Development of HMIS in Least Developed Country Settings: The Case for Uganda

Peter Kintu, Axios International; Miriam Nayunja , WHO Country Office for Uganda; Amos Nzabanita and Ruth Magoola, Ministry of Health, Uganda

Background

Planning, monitoring, and evaluation of healthcare programmes provides a strong foundation for the realisation of quality health service delivery systems. This involves regular collection, analysis, and interpretation of health information to guide proper decision-making and design of appropriate interventions. Therefore, establishment of a robust management information system in any health program is crucial for the efficient delivery of health services to the population.

In Uganda, a health information system (HIS) was designed in 1985 to capture and analyse morbidity data for selected communicable and non-communicable diseases, and other services like immunization and family planning. Information was collected in the health facilities, summarized at the district level and later forwarded to the Ministry of Health at the centre where data analysis would be done. After seven years of implementation, it was felt that the system was leaving out vital management information, such as staffing levels, infrastructure, health facility management, medical equipment availability, financial information, and drug management. A review was therefore commissioned in 1992 with the aim of determining possibilities of collecting management information using the same channel. Based on findings and recommendations of this review, pilot testing in two districts was done for one year and nationwide implementation of the Health Management Information System (HMIS) was initiated in January 1997.

The core function of the Uganda HMIS is to establish and maintain a comprehensive source of health and management information for planning, monitoring, and evaluation of the health sector strategic plan. It focuses on improving and strengthening:

  • Data collection and compilation of health events
  • Timeliness, completeness, and accuracy of reported data
  • Analysis, interpretation, and utilisation for evidence-based decision making and action
  • Regular dissemination and feedback to all stakeholders
  • Enhancement of knowledge and skills of health workers in all aspects of data management, analysis, and utilisation at all levels of service delivery

HMIS Implementation in Uganda

Development of HMIS tools

HMIS tools form the backbone of the system. The 1997 model of the Uganda HMIS was based on a multitude of paper tools (reporting forms, registers, databases, and manuals), each containing a specific set of programme information (morbidity, family planning, immunisation, equipment inventory, drug availability, etc.). Health workers at the lower levels were supposed to record and compile separately a number of forms before forwarding them to the centre. Data on deaths in health facilities and inpatient services were supposed to be compiled and reported on an annual basis. Due to the big number of forms and registers, health workers spent lots of time and effort on tallying and summarising the different data items, and the accuracy of the reports would be jeopardised in the process. The process was labour-intensive. Similarly, reports would take months to move from the health centres to the districts and finally to the several departments within the Ministry of Health.

A review of the HMIS data collection and reporting tools was carried out during 2000-2001. Intensive discussions were held with the different stakeholders in order to come up with the main data variables for each programme. The main purpose for this review was to integrate the major aspects of the health and management information (data on outpatient morbidity, immunisation services, maternity statistics, drug stock monitoring, financial information, etc.) into one reporting form. This would reduce the workload of records assistants who previously had to fill several forms, lessen compilation errors, and improve the consistency of the reporting system. This would further facilitate the smooth running of the central databank at the Ministry of Health since all data for the different programmes would be processed at one location. Among the developments was the introduction of a reporting tool for health facility-based mortality data that was now to be summarised on a monthly basis by all health facilities with inpatient services. This would enable assessment of case management and case fatality ratios, and development of appropriate interventions.

During July 2001, a national dissemination workshop to launch the revised HMIS tools was organised. This workshop drew participants from the Ministry of Health and all the 56 districts of Uganda, including Directors of District Health Services, HMIS, and surveillance focal persons. The revised tools were then disseminated to all districts in Uganda.

HMIS Training

Support supervision from the centre, specifically focussing on HMIS, was strengthened at the district level and district programme managers were encouraged to facilitate this process at the health subdistrict and lower level health facilities. Technical officers from the centre would visit the districts on a quarterly basis to support HMIS focal persons and records assistants with hands-on training on the HMIS and to practically sort out any problems encountered during the execution of the HMIS.

