Improving quality and use of data through data-use workshops: Zanzibar, United Republic of Tanzania

Βraa, Jørn; Heywood, Arthur; Sahay, Sundeep

doi:10.2471/blt.11.99580

Cited by 48 publications

(64 citation statements)

References 3 publications

(3 reference statements)

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“…Examples of such materials include a single source of information containing indicator definitions, guidelines on collating/aggregating, auditing procedures, as well as other steps of data collection, handling, analysis, and reporting. The development of job aids is supported by a study in Tanzania, the use of standardized analysis templates based on the Millennium Development Goals and local strategic plans contributed to improved data quality [24]. Materials to facilitate data use are particularly warranted given that this assessment, as well as work elsewhere [23], found that ownership of data-related tasks at service delivery sites was a key impediment to data quality.…”

Section: Discussionmentioning

confidence: 99%

Improving the quality of health information: a qualitative assessment of data management and reporting systems in Botswana

Ledikwe

Grignon

Lebelonyane

et al. 2014

Health Res Policy Sys

112

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BackgroundEnsuring that data collected through national health information systems are of sufficient quality for meaningful interpretation is a challenge in many resource-limited countries. An assessment was conducted to identify strengths and weaknesses of the health data management and reporting systems that capture and transfer routine monitoring and evaluation (M&E) data in Botswana.MethodsThis was a descriptive, qualitative assessment. In-depth interviews were conducted at the national (n = 27), district (n = 31), and facility/community (n = 71) levels to assess i) M&E structures, functions, and capabilities; ii) indicator definitions and reporting guidelines; iii) data collection forms and tools; iv) data management processes; and v) links with the national reporting system. A framework analysis was conducted using ATLAS.ti v6.1.ResultsHealth programs generally had standardized data collection and reporting tools and defined personnel for M&E responsibilities at the national and district levels. Best practices unique to individual health programs were identified and included a variety of relatively low-resource initiatives such as attention to staffing patterns, making health data more accessible for evidence-based decision-making, developing a single source of information related to indicator definitions, data collection tools, and management processes, and utilization of supportive supervision visits to districts and facilities. Weakness included limited ownership of M&E-related duties within facilities, a lack of tertiary training programs to build M&E skills, few standard practices related to confidentiality and document storage, limited dissemination of indicator definitions, and limited functionality of electronic data management systems.ConclusionsAddressing fundamental M&E system issues, further standardization of M&E practices, and increasing health services management responsiveness to time-sensitive information are critical to sustain progress related to health service delivery in Botswana. In addition to high-resource initiatives, such as investments in electronic medical record systems and tertiary training programs, there are a variety of low-resource initiatives, such as regular data quality checks, that can strengthen national health information systems. Applying best practices that are effective within one health program to data management and reporting systems of other programs is a practical approach for strengthening health informatics and improving data quality.

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Section: Discussionmentioning

confidence: 99%

Improving the quality of health information: a qualitative assessment of data management and reporting systems in Botswana

Ledikwe

Grignon

Lebelonyane

et al. 2014

Health Res Policy Sys

112

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“…It is, however, important to note that the challenges affecting health information systems are complex and multifactorial and that capacity development initiatives must be implemented alongside other system-strengthening initiatives to have the most substantive impact. This would include initiatives to implement electronic data management systems [9,17], instill a culture of data use [27], and harmonize data collection efforts [17,26,28,29]. …”

Section: Discussionmentioning

confidence: 99%

Establishing a health information workforce: innovation for low- and middle-income countries

