nd

IPT dose, there has been

a stable trend of the doses administered over time.

Figure 7: Distribution of the IPT doses over the reported quarters


11

3.3 Maternity

Maternity section of the HMIS 123 (OPD) has variables which are used to generate maternal

health indicators as specified in Table 2 below. This report presents the reported cases for each

variable over the different quarters. Furthermore, Figure 8 below shows selected maternity

variables (Deliveries HIV positive in unit, Babies born to HIV positive mothers given ARVs, and

Deliveries HIV positive who swallowed ARVs) over the quarters. Ideally, babies born to HIV

positive mothers should be followed up, monitored and given ARVs to prevent HIV

transmission. On average, 77% of the babies born to HIV positive mothers were given ARVs.

Additionally, an average of 89% of the HIV positive deliveries (mothers) swallowed ARVs.


12

Table 2: Cases of maternity indicators reported over the quarters specified

Diagnosis

Q1

2010/11

Q2

2010/11

Q3

2010/11

Q4

2010/11

Q1

2011/12

Admissions 176068 166337 166063 76019 18503

Babies (born to HIV positive mothers) given ARVs 5766 4783 5761 5554 5159

Babies born with low birth weight (<2.5kg) 7755 5509 7909 8630 5471

Birth Asphyxia 2915 2360 2039 2060 1497

Deliveries by private practitioners 1818 1812 1641 2236 2054

Deliveries HIV positive in unit 6825 6806 7430 7094 6712

Deliveries HIV positive who swallowed ARVs 6974 5574 6475 6310 5807

Deliveries in unit 138543 135437 137736 135927 113160

Deliveries with TBA 5811 5356 5468 4975 3702

Live birth to HIV positive mothers 7296 5532 7131 7622 5763

Live births in unit 129118 128647 128793 127758 104348

Maternal deaths 273 368 255 285 297

Referrals from unit 13452 9888 10364 10611 9456

Referrals to unit 11078 8853 9546 9480 8743

Still births in unit 3820 3083 3256 3027 2306


13

Figure 8: Selected maternity variables reported over the quarters

3.4 HIV/AIDS Counseling and Testing

The HMIS collects information on HIV/AIDS counseling and testing (HCT) aggregated by gender

and age. Figure 9 below shows the summary from the districts within this reporting period for

HIV tested in laboratory, those found HIV positive (Prevalence computed), and the individuals

found positive who started on Cotrimoxazole prophylaxis (CTX). National wide there has been

an increase in individuals who were offered a test in laboratory. This also can represent the

individuals who are seeking HCT on average. All Individuals who are found HIV positive are

supposed to be started on CTX prophylaxis and from the graph below an average proportion

87% HIV positive are started on CTX prophylaxis. The HIV prevalence in OPD attendance over

the quarters has an average of 7.5% slightly higher than the national average of 6.0%.


14

Figure 9: Individuals Tested from laboratory, those found HIV positive and those given CTX

prophylaxis

3.5 Essential Drugs, Vaccines and Contraceptives

The HMIS collects information regarding the number of health units for which the drugs,

vaccines or contraceptives (aligned to the HSSIP indicators) were out of stock at any one time

during the month preceding the month of reporting. Presented below is a trend of the quarterly

summary of the proportion of health facilities with no stock out for a selected HSSP tracer drug

items (First line drug for malaria, Measles vaccine, Fansidar, ORS sachets, Cotrimoxazole tabs

and Depo-Provera). The Objective of this indicator is to ensure “No Stockouts” of essential

medicines at all times in order to deliver the Uganda Minimum Healthcare Package. From Table

3 and Figure 10 below, it can be seen that there has been a substantial improvement of

reported no stock out in this reporting period as compared to the previous for essentially all the

items.


15

Table 3: Health Facilities with “No stock-out” of any of the tracer medicines FY 2010/11 and Q1

FY2011/12

Tracer Drugs

Percentage of HF with “NO STOCKOUT” by Quarter

Q1

2010/11

Q2

2010/11

Q3

2010/11

Q4

2010/11

Q1

2011/12

First line drug for

Malaria 84% 88% 87% 89% 93%

Measles vaccine 92% 93% 93% 94% 96%

Fansidar 86% 89% 89% 91% 93%

ORS Sachets 90% 91% 91% 92% 95%

Cotrimoxazole 85% 85% 80% 86% 92%

Depo-Provera 88% 88% 88% 92% 96%

Figure 10: Trend of percentage of Health facilities with no stock out over the quarter below

Additionally presented below is a table that shows the top 10 districts that reported more

health facilities with stock out for the above indicator items. As can be seen in Table 4 below,

the most recurrent districts in reporting health facilities with stock outs are GULU, MASINDI,

NAKAPIRIPIRIT, SIRONKO and SOROTI. MOROTO district only reported the highest and once in stock out

of Fansidar drugs during this reporting period.