Supervision reports showed improvements in HMIS implementation in a number of districts. However, some districts were reportedly lagging behind in terms of data analysis and utilisation, timeliness, and completeness of reporting, and a focused training program was designed. This program was intended to strengthen the data management skills of health workers in order to improve on data analysis and utilisation of data for action at the point of collection, data quality, and reporting. With support from WHO and other development partners, the training programme targeting operational-level health workers continues to be implemented in a number of districts, and this is yielding positive results. A central HMIS team was constituted from the different front-line departments of the Ministry of Health (Epidemiological Surveillance Division, Health Databank/ Resource Centre, Uganda Virus Research Institute, Expanded Programme on Immunisation, and Institute of Public Health). This team selects poorly performing districts and based on a standard curriculum covering all HMIS aspects trains core groups at the district level including in-charges of health subdistricts and health facilities, records assistants, and District HMIS and surveillance focal persons. This district core group then passes on the HMIS improved skills and knowledge to operational-level health workers who are drawn from all health facilities at a training workshop and during follow-up.

HMIS Reporting Mechanism

Reporting of HMIS data in Uganda is done through a network of 56 district health offices, which collect and summarise health information from 214 health subdistricts and more than 2,000 health facilities. Summary reports for the districts are then submitted to the Ministry of Health where data is compiled to derive national figures on health and health management indicators. A feedback mechanism exists whereby the central health databank provides summary analyses on a monthly basis to all districts, showing their comparative performance in terms of reporting (timeliness and completeness) and a selected list of health sector indicators. The districts with poor indicators are encouraged to review their service delivery strategies and reporting status. Districts are further encouraged to replicate this feedback to the lower health facilities. A format for this purpose has been designed and disseminated for use in all districts.

Computerisation

Computerisation of the HMIS in Uganda has been a slow process due to financial and technical limitations. The central health databank at the Ministry of Health has been computerised using both Microsoft Access (1997-2001) and EpiInfo software (2002 to date). The current plan is to establish electronic data management and analysis at district and health subdistrict levels, with a medium-term plan of setting up a district electronic reporting network capable of providing quick and accurate reports to the centre within all districts, and dissemination of prompt feedback to the districts. WHO carried out a computer inventory in 2001 and 70 percent of the districts were found to have computer equipment that could be upgraded to manage the collected data. Proposals have been written to solicit funds to upgrade the district computers, purchase new ones where needed, and train health workers on electronic data management, analysis, and reporting. During 2003, seven new high capacity computer units were provided by USAID through WHO for some districts and have been installed in the districts. Health workers in these districts have also received training on use of EpiInfo software for HMIS data entry and management.

Personnel

There are limited numbers of records assistants who are the primary data collectors of the HMIS at the health facilities. Their day-to-day work involves registering patients, tallying, and compiling reports for transmission to the health subdistrict. Most of these records assistants do not have a medical records training or background and are most often high school dropouts. They are given on-the-job orientation and support by the health facility in-charges who are normally trained nurses, midwives, or clinical officers. Some health units, especially levels 3 and 2, do not have records assistants, in which case one of the few health workers is assigned this work in addition to his/her routine work. This affects timeliness of reports from such health units.

At the health subdistrict level, there is normally a trained records assistant who takes charge of summarising the data from the health facilities and running some simple analyses. Although some health subdistrict records assistants have never had formal training in records management, they have had an extensive degree of exposure through HMIS workshops and support supervision, and have been instrumental in steering HMIS work in the health subdistricts and supervision of the lower health facilities on records management. They are also regularly supported by the health subdistrict in-charge who is normally a trained medical doctor.

At the district level, there are two officers designated to handle HMIS and surveillance activities. These may have formal training in records management and statistics, or may be trained medical personnel with extensive exposure on HMIS implementation. They normally work together to compile reports from the health subdistricts into district summaries, analyse data on health indicators in the district, and are responsible for reporting to the Ministry of Health. They are also responsible for coordination of support supervision and training on HMIS issues in the entire districts.

At the Ministry of Health, a health databank (Resource Centre) is equipped with two biostatisticians and a data manager who receive the reports from the districts, either by post, fax, or hand delivery. They log the date when reports are received and proceed to enter the data into a standardised computer database, based on EpiInfo software. At the end of the month, automated programs are run to produce a number of reports on health sector indicators, including utilisation of out- and inpatient services, coverage rates for immunisation, contraceptive prevalence rates, and morbidity levels for priority diseases. This team ensures that feedback to the districts is provided regularly, including requests for clarifications on inconsistencies in the reported information, and disseminates reports to all stakeholders in the health sector within and outside Uganda, both electronically and in hard copies. In collaboration with development partners, this team also coordinates training activities on HMIS issues in the whole country.

Results

Current Reporting Levels of the HMIS

Timeliness and completeness of HMIS reporting has been considered a key process indicator for the implementation of the Health Sector Strategic Plan (2000/1-2004/5) and the five-year target set at 80 percent. Timeliness in reporting has been defined as receipt of the monthly report at the Ministry of Health by the 28 th day of the following month. On the other hand, completeness is defined as the proportion of health facilities reporting out of the total number of units in the districts.

