ELSEVIER International Journal of Bio-MedicalComputing40 (1995) 107-114

International Journal 01

Bio·Medical

Computing

The Philippine management information system for publichealth programs, vital statistics, mortality and notifiable diseases

Benjamin Ariel Marte*, Detlef Schwefel1

Department of Health, Health and Management Information System (HAMIS), San La::aro Compound, Ri::al Avenue,

1003 Santa Cruz, Manila, Philippines

Abstract

Strengthening the information support for decision making has been identified as an important first step towardimproving the efficiency, effectiveness, and equitability of the health care system in the Philippines. A Philippine-Ger-man Co~peration is in partnership toward developing a need-responsive and cost-effective Health and ManagementInformation System (HAMIS). Four information baskets are being strengthened specifically to address these needs ina cost-effective way: public health information systems, hospital information systCClTIs,jnformation syst~s oneconomics and financing, information systems on good health care management. BLACKBOX is the managementinformation system for public health programs, vital statistics, mortality and notifiable diseases of the Philippines. Ithandles and retrieves all da ta that is being collected by public health workers routinely all over the Philippines. Theeventual aim of BLACKBOX is to encourage the development of an information culture in which health managersactively utilise information for rational planning and decision making for a knowledge based health care delivery.

Keywords: Health And Management Information System; Need-responsive; Cost-effective; Philippines; Public healthprogram; Vital statistics; Mortality and morbidity; Computer application; Information utilisation; Rational planning;Decision making

1. The Health and Management InformationSystem (HAMIS)

Strengthening the information support for deci-sion making has been identified as being an im-pOltant first step toward improving the efficiency,effectiveness and equitability of the health care

• Correspondingauthor.I VisitingProfessor:Departmentof Sociology,Free Univer-

sity of Berlin,Berlin,Germany.

system III the Philippines [2]. In answer to thisneed, since July 1989, the Department of Health(DOH) of the Philippines and the German Min-istry for Economic Cooperation and Development(BMZ) through its German Agency for TechnicalCooperation (GTZ) have been in partnership to-ward developing a need-responsive and cost-effec-tive health and management information system[2]. This collaborative effort has become khownby its acronym HAMIS, which, fittingly, in .somePhilippine languages means 'smooth', while inothers it means 'sweet'.

0020-7101/95/$09.50 © 1995 ElsevierScienceIreland Ltd. All rights reservedSSDI0020-7101(95)01133-Y

108 B. Ariel Marle, D. Schwefel/ Inl.1. Biomed. Comput. 40(1995) 107-114

The need-responsiveness of HAMIS was ar-rived at by assessing the:

• need for accurate information, through a surveywith health personnel in two provinces;

• comparative information needs, as compared toEuropean and OECD experiences;

• normative information needs, through an eco-nomic decision making model and a state-of-the-art statement from public health experts;

• expressed needs for data, information and un-derstanding through ca se studies on good healthca re management, which cases were discoveredby a proper information system [9].

The cost-effectiveness of HAMIS was ensured

through a survey that identified the prioritisationof indicators by some 15 professions involved indecision making for health, and by eomparing thesources of data in terms of different eriteria of

availability and eost [9].Based thereon, HAMIS has developed and

tested eertain strategie elements for strengtheningthe health and management information system inthe Phi!ippines. These 'HAMIS Elements' incl'Jde:

• standardised reporting of routine data on mor-tality morbidity and public health programs(BLACKBOX holds the routine data on vitalstatistics, mortality, morbidity, and publichealth programs of some 30 out of 75 provincesin the country) [9];

• secondary computerisation and simplified pre-sentation of routine data on hospital care (thisHOMISBOX system is ready for encoding ofthe national database of routine hospital statis-tical reports) [9];

• support for the development of a hospital infor-mation system, starting with admissions, dis-charges, and medical records (this LUCENAsystem has been replicated for 14 hospitals in 10provinces) [9];

• development of hitherto neglected financial andmaterial management information systems (thisMARAMAG system is ready for replication);

• design of information systems on health financ-ing and health insurance (through a representa-tive household survey, and institutional cost/finaneing analyses) [9];

• simplified collection and retrieval of cultural,social and economical background data (this

BROWNIES system has been implemented in 4provinces) [91;

• promotion of a simplified community basedspot mapping of a seven-indicator health assess-ment matrix, in the hands of village healthworkers (the DATABOARD system that wasdiscovered by HAMIS and has become a na-tional program) [9];

• discovering good health care management bymeans of a nationwide contest, and learning thelessons of, and organizing the winners of thecontest in order to influence health managementand health policy development. (The 'HAMISContest' has become anational event after two

such contests held in1991-92 and 1993-94)[5,9].