16

Table 4: Top Ten districts reporting Stock out Health facilities for each indicator items

Cotrimoxazole Tabs Depo-Provera Fansidar

Rank District No. HFs

Stock out


Stock out


Stock out

1 GULU 50 1 GULU 50 1 MOROTO 100

2 MASINDI 49 2 MASINDI 47 2 GULU 50

3 NAKAPIRIPIRIT 40 3 NAKAPIRIPIRIT 40 3 MASINDI 47

4 SIRONKO 38 4 SIRONKO 36 4 MITYANA 45

5 KAMWENGE 35 5 SOROTI 32 5 TORORO 42

6 SOROTI 33 6 NAMAYINGO 21 6 NAKAPIRIPIRIT 40

7 TORORO 26 7 KAYUNGA 18 7 SOROTI 40

8 ISINGIRO 26 8 MITYANA 13 8 SIRONKO 34

9 KAYUNGA 25 9 MOYO 10 9 BUGIRI 33

10 BUNDIBUGYO 20 10 JINJA 9 10 MAYUGE 21

First Line drug for Malaria Measles Vaccine ORS Sachets


Stock out


Stock out


Stock out

1 GULU 50 1 GULU 49 1 GULU 50

2 MASINDI 48 2 MASINDI 48 2 MASINDI 47

3 NAKAPIRIPIRIT 40 3 NAKAPIRIPIRIT 40 3 NAKAPIRIPIRIT 40

4 SIRONKO 39 4 SOROTI 33 4 KAMWENGE 37

5 BUGIRI 39 5 SIRONKO 30 5 SOROTI 35

6 KAABONG 33 6 BUGIRI 30 6 SIRONKO 30

7 SOROTI 33 7 KAYUNGA 18 7 BUGIRI 28

8 KAYUNGA 22 8 BUNDIBUGYO 12 8 BUNDIBUGYO 25

9 MOYO 19 9 JINJA 10 9 KAYUNGA 19

10 NAKASONGOLA 17 10 MAYUGE 7 10 MAYUGE 9


17

4.0 Quarterly League Table

4.1 Sorted by Rank

Q1 2011/2012 LEAGUE TABLE D

IST

RIC

T

Po

pu

lati

on

Est

ima

te

Nu

mb

er

of

He

alt

h F

aci

lity

Re

po

rts

OP

D H

ea

lth

Un

it R

ep

ort

ing

OP

D R

ep

ort

ing

Tim

eli

ne

ss

DP

T3

fo

r <

1y

r o

n S

che

du

le

AN

C R

e-a

tte

nd

an

ce 4

th v

isit

% D

eli

ve

rie

s in

Go

vt

an

d N

GO

he

alt

h

faci

liti

es

% P

reg

na

nt

wo

me

n r

ece

ivin

g 2

nd

do

se

Fa

nsi

da

r fo

r IP

T

% P

lan

ne

d O

utr

ea

ch A

ctiv

itie

s

Co

nd

uct

ed

% P

reg

na

nt

Wo

me

n a

tte

nd

ing

An

ten

ata

l C

lin

ic.

(An

ten

ata

l C

ov

era

ge

)

% M

ala

ria

po

siti

vit

y r

ate

fo

r ch

ild

ren

un

de

r 5

ye

ars

TO

TA

L

RA

NK

ING

%

10

%

10

%

15 12.

5 %

12.