et al. 2013

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BackgroundTo address the shortage of health information personnel within Botswana, an innovative human resources approach was taken. University graduates without training or experience in health information or health sciences were hired and provided with on-the-job training and mentoring to create a new cadre of health worker: the district Monitoring and Evaluation (M&E) Officer. This article describes the early outcomes, achievements, and challenges from this initiative.MethodsData were collected from the district M&E Officers over a 2-year period and included a skills assessment at baseline and 12 months, pre- and post-training tests, interviews during stakeholder site visits, a survey of achievements, focus group discussions, and an attrition assessment.ResultsAn average of 2.7 mentoring visits were conducted for M&E Officers in each district. There were five training sessions over 18 months. Knowledge scores significantly increased (p < 0.05) during the three trainings in which pre/post tests were administered. Over 1 year, there were significant improvements (p < 0.05) in self-rated skills related to computer literacy, checking data validity, implementing data quality procedures, using data to support program planning, proposing indicators, and writing M&E reports. Out of the 34 district M&E Officers interviewed during site visits, most were conducting facility visits to review data (27/34; 79%), comparing data sets over time (31/34; 91%), backing up data (32/34; 94%), and analyzing data (32/34; 94%). Common challenges included late facility reports (28/34; 82%), lack of transportation (22/34; 65%), inaccurate facility reports (10/34; 29%), and colleagues’ misunderstanding of M&E (10/34; 29%). Six posts were vacated in the first year (6/51; 12%). A total of 49 Officers completed the achievements survey; of these, common accomplishments related to improvements in data management (35/49; 71%), data quality (31/49; 63%), data use (29/49; 59%), and capacity development (26/49; 53%).ConclusionsThe development of a cadre of district M&E Officers has contributed positively to the health information system in Botswana. In the absence of tertiary training related to health information, on-the-job training and mentoring of university graduates can be an effective approach for developing a new professional cadre of M&E expertise and for strengthening capacity within a national health system.

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“…Quality data are the foundation to health system improvements [1-3]; however, health programs frequently fall short of efficient use of data to inform decisions [4]. Too often, data linger in reports and databases, and are not sufficiently used to inform program development and improvement, policy development, strategic planning, or advocacy.…”

Section: Introductionmentioning

confidence: 99%

“…Too often, data linger in reports and databases, and are not sufficiently used to inform program development and improvement, policy development, strategic planning, or advocacy. Part of the reason for the breakdown in the process is that health information systems (HIS) a are fragmented, complex, and do not fully respond to information needs [4-10]. As a result, decision makers are often unable to access the data they need in a timely manner to inform their upcoming decisions.…”

Section: Introductionmentioning

confidence: 99%

“…There are many different types of electronic decision-support tools, ranging from comprehensive tools that address multiple health programs to specific tools that address just one health program or specific elements of a health program. Comprehensive decision-support tools can serve to quickly integrate and streamline data from multiple sources including Demographic and Health Survey datasets, census statistics, and routinely collected data (project- or facility-specific) [4,20,21]. These types of systems commonly have a data dashboard function that allows data users and decision makers to easily and quickly view data on multiple health programs at different levels of the health system (national, regional, district, health facility) at regular intervals.…”

Section: Introductionmentioning

confidence: 99%

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Impact of a decision-support tool on decision making at the district level in Kenya

Nutley

McNabb

Salentine

2013

Health Res Policy Sys

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BackgroundIn many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district level and to enable district health management teams to review and monitor program progress for specific health issues to make informed service delivery decisions.MethodsThirteen in-depth interviews were conducted with ten tool users and three non-users in six districts to qualitatively assess the process of implementing the tool and its effect on data-informed decision making at the district level. The factors that affected use or non-use of the tool were also investigated. Respondents were selected via convenience sample from among those that had been trained to use the DHP tool except for one user who was self-taught to use the tool. Selection criteria also included respondents from urban districts with significant resources as well as respondents from more remote, under-resourced districts.ResultsFindings from the in-depth interviews suggest that among those who used it, the DHP tool had a positive effect on data analysis, review, interpretation, and sharing at the district level. The automated function of the tool allowed for faster data sharing and immediate observation of trends that facilitated data-informed decision making. All respondents stated that the DHP tool assisted them to better target existing services in need of improvement and to plan future services, thus positively influencing program improvement.ConclusionsThis paper stresses the central role that a targeted decision-support tool can play in making data aggregation, analysis, and presentation easier and faster. The visual synthesis of data facilitates the use of information in health decision making at the district level of a health system and promotes program improvement. The experience in Kenya can be applied to other countries that face challenges making district-level, data-informed decisions with data from fragmented information systems.

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Improving quality and use of data through data-use workshops: Zanzibar, United Republic of Tanzania

Cited by 48 publications

References 3 publications

Improving the quality of health information: a qualitative assessment of data management and reporting systems in Botswana

Improving the quality of health information: a qualitative assessment of data management and reporting systems in Botswana

Establishing a health information workforce: innovation for low- and middle-income countries

Impact of a decision-support tool on decision making at the district level in Kenya

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