This paper shall focus on one such HAMISElement, which deals with the public health infor-mation system, by way of elucidating that infor-mation translated into action means the improve-ment of health management in the Philippines.

2. The Philippine public heaIth informationsystem (BLACKBOX)

BLACKBOX is the management informationsystem for public health programs, vital statistics,mortality and notifiable diseases. It is a computerapplication developed by HAMIS in and for theDepartment of Health of the Philippines. Theprogram was written in dBASE/Clipper language,and has 2 modules: one for Public Health Pro-

grams (version 5.8), and one for Vital StatisticsMortality and Notifiable Diseases (M&M).BLACKBOX is capable of accessing the data filesfor any Regional Health Office (RHO) ProvincialHealth Office (PHO), District or City HealthOffice (DHO or CHO), Rural Health Unit (RHU,also known as the Munieipal Health Office), orBarangay Health Station (BHS) in the country. Indescending order, these are the sequential report-ing levels in the publie health information systemstrueture.

The data files are those collected by the FieldHealth Services Information System (FHSIS). The

B. Ariel Marle, D. Sc/live/ei / Inl. 1. Biomed. Comput. 40 (/995) 107-114

FHSIS is the computerised routine reporting sys-tem for Public Health Pro grams[I]. It was imple-mented nationwide in April 1990. The NotifiableDisease Module of the FHSIS (HISWK) wasimplemented in 1992. In the reporting scheme ofthe FHSIS, the data of the BHS, RHU, andDHO/CHO are encoded and processed at thePHO Computer Station. In return, the PHO isexpected to feedback information outputs to thereporting units, and to forward a copy of the datato the RHO. The RHO should also forward a

copy of the data to the DOH Central Office [4].The reporting scheme of the Notifiable Diseasemodule is similar, except that the lowest reportinglevel is the RHU and not the BHS.

Very often, computerised information systemsare actually data systems that tend to focus heav-ily on database management. This involves col-lecting, encoding, editing, deleting, backing upand generally assuring the quality and integrity ofdata [6]. Many such data systems genera te infor-mation that may be accessible and relevant onlyto a select group of high level users. These includethe programmers, analysts, and other technicalpersons who have an intimate knowledge of thecomputer system. Unfortunately, those who havethe most need of the information can often be

those with the lowest level of computer literacy.Most health managers belong to this category.For people such as these, the computerised systemappears to be a BLACKHOLE that sucks in data,but from which hardly any information comesout. This situation might, most aptly, be termedan electronic DINOsaur: Data In, Nothing Out.

BLACKBOX was so named in order to dispelthe mystery and mystique of the electronic FHSISdatabase. It should be a BACKBOX that bringsdata back to those that produce it. The system iscompletely menu driven. It allows even a low leveluser to select from a package of analytic outputs,and to automatical1y generate health service re-ports. The outputs can be consolidated for anyBHS, RHU, DHO/CHO, PHO, RHO, or even forthe entire country. The outputs can also be con-solidated for any number of months, quarters, oreven for the whole year. The health manager,after all, should not have to be a computer wizardto tap into the health database and make sense ofit.

3. Operating BLACKBOX

BLACKBOX operates on the very simple com-puters found at PHO Computer Stations. Theseare IBM eompatible 286 or 386 systems. To startthe program, a single command is entered:BLACKBOX. From then on, all the user has todo is select from aseries of menus by manipulat-ing a lightbar, using the cursor keys.

The user first has to indicate the health unit, oraggregate of units, that he would like informationon. He does this by selecting the Region,Province, District, RHU, or BHS of choice. Thisis the 'geographie aggregating sequenee' that al-lows the user to select the most elemental report-ing unit, the BHS, or to aggregate units atdifferent reporting levels. Having made his choice,the user is then prompted to indicate the year ofreference.