5 %

10

% 10

% 10

% 10

Sco

re

Sco

re

Sco

re

%

Sco

re

Sco

re

Sco

re

Sco

re

Sco

re

Sco

re

KALANGALA 58100 26 79 8

10

0 10

16

2 15

4

8 6 86 11 78 8 74 7

18

3 10 80 8 83 1

ISINGIRO 396700

16

0 90 9 67 7

98 15

8

5 11 46 6 56 6 80 8

12

5 10 47 5 75 2

BULIISA 76900 29 97 10 67 7

13

1 15

4

8 6 37 5 77 8 87 9

13

2 10 55 5 74 3

SERERE 128700 59 94 9 67 7

14

3 15

3

3 4 83 10

12

8 10 31 3

23

6 10 47 5 73 4

ZOMBO 208600 57 10 10 10 10 93 14 4 5 49 6 63 6 93 9 86 9 35 4 73 5


19

0 0 2

RUKUNGIRI 311600

22

7 99 10 33 3

98 15

7

0 9 71 9 64 6 75 8

23

9 10 32 3 73 6

LYANTONDE 77100 84

10

0 10 0 0

15

5 15

9

6 12 82 10

10

8 10 0 0

24

2 10 49 5 72 7

MPIGI 209400 83

10

0 10 67 7

96 14

3

4 4 44 6 71 7 90 9

13

0 10 43 4 71 8

MANAFWA 343200 68 99 10

10

0 10

14

5 15

3

1 4

15

1 13 42 4 0 0

14

8 10 55 6 71 9

MUKONO 522100

12

9

10

0 10

10

0 10

91 14

2

8 4 51 6 34 3 76 8

10

2 10 54 5 70 10

DOKOLO 171000 39

10

0 10

10

0 10

11

4 15

4

0 5 26 3 58 6 77 8 72 7 55 6 69 11

BUTALEJA 206200 72

10

0 10 33 3

10

3 15

1

8 2 54 7 80 8 76 8

11

6 10 64 6 69 12

KISORO 247300

10

5 95 10 67 7

11

0 15

3

9 5 72 9 32 3 88 9

14

1 10 21 2 69 13

BUIKWE 407100

12

1

10

0 10

10

0 10

83 13

4

0 5 40 5 48 5 62 6

10

6 10 54 5 69 14

KYENJOJO 356200 80 99 10 67 7

11

4 15

3

7 5 26 3 56 6 91 9

11

2 10 43 4 68 15

OTUKE 80600 30

10

0 10 67 7

13

0 15

2

2 3 28 4 58 6 81 8 90 9 66 7 68 16

MITYANA 301800

15

5 94 9 33 3

99 15

3

0 4 56 7 50 5 81 8 97 10 61 6 67 17

BUSHENYI 241500 96 87 9 33 3

10

7 15

4

3 5 72 9 37 4 99 10

10

3 10 23 2 67 18

MBARARA 427200

19

2 96 10 33 3

11

0 15

9

1 11 77 10 53 5 0 0

14

0 10 28 3 67 19

KYEGEGWA 148500 42

10

0 10

10

0 10

12

1 15

4

4 5 43 5 61 6 0 0

12

7 10 42 4 66 20

NAKAPIRIPIRIT 143800 51

10

0 10 67 7

10

3 15

4

2 5 14 2 52 5 72 7 82 8 63 6 66 21


20

MASAKA 247000 78 87 9 67 7

84 13

3

1 4 59 7 37 4 82 8 86 9 58 6 65 22

SIRONKO 227800 87

10

0 10 33 3

12

2 15

3

8 5 39 5 48 5 73 7

12

7 10 48 5 65 23

LAMWO 132300 60

10

0 10 67 7

98 15

2

3 3 48 6 60 6 77 8 84 8 15 1 64 24

NWOYA 51100 31 97 10 33 3

12

7 15

4

1 5 52 7 39 4 61 6

10

8 10 32 3 63 25

RUBIRIZI 119500 51

10

0 10 67 7

14

1 15

2

9 4 27 3 32 3 90 9 95 9 25 2 63 26

WAKISO

126090

0

29

3 96 10 67 7

10

5 15

3

2 4 35 4 38 4 76 8 79 8 36 4 63 27

OYAM 353700 72

10

0 10 67 7

79 12

3

5 4 41 5 63 6 70 7 90 9 23 2 63 28

KABAROLE 403200

16

1 96 10 67 7

13

8 15

4

3 5 70 9 36 4 0 0

11

5 10 34 3 62 29

MBALE 416600

11

7 98 10 33 3

10

1 15

3

4 4 27 3 46 5 77 8 84 8 43 4 61 30

PALLISA 337700 83 95 10 67 7

66 10

1

8 2 51 6 59 6 78 8 82 8 38 4 60 31

NAKASONGOL

A 150000 88 89 9 33 3

83 12

4

3 5 37 5 64 6 41 4

10

5 10 51 5 60 32

TORORO 463600

18

6

10

0 10

10

0 10

71 11

2

0 3 23 3 36 4 88 9 63 6 47 5 59 33

SEMBABULE 210900 69

10

0 10 33 3

10

3 15

2

0 3 17 2 33 3 77 8 90 9 62 6 59 34

BUDAKA 169300 49 86 9 67 7

68 10

2

7 3 33 4 48 5 74 7 79 8 55 6 59 35

AMOLATAR 120400 23

10