During the past 3 years, the timeliness of monthly reporting of outpatient data from the districts to the central level has improved markedly from a national average of 21 percent in 2000, 53 percent in 2001, 63 percent in 2002, and 79 percent in 2003. The graph below shows the trend in timeliness of monthly HMIS reporting from the districts to the centre.

Figure 2. Timeliness of Reporting

Source: Health Databank, Ministry of Health

Similarly, there has also been general improvement in completeness of the data reported to the Ministry of Health from 72 percent in 1999 to 85 percent in 2002 and 92 percent in 2003 (graph below).

Figure 3. Completeness of Reporting  

Source: Health Databank, Ministry of Health

Discussion

During 2000, the number of districts submitting monthly reports in time was very small (<50 percent). However, with improved feedback from the centre to the districts, reporting improved significantly during most of 2001. This feedback included a summary showing the performance of all districts in terms of HMIS reporting and some graphs of key disease trends. This feedback would not only be sent to the district health team, but would also be copied to the district political leaders (Chief Administrative Officer, District Chairperson, and Secretary for Health) and would sometimes be discussed in the district council.

During 2002, there was some decline in the level of reporting. This was mainly caused by the limited availability of HMIS reporting tools in most of the districts, which have traditionally been supplied by the Ministry of Health in order to maintain uniformity and standardisation. However, due to increased knowledge and motivation of health workers on the use of HMIS, coupled with funding gaps, the ministry could not cope with the level of utilization of the HMIS tools in the districts. Also, the established reporting process from the districts used to be bogged down by the many focal points in the Ministry of Health, which could sometimes lead to late processing or even loss of the forms. Towards the end of 2002, funds were secured to print and disseminate enough HMIS materials, and the result can be seen in the improved levels of reporting during 2003. The main health databank has also been equipped with improved communication means (fax, telephone, and e-mail) so that all reports from the districts are received and processed at one point.

The initial focus of the HMIS in Uganda was on outpatient data. However, since 2003, revised inpatient forms have been introduced for collection and reporting of inpatient and mortality data on a monthly basis. There has been slow uptake of inpatient reporting, however district and regional referral hospitals have been picking up.

The rapid implementation of the Integrated Disease Surveillance and Response (IDSR) strategy in Uganda has also contributed greatly to the registered improvements in HMIS reporting. The strategy has strengthened ownership of the HMIS since all programmes plan supervision, monitoring, and training together, resulting into an improved integrated reporting system.

Use of HMIS Data for Programme Planning

Many programmes in the Ministry of Health are using HMIS data for planning and monitoring purposes. A quick example is the Expanded Programme on Immunisation (EPI) which regularly reviews the coverage rates and identifies poorly performing districts for support supervision and more financial help where necessary. All this analysis and assessment is based on the HMIS data reported from the districts to the Ministry of Health.

A review of measles epidemiology in 2002 used HMIS as one of the data sources to determine trends of measles cases over time and the impact of under-five immunisation campaigns on the routine immunisation coverage rates on the trends (Nanyunja et al 2003). Together with sentinel sites and laboratory data, it was shown that over 90 percent of the measles cases were in the age group of 6 months to 14 years. This formed the basis for the current 5-year measles control strategy, which included among other activities under-15 mass campaigns to cover the most affected age groups.

The cholera trend in Uganda and the impact of the program interventions can be clearly shown since 1997 using HMIS data. There was a huge cholera epidemic in 1998, which covered the whole country, most probably as a result of the heavy El nino rains. A multisectoral intervention programme spearheaded by the Ministry of Health was implemented and within less than a year, HMIS data shows that the epidemic had been brought down in most parts of the country. Since 2001, there have been sporadic cholera cases, and HMIS data provides a distribution with districts bordering the Democratic Republic of Congo as affected, probably due to the poor sanitation levels and the recurrent movement of refugees. Interventions to control the spread of cholera are therefore being targeted in these districts.

Figure 4. Location of Sporadic Cholera Cases in Uganda: 2001-2004


Source: Constructed using HMIS data from Ministry of Health

HMIS data is also used for monitoring progress of implementation of some key government programmes. A case in point is the home-based management of fever (malaria) strategy, a programme that intends to reduce malaria morbidity and mortality in children under five years through the provision of anti-malaria drugs in the communities up to the household level. HMIS data is used to monitor the trends of key indicators for the programme at the health facility level, for instance, the number of under-five malaria cases, severe malaria admissions and deaths, and coverage for the intermittent presumptive treatment (IPT). Based on the positive results from the HMIS analysis, the strategy has been scaled up to currently cover 30 out of the 56 districts and eventually implementation will be scaled up to all districts in Uganda.