In version 5.8 of BLACKBOX, the user is nextpresented with the array of public health pro-grams for which the FHSIS collects data. Heselects one, and is then prompted to select ananalytic output. If the data is reported monthly,the user can specify the number of months andthe starting month to aggregate. This is the 'tem-poral aggregating sequence' that al10ws the userto indicate the number of months or quarters forwhich he would like the data to be aggregated,depending on the frequency of data reporting. Ina similar manner, the M&M module of BLACK-BOX al10ws the user to select the notifiable dis-ease of interest, as wel1 as the number of weeksand starting week for which he would like thedata to be aggregated.

Having processed the data, BLACKBOX thenoffers to present the output in the form of a tableor a graph. The output tables contain just enoughinformation to be appreciated at a glance. More-over, the tables were designed to be analytie out-puts in themselves. The health manager need onlyexercise his intel1ect to formulate an interpreta-tion. The graphs were designed to aid and tosome degree direct, the interpretation. In theM&M module where the disease of choice may beanalyzed for 52 weeks according to age group, thegraphs are in the form of time trend series. Ac-cordingly, there is one graph per age group andone for the aggregate.

110 B. Ariel Marte, D. Schwefel / Inf. J. Biomed. Compuf. 40 (/995) 107-114

Each table comes with a 'completion level'.This is the percentage of reporting units read fromthe database, over the total number of reportingunits expected for the specified level of geographie

aggregation. Completeness is one component ofdata accuracy that ean be easily programmed. Ifroutine health reports must be taken 'with a grainof salt', the completion level is a measure of howbig that grain of salt must be. Consisteney is oneother eomponent that ean be satisfied by eross-eheeking one report against another. For instance,the number of live births can be compared to thenumber of pregnant women seen; or, the inei-dence of diarrhea ean be eompared to the ratio ofdeep wells to households. Regular updating is athird important eomponent of data accuracy thatdepends mostlyon the reporting proeedure. Regu-larity ean of eourse be improved by threateningdire eonsequenees if data reports are not submit-ted on time at specified intervals. It is probablymore effective however, to convince the health

worker in the field, that coming up with regularreports will 'make areal difference', e.g. in theallocation of health resources.

The BLACKBOX outputs can be directed toscreen, printer, or file. The tables are saved in theform of ASCII text files while the graphs are inthe form of PCX files. The tables are viewed on a

special word processing screen with full editingfeatures. This allows the user to type in his inter-pretation and, later present the printout as aformal report. Of course, this does not preventhirn from altering the figures in the table, but it isan incentive to be honest. In the sense that 'the

squeaky wheel gets the grease', the 'bad-Iooking'report gets to be alloeated more resourees. Be-sides, the database is in no way altered, and soanyone who would like to verify the report onlyhas to run BLACKBOX for hirnself. Another

special feature of the BLACKBOX word proces-sor is the ability to split the screen horizontallyand to view two tables in juxtaposition. For manyhealth managers t/lis is the most sophisticatedmethod of further analysis that they would everwant or need to do. In contrast to the tables the

graphs can only be viewed and not edited. Aspecial feature however, is that several graphs canbe viewed sequentially in the form of a 'slide

show' by pressing any key after each graph. Thisis the ca se when viewing the time trend series byage group in the M&M module.

Finally, in the programming design of BLACK-BOX, a special feature is the modular nature ofthe output tables and graphs. What this means isthat a health manager can request more tablesand graphs to be programmed, as long as the dataelements are present, and the request can be an-swered in a matter of hours. All that has to be

done is to take the 'skeleton program', plug in thenew variables and calculations, then recompile theprogram.

4. Utilizing heaIth information

The health management information system ex-ists, essentially, to answer four very importantand pressing questions for the health managerand decision maker.

I. What are our health problems? An importantfirst step in determining the health problems ofa given community or population is to look attheir mortality and morbidity profile. The mor-tality and morbidity profile answers the ques-tion 'What are people getting siek of? What arethey dying of?' It provides a starting point foranalyzing the health situation of the commu-nity or population.