0 10 33 3

13

3 15

1

2 1 28 3 45 5 66 7

11

0 10 41 4 59 36

GOMBA 148700 54 95 9 67 7

10

0 15

1

2 2 17 2 28 3

10

3 10 62 6 46 5 59 37

MOROTO 121300 33 92 9 33 3

83 12

3

1 4 14 2 46 5 92 9 83 8 53 5 58 38


21

NAMUTUMBA 207300

10

2

10

0 10 0 0

85 13

1

5 2 30 4 43 4

10

0 10 90 9 62 6 58 39

IBANDA 242800 77 63 6 33 3

96 14

2

6 3 41 5 27 3 85 8

10

4 10 40 4 58 40

MASINDI 316800

10

8 97 10 33 3

60 9

4

2 5 29 4 45 4 83 8 90 9 47 5 57 41

KAMWENGE 317000 93 97 10 0 0

11

0 15

3

2 4 20 2 41 4 64 6 94 9 62 6 57 42

KAYUNGA 344600 72

10

0 10 67 7

66 10

1

7 2 27 3 36 4 84 8 78 8 52 5 57 43

APAC 326300 90

10

0 10 33 3

89 13

2

2 3 35 4 49 5 67 7 87 9 27 3 57 44

PADER 210100 78 96 10 67 7

88 13

2

0 3 16 2 38 4 85 9 75 8 30 3 57 45

KOLE 216900 21 95 10 67 7

56 8

1

9 2 19 2

23

3 10 79 8 55 5 41 4 57 46

SOROTI 426400 93 89 9 67 7

58 9

2

0 3 57 7 54 5 55 5 72 7 47 5 57 47

KABALE 490200

21

0 98 10 67 7

71 11

2

2 3 29 4 48 5 87 9 76 8 17 2 56 48

MAYUGE 429300

11

4 93 9 0 0

91 14

1

4 2 30 4 39 4 79 8

10

0 10 61 6 56 49

HOIMA 499100

21

0

10

0 10 0 0

79 12

2

7 3 40 5 55 6 55 5

10

4 10 50 5 56 50

BUHWEJU 97400 37 86 9 67 7

82 12

1

8 2 16 2 27 3

10

0 10

10

9 10 14 1 56 51

BUVUMA 52400 20 91 9 67 7

66 10

2

4 3 14 2 45 5 57 6

11

6 10 49 5 56 52

KANUNGU 241800

12

1 88 9 33 3

62 9

3

8 5 38 5 47 5 74 7 84 8 36 4 55 53

KAPCHORWA 104600 49 98 10 33 3

85 13

2

4 3 42 5 37 4 72 7 85 9 14 1 55 54

JINJA 475700

19

6 95 10 33 3

69 10

4

3 5 47 6 48 5 0 0

10

7 10 51 5 54 55


22

KIBAALE 613300

13

5 83 8

10

0 10

78 12

1

5 2 19 2 40 4 31 3 92 9 28 3 53 56

KALUNGU 173800 56 75 7 33 3

11

4 15

2

1 3 20 2 25 2 90 9 45 5 63 6 53 57

IGANGA 466200

10

3 99 10 33 3

66 10

1

6 2 34 4 28 3 80 8 74 7 57 6 53 58

NAPAK 176500 36

10

0 10 0 0

11

7 15

3

4 4 20 3 32 3 94 9 51 5 34 3 53 59

NTUNGAMO 458000 82 98 10 67 7

60 9

2

0 3 24 3 28 3 96 10 70 7 24 2 53 60

LWENGO 262000 49 98 10 67 7

62 9

1

1 1 11 1 22 2 86 9 76 8 56 6 53 61

BUDUDA 167000 42 93 9 33 3

16

2 15

3

6 5 36 5 41 4 0 0 86 9 22 2 52 62

LIRA 377800 47

10

0 10 33 3

72 11

2

2 3 30 4 26 3 62 6 76 8 40 4 51 63

BUGIRI 387800

11

1 86 9 0 0

11

1 15

1

6 2 27 3 36 4 39 4 79 8 65 7 51 64

YUMBE 466400 66

10

0 10

10

0 10

63 9

2

3 3 37 5 40 4 0 0 47 5 49 5 50 65

LUUKA 243200 74 80 8 33 3

10

2 15

8 1 17 2 18 2 67 7 54 5 64 6 50 66

KOTIDO 204600 51

10

0 10 33 3

96 14

2

0 2 29 4 37 4 0 0 66 7 48 5 49 67

RAKAI 466900

27

0 91 9 0 0

70 11

4

0 5 24 3 51 5 0 0

11

4 10 54 5 48 68

ABIM 55200 18

10

0 10 0 0

71 11

2

0 2 16 2 29 3 86 9 64 6 47 5 48 69

KIRUHURA 280200 76 96 10 67 7

78 12

1

9 2 19 2 36 4 0 0 59 6 36 4 46 70

KOBOKO 209600 26

10

0 10 0 0

69 10

1

4 2 19 2 19 2 89 9 49 5 52 5 45 71

BUNDIBUGYO 236500 50 94 9 67 7

65 10

2

5 3 29 4 24 2 0 0 63 6 42 4 45 72


23

BUYENDE 248000 39 85 8 0 0

41 6

1

9 2 42 5 33 3 63 6 85 9 31 3 43 73

MOYO 354300

11

4

10

0 10

10

0 10

31 5

1

6 2 22 3 21 2 45 4 25 2 50 5 43 74

KABERAMAIDO 183100 41 98 10 33 3

55 8