Challenges

For the success of any programme, human resources play a crucial part. There is a small number of trained data managers at the Ministry of Health to process the huge volumes of data generated from the districts and be able to produce outputs timely. The districts, health subdistricts and health centres also lack trained data managers and records assistants.

Although tools for capturing inpatient data were designed and disseminated to all districts, the response in terms of reporting has been minimal. For instance, during 2003, only 18 (32 percent) out of the 56 districts had reported inpatient data to the Ministry of Health. Out of these, only 6 had reported inpatient data every month. Some of the factors contributing to this include the little sensitisation that was given to the clinicians in the health facilities on the importance of reporting inpatient data. Also, the form appears too big as it requires data on admissions and deaths for about 70 different diseases and conditions, and computation of some indicators (for example, number of patient days, average bed occupancy, etc.) on a monthly basis.

The availability of HMIS tools (forms, patient cards, databases, and manuals) needs further streamlining. Provision of these tools by the Ministry of Health seems not to be sustainable as there are frequent shortages.

Data analysis practice has taken root in most of the health facilities. Graphs of disease trends and key indicator levels are regularly plotted and displayed in many health facilities. There is, however, little evidence to show how this data is utilised, especially at the district, health subdistrict and health facility levels.

Electronic data management and reporting is still lacking. There is the big challenge of acquiring the necessary financial resources to upgrade computer units in the districts and purchase new ones, install the appropriate data management software, train users, and connectivity to the electronic network.

Recommendations

There is need to establish and train the appropriate cadre of staff in order to have a good quality HMIS. This calls for additional training and support supervision on data analysis and utilisation of the outputs for planning, forecasting drug or vaccine needs and response to disease outbreaks.

There is need to simplify the inpatient reporting tool and to sensitize more health workers in hospitals and health centres with inpatient services on the advantages and use of inpatient data.

Since districts are now decentralised and manage funds for primary health care, it will be necessary to empower districts and health subdistricts to purchase HMIS tools from a standardised source. The challenge then will be on the districts to purchase all the required forms. The implication is that the Ministry of Health funds that are earmarked for HMIS forms thus must be distributed to the districts.

It is necessary to do more advocacy to development partners in order to realise the HMIS computerisation project. This will improve on the reporting and feedback to and from districts to Ministry of Health, reduce on errors in reported data, and improve on the data analysis culture by health workers.

Conclusion

Although there are some bottlenecks, the HMIS is established and functioning in Uganda. Even with limited resources, it has been proven that HMIS can be implemented to provide the basic information required for planning, monitoring, and evaluation of health programs. Significant progress has so far been registered in regular reporting through a network of districts, health subdistricts and health facilities, linked to the central Ministry of Health. The data processing machinery is in place at the centre and a regular feedback mechanism has been established. If the main challenges of human resource capacity, inpatient data collection and processing, regular availability of HMIS tools, data utilisation, and electronic data management are adequately addressed, a robust and high quality HMIS will be fully operational in Uganda.

References

  1. The Health Information System for Uganda: a guide for health workers; Ministry of Health, 1985
  2. Review of the Health Management Information System for Uganda: final report; Ministry of Health, 1997
  3. District Computer Inventory Survey Report; WHO Country Office for Uganda, July 2001
  4. HMIS Manual; Ministry of Health, revised edition, November 2001
  5. Indicator Manual for Monitoring HSSP Performance; Resource Centre, Ministry of Health, 2001
  6. Technical   Guidelines on Integrated Disease Surveillance and Response for Uganda; Ministry of Health, March 2002
  7. Data Analysis and Utilisation Guide for District, Health Sub-district and Health Facility Level; Epidemiological Surveillance Division, Ministry of Health, September 2003
  8. Draft Epiinfo Training Guide, WHO Country Office for Uganda, 2003
  9. Impact of Mass Measles Campaigns among Children less than 5 years old in Uganda; Nanyunja M, Lewis R, Makumbi I, Seruyange R, Kabwongera E, Mugyenyi P and Talisuna A - Journal of Infectious Diseases 2003;187 (suppl 1): S63-8

Source: 2004 IFHRO Congress & AHIMA Convention Proceedings, October 2004