2. What are we doing about them? Public healthprograms are interventive strategies designedto address some of the more important healthproblems of the population. BLACKBOX ana-Iyzes the performance of these public healthprograms. It provides some measure of theextent to wh ich these interventive strategieshave been addressing the health needs of thepopulation. It looks at health program perfor-mance from different perspectives, and tries todevelop a total picture of the activity of thehealth sector.

3. What else should we do? No interventive strat-

egy can, of course, be perfeet. It would bedespairing, however, to say that 'so much wasdone because only so much could be done.'Rather the analyses of health problems andpublic health pro gram performance should in-

B. Arie! Marle, D. Schwef'el /Inf. J. Biomed. Comput. 40 (1995) 107-114 111

dieate what else needs to be done, and whiehdireetions these strategies should take in thefuture.

4. How best should we manage our health re-sourees to this end? The optimal managementof health resources is all the more imperativewhere economic difficulty is the norm. Thescarcity of health resources may be more rela-tive than absolute, in which case wise manage-ment may overcome, or at least attenuate, theabsolute scarcity of resourees. To some extent,a proper interpretation of the BLACKBOXanalyses may guide the health manager on howbest to manage health resources in order tomeet the specific demands of health pro gramintervention.

Following is a ease example of utilizing healthinformation primarily on the basis of theBLACKBOX analyses. It is a situational analysisof pulmonary tubereulosis (TB) that tries to an-swer the four questions mentioned above. These'Facts and Figures' were submitted to the Seere-tary of Health as a special report on September13, 1994. The report was eventually published inat least two of the leading daily newspapers in thePhilippines, the Manila Bulletin [3] and the TimesJournal [6].

"Pulmonary tuberculosis (TB) continues to beone of the most important causes of illness anddeath in the Philippines. In 1992 and 1993, TBwas the fourth leading eause of death, compris-ing 6% of all deaths in both years. This is basedon the BLACKBOX analysis of data eollectedfrom the Field Health Services Information

System (FHSIS) of Region 10 (NorthernMindanao).

"The top three causes of death in 1992 and1993 were pneumonia (18% of all deaths in1992, 15% in 1993), vascular disease (10% of alldeaths in 1992, 11% in 1993), and aecidents (9%of all deaths in 1992, 8% in 1993)."

The foregoing paragraphs of the 'Facts andFigures' report were based on data for 1992 and'93. Fig. 1 shows the data for 1993. Similar datawas obtained for 1992.

The report eontinued,

"About 1% of the total population 15 years andolder were identified to have TB. This was truefor both 1992 and 1993."

This part of the report was based on the data inFigs. 2 and 3 for 1993 as weH as the correspond-ing figures for 1992.

"All identified eases of TB were subsequentlyplaced und er treatment: 2/3 on short coursechemotherapy (SCC) and 1/3 on standard regi-men (SR). SCC eonsists of rifampicin, isoniazidand pyrazinamide taken over aperiod of 6months. SR consists of streptomycin and isoni-azid over aperiod of up to 12 months. SCCwas highly effective, with 97'Yo sputum conver-sion after the first 2 months of treatment. This

means that 9 out of 10 TB patients were nolonger infective 2 months after starting treat-ment on SCc. Moreover, 50% of patients onSCC complete the treatment within the year.

---~------~-------~'HAMIS=REGION Reqion 10 Northern KindanaoLEVEL Reqional Health OfficeVITAL STATISTICS MortalityTABLE proportionate 'tlortality ratio.

CAUSE OF DEATIL ..•NO __ OFPHR

DEATHS(')

Accidents

8858.41Cancer

5625.34Diabetes

1911.82DiarrhoA

1731.64Diphtherie.

430.41Hypertension

5975.68Influenza

70.07Kidnay dicoasG

1771.68Leprosy

110.10Liver dis.

, cir2502.38Malaria

560.53Heasles

8'0.84Meningitis

610.58Whoopinq couqh

120.11Pneumonla

158515.07Poliol:lyelitis

10.01Schistosomiasis

340.32Septlcemla

2792.65TB.