1

3 2 27 3 41 4 0 0 61 6 64 6 43 75

KAMULI 468700 98 92 9 0 0

84 13

1

5 2 28 4 33 3 0 0 80 8 44 4 43 76

KWEEN 94600 32

10

0 10 33 3

56 8

1

1 1 7 1 27 3 78 8 44 4 38 4 43 77

AMURU 169300 50 83 8 33 3

57 9

1

6 2 17 2 28 3 63 6 54 5 36 4 42 78

BUKOMANSIM

BI 150900 27 96 10 0 0

45 7

2

9 4 13 2 20 2 88 9 49 5 53 5 42 79

NAMAYINGO 211200 51 88 9 67 7

20 3

1

4 2 12 1 24 2 48 5 59 6 72 7 42 80

KITGUM 254800 39 93 9 0 0

46 7

2

1 3 45 6 32 3 79 8 48 5 12 1 42 81

MUBENDE 566600

11

0 93 9 33 3

60 9

1

8 2 16 2 36 4 0 0 75 7 45 5 42 82

KAMPALA

159780

0

29

6 49 5 33 3

10

3 15

3

9 5 17 2 18 2 0 0 41 4 40 4 40 83

KAABONG 345300 78

10

0 10 67 7

37 6

8 1 4 0 8.9 1 88 9 18 2 47 5 40 84

KATAKWI 163000 42

10

0 10 33 3

45 7

1

5 2 21 3 33 3 0 0 68 7 49 5 40 85

BUSIA 281200 50 93 9 33 3

55 8

1

3 2 26 3 33 3 0 0 62 6 40 4 39 86

AMURIA 344200 68

10

0 10 0 0

41 6

5 1 12 2 34 3 82 8 40 4 46 5 38 87

BUKWO 67500 13

10

0 10 0 0

41 6

9 1 9 1 24 2 79 8 43 4 44 4 38 88

BUKEDEA 171100 10 91 9 0 0 35 5 6 1 15 2 22 2 88 9 30 3 54 5 36 89


24

SHEEMA 211400 33

10

0 10 0 0

22 3

1

8 2 17 2 17 2

11

0 10 34 3 33 3 36 90

GULU 374700 68

10

0 10 0 0

26 4

7 1 18 2 17 2 68 7 43 4 41 4 34 91

KASESE 695500 72 85 8 0 0

33 5

1

4 2 14 2 18 2 87 9 38 4 22 2 33 92

NTOROKO 76000 15 83 8 67 7 36 5 9 1 12 1 19 2 0 0 38 4 35 3 32 93

KALIRO 202200 32 64 6 0 0 56 8 8 1 19 2 17 2 0 0 72 7 48 5 32 94

NAKASEKE 178600 21 95 10 33 3 0 0 0 0 0 0 0 0 80 8 0 0 97 10 31 95

KIBUKU 169200 13 87 9 0 0 25 4 4 0 14 2 18 2 60 6 32 3 31 3 29 96

AMUDAT 101100 4

10

0 10 33 3

9.5 1

2 0 3 0 2.7 0 65 7 10 1 20 2 25 97

LUWERO 418000 58 87 9 0 0

29 4

1

1 1 13 2 18 2 0 0 32 3 37 4 25 98

ADJUMANI 331600 30 88 9 0 0 10 2 9 1 6 1 7.5 1 55 5 14 1 20 2 22 99

AGAGO 271700 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

ALEBTONG 211500 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

ARUA 713700 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

BULAMBULI 118900 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

BUTAMBALA 96700 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

KIBOGA 185900 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

KIRYANDONG

O 285300 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

KUMI 233800 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

KYANKWANZI 133700 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0


25

MITOOMA 188800 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

NEBBI 328600 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

NGORA 144100 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

NYADRI 200700 0 0 0 0 0

0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

10

0

APPENDIX:

A: TIMELINESS PER DISTRICT


26

DistrictDistrictDistrictDistrict JANJANJANJAN FEBFEBFEBFEB MARMARMARMAR APRAPRAPRAPR MAYMAYMAYMAY JUNJUNJUNJUN JULJULJULJUL AUGAUGAUGAUG SEPSEPSEPSEP

Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect. Date for monthly

reports--->

Cod

e 28th Feb 28th Mar

28th

April 28th May 28th June

28th

July

28th

Aug.

28th

Sept.

28th

Oct. % T % C timely late

not

received reports

Abim

57

3 L T T T L L T N N

44

%

78

% 4 3 2 9

Adjumani

50

1 T N T T T T N L N

56

%

67

% 5 1 3 9

Agago T T T T T T L N T

78

%

89

% 7 1 1 9

Alebtong N N N N N N N N N 0% 0% 0 0 9 9

Amolatar

56

4 L T L L T T L L T

44

%

100

% 4 5 0 9

Amudat L T T T T T N N T

67

%

78

% 6 1 2 9

Amuria

56

5 T T T T L L L T N

56

%

89

% 5 3 1 9

AMURU

57

0 T T T T T T T T T

100

%

100

% 9 0 0 9

Apac

50

2 T T T T L T T T T

89

%

100

% 8 1 0 9

Arua

50

3 L T L T T T N N N

44

%

67

% 4 2 3 9

Budaka

57

1 T T T T T T T T T

100

%

100

% 9 0 0 9

Bududa

57

9 T T T T T T T T T

100

%

100

% 9 0 0 9

Bugiri

50

4 T T T T T T T L T

90

%

100

% 9 1 0 10

Buhweju L L T L N L L T T

33

%

89

% 3 5 1 9

Buikwe T T T T T T T T T

100

%

100

% 9 0 0 9

Bukedea

57

8 T T L L T T N T N

56

%

78

% 5 2 2 9

Bukomansim

bi N T T T T T T N T

78

%

78

% 7 0 2 9


27


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Bulambuli L L T L L N N N N

11

%

56

% 1 4 4 9

Bukwo

56

7 T L T T T T N T L

67

%

89

% 6 2 1 9

Buliisa

57

6 T T T T L T T T T

89

%

100

% 8 1 0 9

Bundibugyo

50

5 T T T T T T T N T

89

%

89

% 8 0 1 9

Bushenyi

50

6 T T T T T L T T T

89

%

100

% 8 1 0 9

Busia

50

7 T T N N T T T T T

78

%

78

% 7 0 2 9

Butaleja

55

7 T T T T T T T T T

100

%

100

% 9 0 0 9

Butambala L T L T T L N N T

44

%

78

% 4 3 2 9

Buvuma T T T T T T T T T

100

%

100

% 9 0 0 9

Buyende L L L L L T N L L

11

%

89

% 1 7 1 9

Dokolo

57

5 T T T T T T T T T

100

%

100

% 9 0 0 9

Gomba L T T T T T L T T

78

%

100

% 7 2 0 9

Gulu

50

8 T T T T T T T N T

89

%

89

% 8 0 1 9

Hoima

50

9 T T T T T T T T T

100

%

100

% 9 0 0 9

Ibanda

55

8 T T T T T T T T T

100

%

100

% 9 0 0 9

Iganga

51

0 T T T T T T T T T

100

%

100

% 9 0 0 9

Isingiro

56

0 T T T T T T L T T

89

%

100

% 8 1 0 9


28


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Jinja

51

1 T T L T T T T T T

89

%

100

% 8 1 0 9

Kaabong

55

9 T T T T L T T T T

89

%

100

% 8 1 0 9

Kabale

51

2 T T T T T T T T N

89

%

89

% 8 0 1 9

Kabarole

51

3 T T T T T T T T T

100

%

100

% 9 0 0 9

Kaberamaid

o

51

4 T L L T T T L T T

67

%

100

% 6 3 0 9

Kalangala

51

5 T T T T T T T T T

100

%

100

% 9 0 0 9

Kaliro

56

1 T L L L T L L T T

44

%

100

% 4 5 0 9

Kalungu L L T T T T T T T

78

%

100

% 7 2 0 9

Kampala

51

6 T T T T T T T T T

100

%

100

% 9 0 0 9