Meningitis 380.36TB,

Pull1lonary 6696.36TB.

other fortlS 990.94Tetanus

280.27Vll.scul11.r disell.se

115811.01Unknovn

5775.49Other causes

293827.93

TOTAL

10519100.0

Data vere consolidated for 12 months starting January 1, 1993.Tho. do.nominator us~d was the total n\Ul1bQrof doaths.

completion Level of Reports:

Janull.ry 91 of 131 reports in ( 70t)February 100 of 131 reports in ( 76%)March 92 of 131 reports in ( 70t)April 92 of 131 reports in ( 70t)May 100 of 131 reports in ( 76%)June 97 of 131 reports in ( 74%1

July 91 of 131 reports in ( 69t)August •.•.• 97 of 131 reports in ( 74t)September .•... 85 of 131 reports in ( 65t)october •••.• 92 of 131 reports in ( 70\)November . . . . . 75 of 131 reports in ( 57t)December ..... 87 of 131 reports in ( 66\)--- -- ----------------- -- ----------------- --- --- ---TOTAL ..... 1099 of 1572 reports in (70t)

Fig. I. BLACKBOX report of the proportionate mortalityratios (PMRs) of notifiable causes of death, in region 10(Northern Mindanao) of the Philippines, comprising 7 out of75 provinces, aggregated for the whole year of 1993.

112 B. Ariel Marte, D. Sc/llrefel / 1111. 1. Biomed. Comput. 40 (/995) 107-114

Data were consolldated for 1993.

Number ot' Married Couples ot' Reproductive Age (MCRA) 296447

~----~---~---~-----~--_HAMIS-Region 10 Northern MindanaoRegional Hea1th OfficepopulationPopulation by Age and Sex

AGE GROUP MALEFEMALETOTAL

Less than 1 year

261632542051583

1 -4 years 107488103230210718

5 -

6 years 462174345789674

7 - 14 years

151895144992296887

15 - 49 yellrs

321852322318644170

:>0 - 64

YOIlJ;'S S6~S558:124115279

65 yeaJ;'s l!lnd over

22801406509429310

TOTAL

733371110425018~7621

REGIONLEVELVITAL STATISTICSTABLE

cocpletion Level cf Reports:

..... 33.3ot' 799 reports in ( 39t)

community organisations in particular, couldbenefit from volume procurement of drugs.This approach is being spearheaded by theCommunity Health Service.

"TB is definitely still a major public health

problem. The difficulties do not seem insur-mountable, however. Short course chemother-apy especially, appears to be a cost-effectivesolution to invest in."

It is interesting that prior to the 'Facts andFigures' report on TB, the policy of the DOH wasto cover only about 70% of TB cases with SCC, inthe belief that SR was the cheaper treatmentmodality. The report has made it possible for theTB Control Program managers to more stronglyconsider covering a much greater percentage ofTB patients with the more cost-effective treatmentmodality, namely SCc.

5. The next steps

The eventual aim of BLACKBOX is to encour-age the development of an information culture inwhich health managers actively utilise informationfor rational planning and decision making. Onestep toward this direction could be to develop a

TOTAL ..... 313 or 799 reports in (39\) I

Fig. 3. BLACKBOX report of the population by age and sexin Region 10 of the Philippines, for the year 1993.

COlllpleted treatment 692643.82\

Oied

JO<1.94\Transferred out

7154.52\Defaulted

JOO1. 90\:Advorse reaction

139o.auRefused

2131.35lLost

5213.30%

TOTAL

(premature discharqes) 219413.anTOTAL

(treatment completions 912057.71.\+ premature discharges)

TOTAL

(continuing treatment) 668442.29\:

OVERALL(SeC + SR) No.•

ICarryover patients 7006-New patients 8798-I TOTAL (patients) 15804Referonce

"Based on the cost ca1culations of the TB Con-

trol Service, SCC costs approximately P 500.00(i.e. about US $19.00) per patient, per course.This amounts to only P 3.00 per day over 6months. On the other hand, SR costs around P700.00 per patient per course. These cost pro-jections are based on wholesale procurement ofdrugs. The Community Drug Insurance Pro-gram of the DOH could be one means by which

Data were consolidated tor 12Illonths start!nq January 1, 1993.The "referencetl figure was the denotllinator used to cotllpute for the

percentage figures in the table.

Cotllpletion Level of Reports:January 901 of 1095 reports in ( 82\)February 901 of 1095 reporta in ( 82\)March 893 of 1095 reports in ( 82\)April 868 of 1095 reporh in ( 79t)May 882 of 1095 reporta in ( 81t)June 876 of 1095 reports in ( 80t)July 882 of 1095 reports in ( 8lt)August 886 of 1095 reports in ( 81t)September ..... 888 of 1095 reports in ( 81\)OCtober ..••. 880 of 1095 reports in ( 80t)Novecl>er ••••• 873 of 1095 reports in ( 80t)December •..•. 855 of 1095 reports in ( 78t)

TOTAL ...•• 10585 of 13140 reports in (811)

On the other hand, it was observed that thedrop-out rate was twice as high for SR (12% in1992 and 11% in 1993) as it was for SCC (7% in1992 and 6% in 1993)."

••••••••••.......... ~ ..: .••....... ~-.

--------~~------------_llAHIS_REGION Region 10 Northern MindanaoLEVEL Regional Hell.lth OfticePROGRAM National Tuberculosis Proqral:lTABLE Number and percentage of selected indicators tor both

short course checotherapy (seC) and standard regilllen (SR).

Fig. 2. BLACKBOX repon showing the number of TB pa-tients identified and treated with short course chemotherapy(SCC, consisting of isoniazid, rifampicin, and pyrazinamide)and standard regimen (SR, consisting of isoniazid and strepto-mycin) in Region 10 of the Philippines, aggregated for thewhole year of 1993.

The foregoing paragraph in the report wasbased on the data in Figs. 4 and 5 for 1993, andcorresponding data for 1992.

B. Arie! Marle, D. Schwefel / Inl. J. Biomed. Compul. 40 (1995) 107-114 113

___________ ~~~~ ~ HAMIS_

SHORTCOURSECHEMOTHERAPY(sec)Ho.•

ICarryover patients 3979-

Hell patients6642-I TOTAL (patients) 1.0621Refarence

Data were consolidll.ted tor 12 months startinq January 1., 1993.The "reference" figura W'as the denominator usad to compute for the

p'ilrc:ent~ge figures in the table.

completion Lovel of Reports:January 901 of 1095 reports in 82')Fcbruary 901 of 1095 reports in 82\)March 893 of 1095 reports in 82'>April 868 of 1095 reports in 79')May 882 of 1095 reports in an}June 876 of 1095 reports in 80')July 882 of 1095 reports in 8H)August 886 of 1095 reports in 8H)september 888 of 1095 reports in 81')October 880 of 1095 reports in 80\)November 873 of 1095 reports in 80\)December 855 of 1095 reports in 78\)

Region 10 Northern MindanaoRegional Health OfficeNational Tuberculosis ProgramNUlllber and percentaqe of selected indicators forstandard regimen (SR).

REGIONLEVELPROGRAMTABLE

--------------~~--~-----'HAMI=

eases' as the eentrepieee, present minireasearehesthat are diseussed with invited and involved

speakers, and that lead to a strategie plan on howto eonvert information into implementation. So-eial proeesses are thus Iinked to information sys-tems.

Probably the most important, and quite urgent,next step would be to develop an 'expert system'that uses the indieators to interpret the many dataand to seleet and eomment on those that are

relevant to improving health management, as weilas to develop scenarios far health planning anddeeision making. Most likely this will take thefarm of a systematised situation al analysis basedon a reading of the BLACKBOX outputs, plusother relevant information sourees. It will tran-

seend mere data orientation by engineering thebroader body of knowledge of good health earemanagers that understand the interaetion between

....~ .............. ~~-:~:: ....

Region 10 Northern MindanaoRegional Hell.lth OfficeNational Tuberculosis ProgramNUI1lberand percentage cfselected indicators tor shortcourße chemotherapy (sec).