Kamuli

51

7 T T T T T T T L N

78

%

89

% 7 1 1 9

Kamwenge

51

8 T T T T T T L L T

78

%

100

% 7 2 0 9

Kanungu

51

9 T T T T T T T T T

100

%

100

% 10 0 0 10

Kapchorwa

52

0 T T T L N T T T T

80

%

90

% 8 1 1 10

Kasese

52

1 L T T T T T T N N

67

%

78

% 6 1 2 9

Katakwi

52

2 L T T T T T T N T

78

%

89

% 7 1 1 9

Kayunga

52

3 T T T T T T T T T

100

%

100

% 9 0 0 9

Kibaale

52

4 T T T T T T T T T

100

%

100

% 9 0 0 9


29


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Kibuku T T T L T N N T T

67

%

78

% 6 1 2 9

Kiboga

52

5 T T T T T T T T T

100

%

100

% 10 0 0 10

Kiruhura

56

2 T T T T T T T T L

89

%

100

% 8 1 0 9

Kiryandongo L L L L T L L T T

33

%

100

% 3 6 0 9

Kisoro

52

6 T T T T T T T T T

100

%

100

% 9 0 0 9

Kitgum

52

7 T T T N L T T N T

67

%

78

% 6 1 2 9

Koboko

56

3 T T T L L T L N T

56

%

89

% 5 3 1 9

Kole L T T T T N T T T

78

%

89

% 7 1 1 9

Kotido

52

8 T T T T T L T T T

89

%

100

% 8 1 0 9

Kumi

52

9 T T T T T T N T T

89

%

89

% 8 0 1 9

Kween L N T T T T N T T

67

%

78

% 6 1 2 9

Kyankwanzi L T T T T T N N T

67

%

78

% 6 1 2 9

Kyegegwa L L T T T T T T T

78

%

100

% 7 2 0 9

Kyenjojo

53

0 T T L T T T T T T

89

%

100

% 8 1 0 9

Lamwo T T L T T T T T T

89

%

100

% 8 1 0 9

Lira

53

1 T T T T T T T T T

100

%

100

% 9 0 0 9

Luuka T T T N T N T T T

78

%

78

% 7 0 2 9


30


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Luwero

53

2 T T L L T T T T T

78

%

100

% 7 2 0 9

Lwengo N N N N T T T N T

44

%

44

% 4 0 5 9

Lyantonde

58

0 T T T L L T L L T

56

%

100

% 5 4 0 9

Manafwa

56

6 T T T T T T T T T

100

%

100

% 9 0 0 9

Masaka

53

3 T T T T T T T T T

100

%

100

% 9 0 0 9

Masindi

53

4 T T T T T T T T N

89

%

89

% 8 0 1 9

Mayuge

53

5 T N T T L L T T L

56

%

89

% 5 3 1 9

Mbale

53

6 T T T T T T T T T

100

%

100

% 9 0 0 9

Mbarara

53

7 T T T L T T T T T

89

%

100

% 8 1 0 9

Mitooma T N N L T N T N N

40

%

50

% 4 1 5 10

Mityana

56

8 T T T T T T T T T

100

%

100

% 9 0 0 9

Moroto

53

8 T T T T T T T T T

100

%

100

% 9 0 0 9

Moyo

53

9 T T T T T T T T T

100

%

100

% 9 0 0 9

Mpigi

54

0 T T T T T T T T T

100

%

100

% 9 0 0 9

Mubende

54

1 T T T T T T T N T

89

%

89

% 8 0 1 9

Mukono

54

2 T T T T T T T T T

100

%

100

% 10 0 0 10

Nwoya N T T L N T N T T

56

%

67

% 5 1 3 9


31


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Nakapiripirit

54

3 T T T T T T T T T

100

%