COlllpleted treatl:l.ent 532950.17-1

Died

"71.85\Transferred out

3.03.67\Defll.ulted

1631.53\Adverss reaction

77O.7nRefused

10.1.03tLost

2532.38\:

TOTAL

(pretllature discharges) 118911.19t

TOTAL

(treatment cOl:lpletions 651861. 37t+ prenature discharges)

TOTAL

(continuing treatment) 410338.63t

REGIONLEVELPROGRAMTABLE

TOTAL ..... 10585 of 13140 reports in (8H)

Fig. 4. BLACKBOX report showing- the number of TB pa-tients identified and treated with short course chemotherapy

(SCC, consisting of isoniazid, rifampicin, and pyrazinamide),in Region 10 of the Philippines, aggregated for the wh oIe yearof 1993.

Geographie Information System (GIS) that de-piets the health indieators spread out on a map.The geographie spread of health indieators tendsto have greater appeal espeeially with politiealdeeision makers. It would also be a useful tool for

rapidly assessing the spread of eertain indieatorswithin and aeross boundaries of health adminis-tration.

Information based quality assuranee eonfer-enees that deal with this data in the eontext of

other information systems, and that try to eross-fertilise data, information, understanding andknowledge, are an important next step to eonvertdata into deeds. Currently we are testing differentkinds of provineial clarifieation and consensuseonferenees that present results of health andmanagement information systems, analyse dataand information on 'avoidable deaths and dis-

STANDARDREGIMEN(SR)No.•

ICarryover patients 3027-Ne", patients

--~-2156-I TOTAL(patients) 5183Reference

CO'Dpleted treatment 159730.81\

Died

10.2.10'Transferred out

3256.27\Defaulted

1372.64'Mv.ra. r ••.ction

.,1.20\Retused

10.2.0ltLost

2••5.17\

TOTAL

(pretllature discharges) 100519.39\

TOTAL

(treatnent conpletions 260250.20'+ premo.ture. dischll.rges)

TOTAL

(continuing treatDent) 258149.80\

••••••••••.......... :::~.:.:.-:.: ...........

h •• w ••••••• ti:::-::·.~:-t:·::_.•..•..••. ~._ •.

Data were conso1ido.ted for 12 months starting January 1, 1993.Th'il tlroforonco" fiquro. "'ao. ~ho. d•••nominatoo,," '-'<>odto cornp~'to•• Eor toh.

percentago figures in the table.

Completion Level cf Reports:January 901 of 1095 reports in 82')February 901 of 1095 reports in 82')March 893 of 1095 reports in 82\:)April 868 of 1095 reports in 79\)May 882 of 1095 reports in 81%)June 876 of 1095 reports in 80')July 882 of 1095 reports in 81\)August 886 of 1095 reports in 81\:)September 888 of 1095 reports in 81\:)october 880 of 1095 reports in 80\)November 873 of 1095 reports in 80')December 855 of 1095 reports in 781;)

TOTAL •.••• 10585 of 13140 reports in (8U)

Fig. 5. BLACKBOX report showing the Bumber of TBpa teints identified and treated with standard regimen (SR,consisting of isoniazid, and streptomycin), in Region 10 of thePhilippines, aggregated for the whole year of 1993.

114 B. Ariel Marte, D. Schwefel / Int. J. Biomed. CompUl. 40(1995) 107-114

data, information understanding, knowledge, de-cisions and deeds. Such a systematised situational

analysis, as much as possible, should answer, atleast the four important questions, namely: Whatare our health problems? Wh at are we doingabout them? What else should we do? How best

should we manage our health reSOUl'ces to thisend?

Routine health data will prabably never begood enough to satisfy the requirements, espe-cially of those in the academe. But especiallywhere the health and the lives of people areconcerned, perhaps it may be good to bear inmind that 'it is always bettel' to be roughly correctthan to be precise\y wrang' [8].

References

[I] Department of Health: Field Health Services InformationSystem Manual 0/ Procedures. Department of Health,Manila, 1990 234pp.

[2] Pons Melahi C, Schwefel D: Strengthening Information

Support for Health Care: A Goal-Oriented Project Plan-

ning Exercise in the Philippine Context.HAMIS Occa-

sional Paper No. IDepartment of Health, Manila, 1993,

168pp.

[3] Requintina, RR: TB patient found immune to drugs:

Flavier alarmed on unique case. InThe Manila Bullelin

Manila, September 25, 1994, p. 28.

[4] Robey, 1M, Lee SH: Information System Development in

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