100

% 9 0 0 9

Nakaseke

56

9 T T T T T T T T T

100

%

100

% 9 0 0 9

Nakasongola

54

4 T T T T T T L T T

89

%

100

% 8 1 0 9

Namayingo T L T T T T L L T

67

%

100

% 6 3 0 9

Namutumba

57

4 T T T T T T T T T

100

%

100

% 9 0 0 9

Napak T T T T T T L T T

89

%

100

% 8 1 0 9

Nebbi

54

5 T T T T T N L L T

67

%

89

% 6 2 1 9

Ngora L L T L L N N N N

11

%

56

% 1 4 4 9

Ntoroko T T T T T T N T T

89

%

89

% 8 0 1 9

Ntungamo

54

6 T T T T T T T T N

89

%

89

% 8 0 1 9

MARACHA

57

7 T T T T T T T T T

100

%

100

% 9 0 0 9

Otuke T N T L L T T L T

56

%

89

% 5 3 1 9

OYAM

57

2 T T T T T T T T T

100

%

100

% 9 0 0 9

Pader

54

7 T T T T L T T T T

89

%

100

% 8 1 0 9

Pallisa

54

8 T T T T T T L T L

78

%

100

% 7 2 0 9

Rakai

54

9 T T T T T T L L T

78

%

100

% 7 2 0 9

Rubirizi T T T T T T T T N

89

%

89

% 8 0 1 9


32


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Rukungiri

55

0 T T T T T T T T T

100

%

100

% 9 0 0 9

Serere L T T L T T T T T

78

%

100

% 7 2 0 9

Sheema L T T N T N L N N

33

%

56

% 3 2 4 9

Ssembabule

55

1 T T T T T T T T T

100

%

100

% 9 0 0 9

Sironko

55

2 T T T T T L T T T

89

%

100

% 8 1 0 9

Soroti

55

3 L T L L T L L T T

44

%

100

% 4 5 0 9

Tororo

55

4 T T T T T T T T T

100

%

100

% 10 0 0 10

Wakiso

55

5 T T T T T T T T T

100

%

100

% 9 0 0 9

Yumbe

55

6 T T T T T T T T T

100

%

100

% 10 0 0 10

Zombo T T T T T T T T T

100

%

100

% 9 0 0 9

T (Timely

report) 87 94 95 87 94 92 76 81 91

% timely

report 78% 84% 85% 78% 84% 82%

68

% 72% 81%

L (Late

report) 21 11 13 19 14 11 20 11 5

% late

report 19% 10% 12% 17% 13% 10%

18

% 10% 4%

N (No

report) 4 7 4 6 4 9 16 20 16

% not

reported 4% 6% 4% 5% 4% 8%

14

% 18% 14%


33


Report

s on

time

Total

report

s

receiv

ed

Total

T

Total

L

Total

N

Total No

Expect.

Completen

ess 96% 94% 96% 95% 96% 92%

86

% 82% 86%

NATIONAL NATIONAL NATIONAL NATIONAL

TotalTotalTotalTotal

79797979

%%%%

92929292

%%%% 805805805805 125125125125 86868686 1016101610161016

- Target of reporting is the 28th of the next month

- A Timely report is having the report received at Central level within 1st to 28th of the next month

- Late is a report that was received at Central level after the 28th of the next month.

Documents

Q1 2011 12 HMIS Report - Ministry of Health HMIS Report.pdf · Ministry of Health Resource Centre 4 2.0 HMIS Reporting 2.1 Completeness Table 1 below shows the extent to which the